R version 3.4.0 (2017-04-21) -- "You Stupid Darkness"
Copyright (C) 2017 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)
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Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> x <- array(list(0.36
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+ ,3.01
+ ,202.46
+ ,13.08
+ ,10
+ ,2.1
+ ,2.71
+ ,8.01
+ ,165.67
+ ,6.03
+ ,13
+ ,1.2
+ ,5.72
+ ,0.58
+ ,153.92
+ ,-1.73
+ ,15
+ ,0.3
+ ,1.89
+ ,-10.58
+ ,115.48
+ ,8.09
+ ,11
+ ,1.3
+ ,-4.52
+ ,6.5
+ ,164.07
+ ,7.51
+ ,15
+ ,1.1
+ ,-0.99
+ ,-18.24
+ ,96.94
+ ,-5.4
+ ,11
+ ,-0.4
+ ,-12.3
+ ,2.42
+ ,192.73
+ ,9.54
+ ,10
+ ,0.9
+ ,5.62
+ ,-5.6
+ ,106.17
+ ,0.59
+ ,14
+ ,0.6
+ ,-6.8
+ ,-12.51
+ ,97.53
+ ,-19.53
+ ,17
+ ,-1.2
+ ,-16.02
+ ,-9.17
+ ,158.77
+ ,1.19
+ ,12
+ ,0.8
+ ,-3.1
+ ,20.08
+ ,259.54
+ ,18.88
+ ,12
+ ,1.5
+ ,5.06
+ ,12.18
+ ,153.83
+ ,-3.51
+ ,17
+ ,-0.6
+ ,4.26
+ ,2.52
+ ,127.71
+ ,-5.09
+ ,10
+ ,0.2
+ ,-3.74
+ ,-13.3
+ ,125.39
+ ,-3.45
+ ,16
+ ,-0.3
+ ,-4.32
+ ,-1.36
+ ,173.55
+ ,2.94
+ ,11
+ ,0.2
+ ,2.75
+ ,-9.69
+ ,141.68
+ ,-1.27
+ ,11
+ ,0.3
+ ,-2.26
+ ,-4.3
+ ,98.84
+ ,-18.16
+ ,15
+ ,-1.5
+ ,-15.63
+ ,10.98
+ ,262.03
+ ,9.65
+ ,11
+ ,0.5
+ ,8.58
+ ,-14.6
+ ,128.62
+ ,-11.49
+ ,14
+ ,-0.5
+ ,-10.74
+ ,-12.82
+ ,113.30
+ ,-8.79
+ ,14
+ ,-0.7
+ ,-12.35
+ ,15.01
+ ,282.59
+ ,13.59
+ ,17
+ ,1.9
+ ,11.58
+ ,-14.26
+ ,140.46
+ ,-12.12
+ ,12
+ ,-1.4
+ ,-2.2
+ ,3.64
+ ,273.29
+ ,8.98
+ ,14
+ ,1.3
+ ,9.87
+ ,-4.4
+ ,108.21
+ ,5.27
+ ,14
+ ,0.9
+ ,0.92
+ ,-9.37
+ ,91.26
+ ,-7.61
+ ,17
+ ,0.9
+ ,-14.4
+ ,7.13
+ ,167.08
+ ,1.43
+ ,11
+ ,0.0
+ ,8.79
+ ,-6.44
+ ,116.00
+ ,-14.63
+ ,17
+ ,-0.7
+ ,-3.27
+ ,5.44
+ ,161.66
+ ,12.32
+ ,11
+ ,0.7
+ ,3.26
+ ,-1.19
+ ,88.70
+ ,-13.24
+ ,14
+ ,-1.4
+ ,-8.48
+ ,-7.75
+ ,166.47
+ ,1.18
+ ,12
+ ,0.0
+ ,6.28
+ ,1.38
+ ,178.58
+ ,2.26
+ ,13
+ ,-0.1
+ ,1.93
+ ,6.81
+ ,171.93
+ ,10.8
+ ,12
+ ,0.8
+ ,6.54
+ ,-4.43
+ ,167.13
+ ,-2.14
+ ,14
+ ,-0.8
+ ,-0.21
+ ,-10.65
+ ,160.57
+ ,-15.22
+ ,13
+ ,-2.5
+ ,1.23
+ ,8.09
+ ,165.68
+ ,1.83
+ ,12
+ ,-1.3
+ ,-0.57
+ ,-9.12
+ ,95.36
+ ,-11.29
+ ,18
+ ,-0.8
+ ,-12.83
+ ,2.3
+ ,204.46
+ ,-4.09
+ ,14
+ ,-0.1
+ ,3.71
+ ,3.39
+ ,130.25
+ ,1.83
+ ,9
+ ,1.6
+ ,-3.92
+ ,-6.18
+ ,126.49
+ ,-12.46
+ ,15
+ ,-0.5
+ ,-9.58
+ ,-11.97
+ ,95.46
+ ,-16.72
+ ,12
+ ,-1.1
+ ,-11.78
+ ,11.87
+ ,193.62
+ ,6.69
+ ,18
+ ,1.2
+ ,-1.01
+ ,15.93
+ ,288.32
+ ,15.04
+ ,18
+ ,1.5
+ ,9.75
+ ,-13.59
+ ,163.16
+ ,1.84
+ ,12
+ ,0.7
+ ,-9.21
+ ,0.07
+ ,188.32
+ ,-2.08
+ ,12
+ ,-0.2
+ ,2.45
+ ,-11.94
+ ,118.33
+ ,-10.76
+ ,9
+ ,-0.3
+ ,-9.03
+ ,2.96
+ ,141.43
+ ,6.55
+ ,12
+ ,0.6
+ ,-1.51
+ ,13.36
+ ,239.37
+ ,5.69
+ ,16
+ ,0.1
+ ,8.94
+ ,-6.79
+ ,116.21
+ ,-12.02
+ ,15
+ ,-0.6
+ ,-4.05
+ ,17.56
+ ,250.15
+ ,16.34
+ ,13
+ ,1.2
+ ,13.72
+ ,-1.79
+ ,218.34
+ ,15.36
+ ,10
+ ,0.0
+ ,9.25
+ ,-5.53
+ ,127.36
+ ,-2.71
+ ,12
+ ,0.5
+ ,-6.88
+ ,8.65
+ ,167.08
+ ,2.46
+ ,13
+ ,0.4
+ ,8.32
+ ,1.68
+ ,216.47
+ ,13.59
+ ,13
+ ,1.1
+ ,3.19
+ ,-2.5
+ ,197.31
+ ,0.2
+ ,13
+ ,0.1
+ ,4.73
+ ,3.59
+ ,110.24
+ ,11.14
+ ,8
+ ,0.7
+ ,4.09
+ ,7.55
+ ,212.18
+ ,6.56
+ ,14
+ ,0.2
+ ,10.98
+ ,-9.7
+ ,123.51
+ ,-6.26
+ ,14
+ ,-0.2
+ ,-3.65
+ ,-10.05
+ ,117.18
+ ,-10.42
+ ,13
+ ,-0.6
+ ,-9.34
+ ,-1.21
+ ,119.59
+ ,-6.61
+ ,14
+ ,-0.3
+ ,-6.51
+ ,-12.88
+ ,90.61
+ ,-15.79
+ ,14
+ ,-1.0
+ ,-13.1
+ ,8.25
+ ,208.46
+ ,12.73
+ ,14
+ ,1.8
+ ,4.82
+ ,7.49
+ ,187.23
+ ,5.06
+ ,14
+ ,0.1
+ ,1.5
+ ,-10.33
+ ,112.67
+ ,-20.99
+ ,15
+ ,-2.1
+ ,-8.17
+ ,-4.39
+ ,113.99
+ ,1.55
+ ,12
+ ,0.2
+ ,-8.49
+ ,5.46
+ ,176.27
+ ,7.3
+ ,11
+ ,-0.1
+ ,2.83
+ ,4.27
+ ,265.27
+ ,14.33
+ ,10
+ ,1.5
+ ,14.67
+ ,-1.99
+ ,108.58
+ ,-0.46
+ ,11
+ ,0.0
+ ,-9.35
+ ,18.82
+ ,291.56
+ ,20.73
+ ,6
+ ,1.8
+ ,14.87
+ ,14.98
+ ,244.56
+ ,17.84
+ ,13
+ ,2.0
+ ,12.21
+ ,11.16
+ ,198.22
+ ,8.5
+ ,16
+ ,0.7
+ ,2.3
+ ,1.11
+ ,115.28
+ ,-15.4
+ ,17
+ ,-0.3
+ ,-6.79
+ ,4.74
+ ,260.73
+ ,14.42
+ ,10
+ ,2.2
+ ,4.82
+ ,0.7
+ ,229.19
+ ,11.05
+ ,11
+ ,1.0
+ ,5.38
+ ,1.53
+ ,175.28
+ ,-7.66
+ ,14
+ ,-1.3
+ ,1.97
+ ,15.72
+ ,226.36
+ ,6.46
+ ,14
+ ,0.7
+ ,8.99
+ ,8.12
+ ,192.94
+ ,6.32
+ ,15
+ ,0.1
+ ,7.37
+ ,-8.96
+ ,156.51
+ ,-5.92
+ ,16
+ ,-1.3
+ ,5.62
+ ,-13.67
+ ,112.89
+ ,-11.63
+ ,16
+ ,-1.8
+ ,0.13
+ ,-6.97
+ ,169.16
+ ,-3.57
+ ,15
+ ,-1.2
+ ,-3.06
+ ,5.97
+ ,149.19
+ ,6.26
+ ,13
+ ,1.0
+ ,-0.06
+ ,-10.03
+ ,127.38
+ ,-4.98
+ ,15
+ ,0.1
+ ,-5.43
+ ,-4.84
+ ,142.51
+ ,-12.22
+ ,16
+ ,-1.8
+ ,2.05
+ ,-5.8
+ ,120.30
+ ,-11.31
+ ,12
+ ,-0.8
+ ,-8.49
+ ,-0.91
+ ,229.77
+ ,-2.18
+ ,13
+ ,-0.4
+ ,2.05
+ ,7.83
+ ,172.36
+ ,5.88
+ ,14
+ ,1.2
+ ,0.51
+ ,-3.73
+ ,130.59
+ ,2.13
+ ,13
+ ,1.6
+ ,0.57
+ ,12.54
+ ,223.00
+ ,18.81
+ ,12
+ ,1.0
+ ,6.91
+ ,-4.51
+ ,163.48
+ ,-1.51
+ ,15
+ ,-1.1
+ ,4.34
+ ,8.97
+ ,150.73
+ ,6.45
+ ,12
+ ,0.3
+ ,-2.91
+ ,10.59
+ ,256.98
+ ,13.94
+ ,17
+ ,0.4
+ ,10.31
+ ,1.75
+ ,256.84
+ ,1.09
+ ,14
+ ,0.1
+ ,11.87
+ ,8.77
+ ,264.16
+ ,9.4
+ ,13
+ ,0.2
+ ,7.84
+ ,2.63
+ ,201.22
+ ,11.39
+ ,10
+ ,1.6
+ ,2.58
+ ,-18.86
+ ,118.12
+ ,-14.24
+ ,9
+ ,-1.5
+ ,-11.62
+ ,1.34
+ ,188.99
+ ,3.04
+ ,12
+ ,0.0
+ ,4.03
+ ,4.94
+ ,130.55
+ ,10.16
+ ,10
+ ,1.1
+ ,-4.69
+ ,4.1
+ ,106.91
+ ,-7.26
+ ,15
+ ,0.2
+ ,-4.95
+ ,-6.54
+ ,130.06
+ ,-13.59
+ ,16
+ ,-1.1
+ ,0.29
+ ,6.91
+ ,126.91
+ ,-4.74
+ ,15
+ ,-0.5
+ ,-1.31
+ ,-0.01
+ ,156.67
+ ,-18.85
+ ,16
+ ,-2.4
+ ,-2.73
+ ,2.63
+ ,261.67
+ ,8.73
+ ,11
+ ,1.3
+ ,9.53
+ ,17.27
+ ,275.37
+ ,11.53
+ ,15
+ ,0.5
+ ,14.31
+ ,8.65
+ ,181.35
+ ,11.39
+ ,14
+ ,-0.1
+ ,1.98
+ ,-5.99
+ ,123.87
+ ,-1.23
+ ,11
+ ,0.6
+ ,-4.98
+ ,-13.33
+ ,86.31
+ ,-15.45
+ ,14
+ ,-1.9
+ ,-8.89
+ ,-3.92
+ ,106.65
+ ,-14.27
+ ,10
+ ,-1.0
+ ,-7.46
+ ,3.21
+ ,187.69
+ ,-2.27
+ ,15
+ ,-0.7
+ ,3.88
+ ,-8.25
+ ,187.87
+ ,-0.95
+ ,12
+ ,-0.7
+ ,0.87
+ ,11
+ ,210.93
+ ,5.04
+ ,16
+ ,-0.2
+ ,3.2
+ ,0.73
+ ,162.82
+ ,-3.7
+ ,16
+ ,-0.8
+ ,-2.82
+ ,19.98
+ ,214.31
+ ,9.73
+ ,15
+ ,1.1
+ ,8.03
+ ,9.03
+ ,175.95
+ ,6.55
+ ,14
+ ,0.1
+ ,2.45
+ ,9.57
+ ,197.13
+ ,7.59
+ ,13
+ ,0.6
+ ,3.94
+ ,8.68
+ ,120.52
+ ,9.62
+ ,11
+ ,1.5
+ ,-4.28
+ ,12.03
+ ,140.42
+ ,4.77
+ ,14
+ ,0.6
+ ,-6.89
+ ,15.3
+ ,197.83
+ ,10.85
+ ,13
+ ,0.9
+ ,8.06
+ ,1.37
+ ,102.99
+ ,-17.03
+ ,18
+ ,-0.9
+ ,-4.68)
+ ,dim=c(6
+ ,504)
+ ,dimnames=list(c('SRS'
+ ,'4yrRecAvg'
+ ,'lySRS'
+ ,'retStrt'
+ ,'lyYPPdiff'
+ ,'alltimeSRS')
+ ,1:504))
> y <- array(NA,dim=c(6,504),dimnames=list(c('SRS','4yrRecAvg','lySRS','retStrt','lyYPPdiff','alltimeSRS'),1:504))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par5 = '0'
> par4 = '0'
> par3 = 'No Linear Trend'
> par2 = 'Do not include Seasonal Dummies'
> par1 = '1'
> par5 <- '0'
> par4 <- '0'
> par3 <- 'No Linear Trend'
> par2 <- 'Do not include Seasonal Dummies'
> par1 <- '1'
> #'GNU S' R Code compiled by R2WASP v. 1.2.327 (Wed, 08 Jun 2016 16:18:16 +0100)
> #Author: root
> #To cite this work: Wessa P., (2015), Multiple Regression (v1.0.38) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_multipleregression.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #
> library(lattice)
> library(lmtest)
Loading required package: zoo
Attaching package: 'zoo'
The following objects are masked from 'package:base':
as.Date, as.Date.numeric
> n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
> mywarning <- ''
> par1 <- as.numeric(par1)
> if(is.na(par1)) {
+ par1 <- 1
+ mywarning = 'Warning: you did not specify the column number of the endogenous series! The first column was selected by default.'
