R version 2.15.1 (2012-06-22) -- "Roasted Marshmallows"
Copyright (C) 2012 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i686-pc-linux-gnu (32-bit)
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> x <- array(list(87.28
+ ,255
+ ,87.28
+ ,280.2
+ ,87.09
+ ,299.9
+ ,86.92
+ ,339.2
+ ,87.59
+ ,374.2
+ ,90.72
+ ,393.5
+ ,90.69
+ ,389.2
+ ,90.3
+ ,381.7
+ ,89.55
+ ,375.2
+ ,88.94
+ ,369
+ ,88.41
+ ,357.4
+ ,87.82
+ ,352.1
+ ,87.07
+ ,346.5
+ ,86.82
+ ,342.9
+ ,86.4
+ ,340.3
+ ,86.02
+ ,328.3
+ ,85.66
+ ,322.9
+ ,85.32
+ ,314.3
+ ,85
+ ,308.9
+ ,84.67
+ ,294
+ ,83.94
+ ,285.6
+ ,82.83
+ ,281.2
+ ,81.95
+ ,280.3
+ ,81.19
+ ,278.8
+ ,80.48
+ ,274.5
+ ,78.86
+ ,270.4
+ ,69.47
+ ,263.4
+ ,68.77
+ ,259.9
+ ,70.06
+ ,258
+ ,73.95
+ ,262.7
+ ,75.8
+ ,284.7
+ ,77.79
+ ,311.3
+ ,81.57
+ ,322.1
+ ,83.07
+ ,327
+ ,84.34
+ ,331.3
+ ,85.1
+ ,333.3
+ ,85.25
+ ,321.4
+ ,84.26
+ ,327
+ ,83.63
+ ,320
+ ,86.44
+ ,314.7
+ ,85.3
+ ,316.7
+ ,84.1
+ ,314.4
+ ,83.36
+ ,321.3
+ ,82.48
+ ,318.2
+ ,81.58
+ ,307.2
+ ,80.47
+ ,301.3
+ ,79.34
+ ,287.5
+ ,82.13
+ ,277.7
+ ,81.69
+ ,274.4
+ ,80.7
+ ,258.8
+ ,79.88
+ ,253.3
+ ,79.16
+ ,251
+ ,78.38
+ ,248.4
+ ,77.42
+ ,249.5
+ ,76.47
+ ,246.1
+ ,75.46
+ ,244.5
+ ,74.48
+ ,243.6
+ ,78.27
+ ,244
+ ,80.7
+ ,240.8
+ ,79.91
+ ,249.8
+ ,78.75
+ ,248
+ ,77.78
+ ,259.4
+ ,81.14
+ ,260.5
+ ,81.08
+ ,260.8
+ ,80.03
+ ,261.3
+ ,78.91
+ ,259.5
+ ,78.01
+ ,256.6
+ ,76.9
+ ,257.9
+ ,75.97
+ ,256.5
+ ,81.93
+ ,254.2
+ ,80.27
+ ,253.3
+ ,78.67
+ ,253.8
+ ,77.42
+ ,255.5
+ ,76.16
+ ,257.1
+ ,74.7
+ ,257.3
+ ,76.39
+ ,253.2
+ ,76.04
+ ,252.8
+ ,74.65
+ ,252
+ ,73.29
+ ,250.7
+ ,71.79
+ ,252.2
+ ,74.39
+ ,250
+ ,74.91
+ ,251
+ ,74.54
+ ,253.4
+ ,73.08
+ ,251.2
+ ,72.75
+ ,255.6
+ ,71.32
+ ,261.1
+ ,70.38
+ ,258.9
+ ,70.35
+ ,259.9
+ ,70.01
+ ,261.2
+ ,69.36
+ ,264.7
+ ,67.77
+ ,267.1
+ ,69.26
+ ,266.4
+ ,69.8
+ ,267.7
+ ,68.38
+ ,268.6
+ ,67.62
+ ,267.5
+ ,68.39
+ ,268.5
+ ,66.95
+ ,268.5
+ ,65.21
+ ,270.5
+ ,66.64
+ ,270.9
+ ,63.45
+ ,270.1
+ ,60.66
+ ,269.3
+ ,62.34
+ ,269.8
+ ,60.32
+ ,270.1
+ ,58.64
+ ,264.9
+ ,60.46
+ ,263.7
+ ,58.59
+ ,264.8
+ ,61.87
+ ,263.7
+ ,61.85
+ ,255.9
+ ,67.44
+ ,276.2
+ ,77.06
+ ,360.1
+ ,91.74
+ ,380.5
+ ,93.15
+ ,373.7
+ ,94.15
+ ,369.8
+ ,93.11
+ ,366.6
+ ,91.51
+ ,359.3
+ ,89.96
+ ,345.8
+ ,88.16
+ ,326.2
+ ,86.98
+ ,324.5
+ ,88.03
+ ,328.1
+ ,86.24
+ ,327.5
+ ,84.65
+ ,324.4
+ ,83.23
+ ,316.5
+ ,81.7
+ ,310.9
+ ,80.25
+ ,301.5
+ ,78.8
+ ,291.7
+ ,77.51
+ ,290.4
+ ,76.2
+ ,287.4
+ ,75.04
+ ,277.7
+ ,74
+ ,281.6
+ ,75.49
+ ,288
+ ,77.14
+ ,276
+ ,76.15
+ ,272.9
+ ,76.27
+ ,283
+ ,78.19
+ ,283.3
+ ,76.49
+ ,276.8
+ ,77.31
+ ,284.5
+ ,76.65
+ ,282.7
+ ,74.99
+ ,281.2
+ ,73.51
+ ,287.4
+ ,72.07
+ ,283.1
+ ,70.59
+ ,284
+ ,71.96
+ ,285.5
+ ,76.29
+ ,289.2
+ ,74.86
+ ,292.5
+ ,74.93
+ ,296.4
+ ,71.9
+ ,305.2
+ ,71.01
+ ,303.9
+ ,77.47
+ ,311.5
+ ,75.78
+ ,316.3
+ ,76.6
+ ,316.7
+ ,76.07
+ ,322.5
+ ,74.57
+ ,317.1
+ ,73.02
+ ,309.8
+ ,72.65
+ ,303.8
+ ,73.16
+ ,290.3
+ ,71.53
+ ,293.7
+ ,69.78
+ ,291.7
+ ,67.98
+ ,296.5
+ ,69.96
+ ,289.1
+ ,72.16
+ ,288.5
+ ,70.47
+ ,293.8
+ ,68.86
+ ,297.7
+ ,67.37
+ ,305.4
+ ,65.87
+ ,302.7
+ ,72.16
+ ,302.5
+ ,71.34
+ ,303
+ ,69.93
+ ,294.5
+ ,68.44
+ ,294.1
+ ,67.16
+ ,294.5
+ ,66.01
+ ,297.1
+ ,67.25
+ ,289.4
+ ,70.91
+ ,292.4
+ ,69.75
+ ,287.9
+ ,68.59
+ ,286.6
+ ,67.48
+ ,280.5
+ ,66.31
+ ,272.4
+ ,64.81
+ ,269.2
+ ,66.58
+ ,270.6
+ ,65.97
+ ,267.3
+ ,64.7
+ ,262.5
+ ,64.7
+ ,266.8
+ ,60.94
+ ,268.8
+ ,59.08
+ ,263.1
+ ,58.42
+ ,261.2
+ ,57.77
+ ,266
+ ,57.11
+ ,262.5
+ ,53.31
+ ,265.2
+ ,49.96
+ ,261.3
+ ,49.4
+ ,253.7
+ ,48.84
+ ,249.2
+ ,48.3
+ ,239.1
+ ,47.74
+ ,236.4
+ ,47.24
+ ,235.2
+ ,46.76
+ ,245.2
+ ,46.29
+ ,246.2
+ ,48.9
+ ,247.7
+ ,49.23
+ ,251.4
+ ,48.53
+ ,253.3
+ ,48.03
+ ,254.8
+ ,54.34
+ ,250
+ ,53.79
+ ,249.3
+ ,53.24
+ ,241.5
+ ,52.96
+ ,243.3
+ ,52.17
+ ,248
+ ,51.7
+ ,253
+ ,58.55
+ ,252.9
+ ,78.2
+ ,251.5
+ ,77.03
+ ,251.6
+ ,76.19
+ ,253.5
+ ,77.15
+ ,259.8
+ ,75.87
+ ,334.1
+ ,95.47
+ ,448
+ ,109.67
+ ,445.8
+ ,112.28
+ ,445
+ ,112.01
+ ,448.2
+ ,107.93
+ ,438.2
+ ,105.96
+ ,439.8
+ ,105.06
+ ,423.4
+ ,102.98
+ ,410.8
+ ,102.2
+ ,408.4
+ ,105.23
+ ,406.7
+ ,101.85
+ ,405.9
+ ,99.89
+ ,402.7
+ ,96.23
+ ,405.1
+ ,94.76
+ ,399.6
+ ,91.51
+ ,386.5
+ ,91.63
+ ,381.4
+ ,91.54
+ ,375.2
+ ,85.23
+ ,357.7
+ ,87.83
+ ,359
+ ,87.38
+ ,355
+ ,84.44
+ ,352.7
+ ,85.19
+ ,344.4
+ ,84.03
+ ,343.8
+ ,86.73
+ ,338
+ ,102.52
+ ,339
+ ,104.45
+ ,333.3
+ ,106.98
+ ,334.4
+ ,107.02
+ ,328.3
+ ,99.26
+ ,330.7
+ ,94.45
+ ,330
+ ,113.44
+ ,331.6
+ ,157.33
+ ,351.2
+ ,147.38
+ ,389.4
+ ,171.89
+ ,410.9
+ ,171.95
+ ,442.8
+ ,132.71
+ ,462.8
+ ,126.02
+ ,466.9
+ ,121.18
+ ,461.7
+ ,115.45
+ ,439.2
+ ,110.48
+ ,430.3
+ ,117.85
+ ,416.1
+ ,117.63
+ ,402.5
+ ,124.65
+ ,397.3
+ ,109.59
+ ,403.3
+ ,111.27
+ ,395.9
+ ,99.78
+ ,387.8
+ ,98.21
+ ,378.6
+ ,99.2
+ ,377.1
+ ,97.97
+ ,370.4
+ ,89.55
+ ,362
+ ,87.91
+ ,350.3
+ ,93.34
+ ,348.2
+ ,94.42
+ ,344.6
+ ,93.2
+ ,343.5
+ ,90.29
+ ,342.8
+ ,91.46
+ ,347.6
+ ,89.98
+ ,346.6
+ ,88.35
+ ,349.5
+ ,88.41
+ ,342.1
+ ,82.44
+ ,342
+ ,79.89
+ ,342.8
+ ,75.69
+ ,339.3
+ ,75.66
+ ,348.2
+ ,84.5
+ ,333.7
+ ,96.73
+ ,334.7
+ ,87.48
+ ,354
+ ,82.39
+ ,367.7
+ ,83.48
+ ,363.3
+ ,79.31
+ ,358.4
+ ,78.16
+ ,353.1
+ ,72.77
+ ,343.1
+ ,72.45
+ ,344.6
+ ,68.46
+ ,344.4
+ ,67.62
+ ,333.9
+ ,68.76
+ ,331.7
+ ,70.07
+ ,324.3
+ ,68.55
+ ,321.2
+ ,65.3
+ ,322.4
+ ,58.96
+ ,321.7
+ ,59.17
+ ,320.5
+ ,62.37
+ ,312.8
+ ,66.28
+ ,309.7
+ ,55.62
+ ,315.6
+ ,55.23
+ ,309.7
+ ,55.85
+ ,304.6
+ ,56.75
+ ,302.5
+ ,50.89
+ ,301.5
+ ,53.88
+ ,298.8
+ ,52.95
+ ,291.3
+ ,55.08
+ ,293.6
+ ,53.61
+ ,294.6
+ ,58.78
+ ,285.9
+ ,61.85
+ ,297.6
+ ,55.91
+ ,301.1
+ ,53.32
+ ,293.8
+ ,46.41
+ ,297.7
+ ,44.57
+ ,292.9
+ ,50
+ ,292.1
+ ,50
+ ,287.2
+ ,53.36
+ ,288.2
+ ,46.23
+ ,283.8
+ ,50.45
+ ,299.9
+ ,49.07
+ ,292.4
+ ,45.85
+ ,293.3
+ ,48.45
+ ,300.8
+ ,49.96
+ ,293.7
+ ,46.53
+ ,293.1
+ ,50.51
+ ,294.4
+ ,47.58
+ ,292.1
+ ,48.05
+ ,291.9
+ ,46.84
+ ,282.5
+ ,47.67
+ ,277.9
+ ,49.16
+ ,287.5
+ ,55.54
+ ,289.2
+ ,55.82
+ ,285.6
+ ,58.22
+ ,293.2
+ ,56.19
+ ,290.8
+ ,57.77
+ ,283.1
+ ,63.19
+ ,275
+ ,54.76
+ ,287.8
+ ,55.74
+ ,287.8
+ ,62.54
+ ,287.4
+ ,61.39
+ ,284
+ ,69.6
+ ,277.8
+ ,79.23
+ ,277.6
+ ,80
+ ,304.9
+ ,93.68
+ ,294
+ ,107.63
+ ,300.9
+ ,100.18
+ ,324
+ ,97.3
+ ,332.9
+ ,90.45
+ ,341.6
+ ,80.64
+ ,333.4
+ ,80.58
+ ,348.2
+ ,75.82
+ ,344.7
+ ,85.59
+ ,344.7
+ ,89.35
+ ,329.3
+ ,89.42
+ ,323.5
+ ,104.73
+ ,323.2
+ ,95.32
+ ,317.4
+ ,89.27
+ ,330.1
+ ,90.44
+ ,329.2
+ ,86.97
+ ,334.9
+ ,79.98
+ ,315.8
+ ,81.22
+ ,315.4
+ ,87.35
+ ,319.6
+ ,83.64
+ ,317.3
+ ,82.22
+ ,313.8
+ ,94.4
+ ,315.8
+ ,102.18
+ ,311.3)
+ ,dim=c(2
+ ,360)
+ ,dimnames=list(c('Colombia'
+ ,'USA')
+ ,1:360))
> y <- array(NA,dim=c(2,360),dimnames=list(c('Colombia','USA'),1:360))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par3 = 'No Linear Trend'
> par2 = 'Include Monthly Dummies'
> par1 = '2'
> par3 <- 'No Linear Trend'
> par2 <- 'Include Monthly Dummies'
> par1 <- '2'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: Write here your technical program description (don't use hard returns!)