+ }
> if (par4=='') par4 <- 0
> par4 <- as.numeric(par4)
> if (par5=='') par5 <- 0
> par5 <- as.numeric(par5)
> x <- na.omit(t(y))
> k <- length(x[1,])
> n <- length(x[,1])
> x1 <- cbind(x[,par1], x[,1:k!=par1])
> mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
> colnames(x1) <- mycolnames #colnames(x)[par1]
> x <- x1
> if (par3 == 'First Differences'){
+ (n <- n -1)
+ x2 <- array(0, dim=c(n,k), dimnames=list(1:n, paste('(1-B)',colnames(x),sep='')))
+ for (i in 1:n) {
+ for (j in 1:k) {
+ x2[i,j] <- x[i+1,j] - x[i,j]
+ }
+ }
+ x <- x2
+ }
> if (par3 == 'Seasonal Differences (s=12)'){
+ (n <- n - 12)
+ x2 <- array(0, dim=c(n,k), dimnames=list(1:n, paste('(1-B12)',colnames(x),sep='')))
+ for (i in 1:n) {
+ for (j in 1:k) {
+ x2[i,j] <- x[i+12,j] - x[i,j]
+ }
+ }
+ x <- x2
+ }
> if (par3 == 'First and Seasonal Differences (s=12)'){
+ (n <- n -1)
+ x2 <- array(0, dim=c(n,k), dimnames=list(1:n, paste('(1-B)',colnames(x),sep='')))
+ for (i in 1:n) {
+ for (j in 1:k) {
+ x2[i,j] <- x[i+1,j] - x[i,j]
+ }
+ }
+ x <- x2
+ (n <- n - 12)
+ x2 <- array(0, dim=c(n,k), dimnames=list(1:n, paste('(1-B12)',colnames(x),sep='')))
+ for (i in 1:n) {
+ for (j in 1:k) {
+ x2[i,j] <- x[i+12,j] - x[i,j]
+ }
+ }
+ x <- x2
+ }
> if(par4 > 0) {
+ x2 <- array(0, dim=c(n-par4,par4), dimnames=list(1:(n-par4), paste(colnames(x)[par1],'(t-',1:par4,')',sep='')))
+ for (i in 1:(n-par4)) {
+ for (j in 1:par4) {
+ x2[i,j] <- x[i+par4-j,par1]
+ }
+ }
+ x <- cbind(x[(par4+1):n,], x2)
+ n <- n - par4
+ }
> if(par5 > 0) {
+ x2 <- array(0, dim=c(n-par5*12,par5), dimnames=list(1:(n-par5*12), paste(colnames(x)[par1],'(t-',1:par5,'s)',sep='')))
+ for (i in 1:(n-par5*12)) {
+ for (j in 1:par5) {
+ x2[i,j] <- x[i+par5*12-j*12,par1]
+ }
+ }
+ x <- cbind(x[(par5*12+1):n,], x2)
+ n <- n - par5*12
+ }
> if (par2 == 'Include Monthly Dummies'){
+ x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
+ for (i in 1:11){
+ x2[seq(i,n,12),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> if (par2 == 'Include Quarterly Dummies'){
+ x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
+ for (i in 1:3){
+ x2[seq(i,n,4),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> (k <- length(x[n,]))
[1] 6
> if (par3 == 'Linear Trend'){
+ x <- cbind(x, c(1:n))
+ colnames(x)[k+1] <- 't'
+ }
> x
SRS 4yrRecAvg lySRS retStrt lyYPPdiff alltimeSRS
1 0.36 105.43 2.20 11 -0.3 1.16
2 -0.37 85.27 -9.23 12 -0.3 -11.67
3 23.72 314.56 20.34 11 1.8 13.27
4 5.05 87.46 -6.56 20 0.9 -4.33
5 1.27 195.26 11.90 12 0.0 1.73
6 4.91 212.21 13.26 16 0.3 3.52
7 12.79 217.77 14.91 15 0.7 6.77
8 0.74 130.73 -3.96 14 0.4 -9.73
9 -11.82 71.85 -12.95 9 -0.9 3.37
10 7.16 269.85 14.99 12 1.0 8.69
11 -10.66 107.35 -8.35 18 -0.7 -8.32
12 13.08 209.47 14.97 17 1.3 2.71
13 6.03 167.70 10.58 16 1.3 5.72
14 -1.73 152.65 6.04 9 0.6 1.89
15 8.09 117.22 -6.66 14 -0.5 -4.52
16 7.51 155.51 4.38 14 0.8 -0.99
17 -5.40 90.35 -9.34 11 0.1 -12.30
18 9.54 192.45 2.55 17 -0.2 5.62
19 -18.85 143.11 1.98 9 0.5 -2.73
20 0.59 109.68 -5.84 12 0.4 -6.80
21 1.19 166.67 2.42 12 0.3 -3.10
22 18.88 253.33 11.63 11 1.4 5.06
23 -3.51 163.66 -3.63 16 -1.2 4.26
24 -5.09 105.27 5.47 13 1.4 -3.74
25 -3.45 130.23 -15.72 14 -0.7 -4.32
26 2.94 163.24 6.64 12 0.1 2.75
27 -1.27 137.29 2.35 11 1.4 -2.26
28 -18.16 95.87 -19.82 13 -2.2 -15.63
29 9.65 268.54 8.12 10 0.6 8.58
30 -11.49 128.07 -9.68 12 -0.8 -10.74
31 -8.79 115.78 -6.95 16 -1.1 -12.35
32 13.59 280.66 14.48 11 0.9 11.58
33 -12.12 126.88 -5.52 12 -1.1 -2.20
34 8.98 271.65 18.84 12 2.0 9.87
35 5.27 76.02 1.89 12 1.3 0.92
36 -7.61 71.94 -20.41 17 -1.2 -14.40
37 1.43 170.41 15.92 13 0.4 8.79
38 -14.63 115.71 -9.08 13 -0.9 -3.27
39 12.32 153.88 0.85 13 0.8 3.26
40 -13.24 86.94 -19.67 13 -1.7 -8.48
41 1.18 168.01 -2.53 14 -0.6 6.28
42 2.26 179.02 -5.32 12 -0.1 1.93
43 10.80 176.14 1.37 13 0.2 6.54
44 -2.14 162.12 -8.64 15 -1.6 -0.21
45 -15.22 158.13 -6.86 8 -1.7 1.23
46 1.83 162.17 12.73 12 0.7 -0.57
47 -11.29 100.31 -13.04 16 -1.0 -12.83
48 -4.09 199.50 1.55 14 -0.1 3.71
49 15.04 277.45 10.75 15 0.7 9.75
50 1.83 125.14 5.46 12 1.0 -3.92
51 -12.46 121.18 -1.57 11 0.0 -9.58
52 -16.72 90.79 -9.82 14 -0.6 -11.78
53 6.69 192.63 10.52 9 0.7 -1.01
54 1.84 155.01 12.55 11 2.9 -9.21
55 -2.08 191.35 1.58 10 -0.2 2.45
56 -10.76 87.26 -12.61 19 0.0 -9.03
57 6.55 129.68 7.22 11 0.8 -1.51
58 5.69 246.73 8.04 11 1.9 8.94
59 -12.02 113.94 -13.99 12 -0.5 -4.05
60 16.34 248.33 1.82 17 0.5 13.72
61 15.36 210.28 16.07 13 1.4 9.25
62 -2.71 115.63 -3.52 13 0.0 -6.88
63 2.46 163.59 6.74 13 0.0 8.32
64 14.42 237.51 16.80 16 1.3 4.82
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454 -1.99 108.58 -0.46 11 0.0 -9.35
455 18.82 291.56 20.73 6 1.8 14.87
456 14.98 244.56 17.84 13 2.0 12.21
457 11.16 198.22 8.50 16 0.7 2.30
458 1.11 115.28 -15.40 17 -0.3 -6.79
459 4.74 260.73 14.42 10 2.2 4.82
460 0.70 229.19 11.05 11 1.0 5.38
461 1.53 175.28 -7.66 14 -1.3 1.97
462 15.72 226.36 6.46 14 0.7 8.99
463 8.12 192.94 6.32 15 0.1 7.37
464 -8.96 156.51 -5.92 16 -1.3 5.62
465 -13.67 112.89 -11.63 16 -1.8 0.13
466 -6.97 169.16 -3.57 15 -1.2 -3.06
467 5.97 149.19 6.26 13 1.0 -0.06
468 -10.03 127.38 -4.98 15 0.1 -5.43
469 -4.84 142.51 -12.22 16 -1.8 2.05
470 -5.80 120.30 -11.31 12 -0.8 -8.49
471 -0.91 229.77 -2.18 13 -0.4 2.05
472 7.83 172.36 5.88 14 1.2 0.51
473 -3.73 130.59 2.13 13 1.6 0.57
474 12.54 223.00 18.81 12 1.0 6.91
475 -4.51 163.48 -1.51 15 -1.1 4.34
476 8.97 150.73 6.45 12 0.3 -2.91
477 10.59 256.98 13.94 17 0.4 10.31
478 1.75 256.84 1.09 14 0.1 11.87
479 8.77 264.16 9.40 13 0.2 7.84
480 2.63 201.22 11.39 10 1.6 2.58
481 -18.86 118.12 -14.24 9 -1.5 -11.62
482 1.34 188.99 3.04 12 0.0 4.03
483 4.94 130.55 10.16 10 1.1 -4.69
484 4.10 106.91 -7.26 15 0.2 -4.95
485 -6.54 130.06 -13.59 16 -1.1 0.29
486 6.91 126.91 -4.74 15 -0.5 -1.31
487 -0.01 156.67 -18.85 16 -2.4 -2.73
488 2.63 261.67 8.73 11 1.3 9.53
489 17.27 275.37 11.53 15 0.5 14.31
490 8.65 181.35 11.39 14 -0.1 1.98
491 -5.99 123.87 -1.23 11 0.6 -4.98
492 -13.33 86.31 -15.45 14 -1.9 -8.89
493 -3.92 106.65 -14.27 10 -1.0 -7.46
494 3.21 187.69 -2.27 15 -0.7 3.88
495 -8.25 187.87 -0.95 12 -0.7 0.87
496 11.00 210.93 5.04 16 -0.2 3.20
497 0.73 162.82 -3.70 16 -0.8 -2.82
498 19.98 214.31 9.73 15 1.1 8.03
499 9.03 175.95 6.55 14 0.1 2.45
500 9.57 197.13 7.59 13 0.6 3.94
501 8.68 120.52 9.62 11 1.5 -4.28
502 12.03 140.42 4.77 14 0.6 -6.89
503 15.30 197.83 10.85 13 0.9 8.06
504 1.37 102.99 -17.03 18 -0.9 -4.68
> (k <- length(x[n,]))
[1] 6
> head(x)
SRS 4yrRecAvg lySRS retStrt lyYPPdiff alltimeSRS
1 0.36 105.43 2.20 11 -0.3 1.16
2 -0.37 85.27 -9.23 12 -0.3 -11.67
3 23.72 314.56 20.34 11 1.8 13.27
4 5.05 87.46 -6.56 20 0.9 -4.33
5 1.27 195.26 11.90 12 0.0 1.73
6 4.91 212.21 13.26 16 0.3 3.52
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) `4yrRecAvg` lySRS retStrt lyYPPdiff alltimeSRS
-16.19305 0.03372 0.37389 0.83044 1.52881 0.25811
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-15.9832 -4.4952 0.0909 4.2761 17.2907
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -16.193055 1.943518 -8.332 7.79e-16 ***
`4yrRecAvg` 0.033718 0.008784 3.839 0.000140 ***
lySRS 0.373886 0.061402 6.089 2.27e-09 ***
retStrt 0.830445 0.106592 7.791 3.90e-14 ***
lyYPPdiff 1.528809 0.458228 3.336 0.000912 ***
alltimeSRS 0.258107 0.069148 3.733 0.000211 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 5.774 on 498 degrees of freedom
Multiple R-squared: 0.6741, Adjusted R-squared: 0.6709
F-statistic: 206 on 5 and 498 DF, p-value: < 2.2e-16
> if (n > n25) {
+ kp3 <- k + 3
+ nmkm3 <- n - k - 3
+ gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
+ numgqtests <- 0
+ numsignificant1 <- 0
+ numsignificant5 <- 0
+ numsignificant10 <- 0
+ for (mypoint in kp3:nmkm3) {
+ j <- 0
+ numgqtests <- numgqtests + 1
+ for (myalt in c('greater', 'two.sided', 'less')) {
+ j <- j + 1
+ gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
+ }
+ if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
+ }
+ gqarr
+ }
[,1] [,2] [,3]
[1,] 0.19944899 0.39889798 0.80055101
[2,] 0.21456786 0.42913573 0.78543214
[3,] 0.13432731 0.26865463 0.86567269
[4,] 0.08627423 0.17254846 0.91372577
[5,] 0.16749793 0.33499585 0.83250207
[6,] 0.27090915 0.54181829 0.72909085
[7,] 0.63075691 0.73848618 0.36924309
[8,] 0.54517208 0.90965585 0.45482792
[9,] 0.49047950 0.98095899 0.50952050
[10,] 0.45438344 0.90876688 0.54561656
[11,] 0.90906833 0.18186334 0.09093167
[12,] 0.88454307 0.23091385 0.11545693
[13,] 0.84536931 0.30926138 0.15463069
[14,] 0.84941720 0.30116561 0.15058280
[15,] 0.83037385 0.33925230 0.16962615
[16,] 0.81988645 0.36022710 0.18011355
[17,] 0.79235150 0.41529699 0.20764850
[18,] 0.75307473 0.49385054 0.24692527
[19,] 0.71854737 0.56290526 0.28145263
[20,] 0.70259007 0.59481986 0.29740993
[21,] 0.65207396 0.69585209 0.34792604
[22,] 0.62168699 0.75662602 0.37831301
[23,] 0.56693238 0.86613524 0.43306762
[24,] 0.50952291 0.98095418 0.49047709
[25,] 0.48620276 0.97240552 0.51379724
[26,] 0.54045909 0.91908181 0.45954091
[27,] 0.53496413 0.93007174 0.46503587
[28,] 0.48566012 0.97132024 0.51433988
[29,] 0.44305415 0.88610830 0.55694585
[30,] 0.49509307 0.99018615 0.50490693
[31,] 0.52871851 0.94256298 0.47128149
[32,] 0.47912414 0.95824827 0.52087586
[33,] 0.42902020 0.85804041 0.57097980
[34,] 0.38239172 0.76478343 0.61760828
[35,] 0.38916974 0.77833948 0.61083026
[36,] 0.34831431 0.69662863 0.65168569
[37,] 0.32320290 0.64640580 0.67679710
[38,] 0.28646086 0.57292172 0.71353914
[39,] 0.25921256 0.51842513 0.74078744
[40,] 0.31121927 0.62243854 0.68878073
[41,] 0.27163401 0.54326801 0.72836599
[42,] 0.23784854 0.47569708 0.76215146
[43,] 0.23056566 0.46113132 0.76943434
[44,] 0.25640648 0.51281296 0.74359352
[45,] 0.27713212 0.55426424 0.72286788
[46,] 0.27233191 0.54466383 0.72766809
[47,] 0.23863402 0.47726803 0.76136598
[48,] 0.30571175 0.61142350 0.69428825
[49,] 0.33297346 0.66594692 0.66702654
[50,] 0.38522616 0.77045232 0.61477384
[51,] 0.37737378 0.75474756 0.62262622
[52,] 0.34439799 0.68879599 0.65560201
[53,] 0.32066468 0.64132935 0.67933532
[54,] 0.29052657 0.58105314 0.70947343
[55,] 0.25862586 0.51725171 0.74137414
[56,] 0.22771033 0.45542066 0.77228967
[57,] 0.25826571 0.51653143 0.74173429
[58,] 0.27047593 0.54095186 0.72952407
[59,] 0.36894505 0.73789010 0.63105495
[60,] 0.34390991 0.68781982 0.65609009
[61,] 0.31005445 0.62010890 0.68994555
[62,] 0.28794590 0.57589181 0.71205410
[63,] 0.25779618 0.51559237 0.74220382
[64,] 0.25327209 0.50654418 0.74672791
[65,] 0.30662661 0.61325323 0.69337339
[66,] 0.27493109 0.54986218 0.72506891
[67,] 0.37774801 0.75549602 0.62225199
[68,] 0.37213480 0.74426961 0.62786520
[69,] 0.40372675 0.80745350 0.59627325
[70,] 0.38061923 0.76123846 0.61938077
[71,] 0.38304765 0.76609530 0.61695235
[72,] 0.35021455 0.70042911 0.64978545
[73,] 0.33357425 0.66714849 0.66642575
[74,] 0.32156400 0.64312800 0.67843600
[75,] 0.39858979 0.79717958 0.60141021
[76,] 0.37003639 0.74007279 0.62996361
[77,] 0.38366405 0.76732810 0.61633595
[78,] 0.35615703 0.71231405 0.64384297
[79,] 0.32742105 0.65484210 0.67257895
[80,] 0.34056534 0.68113067 0.65943466
[81,] 0.35918371 0.71836742 0.64081629
[82,] 0.32835523 0.65671047 0.67164477
[83,] 0.30929193 0.61858386 0.69070807
[84,] 0.28009696 0.56019392 0.71990304
[85,] 0.26111774 0.52223548 0.73888226
[86,] 0.26194497 0.52388995 0.73805503
[87,] 0.32353799 0.64707598 0.67646201
[88,] 0.30673861 0.61347722 0.69326139
[89,] 0.28707928 0.57415855 0.71292072
[90,] 0.32403171 0.64806342 0.67596829
[91,] 0.33120686 0.66241373 0.66879314
[92,] 0.30369782 0.60739564 0.69630218
[93,] 0.28819166 0.57638332 0.71180834
[94,] 0.26604577 0.53209154 0.73395423
[95,] 0.30043012 0.60086025 0.69956988
[96,] 0.27573738 0.55147476 0.72426262
[97,] 0.25022118 0.50044236 0.74977882
[98,] 0.26841278 0.53682556 0.73158722
[99,] 0.25200100 0.50400200 0.74799900
[100,] 0.24588107 0.49176215 0.75411893
[101,] 0.22264403 0.44528807 0.77735597
[102,] 0.29051450 0.58102901 0.70948550
[103,] 0.26930553 0.53861107 0.73069447
[104,] 0.32002488 0.64004975 0.67997512
[105,] 0.29549737 0.59099475 0.70450263
[106,] 0.31290978 0.62581955 0.68709022
[107,] 0.33469392 0.66938784 0.66530608
[108,] 0.31579694 0.63159388 0.68420306