> library(lattice)
> library(lmtest)
Loading required package: zoo
Attaching package: 'zoo'
The following object(s) are masked from 'package:base':
as.Date, as.Date.numeric
> n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
> par1 <- as.numeric(par1)
> x <- 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'){
+ x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
+ for (i in 1:n-1) {
+ for (j in 1:k) {
+ x2[i,j] <- x[i+1,j] - x[i,j]
+ }
+ }
+ x <- x2
+ }
> 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[1,])
> if (par3 == 'Linear Trend'){
+ x <- cbind(x, c(1:n))
+ colnames(x)[k+1] <- 't'
+ }
> x
USA Colombia M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11
1 255.0 87.28 1 0 0 0 0 0 0 0 0 0 0
2 280.2 87.28 0 1 0 0 0 0 0 0 0 0 0
3 299.9 87.09 0 0 1 0 0 0 0 0 0 0 0
4 339.2 86.92 0 0 0 1 0 0 0 0 0 0 0
5 374.2 87.59 0 0 0 0 1 0 0 0 0 0 0
6 393.5 90.72 0 0 0 0 0 1 0 0 0 0 0
7 389.2 90.69 0 0 0 0 0 0 1 0 0 0 0
8 381.7 90.30 0 0 0 0 0 0 0 1 0 0 0
9 375.2 89.55 0 0 0 0 0 0 0 0 1 0 0
10 369.0 88.94 0 0 0 0 0 0 0 0 0 1 0
11 357.4 88.41 0 0 0 0 0 0 0 0 0 0 1
12 352.1 87.82 0 0 0 0 0 0 0 0 0 0 0
13 346.5 87.07 1 0 0 0 0 0 0 0 0 0 0
14 342.9 86.82 0 1 0 0 0 0 0 0 0 0 0
15 340.3 86.40 0 0 1 0 0 0 0 0 0 0 0
16 328.3 86.02 0 0 0 1 0 0 0 0 0 0 0
17 322.9 85.66 0 0 0 0 1 0 0 0 0 0 0
18 314.3 85.32 0 0 0 0 0 1 0 0 0 0 0
19 308.9 85.00 0 0 0 0 0 0 1 0 0 0 0
20 294.0 84.67 0 0 0 0 0 0 0 1 0 0 0
21 285.6 83.94 0 0 0 0 0 0 0 0 1 0 0
22 281.2 82.83 0 0 0 0 0 0 0 0 0 1 0
23 280.3 81.95 0 0 0 0 0 0 0 0 0 0 1
24 278.8 81.19 0 0 0 0 0 0 0 0 0 0 0
25 274.5 80.48 1 0 0 0 0 0 0 0 0 0 0
26 270.4 78.86 0 1 0 0 0 0 0 0 0 0 0
27 263.4 69.47 0 0 1 0 0 0 0 0 0 0 0
28 259.9 68.77 0 0 0 1 0 0 0 0 0 0 0
29 258.0 70.06 0 0 0 0 1 0 0 0 0 0 0
30 262.7 73.95 0 0 0 0 0 1 0 0 0 0 0
31 284.7 75.80 0 0 0 0 0 0 1 0 0 0 0
32 311.3 77.79 0 0 0 0 0 0 0 1 0 0 0
33 322.1 81.57 0 0 0 0 0 0 0 0 1 0 0
34 327.0 83.07 0 0 0 0 0 0 0 0 0 1 0
35 331.3 84.34 0 0 0 0 0 0 0 0 0 0 1
36 333.3 85.10 0 0 0 0 0 0 0 0 0 0 0
37 321.4 85.25 1 0 0 0 0 0 0 0 0 0 0
38 327.0 84.26 0 1 0 0 0 0 0 0 0 0 0
39 320.0 83.63 0 0 1 0 0 0 0 0 0 0 0
40 314.7 86.44 0 0 0 1 0 0 0 0 0 0 0
41 316.7 85.30 0 0 0 0 1 0 0 0 0 0 0
42 314.4 84.10 0 0 0 0 0 1 0 0 0 0 0
43 321.3 83.36 0 0 0 0 0 0 1 0 0 0 0
44 318.2 82.48 0 0 0 0 0 0 0 1 0 0 0
45 307.2 81.58 0 0 0 0 0 0 0 0 1 0 0
46 301.3 80.47 0 0 0 0 0 0 0 0 0 1 0
47 287.5 79.34 0 0 0 0 0 0 0 0 0 0 1
48 277.7 82.13 0 0 0 0 0 0 0 0 0 0 0
49 274.4 81.69 1 0 0 0 0 0 0 0 0 0 0
50 258.8 80.70 0 1 0 0 0 0 0 0 0 0 0
51 253.3 79.88 0 0 1 0 0 0 0 0 0 0 0
52 251.0 79.16 0 0 0 1 0 0 0 0 0 0 0
53 248.4 78.38 0 0 0 0 1 0 0 0 0 0 0
54 249.5 77.42 0 0 0 0 0 1 0 0 0 0 0
55 246.1 76.47 0 0 0 0 0 0 1 0 0 0 0
56 244.5 75.46 0 0 0 0 0 0 0 1 0 0 0
57 243.6 74.48 0 0 0 0 0 0 0 0 1 0 0
58 244.0 78.27 0 0 0 0 0 0 0 0 0 1 0
59 240.8 80.70 0 0 0 0 0 0 0 0 0 0 1
60 249.8 79.91 0 0 0 0 0 0 0 0 0 0 0
61 248.0 78.75 1 0 0 0 0 0 0 0 0 0 0
62 259.4 77.78 0 1 0 0 0 0 0 0 0 0 0
63 260.5 81.14 0 0 1 0 0 0 0 0 0 0 0
64 260.8 81.08 0 0 0 1 0 0 0 0 0 0 0
65 261.3 80.03 0 0 0 0 1 0 0 0 0 0 0
66 259.5 78.91 0 0 0 0 0 1 0 0 0 0 0
67 256.6 78.01 0 0 0 0 0 0 1 0 0 0 0
68 257.9 76.90 0 0 0 0 0 0 0 1 0 0 0
69 256.5 75.97 0 0 0 0 0 0 0 0 1 0 0
70 254.2 81.93 0 0 0 0 0 0 0 0 0 1 0
71 253.3 80.27 0 0 0 0 0 0 0 0 0 0 1
72 253.8 78.67 0 0 0 0 0 0 0 0 0 0 0
73 255.5 77.42 1 0 0 0 0 0 0 0 0 0 0
74 257.1 76.16 0 1 0 0 0 0 0 0 0 0 0
75 257.3 74.70 0 0 1 0 0 0 0 0 0 0 0
76 253.2 76.39 0 0 0 1 0 0 0 0 0 0 0
77 252.8 76.04 0 0 0 0 1 0 0 0 0 0 0
78 252.0 74.65 0 0 0 0 0 1 0 0 0 0 0
79 250.7 73.29 0 0 0 0 0 0 1 0 0 0 0
80 252.2 71.79 0 0 0 0 0 0 0 1 0 0 0
81 250.0 74.39 0 0 0 0 0 0 0 0 1 0 0
82 251.0 74.91 0 0 0 0 0 0 0 0 0 1 0
83 253.4 74.54 0 0 0 0 0 0 0 0 0 0 1
84 251.2 73.08 0 0 0 0 0 0 0 0 0 0 0
85 255.6 72.75 1 0 0 0 0 0 0 0 0 0 0
86 261.1 71.32 0 1 0 0 0 0 0 0 0 0 0
87 258.9 70.38 0 0 1 0 0 0 0 0 0 0 0
88 259.9 70.35 0 0 0 1 0 0 0 0 0 0 0
89 261.2 70.01 0 0 0 0 1 0 0 0 0 0 0
90 264.7 69.36 0 0 0 0 0 1 0 0 0 0 0
91 267.1 67.77 0 0 0 0 0 0 1 0 0 0 0
92 266.4 69.26 0 0 0 0 0 0 0 1 0 0 0
93 267.7 69.80 0 0 0 0 0 0 0 0 1 0 0
94 268.6 68.38 0 0 0 0 0 0 0 0 0 1 0
95 267.5 67.62 0 0 0 0 0 0 0 0 0 0 1
96 268.5 68.39 0 0 0 0 0 0 0 0 0 0 0
97 268.5 66.95 1 0 0 0 0 0 0 0 0 0 0
98 270.5 65.21 0 1 0 0 0 0 0 0 0 0 0
99 270.9 66.64 0 0 1 0 0 0 0 0 0 0 0
100 270.1 63.45 0 0 0 1 0 0 0 0 0 0 0
101 269.3 60.66 0 0 0 0 1 0 0 0 0 0 0
102 269.8 62.34 0 0 0 0 0 1 0 0 0 0 0
103 270.1 60.32 0 0 0 0 0 0 1 0 0 0 0
104 264.9 58.64 0 0 0 0 0 0 0 1 0 0 0
105 263.7 60.46 0 0 0 0 0 0 0 0 1 0 0
106 264.8 58.59 0 0 0 0 0 0 0 0 0 1 0
107 263.7 61.87 0 0 0 0 0 0 0 0 0 0 1
108 255.9 61.85 0 0 0 0 0 0 0 0 0 0 0
109 276.2 67.44 1 0 0 0 0 0 0 0 0 0 0
110 360.1 77.06 0 1 0 0 0 0 0 0 0 0 0
111 380.5 91.74 0 0 1 0 0 0 0 0 0 0 0
112 373.7 93.15 0 0 0 1 0 0 0 0 0 0 0
113 369.8 94.15 0 0 0 0 1 0 0 0 0 0 0
114 366.6 93.11 0 0 0 0 0 1 0 0 0 0 0
115 359.3 91.51 0 0 0 0 0 0 1 0 0 0 0
116 345.8 89.96 0 0 0 0 0 0 0 1 0 0 0
117 326.2 88.16 0 0 0 0 0 0 0 0 1 0 0
118 324.5 86.98 0 0 0 0 0 0 0 0 0 1 0
119 328.1 88.03 0 0 0 0 0 0 0 0 0 0 1
120 327.5 86.24 0 0 0 0 0 0 0 0 0 0 0
121 324.4 84.65 1 0 0 0 0 0 0 0 0 0 0
122 316.5 83.23 0 1 0 0 0 0 0 0 0 0 0
123 310.9 81.70 0 0 1 0 0 0 0 0 0 0 0
124 301.5 80.25 0 0 0 1 0 0 0 0 0 0 0
125 291.7 78.80 0 0 0 0 1 0 0 0 0 0 0
126 290.4 77.51 0 0 0 0 0 1 0 0 0 0 0
127 287.4 76.20 0 0 0 0 0 0 1 0 0 0 0
128 277.7 75.04 0 0 0 0 0 0 0 1 0 0 0
129 281.6 74.00 0 0 0 0 0 0 0 0 1 0 0
130 288.0 75.49 0 0 0 0 0 0 0 0 0 1 0
131 276.0 77.14 0 0 0 0 0 0 0 0 0 0 1
132 272.9 76.15 0 0 0 0 0 0 0 0 0 0 0
133 283.0 76.27 1 0 0 0 0 0 0 0 0 0 0
134 283.3 78.19 0 1 0 0 0 0 0 0 0 0 0
135 276.8 76.49 0 0 1 0 0 0 0 0 0 0 0
136 284.5 77.31 0 0 0 1 0 0 0 0 0 0 0
137 282.7 76.65 0 0 0 0 1 0 0 0 0 0 0
138 281.2 74.99 0 0 0 0 0 1 0 0 0 0 0
139 287.4 73.51 0 0 0 0 0 0 1 0 0 0 0
140 283.1 72.07 0 0 0 0 0 0 0 1 0 0 0
141 284.0 70.59 0 0 0 0 0 0 0 0 1 0 0
142 285.5 71.96 0 0 0 0 0 0 0 0 0 1 0
143 289.2 76.29 0 0 0 0 0 0 0 0 0 0 1
144 292.5 74.86 0 0 0 0 0 0 0 0 0 0 0
145 296.4 74.93 1 0 0 0 0 0 0 0 0 0 0
146 305.2 71.90 0 1 0 0 0 0 0 0 0 0 0
147 303.9 71.01 0 0 1 0 0 0 0 0 0 0 0
148 311.5 77.47 0 0 0 1 0 0 0 0 0 0 0
149 316.3 75.78 0 0 0 0 1 0 0 0 0 0 0
150 316.7 76.60 0 0 0 0 0 1 0 0 0 0 0
151 322.5 76.07 0 0 0 0 0 0 1 0 0 0 0
152 317.1 74.57 0 0 0 0 0 0 0 1 0 0 0
153 309.8 73.02 0 0 0 0 0 0 0 0 1 0 0
154 303.8 72.65 0 0 0 0 0 0 0 0 0 1 0
155 290.3 73.16 0 0 0 0 0 0 0 0 0 0 1
156 293.7 71.53 0 0 0 0 0 0 0 0 0 0 0
157 291.7 69.78 1 0 0 0 0 0 0 0 0 0 0
158 296.5 67.98 0 1 0 0 0 0 0 0 0 0 0
159 289.1 69.96 0 0 1 0 0 0 0 0 0 0 0
160 288.5 72.16 0 0 0 1 0 0 0 0 0 0 0
161 293.8 70.47 0 0 0 0 1 0 0 0 0 0 0
162 297.7 68.86 0 0 0 0 0 1 0 0 0 0 0
163 305.4 67.37 0 0 0 0 0 0 1 0 0 0 0
164 302.7 65.87 0 0 0 0 0 0 0 1 0 0 0
165 302.5 72.16 0 0 0 0 0 0 0 0 1 0 0
166 303.0 71.34 0 0 0 0 0 0 0 0 0 1 0
167 294.5 69.93 0 0 0 0 0 0 0 0 0 0 1
168 294.1 68.44 0 0 0 0 0 0 0 0 0 0 0
169 294.5 67.16 1 0 0 0 0 0 0 0 0 0 0
170 297.1 66.01 0 1 0 0 0 0 0 0 0 0 0
171 289.4 67.25 0 0 1 0 0 0 0 0 0 0 0
172 292.4 70.91 0 0 0 1 0 0 0 0 0 0 0
173 287.9 69.75 0 0 0 0 1 0 0 0 0 0 0
174 286.6 68.59 0 0 0 0 0 1 0 0 0 0 0
175 280.5 67.48 0 0 0 0 0 0 1 0 0 0 0
176 272.4 66.31 0 0 0 0 0 0 0 1 0 0 0
177 269.2 64.81 0 0 0 0 0 0 0 0 1 0 0
178 270.6 66.58 0 0 0 0 0 0 0 0 0 1 0
179 267.3 65.97 0 0 0 0 0 0 0 0 0 0 1
180 262.5 64.70 0 0 0 0 0 0 0 0 0 0 0
181 266.8 64.70 1 0 0 0 0 0 0 0 0 0 0
182 268.8 60.94 0 1 0 0 0 0 0 0 0 0 0
183 263.1 59.08 0 0 1 0 0 0 0 0 0 0 0
184 261.2 58.42 0 0 0 1 0 0 0 0 0 0 0
185 266.0 57.77 0 0 0 0 1 0 0 0 0 0 0
186 262.5 57.11 0 0 0 0 0 1 0 0 0 0 0
187 265.2 53.31 0 0 0 0 0 0 1 0 0 0 0
188 261.3 49.96 0 0 0 0 0 0 0 1 0 0 0
189 253.7 49.40 0 0 0 0 0 0 0 0 1 0 0
190 249.2 48.84 0 0 0 0 0 0 0 0 0 1 0
191 239.1 48.30 0 0 0 0 0 0 0 0 0 0 1
192 236.4 47.74 0 0 0 0 0 0 0 0 0 0 0
193 235.2 47.24 1 0 0 0 0 0 0 0 0 0 0
194 245.2 46.76 0 1 0 0 0 0 0 0 0 0 0
195 246.2 46.29 0 0 1 0 0 0 0 0 0 0 0
196 247.7 48.90 0 0 0 1 0 0 0 0 0 0 0
197 251.4 49.23 0 0 0 0 1 0 0 0 0 0 0
198 253.3 48.53 0 0 0 0 0 1 0 0 0 0 0
199 254.8 48.03 0 0 0 0 0 0 1 0 0 0 0
200 250.0 54.34 0 0 0 0 0 0 0 1 0 0 0
201 249.3 53.79 0 0 0 0 0 0 0 0 1 0 0
202 241.5 53.24 0 0 0 0 0 0 0 0 0 1 0
203 243.3 52.96 0 0 0 0 0 0 0 0 0 0 1
204 248.0 52.17 0 0 0 0 0 0 0 0 0 0 0
205 253.0 51.70 1 0 0 0 0 0 0 0 0 0 0
206 252.9 58.55 0 1 0 0 0 0 0 0 0 0 0
207 251.5 78.20 0 0 1 0 0 0 0 0 0 0 0
208 251.6 77.03 0 0 0 1 0 0 0 0 0 0 0
209 253.5 76.19 0 0 0 0 1 0 0 0 0 0 0
210 259.8 77.15 0 0 0 0 0 1 0 0 0 0 0
211 334.1 75.87 0 0 0 0 0 0 1 0 0 0 0
212 448.0 95.47 0 0 0 0 0 0 0 1 0 0 0
213 445.8 109.67 0 0 0 0 0 0 0 0 1 0 0
214 445.0 112.28 0 0 0 0 0 0 0 0 0 1 0
215 448.2 112.01 0 0 0 0 0 0 0 0 0 0 1
216 438.2 107.93 0 0 0 0 0 0 0 0 0 0 0
217 439.8 105.96 1 0 0 0 0 0 0 0 0 0 0
218 423.4 105.06 0 1 0 0 0 0 0 0 0 0 0
219 410.8 102.98 0 0 1 0 0 0 0 0 0 0 0
220 408.4 102.20 0 0 0 1 0 0 0 0 0 0 0
221 406.7 105.23 0 0 0 0 1 0 0 0 0 0 0
222 405.9 101.85 0 0 0 0 0 1 0 0 0 0 0
223 402.7 99.89 0 0 0 0 0 0 1 0 0 0 0
224 405.1 96.23 0 0 0 0 0 0 0 1 0 0 0
225 399.6 94.76 0 0 0 0 0 0 0 0 1 0 0
226 386.5 91.51 0 0 0 0 0 0 0 0 0 1 0
227 381.4 91.63 0 0 0 0 0 0 0 0 0 0 1
228 375.2 91.54 0 0 0 0 0 0 0 0 0 0 0
229 357.7 85.23 1 0 0 0 0 0 0 0 0 0 0
230 359.0 87.83 0 1 0 0 0 0 0 0 0 0 0
231 355.0 87.38 0 0 1 0 0 0 0 0 0 0 0
232 352.7 84.44 0 0 0 1 0 0 0 0 0 0 0
233 344.4 85.19 0 0 0 0 1 0 0 0 0 0 0
234 343.8 84.03 0 0 0 0 0 1 0 0 0 0 0
235 338.0 86.73 0 0 0 0 0 0 1 0 0 0 0
236 339.0 102.52 0 0 0 0 0 0 0 1 0 0 0
237 333.3 104.45 0 0 0 0 0 0 0 0 1 0 0
238 334.4 106.98 0 0 0 0 0 0 0 0 0 1 0
239 328.3 107.02 0 0 0 0 0 0 0 0 0 0 1
240 330.7 99.26 0 0 0 0 0 0 0 0 0 0 0
241 330.0 94.45 1 0 0 0 0 0 0 0 0 0 0
242 331.6 113.44 0 1 0 0 0 0 0 0 0 0 0
243 351.2 157.33 0 0 1 0 0 0 0 0 0 0 0
244 389.4 147.38 0 0 0 1 0 0 0 0 0 0 0
245 410.9 171.89 0 0 0 0 1 0 0 0 0 0 0
246 442.8 171.95 0 0 0 0 0 1 0 0 0 0 0
247 462.8 132.71 0 0 0 0 0 0 1 0 0 0 0
248 466.9 126.02 0 0 0 0 0 0 0 1 0 0 0
249 461.7 121.18 0 0 0 0 0 0 0 0 1 0 0
250 439.2 115.45 0 0 0 0 0 0 0 0 0 1 0
251 430.3 110.48 0 0 0 0 0 0 0 0 0 0 1
252 416.1 117.85 0 0 0 0 0 0 0 0 0 0 0
253 402.5 117.63 1 0 0 0 0 0 0 0 0 0 0
254 397.3 124.65 0 1 0 0 0 0 0 0 0 0 0
255 403.3 109.59 0 0 1 0 0 0 0 0 0 0 0
256 395.9 111.27 0 0 0 1 0 0 0 0 0 0 0
257 387.8 99.78 0 0 0 0 1 0 0 0 0 0 0
258 378.6 98.21 0 0 0 0 0 1 0 0 0 0 0
259 377.1 99.20 0 0 0 0 0 0 1 0 0 0 0
260 370.4 97.97 0 0 0 0 0 0 0 1 0 0 0
261 362.0 89.55 0 0 0 0 0 0 0 0 1 0 0
262 350.3 87.91 0 0 0 0 0 0 0 0 0 1 0
263 348.2 93.34 0 0 0 0 0 0 0 0 0 0 1
264 344.6 94.42 0 0 0 0 0 0 0 0 0 0 0
265 343.5 93.20 1 0 0 0 0 0 0 0 0 0 0
266 342.8 90.29 0 1 0 0 0 0 0 0 0 0 0
267 347.6 91.46 0 0 1 0 0 0 0 0 0 0 0
268 346.6 89.98 0 0 0 1 0 0 0 0 0 0 0
269 349.5 88.35 0 0 0 0 1 0 0 0 0 0 0
270 342.1 88.41 0 0 0 0 0 1 0 0 0 0 0
271 342.0 82.44 0 0 0 0 0 0 1 0 0 0 0
272 342.8 79.89 0 0 0 0 0 0 0 1 0 0 0
273 339.3 75.69 0 0 0 0 0 0 0 0 1 0 0
274 348.2 75.66 0 0 0 0 0 0 0 0 0 1 0
275 333.7 84.50 0 0 0 0 0 0 0 0 0 0 1
276 334.7 96.73 0 0 0 0 0 0 0 0 0 0 0
277 354.0 87.48 1 0 0 0 0 0 0 0 0 0 0
278 367.7 82.39 0 1 0 0 0 0 0 0 0 0 0
279 363.3 83.48 0 0 1 0 0 0 0 0 0 0 0
280 358.4 79.31 0 0 0 1 0 0 0 0 0 0 0
281 353.1 78.16 0 0 0 0 1 0 0 0 0 0 0
282 343.1 72.77 0 0 0 0 0 1 0 0 0 0 0
283 344.6 72.45 0 0 0 0 0 0 1 0 0 0 0
284 344.4 68.46 0 0 0 0 0 0 0 1 0 0 0
285 333.9 67.62 0 0 0 0 0 0 0 0 1 0 0
286 331.7 68.76 0 0 0 0 0 0 0 0 0 1 0
287 324.3 70.07 0 0 0 0 0 0 0 0 0 0 1
288 321.2 68.55 0 0 0 0 0 0 0 0 0 0 0
289 322.4 65.30 1 0 0 0 0 0 0 0 0 0 0
290 321.7 58.96 0 1 0 0 0 0 0 0 0 0 0
291 320.5 59.17 0 0 1 0 0 0 0 0 0 0 0
292 312.8 62.37 0 0 0 1 0 0 0 0 0 0 0
293 309.7 66.28 0 0 0 0 1 0 0 0 0 0 0
294 315.6 55.62 0 0 0 0 0 1 0 0 0 0 0
295 309.7 55.23 0 0 0 0 0 0 1 0 0 0 0
296 304.6 55.85 0 0 0 0 0 0 0 1 0 0 0
297 302.5 56.75 0 0 0 0 0 0 0 0 1 0 0
298 301.5 50.89 0 0 0 0 0 0 0 0 0 1 0
299 298.8 53.88 0 0 0 0 0 0 0 0 0 0 1
300 291.3 52.95 0 0 0 0 0 0 0 0 0 0 0
301 293.6 55.08 1 0 0 0 0 0 0 0 0 0 0
302 294.6 53.61 0 1 0 0 0 0 0 0 0 0 0
303 285.9 58.78 0 0 1 0 0 0 0 0 0 0 0
304 297.6 61.85 0 0 0 1 0 0 0 0 0 0 0
305 301.1 55.91 0 0 0 0 1 0 0 0 0 0 0
306 293.8 53.32 0 0 0 0 0 1 0 0 0 0 0
307 297.7 46.41 0 0 0 0 0 0 1 0 0 0 0
308 292.9 44.57 0 0 0 0 0 0 0 1 0 0 0
309 292.1 50.00 0 0 0 0 0 0 0 0 1 0 0
310 287.2 50.00 0 0 0 0 0 0 0 0 0 1 0
311 288.2 53.36 0 0 0 0 0 0 0 0 0 0 1
312 283.8 46.23 0 0 0 0 0 0 0 0 0 0 0
313 299.9 50.45 1 0 0 0 0 0 0 0 0 0 0
314 292.4 49.07 0 1 0 0 0 0 0 0 0 0 0
315 293.3 45.85 0 0 1 0 0 0 0 0 0 0 0
316 300.8 48.45 0 0 0 1 0 0 0 0 0 0 0
317 293.7 49.96 0 0 0 0 1 0 0 0 0 0 0
318 293.1 46.53 0 0 0 0 0 1 0 0 0 0 0
319 294.4 50.51 0 0 0 0 0 0 1 0 0 0 0
320 292.1 47.58 0 0 0 0 0 0 0 1 0 0 0
321 291.9 48.05 0 0 0 0 0 0 0 0 1 0 0
322 282.5 46.84 0 0 0 0 0 0 0 0 0 1 0
323 277.9 47.67 0 0 0 0 0 0 0 0 0 0 1
324 287.5 49.16 0 0 0 0 0 0 0 0 0 0 0
325 289.2 55.54 1 0 0 0 0 0 0 0 0 0 0
326 285.6 55.82 0 1 0 0 0 0 0 0 0 0 0
327 293.2 58.22 0 0 1 0 0 0 0 0 0 0 0
328 290.8 56.19 0 0 0 1 0 0 0 0 0 0 0
329 283.1 57.77 0 0 0 0 1 0 0 0 0 0 0
330 275.0 63.19 0 0 0 0 0 1 0 0 0 0 0
331 287.8 54.76 0 0 0 0 0 0 1 0 0 0 0
332 287.8 55.74 0 0 0 0 0 0 0 1 0 0 0
333 287.4 62.54 0 0 0 0 0 0 0 0 1 0 0
334 284.0 61.39 0 0 0 0 0 0 0 0 0 1 0
335 277.8 69.60 0 0 0 0 0 0 0 0 0 0 1
336 277.6 79.23 0 0 0 0 0 0 0 0 0 0 0
337 304.9 80.00 1 0 0 0 0 0 0 0 0 0 0
338 294.0 93.68 0 1 0 0 0 0 0 0 0 0 0
339 300.9 107.63 0 0 1 0 0 0 0 0 0 0 0
340 324.0 100.18 0 0 0 1 0 0 0 0 0 0 0
341 332.9 97.30 0 0 0 0 1 0 0 0 0 0 0
342 341.6 90.45 0 0 0 0 0 1 0 0 0 0 0
343 333.4 80.64 0 0 0 0 0 0 1 0 0 0 0
344 348.2 80.58 0 0 0 0 0 0 0 1 0 0 0
345 344.7 75.82 0 0 0 0 0 0 0 0 1 0 0
346 344.7 85.59 0 0 0 0 0 0 0 0 0 1 0
347 329.3 89.35 0 0 0 0 0 0 0 0 0 0 1
348 323.5 89.42 0 0 0 0 0 0 0 0 0 0 0
349 323.2 104.73 1 0 0 0 0 0 0 0 0 0 0
350 317.4 95.32 0 1 0 0 0 0 0 0 0 0 0
351 330.1 89.27 0 0 1 0 0 0 0 0 0 0 0
352 329.2 90.44 0 0 0 1 0 0 0 0 0 0 0
353 334.9 86.97 0 0 0 0 1 0 0 0 0 0 0
354 315.8 79.98 0 0 0 0 0 1 0 0 0 0 0
355 315.4 81.22 0 0 0 0 0 0 1 0 0 0 0
356 319.6 87.35 0 0 0 0 0 0 0 1 0 0 0
357 317.3 83.64 0 0 0 0 0 0 0 0 1 0 0
358 313.8 82.22 0 0 0 0 0 0 0 0 0 1 0
359 315.8 94.40 0 0 0 0 0 0 0 0 0 0 1
360 311.3 102.18 0 0 0 0 0 0 0 0 0 0 0
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Colombia M1 M2 M3 M4
157.9765 1.8605 1.0663 3.5934 0.0326 2.4542
M5 M6 M7 M8 M9 M10
3.6159 6.1063 14.9545 16.4514 12.7655 9.8334
M11
2.4788
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-99.525 -22.994 -0.959 26.836 95.948
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 157.97655 9.89078 15.972 <2e-16 ***
Colombia 1.86052 0.09752 19.078 <2e-16 ***
M1 1.06632 8.96616 0.119 0.9054
M2 3.59342 8.96597 0.401 0.6888
M3 0.03260 8.96784 0.004 0.9971
M4 2.45424 8.96759 0.274 0.7845
M5 3.61595 8.96741 0.403 0.6870
M6 6.10634 8.96601 0.681 0.4963
M7 14.95448 8.96910 1.667 0.0964 .