[109,] 0.30356152 0.60712304 0.69643848
[110,] 0.27858963 0.55717926 0.72141037
[111,] 0.25516147 0.51032294 0.74483853
[112,] 0.23509191 0.47018383 0.76490809
[113,] 0.23695013 0.47390026 0.76304987
[114,] 0.23157505 0.46315011 0.76842495
[115,] 0.20988586 0.41977173 0.79011414
[116,] 0.24638457 0.49276914 0.75361543
[117,] 0.23188218 0.46376435 0.76811782
[118,] 0.21086133 0.42172266 0.78913867
[119,] 0.22146911 0.44293822 0.77853089
[120,] 0.25214932 0.50429865 0.74785068
[121,] 0.23111699 0.46223399 0.76888301
[122,] 0.20971191 0.41942383 0.79028809
[123,] 0.27496222 0.54992444 0.72503778
[124,] 0.28847035 0.57694070 0.71152965
[125,] 0.31994950 0.63989900 0.68005050
[126,] 0.38746960 0.77493920 0.61253040
[127,] 0.36654089 0.73308177 0.63345911
[128,] 0.39727107 0.79454213 0.60272893
[129,] 0.36993816 0.73987631 0.63006184
[130,] 0.36550783 0.73101565 0.63449217
[131,] 0.35701592 0.71403183 0.64298408
[132,] 0.34987101 0.69974203 0.65012899
[133,] 0.36389792 0.72779583 0.63610208
[134,] 0.38644164 0.77288328 0.61355836
[135,] 0.36042773 0.72085545 0.63957227
[136,] 0.33547328 0.67094656 0.66452672
[137,] 0.32631469 0.65262939 0.67368531
[138,] 0.30839686 0.61679372 0.69160314
[139,] 0.28551106 0.57102211 0.71448894
[140,] 0.26285050 0.52570099 0.73714950
[141,] 0.24027363 0.48054726 0.75972637
[142,] 0.22781709 0.45563418 0.77218291
[143,] 0.24128544 0.48257089 0.75871456
[144,] 0.27437183 0.54874366 0.72562817
[145,] 0.25558858 0.51117715 0.74441142
[146,] 0.24047341 0.48094683 0.75952659
[147,] 0.22158313 0.44316627 0.77841687
[148,] 0.20133882 0.40267764 0.79866118
[149,] 0.18527194 0.37054389 0.81472806
[150,] 0.20688270 0.41376539 0.79311730
[151,] 0.22601101 0.45202201 0.77398899
[152,] 0.22735650 0.45471300 0.77264350
[153,] 0.21838597 0.43677193 0.78161403
[154,] 0.20175516 0.40351031 0.79824484
[155,] 0.25657239 0.51314478 0.74342761
[156,] 0.23700221 0.47400443 0.76299779
[157,] 0.23655178 0.47310357 0.76344822
[158,] 0.23542750 0.47085500 0.76457250
[159,] 0.22801481 0.45602963 0.77198519
[160,] 0.29255331 0.58510662 0.70744669
[161,] 0.28899996 0.57799992 0.71100004
[162,] 0.30264533 0.60529066 0.69735467
[163,] 0.29185000 0.58370000 0.70815000
[164,] 0.33644325 0.67288651 0.66355675
[165,] 0.31817534 0.63635069 0.68182466
[166,] 0.29455304 0.58910608 0.70544696
[167,] 0.28268685 0.56537369 0.71731315
[168,] 0.40230269 0.80460539 0.59769731
[169,] 0.37751245 0.75502490 0.62248755
[170,] 0.35341235 0.70682469 0.64658765
[171,] 0.33124188 0.66248375 0.66875812
[172,] 0.40571743 0.81143485 0.59428257
[173,] 0.39865049 0.79730098 0.60134951
[174,] 0.39292598 0.78585195 0.60707402
[175,] 0.43543825 0.87087649 0.56456175
[176,] 0.41318381 0.82636761 0.58681619
[177,] 0.38790873 0.77581746 0.61209127
[178,] 0.42609452 0.85218904 0.57390548
[179,] 0.42811506 0.85623012 0.57188494
[180,] 0.40797592 0.81595184 0.59202408
[181,] 0.38885916 0.77771832 0.61114084
[182,] 0.39807143 0.79614286 0.60192857
[183,] 0.41009147 0.82018294 0.58990853
[184,] 0.39713800 0.79427600 0.60286200
[185,] 0.37260894 0.74521787 0.62739106
[186,] 0.36028120 0.72056241 0.63971880
[187,] 0.34868500 0.69737000 0.65131500
[188,] 0.41109982 0.82219964 0.58890018
[189,] 0.38782880 0.77565760 0.61217120
[190,] 0.36296337 0.72592674 0.63703663
[191,] 0.38432005 0.76864010 0.61567995
[192,] 0.37828422 0.75656845 0.62171578
[193,] 0.37925289 0.75850578 0.62074711
[194,] 0.35617160 0.71234319 0.64382840
[195,] 0.34274337 0.68548674 0.65725663
[196,] 0.32763051 0.65526101 0.67236949
[197,] 0.30514688 0.61029376 0.69485312
[198,] 0.29437106 0.58874212 0.70562894
[199,] 0.27594710 0.55189420 0.72405290
[200,] 0.27601129 0.55202257 0.72398871
[201,] 0.26535253 0.53070507 0.73464747
[202,] 0.27073000 0.54146000 0.72927000
[203,] 0.26681680 0.53363361 0.73318320
[204,] 0.24897320 0.49794639 0.75102680
[205,] 0.23021624 0.46043247 0.76978376
[206,] 0.21447070 0.42894139 0.78552930
[207,] 0.20103518 0.40207036 0.79896482
[208,] 0.18565686 0.37131372 0.81434314
[209,] 0.18414330 0.36828660 0.81585670
[210,] 0.17107695 0.34215390 0.82892305
[211,] 0.16508339 0.33016678 0.83491661
[212,] 0.16715053 0.33430106 0.83284947
[213,] 0.15190942 0.30381884 0.84809058
[214,] 0.28474831 0.56949662 0.71525169
[215,] 0.26659221 0.53318441 0.73340779
[216,] 0.24619400 0.49238800 0.75380600
[217,] 0.26894621 0.53789241 0.73105379
[218,] 0.25996722 0.51993444 0.74003278
[219,] 0.25224760 0.50449520 0.74775240
[220,] 0.24827261 0.49654522 0.75172739
[221,] 0.23387535 0.46775070 0.76612465
[222,] 0.34542032 0.69084063 0.65457968
[223,] 0.34078084 0.68156167 0.65921916
[224,] 0.36341436 0.72682872 0.63658564
[225,] 0.41853922 0.83707844 0.58146078
[226,] 0.44302658 0.88605316 0.55697342
[227,] 0.42466992 0.84933984 0.57533008
[228,] 0.41972973 0.83945946 0.58027027
[229,] 0.44969031 0.89938062 0.55030969
[230,] 0.51022205 0.97955591 0.48977795
[231,] 0.48707104 0.97414209 0.51292896
[232,] 0.50474997 0.99050006 0.49525003
[233,] 0.54046293 0.91907414 0.45953707
[234,] 0.58965206 0.82069587 0.41034794
[235,] 0.58319383 0.83361235 0.41680617
[236,] 0.56033051 0.87933899 0.43966949
[237,] 0.54310522 0.91378956 0.45689478
[238,] 0.53227501 0.93544998 0.46772499
[239,] 0.52361499 0.95277001 0.47638501
[240,] 0.53744101 0.92511799 0.46255899
[241,] 0.53553494 0.92893012 0.46446506
[242,] 0.61016790 0.77966420 0.38983210
[243,] 0.60338278 0.79323443 0.39661722
[244,] 0.58114131 0.83771738 0.41885869
[245,] 0.60528950 0.78942101 0.39471050
[246,] 0.58413850 0.83172300 0.41586150
[247,] 0.56102663 0.87794674 0.43897337
[248,] 0.55947580 0.88104839 0.44052420
[249,] 0.54946351 0.90107298 0.45053649
[250,] 0.59696430 0.80607139 0.40303570
[251,] 0.58954020 0.82091960 0.41045980
[252,] 0.56454666 0.87090669 0.43545334
[253,] 0.56764569 0.86470862 0.43235431
[254,] 0.66109130 0.67781740 0.33890870
[255,] 0.67549590 0.64900820 0.32450410
[256,] 0.71194895 0.57610210 0.28805105
[257,] 0.69274587 0.61450826 0.30725413
[258,] 0.67823434 0.64353132 0.32176566
[259,] 0.65904738 0.68190523 0.34095262
[260,] 0.65338594 0.69322812 0.34661406
[261,] 0.65055820 0.69888360 0.34944180
[262,] 0.67585759 0.64828481 0.32414241
[263,] 0.69080160 0.61839680 0.30919840
[264,] 0.69271484 0.61457032 0.30728516
[265,] 0.68870046 0.62259909 0.31129954
[266,] 0.67799602 0.64400796 0.32200398
[267,] 0.65827918 0.68344164 0.34172082
[268,] 0.65144403 0.69711194 0.34855597
[269,] 0.67467217 0.65065566 0.32532783
[270,] 0.69977483 0.60045035 0.30022517
[271,] 0.70147969 0.59704062 0.29852031
[272,] 0.71889720 0.56220561 0.28110280
[273,] 0.73963710 0.52072581 0.26036290
[274,] 0.75719917 0.48560166 0.24280083
[275,] 0.79908863 0.40182274 0.20091137
[276,] 0.83970225 0.32059551 0.16029775
[277,] 0.82794564 0.34410872 0.17205436
[278,] 0.81478432 0.37043136 0.18521568
[279,] 0.79747185 0.40505630 0.20252815
[280,] 0.79982471 0.40035057 0.20017529
[281,] 0.79912223 0.40175555 0.20087777
[282,] 0.78679416 0.42641169 0.21320584
[283,] 0.76881503 0.46236993 0.23118497
[284,] 0.74969851 0.50060298 0.25030149
[285,] 0.75101984 0.49796033 0.24898016
[286,] 0.73160338 0.53679324 0.26839662
[287,] 0.71310326 0.57379348 0.28689674
[288,] 0.72101929 0.55796143 0.27898071
[289,] 0.70878960 0.58242081 0.29121040
[290,] 0.68916401 0.62167199 0.31083599
[291,] 0.66770987 0.66458026 0.33229013
[292,] 0.70659688 0.58680624 0.29340312
[293,] 0.68396528 0.63206945 0.31603472
[294,] 0.68106860 0.63786280 0.31893140
[295,] 0.67026686 0.65946627 0.32973314
[296,] 0.67763431 0.64473138 0.32236569
[297,] 0.66701499 0.66597001 0.33298501
[298,] 0.64357444 0.71285111 0.35642556
[299,] 0.62016739 0.75966521 0.37983261
[300,] 0.61700422 0.76599156 0.38299578
[301,] 0.74192607 0.51614786 0.25807393
[302,] 0.73794371 0.52411259 0.26205629
[303,] 0.74112818 0.51774363 0.25887182
[304,] 0.72532351 0.54935297 0.27467649
[305,] 0.70667108 0.58665784 0.29332892
[306,] 0.68510421 0.62979157 0.31489579
[307,] 0.66608173 0.66783655 0.33391827
[308,] 0.82644955 0.34710091 0.17355045
[309,] 0.85152580 0.29694840 0.14847420
[310,] 0.84523759 0.30952482 0.15476241
[311,] 0.83202535 0.33594930 0.16797465
[312,] 0.81971734 0.36056532 0.18028266
[313,] 0.80801026 0.38397948 0.19198974
[314,] 0.80166054 0.39667892 0.19833946
[315,] 0.78423520 0.43152960 0.21576480
[316,] 0.77791885 0.44416231 0.22208115
[317,] 0.80600607 0.38798786 0.19399393
[318,] 0.80082814 0.39834373 0.19917186
[319,] 0.80203483 0.39593034 0.19796517
[320,] 0.80780706 0.38438587 0.19219294
[321,] 0.79058171 0.41883657 0.20941829
[322,] 0.77285165 0.45429671 0.22714835
[323,] 0.75554021 0.48891958 0.24445979
[324,] 0.76081828 0.47836343 0.23918172
[325,] 0.74714420 0.50571159 0.25285580
[326,] 0.72618270 0.54763461 0.27381730
[327,] 0.72045969 0.55908062 0.27954031
[328,] 0.69856305 0.60287389 0.30143695
[329,] 0.78695872 0.42608256 0.21304128
[330,] 0.76830057 0.46339887 0.23169943
[331,] 0.76422600 0.47154800 0.23577400
[332,] 0.79123461 0.41753078 0.20876539
[333,] 0.78612219 0.42775563 0.21387781
[334,] 0.79396556 0.41206887 0.20603444
[335,] 0.79811892 0.40376217 0.20188108
[336,] 0.81379731 0.37240539 0.18620269
[337,] 0.79533187 0.40933627 0.20466813
[338,] 0.78823609 0.42352783 0.21176391
[339,] 0.84039464 0.31921073 0.15960536
[340,] 0.84253093 0.31493814 0.15746907
[341,] 0.82658483 0.34683034 0.17341517
[342,] 0.82990098 0.34019804 0.17009902
[343,] 0.81567934 0.36864132 0.18432066
[344,] 0.84958691 0.30082617 0.15041309
[345,] 0.83402739 0.33194523 0.16597261
[346,] 0.83288841 0.33422319 0.16711159
[347,] 0.81494497 0.37011006 0.18505503
[348,] 0.79592186 0.40815628 0.20407814
[349,] 0.80645769 0.38708463 0.19354231
[350,] 0.78765778 0.42468444 0.21234222
[351,] 0.76986980 0.46026039 0.23013020
[352,] 0.76453800 0.47092400 0.23546200
[353,] 0.74394286 0.51211429 0.25605714
[354,] 0.80746877 0.38506246 0.19253123
[355,] 0.82801523 0.34396953 0.17198477
[356,] 0.82290985 0.35418031 0.17709015
[357,] 0.80370223 0.39259555 0.19629777
[358,] 0.78356105 0.43287791 0.21643895
[359,] 0.78073463 0.43853075 0.21926537
[360,] 0.76381400 0.47237201 0.23618600
[361,] 0.74398726 0.51202547 0.25601274
[362,] 0.74243831 0.51512339 0.25756169
[363,] 0.74648630 0.50702739 0.25351370
[364,] 0.73351415 0.53297170 0.26648585
[365,] 0.71165283 0.57669435 0.28834717
[366,] 0.75067320 0.49865359 0.24932680
[367,] 0.73933177 0.52133647 0.26066823
[368,] 0.71832908 0.56334184 0.28167092
[369,] 0.69639288 0.60721424 0.30360712
[370,] 0.67530419 0.64939163 0.32469581
[371,] 0.71148582 0.57702835 0.28851418
[372,] 0.70830041 0.58339917 0.29169959
[373,] 0.75186556 0.49626889 0.24813444
[374,] 0.73858209 0.52283583 0.26141791
[375,] 0.74167339 0.51665322 0.25832661
[376,] 0.72248601 0.55502799 0.27751399
[377,] 0.69699298 0.60601404 0.30300702
[378,] 0.69883806 0.60232388 0.30116194
[379,] 0.67207545 0.65584910 0.32792455
[380,] 0.65415766 0.69168469 0.34584234
[381,] 0.63002071 0.73995858 0.36997929
[382,] 0.60198625 0.79602750 0.39801375
[383,] 0.68929256 0.62141487 0.31070744
[384,] 0.66130147 0.67739706 0.33869853
[385,] 0.70507396 0.58985209 0.29492604
[386,] 0.68251776 0.63496448 0.31748224
[387,] 0.67538410 0.64923179 0.32461590
[388,] 0.64665867 0.70668266 0.35334133
[389,] 0.68772865 0.62454271 0.31227135
[390,] 0.71669696 0.56660608 0.28330304
[391,] 0.76070969 0.47858063 0.23929031
[392,] 0.79063475 0.41873050 0.20936525
[393,] 0.87499115 0.25001770 0.12500885
[394,] 0.86019736 0.27960528 0.13980264
[395,] 0.87025202 0.25949597 0.12974798
[396,] 0.89504402 0.20991195 0.10495598
[397,] 0.89002786 0.21994429 0.10997214
[398,] 0.89339587 0.21320825 0.10660413
[399,] 0.89152309 0.21695381 0.10847691
[400,] 0.87658737 0.24682526 0.12341263
[401,] 0.87806277 0.24387447 0.12193723
[402,] 0.88590143 0.22819714 0.11409857
[403,] 0.91568357 0.16863286 0.08431643
[404,] 0.92321976 0.15356048 0.07678024
[405,] 0.92191715 0.15616569 0.07808285
[406,] 0.91143819 0.17712363 0.08856181
[407,] 0.89708105 0.20583789 0.10291895
[408,] 0.91219904 0.17560193 0.08780096
[409,] 0.93942229 0.12115543 0.06057771
[410,] 0.92817509 0.14364982 0.07182491
[411,] 0.91603678 0.16792644 0.08396322
[412,] 0.90871120 0.18257761 0.09128880
[413,] 0.89371852 0.21256296 0.10628148
[414,] 0.92793281 0.14413438 0.07206719
[415,] 0.92471766 0.15056467 0.07528234
[416,] 0.91185267 0.17629467 0.08814733
[417,] 0.90771670 0.18456660 0.09228330
[418,] 0.89154582 0.21690835 0.10845418
[419,] 0.87486418 0.25027165 0.12513582
[420,] 0.85560172 0.28879656 0.14439828
[421,] 0.83712132 0.32575737 0.16287868
[422,] 0.91533391 0.16933218 0.08466609
[423,] 0.90037975 0.19924050 0.09962025
[424,] 0.88243974 0.23512052 0.11756026
[425,] 0.86253958 0.27492083 0.13746042
[426,] 0.85195852 0.29608296 0.14804148
[427,] 0.83215568 0.33568863 0.16784432
[428,] 0.81954136 0.36091728 0.18045864
[429,] 0.85276786 0.29446428 0.14723214
[430,] 0.83638483 0.32723034 0.16361517
[431,] 0.82717466 0.34565068 0.17282534
[432,] 0.86304050 0.27391901 0.13695950
[433,] 0.85547128 0.28905744 0.14452872
[434,] 0.83358478 0.33283045 0.16641522
[435,] 0.80638811 0.38722379 0.19361189
[436,] 0.82798465 0.34403069 0.17201535
[437,] 0.81063171 0.37873659 0.18936829
[438,] 0.78357080 0.43285841 0.21642920
[439,] 0.76555803 0.46888395 0.23444197
[440,] 0.75552591 0.48894818 0.24447409
[441,] 0.72467143 0.55065715 0.27532857
[442,] 0.69026791 0.61946418 0.30973209
[443,] 0.67659078 0.64681844 0.32340922
[444,] 0.64746623 0.70506755 0.35253377
[445,] 0.64766473 0.70467055 0.35233527
[446,] 0.60725981 0.78548038 0.39274019
[447,] 0.73131366 0.53737269 0.26868634
[448,] 0.69161992 0.61676016 0.30838008
[449,] 0.65266631 0.69466738 0.34733369
[450,] 0.61968160 0.76063681 0.38031840
[451,] 0.61917588 0.76164825 0.38082412
[452,] 0.63490040 0.73019921 0.36509960
[453,] 0.63836441 0.72327119 0.36163559
[454,] 0.67584649 0.64830701 0.32415351
[455,] 0.63109347 0.73781305 0.36890653
[456,] 0.66536539 0.66926922 0.33463461
[457,] 0.74728572 0.50542855 0.25271428
[458,] 0.78637190 0.42725621 0.21362810
[459,] 0.74582031 0.50835939 0.25417969
[460,] 0.89881900 0.20236201 0.10118100
[461,] 0.87317578 0.25364845 0.12682422
[462,] 0.84374878 0.31250243 0.15625122
[463,] 0.80815412 0.38369175 0.19184588
[464,] 0.77000075 0.45999850 0.22999925
[465,] 0.88820435 0.22359131 0.11179565
[466,] 0.85611790 0.28776420 0.14388210
[467,] 0.88520764 0.22958473 0.11479236
[468,] 0.87732347 0.24535305 0.12267653
[469,] 0.91557481 0.16885038 0.08442519
[470,] 0.90463601 0.19072798 0.09536399
[471,] 0.87302114 0.25395773 0.12697886
[472,] 0.85461339 0.29077322 0.14538661
[473,] 0.80950999 0.38098003 0.19049001
[474,] 0.75802277 0.48395446 0.24197723
[475,] 0.69473236 0.61053528 0.30526764
[476,] 0.62598033 0.74803934 0.37401967
[477,] 0.69748775 0.60502449 0.30251225
[478,] 0.63246922 0.73506156 0.36753078
[479,] 0.74229960 0.51540080 0.25770040
[480,] 0.78071012 0.43857976 0.21928988
[481,] 0.69958761 0.60082478 0.30041239
[482,] 0.60794792 0.78410416 0.39205208
[483,] 0.84978440 0.30043120 0.15021560
[484,] 0.76216684 0.47566631 0.23783316
[485,] 0.99399548 0.01200904 0.00600452
[486,] 0.98607937 0.02784126 0.01392063
[487,] 0.95048260 0.09903479 0.04951740
> postscript(file="/var/wessaorg/rcomp/tmp/1a9fv1497721972.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
> points(x[,1]-mysum$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/2dots1497721972.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/3k1vy1497721972.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/4bpps1497721972.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/5a3nj1497721972.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
> qqline(mysum$resid)
> grid()
> dev.off()
null device
1
> (myerror <- as.ts(mysum$resid))
Time Series:
Start = 1
End = 504
Frequency = 1
1 2 3 4 5 6
3.20000572 9.90433246 6.39018514 3.87958336 -3.98174843 -5.66417954
7 8 9 10 11 12
0.79151384 4.27936869 -0.17562327 -5.08728107 -6.69497445 -0.19132596
13 14 15 16 17 18
-4.13803812 -1.82131697 13.12557861 4.22826218 5.12570319 3.02833612
19 20 21 22 23 24
-15.75634053 6.44666747 1.23468972 9.60183893 -4.03003992 -6.46234974
25 26 27 28 29 30
4.78846171 0.31838011 -1.27656977 -1.18722637 2.31629174 -1.96616602
31 32 33 34 35 36
-2.32007168 1.40631174 -5.85699552 -6.60080870 6.00295131 5.22216883
37 38 39 40 41 42
-7.75108921 -7.51936815 10.14653211 1.36792277 0.32424332 4.09540395
43 44 45 46 47 48
7.75225375 1.86075923 -6.15590302 -3.09288020 -2.05048385 -7.63404934
49 50 51 52 53 54
1.81545745 1.27984833 -6.42807402 -7.58505130 4.17127225 -3.07705659
55 56 57 58 59 60
-1.56059287 -6.24218863 5.70290084 -3.78923142 -2.59366255 5.05630565
61 62 63 64 65 66
3.13097022 1.88035908 -2.32602703 -0.19513843 6.80874175 -7.86851173
67 68 69 70 71 72
12.17727653 -2.19183655 -2.42268861 3.59314062 -0.85805004 -5.01551076
73 74 75 76 77 78
7.91422874 0.14018804 -10.96254724 4.40708046 6.92646450 -1.90779529
79 80 81 82 83 84
6.10984628 0.16050377 5.92405900 4.11021376 -9.65253523 -3.19967049
85 86 87 88 89 90
-6.27299830 -0.72571652 -0.18348521 -5.80825497 -7.53246874 -1.71894365
91 92 93 94 95 96
5.07946547 0.13513340 2.90846085 -6.80034895 11.31962528 -3.46520100
97 98 99 100 101 102
-3.17599733 8.87290932 7.44764982 0.86044771 3.61873959 1.55614537
103 104 105 106 107 108
-7.16112991 -2.17226112 -1.46996525 -7.03398041 -1.72094925 -6.93567985
109 110 111 112 113 114
0.86273821 11.75114071 3.11600438 -8.71722137 1.77442732 -7.90900393
115 116 117 118 119 120
5.64126248 -3.13275869 -4.34920315 -1.89164169 -2.49346903 0.16857127
121 122 123 124 125 126
5.78481400 5.27984774 0.63695816 8.54099331 4.24786705 0.24304618
127 128 129 130 131 132
-7.36594750 9.92997834 1.47925424 1.60937560 11.35044951 5.78666874
133 134 135 136 137 138
6.82297650 10.93409387 2.30467398 -7.19789452 -0.21980488 -5.21659622
139 140 141 142 143 144
5.70596145 5.59228067 7.54500326 -7.40141475 0.22627528 0.28876231
145 146 147 148 149 150
4.86785418 -3.39071177 -1.43570085 0.66900013 0.33698497 -3.96426584
151 152 153 154 155 156
7.45063969 -8.49220692 1.97201588 3.79235633 -2.44910590 0.17041421
157 158 159 160 161 162
-1.94761702 7.51105496 -6.90283349 -6.06288605 4.56971335 -1.51625575
163 164 165 166 167 168
11.44229898 -1.07539237 -5.75791633 -5.58116183 -4.25474303 -11.95412293
169 170 171 172 173 174
-5.00122158 -7.73862552 -4.33344257 9.80082345 -3.26967666 -0.30622534
175 176 177 178 179 180
-3.03048750 14.87086697 -0.35328254 0.12924806 2.06544217 11.63356114
181 182 183 184 185 186
-4.57431469 5.16263489 9.21428709 -1.03471274 0.92743157 -8.71394330
187 188 189 190 191 192
6.19671366 2.92951605 2.49958535 6.47072589 6.63499727 3.88564277
193 194 195 196 197 198
0.66404339 4.55263898 2.60976160 -10.98344856 1.80331152 0.19973171
199 200 201 202 203 204
-7.72630772 5.13760172 -5.79531348 -1.60924649 -3.90699821 -2.17403270
205 206 207 208 209 210
-0.74182367 4.45615463 -2.32487802 -5.83183995 4.05100714 -6.61185983
211 212 213 214 215 216
-4.81869585 -2.09488971 -0.60469154 2.53574560 3.08107673 1.47844080
217 218 219 220 221 222
-5.43483650 -2.83764343 -4.66930181 -5.49309059 -0.63362517 -15.98323495
223 224 225 226 227 228
-1.39050680 0.72050294 -8.40258495 4.41951645 4.70568009 -5.05612103
229 230 231 232 233 234
-3.02686031 14.21673673 5.16714306 -7.90572308 10.18887061 -8.18219524
235 236 237 238 239 240
-3.00909151 -5.14392632 -8.51092914 -10.54694654 -0.91575547 7.51628655
241 242 243 244 245 246
8.87757546 -9.82936758 5.02680119 1.72440844 -3.20198680 -4.32300263
247 248 249 250 251 252
-4.45678395 7.18327953 5.35061560 11.17546646 4.44390738 -1.94147718
253 254 255 256 257 258
-8.22755074 1.89194697 -1.45404601 -5.56760418 4.12195211 9.75875655
259 260 261 262 263 264
-4.69586932 -0.09437979 -6.02707616 12.60382969 7.36144946 9.34810211
265 266 267 268 269 270
-2.06171560 3.32883640 2.07544853 5.10392219 5.42265761 -8.40003298
271 272 273 274 275 276
7.27387035 -6.06520604 -5.20375259 4.27502270 2.26485655 4.60480857
277 278 279 280 281 282
-8.26602256 8.61666491 6.00382198 -7.81030943 -8.14083116 7.79522242
283 284 285 286 287 288
-10.68411515 9.07737881 2.87329372 -2.88807583 -0.66686571 -5.88679427
289 290 291 292 293 294
5.00052784 -3.40427043 0.80759025 1.50873254 5.90147788 -1.20761734
295 296 297 298 299 300
-2.06793087 7.00402074 -3.44241389 -2.27588038 1.43864033 -9.18587557
301 302 303 304 305 306
-0.27948877 -3.62835849 4.30854293 6.04301201 3.29753777 1.14317795
307 308 309 310 311 312
-1.13694483 -5.49157835 -14.53987733 -5.85716962 6.08482233 -1.37265742
313 314 315 316 317 318
2.42458966 -0.85151307 2.36096439 17.29072093 9.56194994 -4.88647525
319 320 321 322 323 324
1.97349603 3.26395725 -3.53962449 -4.65521252 -2.11627080 -4.92468490
325 326 327 328 329 330
9.50951260 4.58502617 -4.88331984 -6.59177443 1.46117478 1.27303858
331 332 333 334 335 336
1.98445535 6.17079773 4.03593447 -0.36197644 -4.95207734 -1.88786669
337 338 339 340 341 342
-13.03757010 1.65582318 -5.92501374 -8.33632844 -3.98610703 7.46642540
343 344 345 346 347 348
6.29998903 -8.66610415 -1.49158751 -4.53857759 -11.59228440 6.42219031
349 350 351 352 353 354
-1.00914315 -5.36585954 -3.12359932 -9.47747224 0.95263428 -5.34149744
355 356 357 358 359 360
-0.14595779 -1.36296483 -6.78026894 0.40352550 2.90313960 4.64810777
361 362 363 364 365 366
2.56253041 -11.14149156 8.12397222 5.18544159 1.10595393 1.14163791
367 368 369 370 371 372
-6.26388136 2.08445893 2.99749618 6.11381289 6.46143611 -4.38353054
373 374 375 376 377 378
2.12009090 -9.87140407 4.47086546 -1.38968363 2.86548604 2.63141478
379 380 381 382 383 384
7.40537887 5.06355781 -10.04693680 -4.12178954 -6.19008465 2.77992049
385 386 387 388 389 390
1.69502553 4.86653841 0.68373368 -4.72825339 2.25580612 -1.17306994
391 392 393 394 395 396
-11.26109414 0.47028855 -8.64520273 -2.58314398 -3.99572325 -0.45155133
397 398 399 400 401 402
-9.16346576 6.89845246 10.19880746 8.66517048 -11.75834141 -2.26830540
403 404 405 406 407 408
-6.80943262 9.22092553 2.61618336 -6.53750922 -4.52913521 -3.41748271
409 410 411 412 413 414
-5.52858918 -8.90031200 -7.06551918 -5.18549558 5.75121377 -0.89161960
415 416 417 418 419 420
0.52950603 9.66540444 -9.19734452 -0.43426216 0.29161822 -3.42102775
421 422 423 424 425 426
-1.47166349 10.18174729 -2.33453413 0.69742927 5.59880773 1.18713030
427 428 429 430 431 432
2.01259611 2.51146714 -2.97940588 -12.24460023 0.39910482 -0.39839146
433 434 435 436 437 438
1.44253977 3.60719338 -0.51521105 3.03772656 -9.39366745 -1.57195533
439 440 441 442 443 444
4.73500781 -7.80773588 -5.20404701 3.13155609 -0.62983483 -5.70925470
445 446 447 448 449 450
-1.37986159 3.93484388 -0.55465782 -2.96744057 3.31197872 2.77451969
451 452 453 454 455 456
-0.69971212 3.26783329 -8.22308117 3.99238940 5.85912810 -0.74792744
457 458 459 460 461 462
2.54059394 7.26756087 -6.16146994 -7.01843531 4.52975755 6.84866612
463 464 465 466 467 468
0.93282460 -8.58090396 -7.50384406 -4.97813514 2.48309548 -7.47797391
469 470 471 472 473 474
0.05246946 4.01451432 -2.36254092 2.42060847 -6.12550004 0.90357220
475 476 477 478 479 480
-5.15969384 7.99634660 -4.48382732 -5.96733881 -0.58341198 -3.63661784
481 482 483 484 485 486
-3.50712074 -0.98135301 4.15692236 7.91791339 -1.33142122 9.24202701
487 488 489 490 491 492
9.03492795 -6.84595118 2.95275483 2.48540946 -2.28047079 -0.69749417
493 494 495 496 497 498
9.16226414 1.53536251 -7.15600097 4.38932142 1.48032558 9.09816919
499 500 501 502 503 504
4.43002151 3.54850342 6.88921616 10.93983509 6.51399084 8.09361987
> postscript(file="/var/wessaorg/rcomp/tmp/6pbnx1497721972.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> dum <- cbind(lag(myerror,k=1),myerror)
> dum
Time Series:
Start = 0
End = 504
Frequency = 1
lag(myerror, k = 1) myerror
0 3.20000572 NA
1 9.90433246 3.20000572
2 6.39018514 9.90433246
3 3.87958336 6.39018514
4 -3.98174843 3.87958336
5 -5.66417954 -3.98174843
6 0.79151384 -5.66417954
7 4.27936869 0.79151384
8 -0.17562327 4.27936869
9 -5.08728107 -0.17562327
10 -6.69497445 -5.08728107
11 -0.19132596 -6.69497445
12 -4.13803812 -0.19132596
13 -1.82131697 -4.13803812
14 13.12557861 -1.82131697
15 4.22826218 13.12557861
16 5.12570319 4.22826218
17 3.02833612 5.12570319