M8 16.45144 8.96819 1.834 0.0674 .
M9 12.76554 8.96793 1.423 0.1555
M10 9.83344 8.96776 1.097 0.2736
M11 2.47877 8.96598 0.276 0.7824
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 34.72 on 347 degrees of freedom
Multiple R-squared: 0.5149, Adjusted R-squared: 0.4981
F-statistic: 30.69 on 12 and 347 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,] 0.803277841 3.934443e-01 1.967222e-01
[2,] 0.855612589 2.887748e-01 1.443874e-01
[3,] 0.776650348 4.466993e-01 2.233497e-01
[4,] 0.675836572 6.483269e-01 3.241634e-01
[5,] 0.571917821 8.561644e-01 4.280822e-01
[6,] 0.469030593 9.380612e-01 5.309694e-01
[7,] 0.370375296 7.407506e-01 6.296247e-01
[8,] 0.291742693 5.834854e-01 7.082573e-01
[9,] 0.227859516 4.557190e-01 7.721405e-01
[10,] 0.314148036 6.282961e-01 6.858520e-01
[11,] 0.348134174 6.962683e-01 6.518658e-01
[12,] 0.584168932 8.316621e-01 4.158311e-01
[13,] 0.564773924 8.704522e-01 4.352261e-01
[14,] 0.494670457 9.893409e-01 5.053295e-01
[15,] 0.429096239 8.581925e-01 5.709038e-01
[16,] 0.363670956 7.273419e-01 6.363290e-01
[17,] 0.330040596 6.600812e-01 6.699594e-01
[18,] 0.284493965 5.689879e-01 7.155060e-01
[19,] 0.239430846 4.788617e-01 7.605692e-01
[20,] 0.199330984 3.986620e-01 8.006690e-01
[21,] 0.162460527 3.249211e-01 8.375395e-01
[22,] 0.144508951 2.890179e-01 8.554910e-01
[23,] 0.130748663 2.614973e-01 8.692513e-01
[24,] 0.100898115 2.017962e-01 8.991019e-01
[25,] 0.088276218 1.765524e-01 9.117238e-01
[26,] 0.075191545 1.503831e-01 9.248085e-01
[27,] 0.058419492 1.168390e-01 9.415805e-01
[28,] 0.043299463 8.659893e-02 9.567005e-01
[29,] 0.031559004 6.311801e-02 9.684410e-01
[30,] 0.022744507 4.548901e-02 9.772555e-01
[31,] 0.016157018 3.231404e-02 9.838430e-01
[32,] 0.011454366 2.290873e-02 9.885456e-01
[33,] 0.010486793 2.097359e-02 9.895132e-01
[34,] 0.007612319 1.522464e-02 9.923877e-01
[35,] 0.007063502 1.412700e-02 9.929365e-01
[36,] 0.009299677 1.859935e-02 9.907003e-01
[37,] 0.012270452 2.454090e-02 9.877295e-01
[38,] 0.017754919 3.550984e-02 9.822451e-01
[39,] 0.019560667 3.912133e-02 9.804393e-01
[40,] 0.022505775 4.501155e-02 9.774942e-01
[41,] 0.023713298 4.742660e-02 9.762867e-01
[42,] 0.021530688 4.306138e-02 9.784693e-01
[43,] 0.026697798 5.339560e-02 9.733022e-01
[44,] 0.043801006 8.760201e-02 9.561990e-01
[45,] 0.046120998 9.224200e-02 9.538790e-01
[46,] 0.040634392 8.126878e-02 9.593656e-01
[47,] 0.034014199 6.802840e-02 9.659858e-01
[48,] 0.036178683 7.235737e-02 9.638213e-01
[49,] 0.039480447 7.896089e-02 9.605196e-01
[50,] 0.041818893 8.363779e-02 9.581811e-01
[51,] 0.040391609 8.078322e-02 9.596084e-01
[52,] 0.040812688 8.162538e-02 9.591873e-01
[53,] 0.038513173 7.702635e-02 9.614868e-01
[54,] 0.034388419 6.877684e-02 9.656116e-01
[55,] 0.047220104 9.444021e-02 9.527799e-01
[56,] 0.048937712 9.787542e-02 9.510623e-01
[57,] 0.044521296 8.904259e-02 9.554787e-01
[58,] 0.040281128 8.056226e-02 9.597189e-01
[59,] 0.036433304 7.286661e-02 9.635667e-01
[60,] 0.032177250 6.435450e-02 9.678227e-01
[61,] 0.028672235 5.734447e-02 9.713278e-01
[62,] 0.025883209 5.176642e-02 9.741168e-01
[63,] 0.023122337 4.624467e-02 9.768777e-01
[64,] 0.021884988 4.376998e-02 9.781150e-01
[65,] 0.021447699 4.289540e-02 9.785523e-01
[66,] 0.020436406 4.087281e-02 9.795636e-01
[67,] 0.019465726 3.893145e-02 9.805343e-01
[68,] 0.018268296 3.653659e-02 9.817317e-01
[69,] 0.018082940 3.616588e-02 9.819171e-01
[70,] 0.022136183 4.427237e-02 9.778638e-01
[71,] 0.028314079 5.662816e-02 9.716859e-01
[72,] 0.031765111 6.353022e-02 9.682349e-01
[73,] 0.035861738 7.172348e-02 9.641383e-01
[74,] 0.038363823 7.672765e-02 9.616362e-01
[75,] 0.044116693 8.823339e-02 9.558833e-01
[76,] 0.056055061 1.121101e-01 9.439449e-01
[77,] 0.060338598 1.206772e-01 9.396614e-01
[78,] 0.065052043 1.301041e-01 9.349480e-01
[79,] 0.083406860 1.668137e-01 9.165931e-01
[80,] 0.106810198 2.136204e-01 8.931898e-01
[81,] 0.124427128 2.488543e-01 8.755729e-01
[82,] 0.167393319 3.347866e-01 8.326067e-01
[83,] 0.213806306 4.276126e-01 7.861937e-01
[84,] 0.231873399 4.637468e-01 7.681266e-01
[85,] 0.272917145 5.458343e-01 7.270829e-01
[86,] 0.321556220 6.431124e-01 6.784438e-01
[87,] 0.345860301 6.917206e-01 6.541397e-01
[88,] 0.376743792 7.534876e-01 6.232562e-01
[89,] 0.402859866 8.057197e-01 5.971401e-01
[90,] 0.415464865 8.309297e-01 5.845351e-01
[91,] 0.443540996 8.870820e-01 5.564590e-01
[92,] 0.446432795 8.928656e-01 5.535672e-01
[93,] 0.438312123 8.766242e-01 5.616879e-01
[94,] 0.440393745 8.807875e-01 5.596063e-01
[95,] 0.591004360 8.179913e-01 4.089956e-01
[96,] 0.647537947 7.049241e-01 3.524621e-01
[97,] 0.663341876 6.733162e-01 3.366581e-01
[98,] 0.656744612 6.865108e-01 3.432554e-01
[99,] 0.646408171 7.071837e-01 3.535918e-01
[100,] 0.624799975 7.504001e-01 3.752000e-01
[101,] 0.596278650 8.074427e-01 4.037214e-01
[102,] 0.568058011 8.638840e-01 4.319420e-01
[103,] 0.539295720 9.214086e-01 4.607043e-01
[104,] 0.509163339 9.816733e-01 4.908367e-01
[105,] 0.482816445 9.656329e-01 5.171836e-01
[106,] 0.464460309 9.289206e-01 5.355397e-01
[107,] 0.435478206 8.709564e-01 5.645218e-01
[108,] 0.406343747 8.126875e-01 5.936563e-01
[109,] 0.378596272 7.571925e-01 6.214037e-01
[110,] 0.353970390 7.079408e-01 6.460296e-01
[111,] 0.331118701 6.622374e-01 6.688813e-01
[112,] 0.317623160 6.352463e-01 6.823768e-01
[113,] 0.315106526 6.302131e-01 6.848935e-01
[114,] 0.303979328 6.079587e-01 6.960207e-01
[115,] 0.288885175 5.777703e-01 7.111148e-01
[116,] 0.277095818 5.541916e-01 7.229042e-01
[117,] 0.264154826 5.283097e-01 7.358452e-01
[118,] 0.250441129 5.008823e-01 7.495589e-01
[119,] 0.236761759 4.735235e-01 7.632382e-01
[120,] 0.222352852 4.447057e-01 7.776471e-01
[121,] 0.206738652 4.134773e-01 7.932613e-01
[122,] 0.192658770 3.853175e-01 8.073412e-01
[123,] 0.180070301 3.601406e-01 8.199297e-01
[124,] 0.171181106 3.423622e-01 8.288189e-01
[125,] 0.166128655 3.322573e-01 8.338713e-01
[126,] 0.160540715 3.210814e-01 8.394593e-01
[127,] 0.153282600 3.065652e-01 8.467174e-01
[128,] 0.141611938 2.832239e-01 8.583881e-01
[129,] 0.131016856 2.620337e-01 8.689831e-01
[130,] 0.125473323 2.509466e-01 8.745267e-01
[131,] 0.125504020 2.510080e-01 8.744960e-01
[132,] 0.126879892 2.537598e-01 8.731201e-01
[133,] 0.117949681 2.358994e-01 8.820503e-01
[134,] 0.114009477 2.280190e-01 8.859905e-01
[135,] 0.107933392 2.158668e-01 8.920666e-01
[136,] 0.104669830 2.093397e-01 8.953302e-01
[137,] 0.102240435 2.044809e-01 8.977596e-01
[138,] 0.100236831 2.004737e-01 8.997632e-01
[139,] 0.096980474 1.939609e-01 9.030195e-01
[140,] 0.090141734 1.802835e-01 9.098583e-01
[141,] 0.085409999 1.708200e-01 9.145900e-01
[142,] 0.084959096 1.699182e-01 9.150409e-01
[143,] 0.083908051 1.678161e-01 9.160919e-01
[144,] 0.076826928 1.536539e-01 9.231731e-01
[145,] 0.069448580 1.388972e-01 9.305514e-01
[146,] 0.063495812 1.269916e-01 9.365042e-01
[147,] 0.060288891 1.205778e-01 9.397111e-01
[148,] 0.060711408 1.214228e-01 9.392886e-01
[149,] 0.062437645 1.248753e-01 9.375624e-01
[150,] 0.058703332 1.174067e-01 9.412967e-01
[151,] 0.055913886 1.118278e-01 9.440861e-01
[152,] 0.053200490 1.064010e-01 9.467995e-01
[153,] 0.051160951 1.023219e-01 9.488390e-01
[154,] 0.051791689 1.035834e-01 9.482083e-01
[155,] 0.050603950 1.012079e-01 9.493960e-01
[156,] 0.046293916 9.258783e-02 9.537061e-01
[157,] 0.041472276 8.294455e-02 9.585277e-01
[158,] 0.036590448 7.318090e-02 9.634096e-01
[159,] 0.032469586 6.493917e-02 9.675304e-01
[160,] 0.030434010 6.086802e-02 9.695660e-01
[161,] 0.030392332 6.078466e-02 9.696077e-01
[162,] 0.029932048 5.986410e-02 9.700680e-01
[163,] 0.028932696 5.786539e-02 9.710673e-01
[164,] 0.026963461 5.392692e-02 9.730365e-01
[165,] 0.024693970 4.938794e-02 9.753060e-01
[166,] 0.023263238 4.652648e-02 9.767368e-01
[167,] 0.020884570 4.176914e-02 9.791154e-01
[168,] 0.018556012 3.711202e-02 9.814440e-01
[169,] 0.016903652 3.380730e-02 9.830963e-01
[170,] 0.015218358 3.043672e-02 9.847816e-01
[171,] 0.013772638 2.754528e-02 9.862274e-01
[172,] 0.013353290 2.670658e-02 9.866467e-01
[173,] 0.013610259 2.722052e-02 9.863897e-01
[174,] 0.013781525 2.756305e-02 9.862185e-01
[175,] 0.013697487 2.739497e-02 9.863025e-01
[176,] 0.013266539 2.653308e-02 9.867335e-01
[177,] 0.012471716 2.494343e-02 9.875283e-01
[178,] 0.012414912 2.482982e-02 9.875851e-01
[179,] 0.011263403 2.252681e-02 9.887366e-01
[180,] 0.010025951 2.005190e-02 9.899740e-01
[181,] 0.009109273 1.821855e-02 9.908907e-01
[182,] 0.008096930 1.619386e-02 9.919031e-01
[183,] 0.007273329 1.454666e-02 9.927267e-01
[184,] 0.007045709 1.409142e-02 9.929543e-01
[185,] 0.008248461 1.649692e-02 9.917515e-01
[186,] 0.009283104 1.856621e-02 9.907169e-01
[187,] 0.010854772 2.170954e-02 9.891452e-01
[188,] 0.011219000 2.243800e-02 9.887810e-01
[189,] 0.010673846 2.134769e-02 9.893262e-01
[190,] 0.010577752 2.115550e-02 9.894222e-01
[191,] 0.010576401 2.115280e-02 9.894236e-01
[192,] 0.018566851 3.713370e-02 9.814331e-01
[193,] 0.032921599 6.584320e-02 9.670784e-01
[194,] 0.053060223 1.061204e-01 9.469398e-01
[195,] 0.079898363 1.597967e-01 9.201016e-01
[196,] 0.076798666 1.535973e-01 9.232013e-01
[197,] 0.239989192 4.799784e-01 7.600108e-01
[198,] 0.353871246 7.077425e-01 6.461288e-01
[199,] 0.464016273 9.280325e-01 5.359837e-01
[200,] 0.627940885 7.441182e-01 3.720591e-01
[201,] 0.772438040 4.551239e-01 2.275620e-01
[202,] 0.882423850 2.351523e-01 1.175761e-01
[203,] 0.925616191 1.487676e-01 7.438381e-02
[204,] 0.948937324 1.021254e-01 5.106268e-02
[205,] 0.962030949 7.593810e-02 3.796905e-02
[206,] 0.967882076 6.423585e-02 3.211792e-02
[207,] 0.974359128 5.128174e-02 2.564087e-02
[208,] 0.976377404 4.724519e-02 2.362260e-02
[209,] 0.981322446 3.735511e-02 1.867755e-02
[210,] 0.985575330 2.884934e-02 1.442467e-02
[211,] 0.988082174 2.383565e-02 1.191783e-02
[212,] 0.990907617 1.818477e-02 9.092383e-03
[213,] 0.992742640 1.451472e-02 7.257360e-03
[214,] 0.992875953 1.424809e-02 7.124047e-03
[215,] 0.992635012 1.472998e-02 7.364988e-03
[216,] 0.992269007 1.546199e-02 7.730993e-03
[217,] 0.991777751 1.644450e-02 8.222249e-03
[218,] 0.990245815 1.950837e-02 9.754185e-03
[219,] 0.988439932 2.312014e-02 1.156007e-02
[220,] 0.986068466 2.786307e-02 1.393153e-02
[221,] 0.987765985 2.446803e-02 1.223402e-02
[222,] 0.990549950 1.890010e-02 9.450050e-03
[223,] 0.992713672 1.457266e-02 7.286328e-03
[224,] 0.994021713 1.195657e-02 5.978287e-03
[225,] 0.993114153 1.377169e-02 6.885847e-03
[226,] 0.991866361 1.626728e-02 8.133639e-03
[227,] 0.994627452 1.074510e-02 5.372548e-03
[228,] 0.999813334 3.733328e-04 1.866664e-04
[229,] 0.999900313 1.993732e-04 9.968658e-05
[230,] 0.999983566 3.286848e-05 1.643424e-05
[231,] 0.999989146 2.170748e-05 1.085374e-05
[232,] 0.999992431 1.513800e-05 7.568999e-06
[233,] 0.999997730 4.539624e-06 2.269812e-06
[234,] 0.999999657 6.858190e-07 3.429095e-07
[235,] 0.999999923 1.532816e-07 7.664081e-08
[236,] 0.999999995 9.656182e-09 4.828091e-09
[237,] 0.999999999 2.197261e-09 1.098631e-09
[238,] 0.999999999 1.818438e-09 9.092192e-10
[239,] 0.999999999 2.428087e-09 1.214043e-09
[240,] 1.000000000 8.336606e-10 4.168303e-10
[241,] 1.000000000 6.093370e-10 3.046685e-10
[242,] 1.000000000 2.912217e-10 1.456109e-10
[243,] 1.000000000 2.067239e-10 1.033620e-10
[244,] 1.000000000 2.105135e-10 1.052568e-10
[245,] 1.000000000 2.770721e-10 1.385360e-10
[246,] 1.000000000 2.974368e-10 1.487184e-10
[247,] 1.000000000 4.265893e-10 2.132946e-10
[248,] 1.000000000 5.606889e-10 2.803444e-10
[249,] 1.000000000 7.400952e-10 3.700476e-10
[250,] 0.999999999 1.266010e-09 6.330051e-10
[251,] 0.999999999 2.021635e-09 1.010818e-09
[252,] 0.999999999 2.863216e-09 1.431608e-09
[253,] 0.999999998 4.425615e-09 2.212808e-09
[254,] 0.999999997 5.949581e-09 2.974791e-09
[255,] 0.999999995 9.753724e-09 4.876862e-09
[256,] 0.999999992 1.515914e-08 7.579571e-09
[257,] 0.999999989 2.191099e-08 1.095550e-08
[258,] 0.999999986 2.717720e-08 1.358860e-08
[259,] 0.999999991 1.859013e-08 9.295066e-09
[260,] 0.999999987 2.549015e-08 1.274507e-08
[261,] 0.999999979 4.121490e-08 2.060745e-08
[262,] 0.999999985 2.921493e-08 1.460747e-08
[263,] 0.999999999 2.949761e-09 1.474880e-09
[264,] 1.000000000 4.159091e-10 2.079545e-10
[265,] 1.000000000 8.908433e-11 4.454216e-11
[266,] 1.000000000 2.789498e-11 1.394749e-11
[267,] 1.000000000 1.327983e-11 6.639916e-12
[268,] 1.000000000 7.181709e-12 3.590854e-12
[269,] 1.000000000 2.926764e-12 1.463382e-12
[270,] 1.000000000 2.300820e-12 1.150410e-12
[271,] 1.000000000 1.712915e-12 8.564574e-13
[272,] 1.000000000 1.327789e-12 6.638946e-13
[273,] 1.000000000 8.861456e-13 4.430728e-13
[274,] 1.000000000 7.459976e-13 3.729988e-13
[275,] 1.000000000 2.254984e-13 1.127492e-13
[276,] 1.000000000 8.872602e-14 4.436301e-14
[277,] 1.000000000 1.595681e-13 7.978404e-14
[278,] 1.000000000 3.820493e-13 1.910247e-13
[279,] 1.000000000 3.671066e-13 1.835533e-13
[280,] 1.000000000 7.135168e-13 3.567584e-13
[281,] 1.000000000 1.708335e-12 8.541674e-13
[282,] 1.000000000 4.089901e-12 2.044951e-12
[283,] 1.000000000 7.628522e-12 3.814261e-12
[284,] 1.000000000 1.226790e-11 6.133952e-12
[285,] 1.000000000 2.379154e-11 1.189577e-11
[286,] 1.000000000 5.509070e-11 2.754535e-11
[287,] 1.000000000 9.893457e-11 4.946728e-11
[288,] 1.000000000 2.300175e-10 1.150088e-10
[289,] 1.000000000 5.366723e-10 2.683362e-10
[290,] 0.999999999 1.192339e-09 5.961696e-10
[291,] 0.999999999 2.725975e-09 1.362987e-09
[292,] 0.999999997 5.691307e-09 2.845654e-09
[293,] 0.999999994 1.252543e-08 6.262715e-09
[294,] 0.999999986 2.738022e-08 1.369011e-08
[295,] 0.999999970 6.003985e-08 3.001992e-08
[296,] 0.999999935 1.296644e-07 6.483218e-08
[297,] 0.999999879 2.417842e-07 1.208921e-07
[298,] 0.999999828 3.434095e-07 1.717047e-07
[299,] 0.999999775 4.507908e-07 2.253954e-07
[300,] 0.999999696 6.076054e-07 3.038027e-07
[301,] 0.999999540 9.204105e-07 4.602053e-07
[302,] 0.999999027 1.946505e-06 9.732526e-07
[303,] 0.999998210 3.580740e-06 1.790370e-06
[304,] 0.999996096 7.807939e-06 3.903969e-06
[305,] 0.999991589 1.682210e-05 8.411052e-06
[306,] 0.999982232 3.553578e-05 1.776789e-05
[307,] 0.999963315 7.336992e-05 3.668496e-05
[308,] 0.999925968 1.480633e-04 7.403163e-05
[309,] 0.999911662 1.766763e-04 8.833814e-05
[310,] 0.999844869 3.102615e-04 1.551307e-04
[311,] 0.999793436 4.131282e-04 2.065641e-04
[312,] 0.999770036 4.599286e-04 2.299643e-04
[313,] 0.999625577 7.488452e-04 3.744226e-04
[314,] 0.999227491 1.545019e-03 7.725095e-04
[315,] 0.998992379 2.015242e-03 1.007621e-03
[316,] 0.997969040 4.061919e-03 2.030960e-03
[317,] 0.996367029 7.265942e-03 3.632971e-03
[318,] 0.995403035 9.193930e-03 4.596965e-03
[319,] 0.994366045 1.126791e-02 5.633955e-03
[320,] 0.995178168 9.643665e-03 4.821832e-03
[321,] 0.997578778 4.842444e-03 2.421222e-03
[322,] 0.997485753 5.028495e-03 2.514247e-03
[323,] 0.996539863 6.920275e-03 3.460137e-03
[324,] 0.993175385 1.364923e-02 6.824615e-03
[325,] 0.983281141 3.343772e-02 1.671886e-02
[326,] 0.961687324 7.662535e-02 3.831268e-02
[327,] 0.970594931 5.881014e-02 2.940507e-02
[328,] 0.941059709 1.178806e-01 5.894029e-02
[329,] 0.886015738 2.279685e-01 1.139843e-01
> postscript(file="/var/fisher/rcomp/tmp/12kj21351781052.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/2br651351781052.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/3ple41351781052.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/4u9u01351781052.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/5o95r1351781052.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 = 360
Frequency = 1
1 2 3 4 5 6
-66.42934594 -43.75645331 -20.14213372 17.05251968 49.64425790 60.63043236
7 8 9 10 11 12
47.53810182 39.26675131 37.84804261 35.71505987 32.45580448 30.73228713
13 14 15 16 17 18
25.46136397 19.79938744 21.54162742 7.82699073 1.93506803 -8.52274136
19 20 21 22 23 24
-22.17552013 -37.95850203 -41.31442121 -40.71714225 -32.62521445 -30.23244283
25 26 27 28 29 30
-34.27778693 -37.89084642 -23.85971168 -28.47898089 -33.94076718 -38.96859048
31 32 33 34 35 36
-29.25870499 -7.85810115 -0.40498079 4.63633213 13.92813466 16.99291073
37 38 39 40 41 42
3.74751653 8.66232731 6.39527719 -6.55442910 -3.59514355 -6.15290283
43 44 45 46 47 48
-6.72426178 -9.68395582 -15.32358602 -16.22630707 -20.56924842 -33.08133481
49 50 51 52 53 54
-36.62902023 -52.91420944 -53.32776011 -56.70981886 -59.02032173 -58.62460663
55 56 57 58 59 60
-69.10525566 -70.32308166 -65.71386999 -69.43315562 -69.79956022 -56.85097290
61 62 63 64 65 66
-57.55908148 -46.88148116 -48.47201958 -50.48202376 -49.19018532 -51.39678647
67 68 69 70 71 72
-61.47046167 -59.60223534 -55.58604983 -66.04267121 -56.49953517 -50.54392390
73 74 75 76 77 78
-47.58458537 -46.16743328 -39.69024898 -49.35616908 -50.26669702 -50.97095685
79 80 81 82 83 84
-58.58879130 -55.79496084 -59.14642289 -56.18179705 -45.73873618 -42.74359819
85 86 87 88 89 90
-38.79594117 -33.16250010 -30.05278796 -31.41860784 -30.64774101 -28.42878815
91 92 93 94 95 96
-31.91870222 -36.88783668 -32.90662055 -26.43257935 -18.76391436 -16.71774351
97 98 99 100 101 102
-15.10490554 -12.39470222 -11.09443051 -8.38099649 -5.15184736 -10.26791399
103 104 105 106 107 108
-15.05780300 -18.62907834 -19.52933214 -12.01805542 -11.86590490 -17.14992058
109 110 111 112 113 114
-8.31656200 55.15809568 51.80643255 39.96145900 33.03922449 29.28378147
115 116 117 118 119 120
16.11247264 3.99932926 -8.56582989 -5.13831430 3.86280337 9.07191408
121 122 123 124 125 126
7.86383056 0.07866639 0.88608733 -8.23778935 -16.50174156 -17.89205373
127 128 129 130 131 132
-27.30291435 -36.34166184 -26.82081877 -20.26090061 -27.97609698 -26.75540498
133 134 135 136 137 138
-17.94498348 -23.74429575 -23.52058584 -19.76785060 -21.50161628 -22.40353480
139 140 141 142 143 144
-22.29810644 -25.41590739 -18.07643403 -16.19325307 -13.19465210 -4.75532981
145 146 147 148 149 150
-2.05188215 9.85839634 13.77508230 6.93446566 13.71703906 10.10102255
151 152 153 154 155 156
8.03895369 3.93278415 3.20249415 0.82298580 -6.27121391 2.64021306
157 158 159 160 161 162
2.82981328 8.45164800 0.92863186 -6.18615517 1.09641824 5.50147354
163 164 165 166 167 168
7.12550714 5.71933759 -2.49745574 2.46027143 3.93827663 8.78923032
169 170 171 172 173 174
10.50438455 12.71687907 6.27065023 0.03949906 -3.46400493 -5.09618514
175 176 177 178 179 180
-17.97915043 -25.39929270 -22.12260886 -21.08363726 -15.89405077 -15.85241222
181 182 183 184 185 186
-12.61872793 -6.15026737 -4.82887372 -7.92256387 -3.07493478 -7.83737669
187 188 189 190 191 192
-6.91553408 -6.07973536 -8.95194351 -9.47795242 -11.21860257 -10.39793563
193 194 195 196 197 198
-11.73398964 -3.36804578 2.06722036 -3.71038125 -1.78606508 -1.07408605
199 200 201 202 203 204
-7.49197061 -25.52882779 -21.51964117 -25.36425531 -15.68864154 -7.04005422
205 206 207 208 209 210
-2.23192393 -17.60361648 -52.00208083 -52.14690405 -49.84577552 -47.82226531
211 212 213 214 215 216
20.01105837 95.94784542 71.01431211 68.29044408 79.34745261 79.41716187
217 218 219 220 221 222
83.61607724 66.36344091 61.19414971 57.82372237 49.32462540 52.32280709
223 224 225 226 227 228
43.92128668 51.63384764 52.55471578 48.43351477 50.46491919 46.91114014
229 230 231 232 233 234
40.08472699 34.02025883 34.41831450 35.16661767 24.30951402 23.37733380
235 236 237 238 239 240
3.70577442 -26.16884444 -31.77375582 -32.44878199 -31.26853570 -11.95210039
241 242 243 244 245 246
-4.76929861 -41.02774505 -99.52529623 -45.23472414 -70.49786340 -41.19988215
247 248 249 250 251 252
42.95890921 58.00885602 65.49968796 56.59258495 64.29405339 38.86076990
253 254 255 256 257 258
24.60376934 3.81578781 41.39609014 28.44877527 40.56447784 31.79511221
259 260 261 262 263 264
19.60504781 13.69653696 24.64804261 18.93139895 14.08342420 10.95283279
265 266 267 268 269 270
11.05635562 13.24337130 19.42737909 18.75931812 23.53026012 13.52824138
271 272 273 274 275 276
15.68741974 19.73479974 27.73489671 39.62281041 16.03045092 -3.24497623
277 278 279 280 281 282
32.19854938 52.84150604 49.97435570 50.41110264 46.08899341 43.62682711
283 284 285 286 287 288
36.87404835 42.60058203 37.34932043 35.96042176 33.47780335 35.68457275
289 290 291 292 293 294
41.86495804 50.43356893 52.40367917 36.32836877 24.79201122 48.03480315
295 296 297 298 299 300
34.01226102 26.26178190 26.17320961 39.00797464 38.09967694 34.80873754