18 -15.75634053 3.02833612
19 6.44666747 -15.75634053
20 1.23468972 6.44666747
21 9.60183893 1.23468972
22 -4.03003992 9.60183893
23 -6.46234974 -4.03003992
24 4.78846171 -6.46234974
25 0.31838011 4.78846171
26 -1.27656977 0.31838011
27 -1.18722637 -1.27656977
28 2.31629174 -1.18722637
29 -1.96616602 2.31629174
30 -2.32007168 -1.96616602
31 1.40631174 -2.32007168
32 -5.85699552 1.40631174
33 -6.60080870 -5.85699552
34 6.00295131 -6.60080870
35 5.22216883 6.00295131
36 -7.75108921 5.22216883
37 -7.51936815 -7.75108921
38 10.14653211 -7.51936815
39 1.36792277 10.14653211
40 0.32424332 1.36792277
41 4.09540395 0.32424332
42 7.75225375 4.09540395
43 1.86075923 7.75225375
44 -6.15590302 1.86075923
45 -3.09288020 -6.15590302
46 -2.05048385 -3.09288020
47 -7.63404934 -2.05048385
48 1.81545745 -7.63404934
49 1.27984833 1.81545745
50 -6.42807402 1.27984833
51 -7.58505130 -6.42807402
52 4.17127225 -7.58505130
53 -3.07705659 4.17127225
54 -1.56059287 -3.07705659
55 -6.24218863 -1.56059287
56 5.70290084 -6.24218863
57 -3.78923142 5.70290084
58 -2.59366255 -3.78923142
59 5.05630565 -2.59366255
60 3.13097022 5.05630565
61 1.88035908 3.13097022
62 -2.32602703 1.88035908
63 -0.19513843 -2.32602703
64 6.80874175 -0.19513843
65 -7.86851173 6.80874175
66 12.17727653 -7.86851173
67 -2.19183655 12.17727653
68 -2.42268861 -2.19183655
69 3.59314062 -2.42268861
70 -0.85805004 3.59314062
71 -5.01551076 -0.85805004
72 7.91422874 -5.01551076
73 0.14018804 7.91422874
74 -10.96254724 0.14018804
75 4.40708046 -10.96254724
76 6.92646450 4.40708046
77 -1.90779529 6.92646450
78 6.10984628 -1.90779529
79 0.16050377 6.10984628
80 5.92405900 0.16050377
81 4.11021376 5.92405900
82 -9.65253523 4.11021376
83 -3.19967049 -9.65253523
84 -6.27299830 -3.19967049
85 -0.72571652 -6.27299830
86 -0.18348521 -0.72571652
87 -5.80825497 -0.18348521
88 -7.53246874 -5.80825497
89 -1.71894365 -7.53246874
90 5.07946547 -1.71894365
91 0.13513340 5.07946547
92 2.90846085 0.13513340
93 -6.80034895 2.90846085
94 11.31962528 -6.80034895
95 -3.46520100 11.31962528
96 -3.17599733 -3.46520100
97 8.87290932 -3.17599733
98 7.44764982 8.87290932
99 0.86044771 7.44764982
100 3.61873959 0.86044771
101 1.55614537 3.61873959
102 -7.16112991 1.55614537
103 -2.17226112 -7.16112991
104 -1.46996525 -2.17226112
105 -7.03398041 -1.46996525
106 -1.72094925 -7.03398041
107 -6.93567985 -1.72094925
108 0.86273821 -6.93567985
109 11.75114071 0.86273821
110 3.11600438 11.75114071
111 -8.71722137 3.11600438
112 1.77442732 -8.71722137
113 -7.90900393 1.77442732
114 5.64126248 -7.90900393
115 -3.13275869 5.64126248
116 -4.34920315 -3.13275869
117 -1.89164169 -4.34920315
118 -2.49346903 -1.89164169
119 0.16857127 -2.49346903
120 5.78481400 0.16857127
121 5.27984774 5.78481400
122 0.63695816 5.27984774
123 8.54099331 0.63695816
124 4.24786705 8.54099331
125 0.24304618 4.24786705
126 -7.36594750 0.24304618
127 9.92997834 -7.36594750
128 1.47925424 9.92997834
129 1.60937560 1.47925424
130 11.35044951 1.60937560
131 5.78666874 11.35044951
132 6.82297650 5.78666874
133 10.93409387 6.82297650
134 2.30467398 10.93409387
135 -7.19789452 2.30467398
136 -0.21980488 -7.19789452
137 -5.21659622 -0.21980488
138 5.70596145 -5.21659622
139 5.59228067 5.70596145
140 7.54500326 5.59228067
141 -7.40141475 7.54500326
142 0.22627528 -7.40141475
143 0.28876231 0.22627528
144 4.86785418 0.28876231
145 -3.39071177 4.86785418
146 -1.43570085 -3.39071177
147 0.66900013 -1.43570085
148 0.33698497 0.66900013
149 -3.96426584 0.33698497
150 7.45063969 -3.96426584
151 -8.49220692 7.45063969
152 1.97201588 -8.49220692
153 3.79235633 1.97201588
154 -2.44910590 3.79235633
155 0.17041421 -2.44910590
156 -1.94761702 0.17041421
157 7.51105496 -1.94761702
158 -6.90283349 7.51105496
159 -6.06288605 -6.90283349
160 4.56971335 -6.06288605
161 -1.51625575 4.56971335
162 11.44229898 -1.51625575
163 -1.07539237 11.44229898
164 -5.75791633 -1.07539237
165 -5.58116183 -5.75791633
166 -4.25474303 -5.58116183
167 -11.95412293 -4.25474303
168 -5.00122158 -11.95412293
169 -7.73862552 -5.00122158
170 -4.33344257 -7.73862552
171 9.80082345 -4.33344257
172 -3.26967666 9.80082345
173 -0.30622534 -3.26967666
174 -3.03048750 -0.30622534
175 14.87086697 -3.03048750
176 -0.35328254 14.87086697
177 0.12924806 -0.35328254
178 2.06544217 0.12924806
179 11.63356114 2.06544217
180 -4.57431469 11.63356114
181 5.16263489 -4.57431469
182 9.21428709 5.16263489
183 -1.03471274 9.21428709
184 0.92743157 -1.03471274
185 -8.71394330 0.92743157
186 6.19671366 -8.71394330
187 2.92951605 6.19671366
188 2.49958535 2.92951605
189 6.47072589 2.49958535
190 6.63499727 6.47072589
191 3.88564277 6.63499727
192 0.66404339 3.88564277
193 4.55263898 0.66404339
194 2.60976160 4.55263898
195 -10.98344856 2.60976160
196 1.80331152 -10.98344856
197 0.19973171 1.80331152
198 -7.72630772 0.19973171
199 5.13760172 -7.72630772
200 -5.79531348 5.13760172
201 -1.60924649 -5.79531348
202 -3.90699821 -1.60924649
203 -2.17403270 -3.90699821
204 -0.74182367 -2.17403270
205 4.45615463 -0.74182367
206 -2.32487802 4.45615463
207 -5.83183995 -2.32487802
208 4.05100714 -5.83183995
209 -6.61185983 4.05100714
210 -4.81869585 -6.61185983
211 -2.09488971 -4.81869585
212 -0.60469154 -2.09488971
213 2.53574560 -0.60469154
214 3.08107673 2.53574560
215 1.47844080 3.08107673
216 -5.43483650 1.47844080
217 -2.83764343 -5.43483650
218 -4.66930181 -2.83764343
219 -5.49309059 -4.66930181
220 -0.63362517 -5.49309059
221 -15.98323495 -0.63362517
222 -1.39050680 -15.98323495
223 0.72050294 -1.39050680
224 -8.40258495 0.72050294
225 4.41951645 -8.40258495
226 4.70568009 4.41951645
227 -5.05612103 4.70568009
228 -3.02686031 -5.05612103
229 14.21673673 -3.02686031
230 5.16714306 14.21673673
231 -7.90572308 5.16714306
232 10.18887061 -7.90572308
233 -8.18219524 10.18887061
234 -3.00909151 -8.18219524
235 -5.14392632 -3.00909151
236 -8.51092914 -5.14392632
237 -10.54694654 -8.51092914
238 -0.91575547 -10.54694654
239 7.51628655 -0.91575547
240 8.87757546 7.51628655
241 -9.82936758 8.87757546
242 5.02680119 -9.82936758
243 1.72440844 5.02680119
244 -3.20198680 1.72440844
245 -4.32300263 -3.20198680
246 -4.45678395 -4.32300263
247 7.18327953 -4.45678395
248 5.35061560 7.18327953
249 11.17546646 5.35061560
250 4.44390738 11.17546646
251 -1.94147718 4.44390738
252 -8.22755074 -1.94147718
253 1.89194697 -8.22755074
254 -1.45404601 1.89194697
255 -5.56760418 -1.45404601
256 4.12195211 -5.56760418
257 9.75875655 4.12195211
258 -4.69586932 9.75875655
259 -0.09437979 -4.69586932
260 -6.02707616 -0.09437979
261 12.60382969 -6.02707616
262 7.36144946 12.60382969
263 9.34810211 7.36144946
264 -2.06171560 9.34810211
265 3.32883640 -2.06171560
266 2.07544853 3.32883640
267 5.10392219 2.07544853
268 5.42265761 5.10392219
269 -8.40003298 5.42265761
270 7.27387035 -8.40003298
271 -6.06520604 7.27387035
272 -5.20375259 -6.06520604
273 4.27502270 -5.20375259
274 2.26485655 4.27502270
275 4.60480857 2.26485655
276 -8.26602256 4.60480857
277 8.61666491 -8.26602256
278 6.00382198 8.61666491
279 -7.81030943 6.00382198
280 -8.14083116 -7.81030943
281 7.79522242 -8.14083116
282 -10.68411515 7.79522242
283 9.07737881 -10.68411515
284 2.87329372 9.07737881
285 -2.88807583 2.87329372
286 -0.66686571 -2.88807583
287 -5.88679427 -0.66686571
288 5.00052784 -5.88679427
289 -3.40427043 5.00052784
290 0.80759025 -3.40427043
291 1.50873254 0.80759025
292 5.90147788 1.50873254
293 -1.20761734 5.90147788
294 -2.06793087 -1.20761734
295 7.00402074 -2.06793087
296 -3.44241389 7.00402074
297 -2.27588038 -3.44241389
298 1.43864033 -2.27588038
299 -9.18587557 1.43864033
300 -0.27948877 -9.18587557
301 -3.62835849 -0.27948877
302 4.30854293 -3.62835849
303 6.04301201 4.30854293
304 3.29753777 6.04301201
305 1.14317795 3.29753777
306 -1.13694483 1.14317795
307 -5.49157835 -1.13694483
308 -14.53987733 -5.49157835
309 -5.85716962 -14.53987733
310 6.08482233 -5.85716962
311 -1.37265742 6.08482233
312 2.42458966 -1.37265742
313 -0.85151307 2.42458966
314 2.36096439 -0.85151307
315 17.29072093 2.36096439
316 9.56194994 17.29072093
317 -4.88647525 9.56194994
318 1.97349603 -4.88647525
319 3.26395725 1.97349603
320 -3.53962449 3.26395725
321 -4.65521252 -3.53962449
322 -2.11627080 -4.65521252
323 -4.92468490 -2.11627080
324 9.50951260 -4.92468490
325 4.58502617 9.50951260
326 -4.88331984 4.58502617
327 -6.59177443 -4.88331984
328 1.46117478 -6.59177443
329 1.27303858 1.46117478
330 1.98445535 1.27303858
331 6.17079773 1.98445535
332 4.03593447 6.17079773
333 -0.36197644 4.03593447
334 -4.95207734 -0.36197644
335 -1.88786669 -4.95207734
336 -13.03757010 -1.88786669
337 1.65582318 -13.03757010
338 -5.92501374 1.65582318
339 -8.33632844 -5.92501374
340 -3.98610703 -8.33632844
341 7.46642540 -3.98610703
342 6.29998903 7.46642540
343 -8.66610415 6.29998903
344 -1.49158751 -8.66610415
345 -4.53857759 -1.49158751
346 -11.59228440 -4.53857759
347 6.42219031 -11.59228440
348 -1.00914315 6.42219031
349 -5.36585954 -1.00914315
350 -3.12359932 -5.36585954
351 -9.47747224 -3.12359932
352 0.95263428 -9.47747224
353 -5.34149744 0.95263428
354 -0.14595779 -5.34149744
355 -1.36296483 -0.14595779
356 -6.78026894 -1.36296483
357 0.40352550 -6.78026894
358 2.90313960 0.40352550
359 4.64810777 2.90313960
360 2.56253041 4.64810777
361 -11.14149156 2.56253041
362 8.12397222 -11.14149156
363 5.18544159 8.12397222
364 1.10595393 5.18544159
365 1.14163791 1.10595393
366 -6.26388136 1.14163791
367 2.08445893 -6.26388136
368 2.99749618 2.08445893
369 6.11381289 2.99749618
370 6.46143611 6.11381289
371 -4.38353054 6.46143611
372 2.12009090 -4.38353054
373 -9.87140407 2.12009090
374 4.47086546 -9.87140407
375 -1.38968363 4.47086546
376 2.86548604 -1.38968363
377 2.63141478 2.86548604
378 7.40537887 2.63141478
379 5.06355781 7.40537887
380 -10.04693680 5.06355781
381 -4.12178954 -10.04693680
382 -6.19008465 -4.12178954
383 2.77992049 -6.19008465
384 1.69502553 2.77992049
385 4.86653841 1.69502553
386 0.68373368 4.86653841
387 -4.72825339 0.68373368
388 2.25580612 -4.72825339
389 -1.17306994 2.25580612
390 -11.26109414 -1.17306994
391 0.47028855 -11.26109414
392 -8.64520273 0.47028855
393 -2.58314398 -8.64520273
394 -3.99572325 -2.58314398
395 -0.45155133 -3.99572325
396 -9.16346576 -0.45155133
397 6.89845246 -9.16346576
398 10.19880746 6.89845246
399 8.66517048 10.19880746
400 -11.75834141 8.66517048
401 -2.26830540 -11.75834141
402 -6.80943262 -2.26830540
403 9.22092553 -6.80943262
404 2.61618336 9.22092553
405 -6.53750922 2.61618336
406 -4.52913521 -6.53750922
407 -3.41748271 -4.52913521
408 -5.52858918 -3.41748271
409 -8.90031200 -5.52858918
410 -7.06551918 -8.90031200
411 -5.18549558 -7.06551918
412 5.75121377 -5.18549558
413 -0.89161960 5.75121377
414 0.52950603 -0.89161960
415 9.66540444 0.52950603
416 -9.19734452 9.66540444
417 -0.43426216 -9.19734452
418 0.29161822 -0.43426216
419 -3.42102775 0.29161822
420 -1.47166349 -3.42102775
421 10.18174729 -1.47166349
422 -2.33453413 10.18174729
423 0.69742927 -2.33453413
424 5.59880773 0.69742927
425 1.18713030 5.59880773
426 2.01259611 1.18713030
427 2.51146714 2.01259611
428 -2.97940588 2.51146714
429 -12.24460023 -2.97940588
430 0.39910482 -12.24460023
431 -0.39839146 0.39910482
432 1.44253977 -0.39839146
433 3.60719338 1.44253977
434 -0.51521105 3.60719338
435 3.03772656 -0.51521105
436 -9.39366745 3.03772656
437 -1.57195533 -9.39366745
438 4.73500781 -1.57195533
439 -7.80773588 4.73500781
440 -5.20404701 -7.80773588
441 3.13155609 -5.20404701
442 -0.62983483 3.13155609
443 -5.70925470 -0.62983483
444 -1.37986159 -5.70925470
445 3.93484388 -1.37986159
446 -0.55465782 3.93484388
447 -2.96744057 -0.55465782
448 3.31197872 -2.96744057
449 2.77451969 3.31197872
450 -0.69971212 2.77451969
451 3.26783329 -0.69971212
452 -8.22308117 3.26783329
453 3.99238940 -8.22308117
454 5.85912810 3.99238940
455 -0.74792744 5.85912810
456 2.54059394 -0.74792744
457 7.26756087 2.54059394
458 -6.16146994 7.26756087
459 -7.01843531 -6.16146994
460 4.52975755 -7.01843531
461 6.84866612 4.52975755
462 0.93282460 6.84866612
463 -8.58090396 0.93282460
464 -7.50384406 -8.58090396
465 -4.97813514 -7.50384406
466 2.48309548 -4.97813514