301 302 303 304 305 306
32.07950703 33.28736904 18.52928329 22.09584093 35.48563871 30.51400694
307 308 309 310 311 312
38.42207727 35.54848568 28.33174246 26.36384045 28.46714910 39.81145468
313 314 315 316 317 318
46.99373030 39.53414520 49.98585065 50.22685428 39.15575285 42.44696072
319 320 321 322 323 324
27.49393140 29.14831029 31.75976306 27.54309435 28.75352716 38.06012117
325 326 327 328 329 330
26.82366627 20.17561236 26.87117639 25.82640328 14.02506522 -6.64935887
331 332 333 334 335 336
12.98670701 9.66643948 0.30077922 1.97247911 -12.14775066 -27.78581700
337 338 339 340 341 342
-2.98473571 -41.86380297 -57.35728403 -22.81802040 -9.72142417 9.23277368
343 344 345 346 347 348
10.43636183 23.85103861 32.89302867 17.64781321 2.60691250 -0.84455029
349 350 351 352 353 354
-30.69547900 -21.51506132 6.00192531 0.50347737 11.49778239 2.91245351
355 356 357 358 359 360
-8.64274174 -17.34470470 -9.05626419 -6.98222299 -20.28873059 -36.78482867
> postscript(file="/var/fisher/rcomp/tmp/60rmm1351781052.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 = 360
Frequency = 1
lag(myerror, k = 1) myerror
0 -66.42934594 NA
1 -43.75645331 -66.42934594
2 -20.14213372 -43.75645331
3 17.05251968 -20.14213372
4 49.64425790 17.05251968
5 60.63043236 49.64425790
6 47.53810182 60.63043236
7 39.26675131 47.53810182
8 37.84804261 39.26675131
9 35.71505987 37.84804261
10 32.45580448 35.71505987
11 30.73228713 32.45580448
12 25.46136397 30.73228713
13 19.79938744 25.46136397
14 21.54162742 19.79938744
15 7.82699073 21.54162742
16 1.93506803 7.82699073
17 -8.52274136 1.93506803
18 -22.17552013 -8.52274136
19 -37.95850203 -22.17552013
20 -41.31442121 -37.95850203
21 -40.71714225 -41.31442121
22 -32.62521445 -40.71714225
23 -30.23244283 -32.62521445
24 -34.27778693 -30.23244283
25 -37.89084642 -34.27778693
26 -23.85971168 -37.89084642
27 -28.47898089 -23.85971168
28 -33.94076718 -28.47898089
29 -38.96859048 -33.94076718
30 -29.25870499 -38.96859048
31 -7.85810115 -29.25870499
32 -0.40498079 -7.85810115
33 4.63633213 -0.40498079
34 13.92813466 4.63633213
35 16.99291073 13.92813466
36 3.74751653 16.99291073
37 8.66232731 3.74751653
38 6.39527719 8.66232731
39 -6.55442910 6.39527719
40 -3.59514355 -6.55442910
41 -6.15290283 -3.59514355
42 -6.72426178 -6.15290283
43 -9.68395582 -6.72426178
44 -15.32358602 -9.68395582
45 -16.22630707 -15.32358602
46 -20.56924842 -16.22630707
47 -33.08133481 -20.56924842
48 -36.62902023 -33.08133481
49 -52.91420944 -36.62902023
50 -53.32776011 -52.91420944
51 -56.70981886 -53.32776011
52 -59.02032173 -56.70981886
53 -58.62460663 -59.02032173
54 -69.10525566 -58.62460663
55 -70.32308166 -69.10525566
56 -65.71386999 -70.32308166
57 -69.43315562 -65.71386999
58 -69.79956022 -69.43315562
59 -56.85097290 -69.79956022
60 -57.55908148 -56.85097290
61 -46.88148116 -57.55908148
62 -48.47201958 -46.88148116
63 -50.48202376 -48.47201958
64 -49.19018532 -50.48202376
65 -51.39678647 -49.19018532
66 -61.47046167 -51.39678647
67 -59.60223534 -61.47046167
68 -55.58604983 -59.60223534
69 -66.04267121 -55.58604983
70 -56.49953517 -66.04267121
71 -50.54392390 -56.49953517
72 -47.58458537 -50.54392390
73 -46.16743328 -47.58458537
74 -39.69024898 -46.16743328
75 -49.35616908 -39.69024898
76 -50.26669702 -49.35616908
77 -50.97095685 -50.26669702
78 -58.58879130 -50.97095685
79 -55.79496084 -58.58879130
80 -59.14642289 -55.79496084
81 -56.18179705 -59.14642289
82 -45.73873618 -56.18179705
83 -42.74359819 -45.73873618
84 -38.79594117 -42.74359819
85 -33.16250010 -38.79594117
86 -30.05278796 -33.16250010
87 -31.41860784 -30.05278796
88 -30.64774101 -31.41860784
89 -28.42878815 -30.64774101
90 -31.91870222 -28.42878815
91 -36.88783668 -31.91870222
92 -32.90662055 -36.88783668
93 -26.43257935 -32.90662055
94 -18.76391436 -26.43257935
95 -16.71774351 -18.76391436
96 -15.10490554 -16.71774351
97 -12.39470222 -15.10490554
98 -11.09443051 -12.39470222
99 -8.38099649 -11.09443051
100 -5.15184736 -8.38099649
101 -10.26791399 -5.15184736
102 -15.05780300 -10.26791399
103 -18.62907834 -15.05780300
104 -19.52933214 -18.62907834
105 -12.01805542 -19.52933214
106 -11.86590490 -12.01805542
107 -17.14992058 -11.86590490
108 -8.31656200 -17.14992058
109 55.15809568 -8.31656200
110 51.80643255 55.15809568
111 39.96145900 51.80643255
112 33.03922449 39.96145900
113 29.28378147 33.03922449
114 16.11247264 29.28378147
115 3.99932926 16.11247264
116 -8.56582989 3.99932926
117 -5.13831430 -8.56582989
118 3.86280337 -5.13831430
119 9.07191408 3.86280337
120 7.86383056 9.07191408
121 0.07866639 7.86383056
122 0.88608733 0.07866639
123 -8.23778935 0.88608733
124 -16.50174156 -8.23778935
125 -17.89205373 -16.50174156
126 -27.30291435 -17.89205373
127 -36.34166184 -27.30291435
128 -26.82081877 -36.34166184
129 -20.26090061 -26.82081877
130 -27.97609698 -20.26090061
131 -26.75540498 -27.97609698
132 -17.94498348 -26.75540498
133 -23.74429575 -17.94498348
134 -23.52058584 -23.74429575
135 -19.76785060 -23.52058584
136 -21.50161628 -19.76785060
137 -22.40353480 -21.50161628
138 -22.29810644 -22.40353480
139 -25.41590739 -22.29810644
140 -18.07643403 -25.41590739
141 -16.19325307 -18.07643403
142 -13.19465210 -16.19325307
143 -4.75532981 -13.19465210
144 -2.05188215 -4.75532981
145 9.85839634 -2.05188215
146 13.77508230 9.85839634
147 6.93446566 13.77508230
148 13.71703906 6.93446566
149 10.10102255 13.71703906
150 8.03895369 10.10102255
151 3.93278415 8.03895369
152 3.20249415 3.93278415
153 0.82298580 3.20249415
154 -6.27121391 0.82298580
155 2.64021306 -6.27121391
156 2.82981328 2.64021306
157 8.45164800 2.82981328
158 0.92863186 8.45164800
159 -6.18615517 0.92863186
160 1.09641824 -6.18615517
161 5.50147354 1.09641824
162 7.12550714 5.50147354
163 5.71933759 7.12550714
164 -2.49745574 5.71933759
165 2.46027143 -2.49745574
166 3.93827663 2.46027143
167 8.78923032 3.93827663
168 10.50438455 8.78923032
169 12.71687907 10.50438455
170 6.27065023 12.71687907
171 0.03949906 6.27065023
172 -3.46400493 0.03949906
173 -5.09618514 -3.46400493
174 -17.97915043 -5.09618514
175 -25.39929270 -17.97915043
176 -22.12260886 -25.39929270
177 -21.08363726 -22.12260886
178 -15.89405077 -21.08363726
179 -15.85241222 -15.89405077
180 -12.61872793 -15.85241222
181 -6.15026737 -12.61872793
182 -4.82887372 -6.15026737
183 -7.92256387 -4.82887372
184 -3.07493478 -7.92256387
185 -7.83737669 -3.07493478
186 -6.91553408 -7.83737669
187 -6.07973536 -6.91553408
188 -8.95194351 -6.07973536
189 -9.47795242 -8.95194351
190 -11.21860257 -9.47795242
191 -10.39793563 -11.21860257
192 -11.73398964 -10.39793563
193 -3.36804578 -11.73398964
194 2.06722036 -3.36804578
195 -3.71038125 2.06722036
196 -1.78606508 -3.71038125
197 -1.07408605 -1.78606508
198 -7.49197061 -1.07408605
199 -25.52882779 -7.49197061
200 -21.51964117 -25.52882779
201 -25.36425531 -21.51964117
202 -15.68864154 -25.36425531
203 -7.04005422 -15.68864154
204 -2.23192393 -7.04005422
205 -17.60361648 -2.23192393
206 -52.00208083 -17.60361648
207 -52.14690405 -52.00208083
208 -49.84577552 -52.14690405
209 -47.82226531 -49.84577552
210 20.01105837 -47.82226531
211 95.94784542 20.01105837
212 71.01431211 95.94784542
213 68.29044408 71.01431211
214 79.34745261 68.29044408
215 79.41716187 79.34745261
216 83.61607724 79.41716187
217 66.36344091 83.61607724
218 61.19414971 66.36344091
219 57.82372237 61.19414971
220 49.32462540 57.82372237
221 52.32280709 49.32462540
222 43.92128668 52.32280709
223 51.63384764 43.92128668
224 52.55471578 51.63384764
225 48.43351477 52.55471578
226 50.46491919 48.43351477
227 46.91114014 50.46491919
228 40.08472699 46.91114014
229 34.02025883 40.08472699
230 34.41831450 34.02025883
231 35.16661767 34.41831450
232 24.30951402 35.16661767
233 23.37733380 24.30951402
234 3.70577442 23.37733380
235 -26.16884444 3.70577442
236 -31.77375582 -26.16884444
237 -32.44878199 -31.77375582
238 -31.26853570 -32.44878199
239 -11.95210039 -31.26853570
240 -4.76929861 -11.95210039
241 -41.02774505 -4.76929861
242 -99.52529623 -41.02774505
243 -45.23472414 -99.52529623
244 -70.49786340 -45.23472414
245 -41.19988215 -70.49786340
246 42.95890921 -41.19988215
247 58.00885602 42.95890921
248 65.49968796 58.00885602
249 56.59258495 65.49968796
250 64.29405339 56.59258495
251 38.86076990 64.29405339
252 24.60376934 38.86076990
253 3.81578781 24.60376934
254 41.39609014 3.81578781
255 28.44877527 41.39609014
256 40.56447784 28.44877527
257 31.79511221 40.56447784
258 19.60504781 31.79511221
259 13.69653696 19.60504781
260 24.64804261 13.69653696
261 18.93139895 24.64804261
262 14.08342420 18.93139895
263 10.95283279 14.08342420
264 11.05635562 10.95283279
265 13.24337130 11.05635562
266 19.42737909 13.24337130
267 18.75931812 19.42737909
268 23.53026012 18.75931812
269 13.52824138 23.53026012
270 15.68741974 13.52824138
271 19.73479974 15.68741974
272 27.73489671 19.73479974
273 39.62281041 27.73489671
274 16.03045092 39.62281041
275 -3.24497623 16.03045092
276 32.19854938 -3.24497623
277 52.84150604 32.19854938
278 49.97435570 52.84150604
279 50.41110264 49.97435570
280 46.08899341 50.41110264
281 43.62682711 46.08899341
282 36.87404835 43.62682711
283 42.60058203 36.87404835
284 37.34932043 42.60058203
285 35.96042176 37.34932043
286 33.47780335 35.96042176
287 35.68457275 33.47780335
288 41.86495804 35.68457275
289 50.43356893 41.86495804
290 52.40367917 50.43356893
291 36.32836877 52.40367917
292 24.79201122 36.32836877
293 48.03480315 24.79201122
294 34.01226102 48.03480315
295 26.26178190 34.01226102
296 26.17320961 26.26178190
297 39.00797464 26.17320961
298 38.09967694 39.00797464
299 34.80873754 38.09967694
300 32.07950703 34.80873754
301 33.28736904 32.07950703
302 18.52928329 33.28736904
303 22.09584093 18.52928329
304 35.48563871 22.09584093
305 30.51400694 35.48563871
306 38.42207727 30.51400694
307 35.54848568 38.42207727
308 28.33174246 35.54848568
309 26.36384045 28.33174246
310 28.46714910 26.36384045
311 39.81145468 28.46714910
312 46.99373030 39.81145468
313 39.53414520 46.99373030
314 49.98585065 39.53414520
315 50.22685428 49.98585065
316 39.15575285 50.22685428
317 42.44696072 39.15575285
318 27.49393140 42.44696072
319 29.14831029 27.49393140
320 31.75976306 29.14831029
321 27.54309435 31.75976306
322 28.75352716 27.54309435
323 38.06012117 28.75352716
324 26.82366627 38.06012117
325 20.17561236 26.82366627
326 26.87117639 20.17561236
327 25.82640328 26.87117639
328 14.02506522 25.82640328
329 -6.64935887 14.02506522
330 12.98670701 -6.64935887
331 9.66643948 12.98670701
332 0.30077922 9.66643948
333 1.97247911 0.30077922
334 -12.14775066 1.97247911
335 -27.78581700 -12.14775066
336 -2.98473571 -27.78581700
337 -41.86380297 -2.98473571
338 -57.35728403 -41.86380297
339 -22.81802040 -57.35728403
340 -9.72142417 -22.81802040
341 9.23277368 -9.72142417
342 10.43636183 9.23277368
343 23.85103861 10.43636183
344 32.89302867 23.85103861
345 17.64781321 32.89302867
346 2.60691250 17.64781321
347 -0.84455029 2.60691250
348 -30.69547900 -0.84455029
349 -21.51506132 -30.69547900
350 6.00192531 -21.51506132
351 0.50347737 6.00192531
352 11.49778239 0.50347737
353 2.91245351 11.49778239
354 -8.64274174 2.91245351
355 -17.34470470 -8.64274174
356 -9.05626419 -17.34470470
357 -6.98222299 -9.05626419
358 -20.28873059 -6.98222299
359 -36.78482867 -20.28873059
360 NA -36.78482867
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -43.75645331 -66.42934594
[2,] -20.14213372 -43.75645331
[3,] 17.05251968 -20.14213372
[4,] 49.64425790 17.05251968
[5,] 60.63043236 49.64425790
[6,] 47.53810182 60.63043236
[7,] 39.26675131 47.53810182
[8,] 37.84804261 39.26675131
[9,] 35.71505987 37.84804261
[10,] 32.45580448 35.71505987
[11,] 30.73228713 32.45580448
[12,] 25.46136397 30.73228713
[13,] 19.79938744 25.46136397
[14,] 21.54162742 19.79938744
[15,] 7.82699073 21.54162742
[16,] 1.93506803 7.82699073
[17,] -8.52274136 1.93506803
[18,] -22.17552013 -8.52274136
[19,] -37.95850203 -22.17552013
[20,] -41.31442121 -37.95850203
[21,] -40.71714225 -41.31442121
[22,] -32.62521445 -40.71714225
[23,] -30.23244283 -32.62521445
[24,] -34.27778693 -30.23244283
[25,] -37.89084642 -34.27778693
[26,] -23.85971168 -37.89084642
[27,] -28.47898089 -23.85971168
[28,] -33.94076718 -28.47898089
[29,] -38.96859048 -33.94076718
[30,] -29.25870499 -38.96859048
[31,] -7.85810115 -29.25870499
[32,] -0.40498079 -7.85810115
[33,] 4.63633213 -0.40498079
[34,] 13.92813466 4.63633213
[35,] 16.99291073 13.92813466
[36,] 3.74751653 16.99291073
[37,] 8.66232731 3.74751653
[38,] 6.39527719 8.66232731
[39,] -6.55442910 6.39527719
[40,] -3.59514355 -6.55442910
[41,] -6.15290283 -3.59514355
[42,] -6.72426178 -6.15290283
[43,] -9.68395582 -6.72426178
[44,] -15.32358602 -9.68395582
[45,] -16.22630707 -15.32358602
[46,] -20.56924842 -16.22630707
[47,] -33.08133481 -20.56924842
[48,] -36.62902023 -33.08133481
[49,] -52.91420944 -36.62902023
[50,] -53.32776011 -52.91420944
[51,] -56.70981886 -53.32776011
[52,] -59.02032173 -56.70981886
[53,] -58.62460663 -59.02032173
[54,] -69.10525566 -58.62460663
[55,] -70.32308166 -69.10525566
[56,] -65.71386999 -70.32308166
[57,] -69.43315562 -65.71386999
[58,] -69.79956022 -69.43315562
[59,] -56.85097290 -69.79956022
[60,] -57.55908148 -56.85097290
[61,] -46.88148116 -57.55908148
[62,] -48.47201958 -46.88148116
[63,] -50.48202376 -48.47201958
[64,] -49.19018532 -50.48202376
[65,] -51.39678647 -49.19018532
[66,] -61.47046167 -51.39678647
[67,] -59.60223534 -61.47046167
[68,] -55.58604983 -59.60223534
[69,] -66.04267121 -55.58604983
[70,] -56.49953517 -66.04267121
[71,] -50.54392390 -56.49953517
[72,] -47.58458537 -50.54392390
[73,] -46.16743328 -47.58458537
[74,] -39.69024898 -46.16743328
[75,] -49.35616908 -39.69024898
[76,] -50.26669702 -49.35616908
[77,] -50.97095685 -50.26669702
[78,] -58.58879130 -50.97095685
[79,] -55.79496084 -58.58879130
[80,] -59.14642289 -55.79496084
[81,] -56.18179705 -59.14642289
[82,] -45.73873618 -56.18179705
[83,] -42.74359819 -45.73873618
[84,] -38.79594117 -42.74359819
[85,] -33.16250010 -38.79594117
[86,] -30.05278796 -33.16250010
[87,] -31.41860784 -30.05278796
[88,] -30.64774101 -31.41860784
[89,] -28.42878815 -30.64774101
[90,] -31.91870222 -28.42878815
[91,] -36.88783668 -31.91870222
[92,] -32.90662055 -36.88783668
[93,] -26.43257935 -32.90662055
[94,] -18.76391436 -26.43257935
[95,] -16.71774351 -18.76391436
[96,] -15.10490554 -16.71774351
[97,] -12.39470222 -15.10490554
[98,] -11.09443051 -12.39470222
[99,] -8.38099649 -11.09443051
[100,] -5.15184736 -8.38099649
[101,] -10.26791399 -5.15184736
[102,] -15.05780300 -10.26791399
[103,] -18.62907834 -15.05780300
[104,] -19.52933214 -18.62907834
[105,] -12.01805542 -19.52933214
[106,] -11.86590490 -12.01805542
[107,] -17.14992058 -11.86590490
[108,] -8.31656200 -17.14992058
[109,] 55.15809568 -8.31656200
[110,] 51.80643255 55.15809568
[111,] 39.96145900 51.80643255
[112,] 33.03922449 39.96145900
[113,] 29.28378147 33.03922449
[114,] 16.11247264 29.28378147
[115,] 3.99932926 16.11247264
[116,] -8.56582989 3.99932926
[117,] -5.13831430 -8.56582989
[118,] 3.86280337 -5.13831430
[119,] 9.07191408 3.86280337
[120,] 7.86383056 9.07191408
[121,] 0.07866639 7.86383056
[122,] 0.88608733 0.07866639
[123,] -8.23778935 0.88608733
[124,] -16.50174156 -8.23778935
[125,] -17.89205373 -16.50174156
[126,] -27.30291435 -17.89205373
[127,] -36.34166184 -27.30291435
[128,] -26.82081877 -36.34166184
[129,] -20.26090061 -26.82081877
[130,] -27.97609698 -20.26090061
[131,] -26.75540498 -27.97609698
[132,] -17.94498348 -26.75540498
[133,] -23.74429575 -17.94498348
[134,] -23.52058584 -23.74429575
[135,] -19.76785060 -23.52058584
[136,] -21.50161628 -19.76785060
[137,] -22.40353480 -21.50161628
[138,] -22.29810644 -22.40353480
[139,] -25.41590739 -22.29810644
[140,] -18.07643403 -25.41590739
[141,] -16.19325307 -18.07643403
[142,] -13.19465210 -16.19325307
[143,] -4.75532981 -13.19465210
[144,] -2.05188215 -4.75532981
[145,] 9.85839634 -2.05188215
[146,] 13.77508230 9.85839634
[147,] 6.93446566 13.77508230
[148,] 13.71703906 6.93446566
[149,] 10.10102255 13.71703906
[150,] 8.03895369 10.10102255
[151,] 3.93278415 8.03895369
[152,] 3.20249415 3.93278415
[153,] 0.82298580 3.20249415
[154,] -6.27121391 0.82298580
[155,] 2.64021306 -6.27121391
[156,] 2.82981328 2.64021306
[157,] 8.45164800 2.82981328
[158,] 0.92863186 8.45164800
[159,] -6.18615517 0.92863186
[160,] 1.09641824 -6.18615517
[161,] 5.50147354 1.09641824
[162,] 7.12550714 5.50147354
[163,] 5.71933759 7.12550714
[164,] -2.49745574 5.71933759
[165,] 2.46027143 -2.49745574
[166,] 3.93827663 2.46027143
[167,] 8.78923032 3.93827663
[168,] 10.50438455 8.78923032
[169,] 12.71687907 10.50438455
[170,] 6.27065023 12.71687907
[171,] 0.03949906 6.27065023
[172,] -3.46400493 0.03949906
[173,] -5.09618514 -3.46400493
[174,] -17.97915043 -5.09618514
[175,] -25.39929270 -17.97915043
[176,] -22.12260886 -25.39929270
[177,] -21.08363726 -22.12260886
[178,] -15.89405077 -21.08363726
[179,] -15.85241222 -15.89405077
[180,] -12.61872793 -15.85241222
[181,] -6.15026737 -12.61872793
[182,] -4.82887372 -6.15026737
[183,] -7.92256387 -4.82887372
[184,] -3.07493478 -7.92256387
[185,] -7.83737669 -3.07493478
[186,] -6.91553408 -7.83737669
[187,] -6.07973536 -6.91553408
[188,] -8.95194351 -6.07973536
[189,] -9.47795242 -8.95194351
[190,] -11.21860257 -9.47795242
[191,] -10.39793563 -11.21860257
[192,] -11.73398964 -10.39793563
[193,] -3.36804578 -11.73398964
[194,] 2.06722036 -3.36804578
[195,] -3.71038125 2.06722036
[196,] -1.78606508 -3.71038125
[197,] -1.07408605 -1.78606508
[198,] -7.49197061 -1.07408605
[199,] -25.52882779 -7.49197061
[200,] -21.51964117 -25.52882779
[201,] -25.36425531 -21.51964117
[202,] -15.68864154 -25.36425531
[203,] -7.04005422 -15.68864154
[204,] -2.23192393 -7.04005422
[205,] -17.60361648 -2.23192393
[206,] -52.00208083 -17.60361648
[207,] -52.14690405 -52.00208083
[208,] -49.84577552 -52.14690405
[209,] -47.82226531 -49.84577552
[210,] 20.01105837 -47.82226531
[211,] 95.94784542 20.01105837
[212,] 71.01431211 95.94784542
[213,] 68.29044408 71.01431211
[214,] 79.34745261 68.29044408
[215,] 79.41716187 79.34745261
[216,] 83.61607724 79.41716187
[217,] 66.36344091 83.61607724
[218,] 61.19414971 66.36344091
[219,] 57.82372237 61.19414971
[220,] 49.32462540 57.82372237
[221,] 52.32280709 49.32462540
[222,] 43.92128668 52.32280709
[223,] 51.63384764 43.92128668
[224,] 52.55471578 51.63384764
[225,] 48.43351477 52.55471578
[226,] 50.46491919 48.43351477
[227,] 46.91114014 50.46491919
[228,] 40.08472699 46.91114014
[229,] 34.02025883 40.08472699
[230,] 34.41831450 34.02025883
[231,] 35.16661767 34.41831450
[232,] 24.30951402 35.16661767
[233,] 23.37733380 24.30951402
[234,] 3.70577442 23.37733380
[235,] -26.16884444 3.70577442
[236,] -31.77375582 -26.16884444
[237,] -32.44878199 -31.77375582
[238,] -31.26853570 -32.44878199
[239,] -11.95210039 -31.26853570
[240,] -4.76929861 -11.95210039
[241,] -41.02774505 -4.76929861
[242,] -99.52529623 -41.02774505
[243,] -45.23472414 -99.52529623
[244,] -70.49786340 -45.23472414
[245,] -41.19988215 -70.49786340
[246,] 42.95890921 -41.19988215
[247,] 58.00885602 42.95890921
[248,] 65.49968796 58.00885602
[249,] 56.59258495 65.49968796
[250,] 64.29405339 56.59258495
[251,] 38.86076990 64.29405339
[252,] 24.60376934 38.86076990
[253,] 3.81578781 24.60376934
[254,] 41.39609014 3.81578781
[255,] 28.44877527 41.39609014
[256,] 40.56447784 28.44877527
[257,] 31.79511221 40.56447784
[258,] 19.60504781 31.79511221
[259,] 13.69653696 19.60504781
[260,] 24.64804261 13.69653696
[261,] 18.93139895 24.64804261
[262,] 14.08342420 18.93139895
[263,] 10.95283279 14.08342420
[264,] 11.05635562 10.95283279
[265,] 13.24337130 11.05635562
[266,] 19.42737909 13.24337130
[267,] 18.75931812 19.42737909
[268,] 23.53026012 18.75931812
[269,] 13.52824138 23.53026012
[270,] 15.68741974 13.52824138
[271,] 19.73479974 15.68741974
[272,] 27.73489671 19.73479974
[273,] 39.62281041 27.73489671
[274,] 16.03045092 39.62281041
[275,] -3.24497623 16.03045092
[276,] 32.19854938 -3.24497623
[277,] 52.84150604 32.19854938
[278,] 49.97435570 52.84150604
[279,] 50.41110264 49.97435570
[280,] 46.08899341 50.41110264
[281,] 43.62682711 46.08899341
[282,] 36.87404835 43.62682711
[283,] 42.60058203 36.87404835