467 -7.47797391 2.48309548
468 0.05246946 -7.47797391
469 4.01451432 0.05246946
470 -2.36254092 4.01451432
471 2.42060847 -2.36254092
472 -6.12550004 2.42060847
473 0.90357220 -6.12550004
474 -5.15969384 0.90357220
475 7.99634660 -5.15969384
476 -4.48382732 7.99634660
477 -5.96733881 -4.48382732
478 -0.58341198 -5.96733881
479 -3.63661784 -0.58341198
480 -3.50712074 -3.63661784
481 -0.98135301 -3.50712074
482 4.15692236 -0.98135301
483 7.91791339 4.15692236
484 -1.33142122 7.91791339
485 9.24202701 -1.33142122
486 9.03492795 9.24202701
487 -6.84595118 9.03492795
488 2.95275483 -6.84595118
489 2.48540946 2.95275483
490 -2.28047079 2.48540946
491 -0.69749417 -2.28047079
492 9.16226414 -0.69749417
493 1.53536251 9.16226414
494 -7.15600097 1.53536251
495 4.38932142 -7.15600097
496 1.48032558 4.38932142
497 9.09816919 1.48032558
498 4.43002151 9.09816919
499 3.54850342 4.43002151
500 6.88921616 3.54850342
501 10.93983509 6.88921616
502 6.51399084 10.93983509
503 8.09361987 6.51399084
504 NA 8.09361987
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 9.90433246 3.20000572
[2,] 6.39018514 9.90433246
[3,] 3.87958336 6.39018514
[4,] -3.98174843 3.87958336
[5,] -5.66417954 -3.98174843
[6,] 0.79151384 -5.66417954
[7,] 4.27936869 0.79151384
[8,] -0.17562327 4.27936869
[9,] -5.08728107 -0.17562327
[10,] -6.69497445 -5.08728107
[11,] -0.19132596 -6.69497445
[12,] -4.13803812 -0.19132596
[13,] -1.82131697 -4.13803812
[14,] 13.12557861 -1.82131697
[15,] 4.22826218 13.12557861
[16,] 5.12570319 4.22826218
[17,] 3.02833612 5.12570319
[18,] -15.75634053 3.02833612
[19,] 6.44666747 -15.75634053
[20,] 1.23468972 6.44666747
[21,] 9.60183893 1.23468972
[22,] -4.03003992 9.60183893
[23,] -6.46234974 -4.03003992
[24,] 4.78846171 -6.46234974
[25,] 0.31838011 4.78846171
[26,] -1.27656977 0.31838011
[27,] -1.18722637 -1.27656977
[28,] 2.31629174 -1.18722637
[29,] -1.96616602 2.31629174
[30,] -2.32007168 -1.96616602
[31,] 1.40631174 -2.32007168
[32,] -5.85699552 1.40631174
[33,] -6.60080870 -5.85699552
[34,] 6.00295131 -6.60080870
[35,] 5.22216883 6.00295131
[36,] -7.75108921 5.22216883
[37,] -7.51936815 -7.75108921
[38,] 10.14653211 -7.51936815
[39,] 1.36792277 10.14653211
[40,] 0.32424332 1.36792277
[41,] 4.09540395 0.32424332
[42,] 7.75225375 4.09540395
[43,] 1.86075923 7.75225375
[44,] -6.15590302 1.86075923
[45,] -3.09288020 -6.15590302
[46,] -2.05048385 -3.09288020
[47,] -7.63404934 -2.05048385
[48,] 1.81545745 -7.63404934
[49,] 1.27984833 1.81545745
[50,] -6.42807402 1.27984833
[51,] -7.58505130 -6.42807402
[52,] 4.17127225 -7.58505130
[53,] -3.07705659 4.17127225
[54,] -1.56059287 -3.07705659
[55,] -6.24218863 -1.56059287
[56,] 5.70290084 -6.24218863
[57,] -3.78923142 5.70290084
[58,] -2.59366255 -3.78923142
[59,] 5.05630565 -2.59366255
[60,] 3.13097022 5.05630565
[61,] 1.88035908 3.13097022
[62,] -2.32602703 1.88035908
[63,] -0.19513843 -2.32602703
[64,] 6.80874175 -0.19513843
[65,] -7.86851173 6.80874175
[66,] 12.17727653 -7.86851173
[67,] -2.19183655 12.17727653
[68,] -2.42268861 -2.19183655
[69,] 3.59314062 -2.42268861
[70,] -0.85805004 3.59314062
[71,] -5.01551076 -0.85805004
[72,] 7.91422874 -5.01551076
[73,] 0.14018804 7.91422874
[74,] -10.96254724 0.14018804
[75,] 4.40708046 -10.96254724
[76,] 6.92646450 4.40708046
[77,] -1.90779529 6.92646450
[78,] 6.10984628 -1.90779529
[79,] 0.16050377 6.10984628
[80,] 5.92405900 0.16050377
[81,] 4.11021376 5.92405900
[82,] -9.65253523 4.11021376
[83,] -3.19967049 -9.65253523
[84,] -6.27299830 -3.19967049
[85,] -0.72571652 -6.27299830
[86,] -0.18348521 -0.72571652
[87,] -5.80825497 -0.18348521
[88,] -7.53246874 -5.80825497
[89,] -1.71894365 -7.53246874
[90,] 5.07946547 -1.71894365
[91,] 0.13513340 5.07946547
[92,] 2.90846085 0.13513340
[93,] -6.80034895 2.90846085
[94,] 11.31962528 -6.80034895
[95,] -3.46520100 11.31962528
[96,] -3.17599733 -3.46520100
[97,] 8.87290932 -3.17599733
[98,] 7.44764982 8.87290932
[99,] 0.86044771 7.44764982
[100,] 3.61873959 0.86044771
[101,] 1.55614537 3.61873959
[102,] -7.16112991 1.55614537
[103,] -2.17226112 -7.16112991
[104,] -1.46996525 -2.17226112
[105,] -7.03398041 -1.46996525
[106,] -1.72094925 -7.03398041
[107,] -6.93567985 -1.72094925
[108,] 0.86273821 -6.93567985
[109,] 11.75114071 0.86273821
[110,] 3.11600438 11.75114071
[111,] -8.71722137 3.11600438
[112,] 1.77442732 -8.71722137
[113,] -7.90900393 1.77442732
[114,] 5.64126248 -7.90900393
[115,] -3.13275869 5.64126248
[116,] -4.34920315 -3.13275869
[117,] -1.89164169 -4.34920315
[118,] -2.49346903 -1.89164169
[119,] 0.16857127 -2.49346903
[120,] 5.78481400 0.16857127
[121,] 5.27984774 5.78481400
[122,] 0.63695816 5.27984774
[123,] 8.54099331 0.63695816
[124,] 4.24786705 8.54099331
[125,] 0.24304618 4.24786705
[126,] -7.36594750 0.24304618
[127,] 9.92997834 -7.36594750
[128,] 1.47925424 9.92997834
[129,] 1.60937560 1.47925424
[130,] 11.35044951 1.60937560
[131,] 5.78666874 11.35044951
[132,] 6.82297650 5.78666874
[133,] 10.93409387 6.82297650
[134,] 2.30467398 10.93409387
[135,] -7.19789452 2.30467398
[136,] -0.21980488 -7.19789452
[137,] -5.21659622 -0.21980488
[138,] 5.70596145 -5.21659622
[139,] 5.59228067 5.70596145
[140,] 7.54500326 5.59228067
[141,] -7.40141475 7.54500326
[142,] 0.22627528 -7.40141475
[143,] 0.28876231 0.22627528
[144,] 4.86785418 0.28876231
[145,] -3.39071177 4.86785418
[146,] -1.43570085 -3.39071177
[147,] 0.66900013 -1.43570085
[148,] 0.33698497 0.66900013
[149,] -3.96426584 0.33698497
[150,] 7.45063969 -3.96426584
[151,] -8.49220692 7.45063969
[152,] 1.97201588 -8.49220692
[153,] 3.79235633 1.97201588
[154,] -2.44910590 3.79235633
[155,] 0.17041421 -2.44910590
[156,] -1.94761702 0.17041421
[157,] 7.51105496 -1.94761702
[158,] -6.90283349 7.51105496
[159,] -6.06288605 -6.90283349
[160,] 4.56971335 -6.06288605
[161,] -1.51625575 4.56971335
[162,] 11.44229898 -1.51625575
[163,] -1.07539237 11.44229898
[164,] -5.75791633 -1.07539237
[165,] -5.58116183 -5.75791633
[166,] -4.25474303 -5.58116183
[167,] -11.95412293 -4.25474303
[168,] -5.00122158 -11.95412293
[169,] -7.73862552 -5.00122158
[170,] -4.33344257 -7.73862552
[171,] 9.80082345 -4.33344257
[172,] -3.26967666 9.80082345
[173,] -0.30622534 -3.26967666
[174,] -3.03048750 -0.30622534
[175,] 14.87086697 -3.03048750
[176,] -0.35328254 14.87086697
[177,] 0.12924806 -0.35328254
[178,] 2.06544217 0.12924806
[179,] 11.63356114 2.06544217
[180,] -4.57431469 11.63356114
[181,] 5.16263489 -4.57431469
[182,] 9.21428709 5.16263489
[183,] -1.03471274 9.21428709
[184,] 0.92743157 -1.03471274
[185,] -8.71394330 0.92743157
[186,] 6.19671366 -8.71394330
[187,] 2.92951605 6.19671366
[188,] 2.49958535 2.92951605
[189,] 6.47072589 2.49958535
[190,] 6.63499727 6.47072589
[191,] 3.88564277 6.63499727
[192,] 0.66404339 3.88564277
[193,] 4.55263898 0.66404339
[194,] 2.60976160 4.55263898
[195,] -10.98344856 2.60976160
[196,] 1.80331152 -10.98344856
[197,] 0.19973171 1.80331152
[198,] -7.72630772 0.19973171
[199,] 5.13760172 -7.72630772
[200,] -5.79531348 5.13760172
[201,] -1.60924649 -5.79531348
[202,] -3.90699821 -1.60924649
[203,] -2.17403270 -3.90699821
[204,] -0.74182367 -2.17403270
[205,] 4.45615463 -0.74182367
[206,] -2.32487802 4.45615463
[207,] -5.83183995 -2.32487802
[208,] 4.05100714 -5.83183995
[209,] -6.61185983 4.05100714
[210,] -4.81869585 -6.61185983
[211,] -2.09488971 -4.81869585
[212,] -0.60469154 -2.09488971
[213,] 2.53574560 -0.60469154
[214,] 3.08107673 2.53574560
[215,] 1.47844080 3.08107673
[216,] -5.43483650 1.47844080
[217,] -2.83764343 -5.43483650
[218,] -4.66930181 -2.83764343
[219,] -5.49309059 -4.66930181
[220,] -0.63362517 -5.49309059
[221,] -15.98323495 -0.63362517
[222,] -1.39050680 -15.98323495
[223,] 0.72050294 -1.39050680
[224,] -8.40258495 0.72050294
[225,] 4.41951645 -8.40258495
[226,] 4.70568009 4.41951645
[227,] -5.05612103 4.70568009
[228,] -3.02686031 -5.05612103
[229,] 14.21673673 -3.02686031
[230,] 5.16714306 14.21673673
[231,] -7.90572308 5.16714306
[232,] 10.18887061 -7.90572308
[233,] -8.18219524 10.18887061
[234,] -3.00909151 -8.18219524
[235,] -5.14392632 -3.00909151
[236,] -8.51092914 -5.14392632
[237,] -10.54694654 -8.51092914
[238,] -0.91575547 -10.54694654
[239,] 7.51628655 -0.91575547
[240,] 8.87757546 7.51628655
[241,] -9.82936758 8.87757546
[242,] 5.02680119 -9.82936758
[243,] 1.72440844 5.02680119
[244,] -3.20198680 1.72440844
[245,] -4.32300263 -3.20198680
[246,] -4.45678395 -4.32300263
[247,] 7.18327953 -4.45678395
[248,] 5.35061560 7.18327953
[249,] 11.17546646 5.35061560
[250,] 4.44390738 11.17546646
[251,] -1.94147718 4.44390738
[252,] -8.22755074 -1.94147718
[253,] 1.89194697 -8.22755074
[254,] -1.45404601 1.89194697
[255,] -5.56760418 -1.45404601
[256,] 4.12195211 -5.56760418
[257,] 9.75875655 4.12195211
[258,] -4.69586932 9.75875655
[259,] -0.09437979 -4.69586932
[260,] -6.02707616 -0.09437979
[261,] 12.60382969 -6.02707616
[262,] 7.36144946 12.60382969
[263,] 9.34810211 7.36144946
[264,] -2.06171560 9.34810211
[265,] 3.32883640 -2.06171560
[266,] 2.07544853 3.32883640
[267,] 5.10392219 2.07544853
[268,] 5.42265761 5.10392219
[269,] -8.40003298 5.42265761
[270,] 7.27387035 -8.40003298
[271,] -6.06520604 7.27387035
[272,] -5.20375259 -6.06520604
[273,] 4.27502270 -5.20375259
[274,] 2.26485655 4.27502270
[275,] 4.60480857 2.26485655
[276,] -8.26602256 4.60480857
[277,] 8.61666491 -8.26602256
[278,] 6.00382198 8.61666491
[279,] -7.81030943 6.00382198
[280,] -8.14083116 -7.81030943
[281,] 7.79522242 -8.14083116
[282,] -10.68411515 7.79522242
[283,] 9.07737881 -10.68411515
[284,] 2.87329372 9.07737881
[285,] -2.88807583 2.87329372
[286,] -0.66686571 -2.88807583
[287,] -5.88679427 -0.66686571
[288,] 5.00052784 -5.88679427
[289,] -3.40427043 5.00052784
[290,] 0.80759025 -3.40427043
[291,] 1.50873254 0.80759025
[292,] 5.90147788 1.50873254
[293,] -1.20761734 5.90147788
[294,] -2.06793087 -1.20761734
[295,] 7.00402074 -2.06793087
[296,] -3.44241389 7.00402074
[297,] -2.27588038 -3.44241389
[298,] 1.43864033 -2.27588038
[299,] -9.18587557 1.43864033
[300,] -0.27948877 -9.18587557
[301,] -3.62835849 -0.27948877
[302,] 4.30854293 -3.62835849
[303,] 6.04301201 4.30854293
[304,] 3.29753777 6.04301201
[305,] 1.14317795 3.29753777
[306,] -1.13694483 1.14317795
[307,] -5.49157835 -1.13694483
[308,] -14.53987733 -5.49157835
[309,] -5.85716962 -14.53987733
[310,] 6.08482233 -5.85716962
[311,] -1.37265742 6.08482233
[312,] 2.42458966 -1.37265742
[313,] -0.85151307 2.42458966
[314,] 2.36096439 -0.85151307
[315,] 17.29072093 2.36096439
[316,] 9.56194994 17.29072093
[317,] -4.88647525 9.56194994
[318,] 1.97349603 -4.88647525
[319,] 3.26395725 1.97349603
[320,] -3.53962449 3.26395725
[321,] -4.65521252 -3.53962449
[322,] -2.11627080 -4.65521252
[323,] -4.92468490 -2.11627080
[324,] 9.50951260 -4.92468490
[325,] 4.58502617 9.50951260
[326,] -4.88331984 4.58502617
[327,] -6.59177443 -4.88331984
[328,] 1.46117478 -6.59177443
[329,] 1.27303858 1.46117478
[330,] 1.98445535 1.27303858
[331,] 6.17079773 1.98445535
[332,] 4.03593447 6.17079773
[333,] -0.36197644 4.03593447
[334,] -4.95207734 -0.36197644
[335,] -1.88786669 -4.95207734
[336,] -13.03757010 -1.88786669
[337,] 1.65582318 -13.03757010
[338,] -5.92501374 1.65582318
[339,] -8.33632844 -5.92501374
[340,] -3.98610703 -8.33632844
[341,] 7.46642540 -3.98610703
[342,] 6.29998903 7.46642540
[343,] -8.66610415 6.29998903
[344,] -1.49158751 -8.66610415
[345,] -4.53857759 -1.49158751
[346,] -11.59228440 -4.53857759
[347,] 6.42219031 -11.59228440
[348,] -1.00914315 6.42219031
[349,] -5.36585954 -1.00914315
[350,] -3.12359932 -5.36585954
[351,] -9.47747224 -3.12359932
[352,] 0.95263428 -9.47747224
[353,] -5.34149744 0.95263428
[354,] -0.14595779 -5.34149744
[355,] -1.36296483 -0.14595779
[356,] -6.78026894 -1.36296483
[357,] 0.40352550 -6.78026894
[358,] 2.90313960 0.40352550
[359,] 4.64810777 2.90313960
[360,] 2.56253041 4.64810777
[361,] -11.14149156 2.56253041
[362,] 8.12397222 -11.14149156
[363,] 5.18544159 8.12397222
[364,] 1.10595393 5.18544159
[365,] 1.14163791 1.10595393
[366,] -6.26388136 1.14163791
[367,] 2.08445893 -6.26388136
[368,] 2.99749618 2.08445893
[369,] 6.11381289 2.99749618
[370,] 6.46143611 6.11381289
[371,] -4.38353054 6.46143611
[372,] 2.12009090 -4.38353054
[373,] -9.87140407 2.12009090
[374,] 4.47086546 -9.87140407
[375,] -1.38968363 4.47086546
[376,] 2.86548604 -1.38968363
[377,] 2.63141478 2.86548604
[378,] 7.40537887 2.63141478
[379,] 5.06355781 7.40537887
[380,] -10.04693680 5.06355781
[381,] -4.12178954 -10.04693680
[382,] -6.19008465 -4.12178954
[383,] 2.77992049 -6.19008465
[384,] 1.69502553 2.77992049
[385,] 4.86653841 1.69502553
[386,] 0.68373368 4.86653841
[387,] -4.72825339 0.68373368
[388,] 2.25580612 -4.72825339
[389,] -1.17306994 2.25580612
[390,] -11.26109414 -1.17306994
[391,] 0.47028855 -11.26109414
[392,] -8.64520273 0.47028855
[393,] -2.58314398 -8.64520273
[394,] -3.99572325 -2.58314398
[395,] -0.45155133 -3.99572325
[396,] -9.16346576 -0.45155133
[397,] 6.89845246 -9.16346576
[398,] 10.19880746 6.89845246
[399,] 8.66517048 10.19880746
[400,] -11.75834141 8.66517048
[401,] -2.26830540 -11.75834141
[402,] -6.80943262 -2.26830540
[403,] 9.22092553 -6.80943262
[404,] 2.61618336 9.22092553
[405,] -6.53750922 2.61618336
[406,] -4.52913521 -6.53750922
[407,] -3.41748271 -4.52913521
[408,] -5.52858918 -3.41748271
[409,] -8.90031200 -5.52858918
[410,] -7.06551918 -8.90031200
[411,] -5.18549558 -7.06551918
[412,] 5.75121377 -5.18549558
[413,] -0.89161960 5.75121377
[414,] 0.52950603 -0.89161960
[415,] 9.66540444 0.52950603
[416,] -9.19734452 9.66540444
[417,] -0.43426216 -9.19734452
[418,] 0.29161822 -0.43426216
[419,] -3.42102775 0.29161822
[420,] -1.47166349 -3.42102775
[421,] 10.18174729 -1.47166349
[422,] -2.33453413 10.18174729
[423,] 0.69742927 -2.33453413
[424,] 5.59880773 0.69742927
[425,] 1.18713030 5.59880773
[426,] 2.01259611 1.18713030
[427,] 2.51146714 2.01259611
[428,] -2.97940588 2.51146714
[429,] -12.24460023 -2.97940588
[430,] 0.39910482 -12.24460023
[431,] -0.39839146 0.39910482
[432,] 1.44253977 -0.39839146
[433,] 3.60719338 1.44253977
[434,] -0.51521105 3.60719338
[435,] 3.03772656 -0.51521105
[436,] -9.39366745 3.03772656
[437,] -1.57195533 -9.39366745
[438,] 4.73500781 -1.57195533
[439,] -7.80773588 4.73500781
[440,] -5.20404701 -7.80773588
[441,] 3.13155609 -5.20404701
[442,] -0.62983483 3.13155609
[443,] -5.70925470 -0.62983483
[444,] -1.37986159 -5.70925470
[445,] 3.93484388 -1.37986159
[446,] -0.55465782 3.93484388
[447,] -2.96744057 -0.55465782
[448,] 3.31197872 -2.96744057
[449,] 2.77451969 3.31197872
[450,] -0.69971212 2.77451969
[451,] 3.26783329 -0.69971212
[452,] -8.22308117 3.26783329
[453,] 3.99238940 -8.22308117
[454,] 5.85912810 3.99238940
[455,] -0.74792744 5.85912810
[456,] 2.54059394 -0.74792744
[457,] 7.26756087 2.54059394
[458,] -6.16146994 7.26756087
[459,] -7.01843531 -6.16146994
[460,] 4.52975755 -7.01843531
[461,] 6.84866612 4.52975755
[462,] 0.93282460 6.84866612
[463,] -8.58090396 0.93282460
[464,] -7.50384406 -8.58090396
[465,] -4.97813514 -7.50384406
[466,] 2.48309548 -4.97813514
[467,] -7.47797391 2.48309548
[468,] 0.05246946 -7.47797391
[469,] 4.01451432 0.05246946
[470,] -2.36254092 4.01451432
[471,] 2.42060847 -2.36254092
[472,] -6.12550004 2.42060847
[473,] 0.90357220 -6.12550004
[474,] -5.15969384 0.90357220
[475,] 7.99634660 -5.15969384
[476,] -4.48382732 7.99634660
[477,] -5.96733881 -4.48382732
[478,] -0.58341198 -5.96733881
[479,] -3.63661784 -0.58341198
[480,] -3.50712074 -3.63661784
[481,] -0.98135301 -3.50712074
[482,] 4.15692236 -0.98135301
[483,] 7.91791339 4.15692236
[484,] -1.33142122 7.91791339
[485,] 9.24202701 -1.33142122
[486,] 9.03492795 9.24202701
[487,] -6.84595118 9.03492795
[488,] 2.95275483 -6.84595118
[489,] 2.48540946 2.95275483
[490,] -2.28047079 2.48540946
[491,] -0.69749417 -2.28047079
[492,] 9.16226414 -0.69749417
[493,] 1.53536251 9.16226414
[494,] -7.15600097 1.53536251
[495,] 4.38932142 -7.15600097
[496,] 1.48032558 4.38932142
[497,] 9.09816919 1.48032558
[498,] 4.43002151 9.09816919
[499,] 3.54850342 4.43002151
[500,] 6.88921616 3.54850342
[501,] 10.93983509 6.88921616
[502,] 6.51399084 10.93983509
[503,] 8.09361987 6.51399084
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 9.90433246 3.20000572
2 6.39018514 9.90433246
3 3.87958336 6.39018514
4 -3.98174843 3.87958336
5 -5.66417954 -3.98174843
6 0.79151384 -5.66417954
7 4.27936869 0.79151384
8 -0.17562327 4.27936869
9 -5.08728107 -0.17562327
10 -6.69497445 -5.08728107
11 -0.19132596 -6.69497445
12 -4.13803812 -0.19132596
13 -1.82131697 -4.13803812
14 13.12557861 -1.82131697
15 4.22826218 13.12557861
16 5.12570319 4.22826218
17 3.02833612 5.12570319
18 -15.75634053 3.02833612
19 6.44666747 -15.75634053
20 1.23468972 6.44666747
21 9.60183893 1.23468972
22 -4.03003992 9.60183893
23 -6.46234974 -4.03003992
24 4.78846171 -6.46234974
25 0.31838011 4.78846171
26 -1.27656977 0.31838011
27 -1.18722637 -1.27656977
28 2.31629174 -1.18722637
29 -1.96616602 2.31629174
30 -2.32007168 -1.96616602
31 1.40631174 -2.32007168
32 -5.85699552 1.40631174
33 -6.60080870 -5.85699552
34 6.00295131 -6.60080870
35 5.22216883 6.00295131
36 -7.75108921 5.22216883
37 -7.51936815 -7.75108921
38 10.14653211 -7.51936815
39 1.36792277 10.14653211
40 0.32424332 1.36792277
41 4.09540395 0.32424332
42 7.75225375 4.09540395
43 1.86075923 7.75225375
44 -6.15590302 1.86075923
45 -3.09288020 -6.15590302
46 -2.05048385 -3.09288020
47 -7.63404934 -2.05048385
48 1.81545745 -7.63404934
49 1.27984833 1.81545745
50 -6.42807402 1.27984833
51 -7.58505130 -6.42807402
52 4.17127225 -7.58505130
53 -3.07705659 4.17127225
54 -1.56059287 -3.07705659
55 -6.24218863 -1.56059287
56 5.70290084 -6.24218863
57 -3.78923142 5.70290084
58 -2.59366255 -3.78923142
59 5.05630565 -2.59366255
60 3.13097022 5.05630565
61 1.88035908 3.13097022
62 -2.32602703 1.88035908
63 -0.19513843 -2.32602703
64 6.80874175 -0.19513843
65 -7.86851173 6.80874175
66 12.17727653 -7.86851173
67 -2.19183655 12.17727653
68 -2.42268861 -2.19183655
69 3.59314062 -2.42268861
70 -0.85805004 3.59314062
71 -5.01551076 -0.85805004
72 7.91422874 -5.01551076
73 0.14018804 7.91422874
74 -10.96254724 0.14018804
75 4.40708046 -10.96254724
76 6.92646450 4.40708046
77 -1.90779529 6.92646450
78 6.10984628 -1.90779529
79 0.16050377 6.10984628
80 5.92405900 0.16050377
81 4.11021376 5.92405900
82 -9.65253523 4.11021376
83 -3.19967049 -9.65253523
84 -6.27299830 -3.19967049
85 -0.72571652 -6.27299830
86 -0.18348521 -0.72571652
87 -5.80825497 -0.18348521
88 -7.53246874 -5.80825497
89 -1.71894365 -7.53246874
90 5.07946547 -1.71894365
91 0.13513340 5.07946547
92 2.90846085 0.13513340
93 -6.80034895 2.90846085
94 11.31962528 -6.80034895
95 -3.46520100 11.31962528
96 -3.17599733 -3.46520100
97 8.87290932 -3.17599733
98 7.44764982 8.87290932
99 0.86044771 7.44764982
100 3.61873959 0.86044771
101 1.55614537 3.61873959
102 -7.16112991 1.55614537
103 -2.17226112 -7.16112991
104 -1.46996525 -2.17226112
105 -7.03398041 -1.46996525
106 -1.72094925 -7.03398041
107 -6.93567985 -1.72094925
108 0.86273821 -6.93567985
109 11.75114071 0.86273821
110 3.11600438 11.75114071
111 -8.71722137 3.11600438
112 1.77442732 -8.71722137
113 -7.90900393 1.77442732
114 5.64126248 -7.90900393
115 -3.13275869 5.64126248
116 -4.34920315 -3.13275869
117 -1.89164169 -4.34920315
118 -2.49346903 -1.89164169
119 0.16857127 -2.49346903
120 5.78481400 0.16857127
121 5.27984774 5.78481400
122 0.63695816 5.27984774
123 8.54099331 0.63695816
124 4.24786705 8.54099331
125 0.24304618 4.24786705
126 -7.36594750 0.24304618
127 9.92997834 -7.36594750
128 1.47925424 9.92997834
129 1.60937560 1.47925424
130 11.35044951 1.60937560
131 5.78666874 11.35044951
132 6.82297650 5.78666874
133 10.93409387 6.82297650
134 2.30467398 10.93409387
135 -7.19789452 2.30467398
136 -0.21980488 -7.19789452
137 -5.21659622 -0.21980488
138 5.70596145 -5.21659622
139 5.59228067 5.70596145
140 7.54500326 5.59228067
141 -7.40141475 7.54500326
142 0.22627528 -7.40141475
143 0.28876231 0.22627528
144 4.86785418 0.28876231
145 -3.39071177 4.86785418
146 -1.43570085 -3.39071177
147 0.66900013 -1.43570085
148 0.33698497 0.66900013
149 -3.96426584 0.33698497
150 7.45063969 -3.96426584
151 -8.49220692 7.45063969
152 1.97201588 -8.49220692
153 3.79235633 1.97201588
154 -2.44910590 3.79235633
155 0.17041421 -2.44910590
156 -1.94761702 0.17041421
157 7.51105496 -1.94761702
158 -6.90283349 7.51105496
159 -6.06288605 -6.90283349
160 4.56971335 -6.06288605
161 -1.51625575 4.56971335
162 11.44229898 -1.51625575
163 -1.07539237 11.44229898
164 -5.75791633 -1.07539237
165 -5.58116183 -5.75791633
166 -4.25474303 -5.58116183
167 -11.95412293 -4.25474303
168 -5.00122158 -11.95412293
169 -7.73862552 -5.00122158
170 -4.33344257 -7.73862552
171 9.80082345 -4.33344257
172 -3.26967666 9.80082345
173 -0.30622534 -3.26967666
174 -3.03048750 -0.30622534
175 14.87086697 -3.03048750
176 -0.35328254 14.87086697
177 0.12924806 -0.35328254
178 2.06544217 0.12924806
179 11.63356114 2.06544217
180 -4.57431469 11.63356114
181 5.16263489 -4.57431469
182 9.21428709 5.16263489
183 -1.03471274 9.21428709
184 0.92743157 -1.03471274
185 -8.71394330 0.92743157
186 6.19671366 -8.71394330
187 2.92951605 6.19671366
188 2.49958535 2.92951605
189 6.47072589 2.49958535
190 6.63499727 6.47072589
191 3.88564277 6.63499727
192 0.66404339 3.88564277
193 4.55263898 0.66404339
194 2.60976160 4.55263898
195 -10.98344856 2.60976160
196 1.80331152 -10.98344856
197 0.19973171 1.80331152
198 -7.72630772 0.19973171
199 5.13760172 -7.72630772
200 -5.79531348 5.13760172
201 -1.60924649 -5.79531348
202 -3.90699821 -1.60924649
203 -2.17403270 -3.90699821
204 -0.74182367 -2.17403270
205 4.45615463 -0.74182367
206 -2.32487802 4.45615463
207 -5.83183995 -2.32487802
208 4.05100714 -5.83183995
209 -6.61185983 4.05100714
210 -4.81869585 -6.61185983
211 -2.09488971 -4.81869585
212 -0.60469154 -2.09488971
213 2.53574560 -0.60469154
214 3.08107673 2.53574560
215 1.47844080 3.08107673
216 -5.43483650 1.47844080
217 -2.83764343 -5.43483650
218 -4.66930181 -2.83764343
219 -5.49309059 -4.66930181
220 -0.63362517 -5.49309059
221 -15.98323495 -0.63362517
222 -1.39050680 -15.98323495
223 0.72050294 -1.39050680
224 -8.40258495 0.72050294
225 4.41951645 -8.40258495
226 4.70568009 4.41951645
227 -5.05612103 4.70568009
228 -3.02686031 -5.05612103
229 14.21673673 -3.02686031
230 5.16714306 14.21673673
231 -7.90572308 5.16714306
232 10.18887061 -7.90572308
233 -8.18219524 10.18887061
234 -3.00909151 -8.18219524
235 -5.14392632 -3.00909151
236 -8.51092914 -5.14392632
237 -10.54694654 -8.51092914
238 -0.91575547 -10.54694654
239 7.51628655 -0.91575547
240 8.87757546 7.51628655
241 -9.82936758 8.87757546
242 5.02680119 -9.82936758
243 1.72440844 5.02680119
244 -3.20198680 1.72440844
245 -4.32300263 -3.20198680
246 -4.45678395 -4.32300263
247 7.18327953 -4.45678395
248 5.35061560 7.18327953
249 11.17546646 5.35061560
250 4.44390738 11.17546646
251 -1.94147718 4.44390738
252 -8.22755074 -1.94147718
253 1.89194697 -8.22755074
254 -1.45404601 1.89194697
255 -5.56760418 -1.45404601
256 4.12195211 -5.56760418
257 9.75875655 4.12195211
258 -4.69586932 9.75875655
259 -0.09437979 -4.69586932
260 -6.02707616 -0.09437979
261 12.60382969 -6.02707616
262 7.36144946 12.60382969
263 9.34810211 7.36144946
264 -2.06171560 9.34810211
265 3.32883640 -2.06171560
266 2.07544853 3.32883640
267 5.10392219 2.07544853
268 5.42265761 5.10392219
269 -8.40003298 5.42265761
270 7.27387035 -8.40003298
271 -6.06520604 7.27387035
272 -5.20375259 -6.06520604
273 4.27502270 -5.20375259
274 2.26485655 4.27502270
275 4.60480857 2.26485655
276 -8.26602256 4.60480857
277 8.61666491 -8.26602256
278 6.00382198 8.61666491
279 -7.81030943 6.00382198
280 -8.14083116 -7.81030943
281 7.79522242 -8.14083116
282 -10.68411515 7.79522242
283 9.07737881 -10.68411515
284 2.87329372 9.07737881
285 -2.88807583 2.87329372
286 -0.66686571 -2.88807583
287 -5.88679427 -0.66686571
288 5.00052784 -5.88679427
289 -3.40427043 5.00052784
290 0.80759025 -3.40427043
291 1.50873254 0.80759025
292 5.90147788 1.50873254
293 -1.20761734 5.90147788
294 -2.06793087 -1.20761734
295 7.00402074 -2.06793087
296 -3.44241389 7.00402074
297 -2.27588038 -3.44241389
298 1.43864033 -2.27588038
299 -9.18587557 1.43864033
300 -0.27948877 -9.18587557
301 -3.62835849 -0.27948877
302 4.30854293 -3.62835849
303 6.04301201 4.30854293
304 3.29753777 6.04301201
305 1.14317795 3.29753777
306 -1.13694483 1.14317795
307 -5.49157835 -1.13694483
308 -14.53987733 -5.49157835
309 -5.85716962 -14.53987733
310 6.08482233 -5.85716962
311 -1.37265742 6.08482233
312 2.42458966 -1.37265742
313 -0.85151307 2.42458966
314 2.36096439 -0.85151307
315 17.29072093 2.36096439
316 9.56194994 17.29072093
317 -4.88647525 9.56194994
318 1.97349603 -4.88647525
319 3.26395725 1.97349603
320 -3.53962449 3.26395725
321 -4.65521252 -3.53962449
322 -2.11627080 -4.65521252
323 -4.92468490 -2.11627080
324 9.50951260 -4.92468490
325 4.58502617 9.50951260
326 -4.88331984 4.58502617
327 -6.59177443 -4.88331984
328 1.46117478 -6.59177443
329 1.27303858 1.46117478
330 1.98445535 1.27303858
331 6.17079773 1.98445535
332 4.03593447 6.17079773
333 -0.36197644 4.03593447
334 -4.95207734 -0.36197644
335 -1.88786669 -4.95207734
336 -13.03757010 -1.88786669
337 1.65582318 -13.03757010
338 -5.92501374 1.65582318
339 -8.33632844 -5.92501374
340 -3.98610703 -8.33632844
341 7.46642540 -3.98610703
342 6.29998903 7.46642540
343 -8.66610415 6.29998903
344 -1.49158751 -8.66610415
345 -4.53857759 -1.49158751
346 -11.59228440 -4.53857759
347 6.42219031 -11.59228440
348 -1.00914315 6.42219031
349 -5.36585954 -1.00914315
350 -3.12359932 -5.36585954
351 -9.47747224 -3.12359932
352 0.95263428 -9.47747224
353 -5.34149744 0.95263428
354 -0.14595779 -5.34149744
355 -1.36296483 -0.14595779
356 -6.78026894 -1.36296483
357 0.40352550 -6.78026894
358 2.90313960 0.40352550
359 4.64810777 2.90313960
360 2.56253041 4.64810777
361 -11.14149156 2.56253041
362 8.12397222 -11.14149156
363 5.18544159 8.12397222
364 1.10595393 5.18544159
365 1.14163791 1.10595393
366 -6.26388136 1.14163791
367 2.08445893 -6.26388136
368 2.99749618 2.08445893
369 6.11381289 2.99749618
370 6.46143611 6.11381289
371 -4.38353054 6.46143611
372 2.12009090 -4.38353054
373 -9.87140407 2.12009090
374 4.47086546 -9.87140407
375 -1.38968363 4.47086546
376 2.86548604 -1.38968363
377 2.63141478 2.86548604
378 7.40537887 2.63141478
379 5.06355781 7.40537887
380 -10.04693680 5.06355781
381 -4.12178954 -10.04693680
382 -6.19008465 -4.12178954
383 2.77992049 -6.19008465
384 1.69502553 2.77992049
385 4.86653841 1.69502553
386 0.68373368 4.86653841
387 -4.72825339 0.68373368
388 2.25580612 -4.72825339
389 -1.17306994 2.25580612
390 -11.26109414 -1.17306994
391 0.47028855 -11.26109414
392 -8.64520273 0.47028855
393 -2.58314398 -8.64520273
394 -3.99572325 -2.58314398
395 -0.45155133 -3.99572325
396 -9.16346576 -0.45155133
397 6.89845246 -9.16346576
398 10.19880746 6.89845246
399 8.66517048 10.19880746
400 -11.75834141 8.66517048
401 -2.26830540 -11.75834141
402 -6.80943262 -2.26830540
403 9.22092553 -6.80943262
404 2.61618336 9.22092553
405 -6.53750922 2.61618336
406 -4.52913521 -6.53750922
407 -3.41748271 -4.52913521
408 -5.52858918 -3.41748271
409 -8.90031200 -5.52858918
410 -7.06551918 -8.90031200
411 -5.18549558 -7.06551918
412 5.75121377 -5.18549558
413 -0.89161960 5.75121377
414 0.52950603 -0.89161960
415 9.66540444 0.52950603
416 -9.19734452 9.66540444
417 -0.43426216 -9.19734452
418 0.29161822 -0.43426216
419 -3.42102775 0.29161822
420 -1.47166349 -3.42102775
421 10.18174729 -1.47166349
422 -2.33453413 10.18174729
423 0.69742927 -2.33453413
424 5.59880773 0.69742927
425 1.18713030 5.59880773
426 2.01259611 1.18713030
427 2.51146714 2.01259611
428 -2.97940588 2.51146714
429 -12.24460023 -2.97940588
430 0.39910482 -12.24460023
431 -0.39839146 0.39910482
432 1.44253977 -0.39839146
433 3.60719338 1.44253977
434 -0.51521105 3.60719338
435 3.03772656 -0.51521105
436 -9.39366745 3.03772656
437 -1.57195533 -9.39366745
438 4.73500781 -1.57195533
439 -7.80773588 4.73500781
440 -5.20404701 -7.80773588
441 3.13155609 -5.20404701
442 -0.62983483 3.13155609
443 -5.70925470 -0.62983483
444 -1.37986159 -5.70925470
445 3.93484388 -1.37986159
446 -0.55465782 3.93484388
447 -2.96744057 -0.55465782
448 3.31197872 -2.96744057
449 2.77451969 3.31197872
450 -0.69971212 2.77451969
451 3.26783329 -0.69971212
452 -8.22308117 3.26783329
453 3.99238940 -8.22308117
454 5.85912810 3.99238940
455 -0.74792744 5.85912810
456 2.54059394 -0.74792744
457 7.26756087 2.54059394
458 -6.16146994 7.26756087
459 -7.01843531 -6.16146994
460 4.52975755 -7.01843531
461 6.84866612 4.52975755
462 0.93282460 6.84866612
463 -8.58090396 0.93282460
464 -7.50384406 -8.58090396
465 -4.97813514 -7.50384406
466 2.48309548 -4.97813514
467 -7.47797391 2.48309548
468 0.05246946 -7.47797391
469 4.01451432 0.05246946
470 -2.36254092 4.01451432
471 2.42060847 -2.36254092
472 -6.12550004 2.42060847
473 0.90357220 -6.12550004
474 -5.15969384 0.90357220
475 7.99634660 -5.15969384
476 -4.48382732 7.99634660
477 -5.96733881 -4.48382732
478 -0.58341198 -5.96733881
479 -3.63661784 -0.58341198
480 -3.50712074 -3.63661784
481 -0.98135301 -3.50712074
482 4.15692236 -0.98135301
483 7.91791339 4.15692236
484 -1.33142122 7.91791339
485 9.24202701 -1.33142122
486 9.03492795 9.24202701
487 -6.84595118 9.03492795
488 2.95275483 -6.84595118
489 2.48540946 2.95275483
490 -2.28047079 2.48540946
491 -0.69749417 -2.28047079
492 9.16226414 -0.69749417
493 1.53536251 9.16226414
494 -7.15600097 1.53536251
495 4.38932142 -7.15600097
496 1.48032558 4.38932142
497 9.09816919 1.48032558
498 4.43002151 9.09816919
499 3.54850342 4.43002151
500 6.88921616 3.54850342
501 10.93983509 6.88921616
502 6.51399084 10.93983509
503 8.09361987 6.51399084
> plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
> lines(lowess(z))
> abline(lm(z))
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/7ict11497721972.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/8omy01497721972.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/9eo9i1497721972.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/wessaorg/rcomp/tmp/1010311497721972.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
+ myeq <- paste(myeq, signif(mysum$coefficients[i,1],6), sep=' ')
+ if (rownames(mysum$coefficients)[i] != '(Intercept)') {
+ myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
+ if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
+ }
+ }
> myeq <- paste(myeq, ' + e[t]')
> a<-table.row.start(a)
> a<-table.element(a, myeq)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, mywarning)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/11cnln1497721972.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Variable',header=TRUE)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
> a<-table.element(a,'2-tail p-value',header=TRUE)
> a<-table.element(a,'1-tail p-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:k){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
+ a<-table.element(a,formatC(signif(mysum$coefficients[i,1],5),format='g',flag='+'))
+ a<-table.element(a,formatC(signif(mysum$coefficients[i,2],5),format='g',flag=' '))
+ a<-table.element(a,formatC(signif(mysum$coefficients[i,3],4),format='e',flag='+'))
+ a<-table.element(a,formatC(signif(mysum$coefficients[i,4],4),format='g',flag=' '))
+ a<-table.element(a,formatC(signif(mysum$coefficients[i,4]/2,4),format='g',flag=' '))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/12lm0c1497721972.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple R',1,TRUE)
> a<-table.element(a,formatC(signif(sqrt(mysum$r.squared),6),format='g',flag=' '))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'R-squared',1,TRUE)
> a<-table.element(a,formatC(signif(mysum$r.squared,6),format='g',flag=' '))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Adjusted R-squared',1,TRUE)
> a<-table.element(a,formatC(signif(mysum$adj.r.squared,6),format='g',flag=' '))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (value)',1,TRUE)
> a<-table.element(a,formatC(signif(mysum$fstatistic[1],6),format='g',flag=' '))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
> a<-table.element(a, signif(mysum$fstatistic[2],6))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
> a<-table.element(a, signif(mysum$fstatistic[3],6))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'p-value',1,TRUE)
> a<-table.element(a,formatC(signif(1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]),6),format='g',flag=' '))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
> a<-table.element(a,formatC(signif(mysum$sigma,6),format='g',flag=' '))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a,formatC(signif(sum(myerror*myerror),6),format='g',flag=' '))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/13ohh81497721972.tab")
> if(n < 200) {
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a, 'Time or Index', 1, TRUE)
+ a<-table.element(a, 'Actuals', 1, TRUE)
+ a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
+ a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
+ a<-table.row.end(a)
+ for (i in 1:n) {
+ a<-table.row.start(a)
+ a<-table.element(a,i, 1, TRUE)
+ a<-table.element(a,formatC(signif(x[i],6),format='g',flag=' '))
+ a<-table.element(a,formatC(signif(x[i]-mysum$resid[i],6),format='g',flag=' '))
+ a<-table.element(a,formatC(signif(mysum$resid[i],6),format='g',flag=' '))
+ a<-table.row.end(a)
+ }
+ a<-table.end(a)
+ table.save(a,file="/var/wessaorg/rcomp/tmp/14ektj1497721972.tab")
+ if (n > n25) {
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'p-values',header=TRUE)
+ a<-table.element(a,'Alternative Hypothesis',3,header=TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'breakpoint index',header=TRUE)
+ a<-table.element(a,'greater',header=TRUE)
+ a<-table.element(a,'2-sided',header=TRUE)
+ a<-table.element(a,'less',header=TRUE)
+ a<-table.row.end(a)
+ for (mypoint in kp3:nmkm3) {
+ a<-table.row.start(a)
+ a<-table.element(a,mypoint,header=TRUE)
+ a<-table.element(a,formatC(signif(gqarr[mypoint-kp3+1,1],6),format='g',flag=' '))
+ a<-table.element(a,formatC(signif(gqarr[mypoint-kp3+1,2],6),format='g',flag=' '))
+ a<-table.element(a,formatC(signif(gqarr[mypoint-kp3+1,3],6),format='g',flag=' '))
+ a<-table.row.end(a)
+ }
+ a<-table.end(a)
+ table.save(a,file="/var/wessaorg/rcomp/tmp/15ozm81497721972.tab")
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'Description',header=TRUE)
+ a<-table.element(a,'# significant tests',header=TRUE)
+ a<-table.element(a,'% significant tests',header=TRUE)
+ a<-table.element(a,'OK/NOK',header=TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'1% type I error level',header=TRUE)
+ a<-table.element(a,signif(numsignificant1,6))
+ a<-table.element(a,formatC(signif(numsignificant1/numgqtests,6),format='g',flag=' '))
+ if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'5% type I error level',header=TRUE)
+ a<-table.element(a,signif(numsignificant5,6))
+ a<-table.element(a,signif(numsignificant5/numgqtests,6))
+ if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'10% type I error level',header=TRUE)
+ a<-table.element(a,signif(numsignificant10,6))
+ a<-table.element(a,signif(numsignificant10/numgqtests,6))
+ if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.end(a)
+ table.save(a,file="/var/wessaorg/rcomp/tmp/1664hb1497721972.tab")
+ }
+ }
>
> try(system("convert tmp/1a9fv1497721972.ps tmp/1a9fv1497721972.png",intern=TRUE))
character(0)
> try(system("convert tmp/2dots1497721972.ps tmp/2dots1497721972.png",intern=TRUE))
character(0)
> try(system("convert tmp/3k1vy1497721972.ps tmp/3k1vy1497721972.png",intern=TRUE))
character(0)
> try(system("convert tmp/4bpps1497721972.ps tmp/4bpps1497721972.png",intern=TRUE))
character(0)
> try(system("convert tmp/5a3nj1497721972.ps tmp/5a3nj1497721972.png",intern=TRUE))
character(0)
> try(system("convert tmp/6pbnx1497721972.ps tmp/6pbnx1497721972.png",intern=TRUE))
character(0)
> try(system("convert tmp/7ict11497721972.ps tmp/7ict11497721972.png",intern=TRUE))
character(0)
> try(system("convert tmp/8omy01497721972.ps tmp/8omy01497721972.png",intern=TRUE))
character(0)
> try(system("convert tmp/9eo9i1497721972.ps tmp/9eo9i1497721972.png",intern=TRUE))
character(0)
> try(system("convert tmp/1010311497721972.ps tmp/1010311497721972.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
10.692 0.695 11.579