[284,] 37.34932043 42.60058203
[285,] 35.96042176 37.34932043
[286,] 33.47780335 35.96042176
[287,] 35.68457275 33.47780335
[288,] 41.86495804 35.68457275
[289,] 50.43356893 41.86495804
[290,] 52.40367917 50.43356893
[291,] 36.32836877 52.40367917
[292,] 24.79201122 36.32836877
[293,] 48.03480315 24.79201122
[294,] 34.01226102 48.03480315
[295,] 26.26178190 34.01226102
[296,] 26.17320961 26.26178190
[297,] 39.00797464 26.17320961
[298,] 38.09967694 39.00797464
[299,] 34.80873754 38.09967694
[300,] 32.07950703 34.80873754
[301,] 33.28736904 32.07950703
[302,] 18.52928329 33.28736904
[303,] 22.09584093 18.52928329
[304,] 35.48563871 22.09584093
[305,] 30.51400694 35.48563871
[306,] 38.42207727 30.51400694
[307,] 35.54848568 38.42207727
[308,] 28.33174246 35.54848568
[309,] 26.36384045 28.33174246
[310,] 28.46714910 26.36384045
[311,] 39.81145468 28.46714910
[312,] 46.99373030 39.81145468
[313,] 39.53414520 46.99373030
[314,] 49.98585065 39.53414520
[315,] 50.22685428 49.98585065
[316,] 39.15575285 50.22685428
[317,] 42.44696072 39.15575285
[318,] 27.49393140 42.44696072
[319,] 29.14831029 27.49393140
[320,] 31.75976306 29.14831029
[321,] 27.54309435 31.75976306
[322,] 28.75352716 27.54309435
[323,] 38.06012117 28.75352716
[324,] 26.82366627 38.06012117
[325,] 20.17561236 26.82366627
[326,] 26.87117639 20.17561236
[327,] 25.82640328 26.87117639
[328,] 14.02506522 25.82640328
[329,] -6.64935887 14.02506522
[330,] 12.98670701 -6.64935887
[331,] 9.66643948 12.98670701
[332,] 0.30077922 9.66643948
[333,] 1.97247911 0.30077922
[334,] -12.14775066 1.97247911
[335,] -27.78581700 -12.14775066
[336,] -2.98473571 -27.78581700
[337,] -41.86380297 -2.98473571
[338,] -57.35728403 -41.86380297
[339,] -22.81802040 -57.35728403
[340,] -9.72142417 -22.81802040
[341,] 9.23277368 -9.72142417
[342,] 10.43636183 9.23277368
[343,] 23.85103861 10.43636183
[344,] 32.89302867 23.85103861
[345,] 17.64781321 32.89302867
[346,] 2.60691250 17.64781321
[347,] -0.84455029 2.60691250
[348,] -30.69547900 -0.84455029
[349,] -21.51506132 -30.69547900
[350,] 6.00192531 -21.51506132
[351,] 0.50347737 6.00192531
[352,] 11.49778239 0.50347737
[353,] 2.91245351 11.49778239
[354,] -8.64274174 2.91245351
[355,] -17.34470470 -8.64274174
[356,] -9.05626419 -17.34470470
[357,] -6.98222299 -9.05626419
[358,] -20.28873059 -6.98222299
[359,] -36.78482867 -20.28873059
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -43.75645331 -66.42934594
2 -20.14213372 -43.75645331
3 17.05251968 -20.14213372
4 49.64425790 17.05251968
5 60.63043236 49.64425790
6 47.53810182 60.63043236
7 39.26675131 47.53810182
8 37.84804261 39.26675131
9 35.71505987 37.84804261
10 32.45580448 35.71505987
11 30.73228713 32.45580448
12 25.46136397 30.73228713
13 19.79938744 25.46136397
14 21.54162742 19.79938744
15 7.82699073 21.54162742
16 1.93506803 7.82699073
17 -8.52274136 1.93506803
18 -22.17552013 -8.52274136
19 -37.95850203 -22.17552013
20 -41.31442121 -37.95850203
21 -40.71714225 -41.31442121
22 -32.62521445 -40.71714225
23 -30.23244283 -32.62521445
24 -34.27778693 -30.23244283
25 -37.89084642 -34.27778693
26 -23.85971168 -37.89084642
27 -28.47898089 -23.85971168
28 -33.94076718 -28.47898089
29 -38.96859048 -33.94076718
30 -29.25870499 -38.96859048
31 -7.85810115 -29.25870499
32 -0.40498079 -7.85810115
33 4.63633213 -0.40498079
34 13.92813466 4.63633213
35 16.99291073 13.92813466
36 3.74751653 16.99291073
37 8.66232731 3.74751653
38 6.39527719 8.66232731
39 -6.55442910 6.39527719
40 -3.59514355 -6.55442910
41 -6.15290283 -3.59514355
42 -6.72426178 -6.15290283
43 -9.68395582 -6.72426178
44 -15.32358602 -9.68395582
45 -16.22630707 -15.32358602
46 -20.56924842 -16.22630707
47 -33.08133481 -20.56924842
48 -36.62902023 -33.08133481
49 -52.91420944 -36.62902023
50 -53.32776011 -52.91420944
51 -56.70981886 -53.32776011
52 -59.02032173 -56.70981886
53 -58.62460663 -59.02032173
54 -69.10525566 -58.62460663
55 -70.32308166 -69.10525566
56 -65.71386999 -70.32308166
57 -69.43315562 -65.71386999
58 -69.79956022 -69.43315562
59 -56.85097290 -69.79956022
60 -57.55908148 -56.85097290
61 -46.88148116 -57.55908148
62 -48.47201958 -46.88148116
63 -50.48202376 -48.47201958
64 -49.19018532 -50.48202376
65 -51.39678647 -49.19018532
66 -61.47046167 -51.39678647
67 -59.60223534 -61.47046167
68 -55.58604983 -59.60223534
69 -66.04267121 -55.58604983
70 -56.49953517 -66.04267121
71 -50.54392390 -56.49953517
72 -47.58458537 -50.54392390
73 -46.16743328 -47.58458537
74 -39.69024898 -46.16743328
75 -49.35616908 -39.69024898
76 -50.26669702 -49.35616908
77 -50.97095685 -50.26669702
78 -58.58879130 -50.97095685
79 -55.79496084 -58.58879130
80 -59.14642289 -55.79496084
81 -56.18179705 -59.14642289
82 -45.73873618 -56.18179705
83 -42.74359819 -45.73873618
84 -38.79594117 -42.74359819
85 -33.16250010 -38.79594117
86 -30.05278796 -33.16250010
87 -31.41860784 -30.05278796
88 -30.64774101 -31.41860784
89 -28.42878815 -30.64774101
90 -31.91870222 -28.42878815
91 -36.88783668 -31.91870222
92 -32.90662055 -36.88783668
93 -26.43257935 -32.90662055
94 -18.76391436 -26.43257935
95 -16.71774351 -18.76391436
96 -15.10490554 -16.71774351
97 -12.39470222 -15.10490554
98 -11.09443051 -12.39470222
99 -8.38099649 -11.09443051
100 -5.15184736 -8.38099649
101 -10.26791399 -5.15184736
102 -15.05780300 -10.26791399
103 -18.62907834 -15.05780300
104 -19.52933214 -18.62907834
105 -12.01805542 -19.52933214
106 -11.86590490 -12.01805542
107 -17.14992058 -11.86590490
108 -8.31656200 -17.14992058
109 55.15809568 -8.31656200
110 51.80643255 55.15809568
111 39.96145900 51.80643255
112 33.03922449 39.96145900
113 29.28378147 33.03922449
114 16.11247264 29.28378147
115 3.99932926 16.11247264
116 -8.56582989 3.99932926
117 -5.13831430 -8.56582989
118 3.86280337 -5.13831430
119 9.07191408 3.86280337
120 7.86383056 9.07191408
121 0.07866639 7.86383056
122 0.88608733 0.07866639
123 -8.23778935 0.88608733
124 -16.50174156 -8.23778935
125 -17.89205373 -16.50174156
126 -27.30291435 -17.89205373
127 -36.34166184 -27.30291435
128 -26.82081877 -36.34166184
129 -20.26090061 -26.82081877
130 -27.97609698 -20.26090061
131 -26.75540498 -27.97609698
132 -17.94498348 -26.75540498
133 -23.74429575 -17.94498348
134 -23.52058584 -23.74429575
135 -19.76785060 -23.52058584
136 -21.50161628 -19.76785060
137 -22.40353480 -21.50161628
138 -22.29810644 -22.40353480
139 -25.41590739 -22.29810644
140 -18.07643403 -25.41590739
141 -16.19325307 -18.07643403
142 -13.19465210 -16.19325307
143 -4.75532981 -13.19465210
144 -2.05188215 -4.75532981
145 9.85839634 -2.05188215
146 13.77508230 9.85839634
147 6.93446566 13.77508230
148 13.71703906 6.93446566
149 10.10102255 13.71703906
150 8.03895369 10.10102255
151 3.93278415 8.03895369
152 3.20249415 3.93278415
153 0.82298580 3.20249415
154 -6.27121391 0.82298580
155 2.64021306 -6.27121391
156 2.82981328 2.64021306
157 8.45164800 2.82981328
158 0.92863186 8.45164800
159 -6.18615517 0.92863186
160 1.09641824 -6.18615517
161 5.50147354 1.09641824
162 7.12550714 5.50147354
163 5.71933759 7.12550714
164 -2.49745574 5.71933759
165 2.46027143 -2.49745574
166 3.93827663 2.46027143
167 8.78923032 3.93827663
168 10.50438455 8.78923032
169 12.71687907 10.50438455
170 6.27065023 12.71687907
171 0.03949906 6.27065023
172 -3.46400493 0.03949906
173 -5.09618514 -3.46400493
174 -17.97915043 -5.09618514
175 -25.39929270 -17.97915043
176 -22.12260886 -25.39929270
177 -21.08363726 -22.12260886
178 -15.89405077 -21.08363726
179 -15.85241222 -15.89405077
180 -12.61872793 -15.85241222
181 -6.15026737 -12.61872793
182 -4.82887372 -6.15026737
183 -7.92256387 -4.82887372
184 -3.07493478 -7.92256387
185 -7.83737669 -3.07493478
186 -6.91553408 -7.83737669
187 -6.07973536 -6.91553408
188 -8.95194351 -6.07973536
189 -9.47795242 -8.95194351
190 -11.21860257 -9.47795242
191 -10.39793563 -11.21860257
192 -11.73398964 -10.39793563
193 -3.36804578 -11.73398964
194 2.06722036 -3.36804578
195 -3.71038125 2.06722036
196 -1.78606508 -3.71038125
197 -1.07408605 -1.78606508
198 -7.49197061 -1.07408605
199 -25.52882779 -7.49197061
200 -21.51964117 -25.52882779
201 -25.36425531 -21.51964117
202 -15.68864154 -25.36425531
203 -7.04005422 -15.68864154
204 -2.23192393 -7.04005422
205 -17.60361648 -2.23192393
206 -52.00208083 -17.60361648
207 -52.14690405 -52.00208083
208 -49.84577552 -52.14690405
209 -47.82226531 -49.84577552
210 20.01105837 -47.82226531
211 95.94784542 20.01105837
212 71.01431211 95.94784542
213 68.29044408 71.01431211
214 79.34745261 68.29044408
215 79.41716187 79.34745261
216 83.61607724 79.41716187
217 66.36344091 83.61607724
218 61.19414971 66.36344091
219 57.82372237 61.19414971
220 49.32462540 57.82372237
221 52.32280709 49.32462540
222 43.92128668 52.32280709
223 51.63384764 43.92128668
224 52.55471578 51.63384764
225 48.43351477 52.55471578
226 50.46491919 48.43351477
227 46.91114014 50.46491919
228 40.08472699 46.91114014
229 34.02025883 40.08472699
230 34.41831450 34.02025883
231 35.16661767 34.41831450
232 24.30951402 35.16661767
233 23.37733380 24.30951402
234 3.70577442 23.37733380
235 -26.16884444 3.70577442
236 -31.77375582 -26.16884444
237 -32.44878199 -31.77375582
238 -31.26853570 -32.44878199
239 -11.95210039 -31.26853570
240 -4.76929861 -11.95210039
241 -41.02774505 -4.76929861
242 -99.52529623 -41.02774505
243 -45.23472414 -99.52529623
244 -70.49786340 -45.23472414
245 -41.19988215 -70.49786340
246 42.95890921 -41.19988215
247 58.00885602 42.95890921
248 65.49968796 58.00885602
249 56.59258495 65.49968796
250 64.29405339 56.59258495
251 38.86076990 64.29405339
252 24.60376934 38.86076990
253 3.81578781 24.60376934
254 41.39609014 3.81578781
255 28.44877527 41.39609014
256 40.56447784 28.44877527
257 31.79511221 40.56447784
258 19.60504781 31.79511221
259 13.69653696 19.60504781
260 24.64804261 13.69653696
261 18.93139895 24.64804261
262 14.08342420 18.93139895
263 10.95283279 14.08342420
264 11.05635562 10.95283279
265 13.24337130 11.05635562
266 19.42737909 13.24337130
267 18.75931812 19.42737909
268 23.53026012 18.75931812
269 13.52824138 23.53026012
270 15.68741974 13.52824138
271 19.73479974 15.68741974
272 27.73489671 19.73479974
273 39.62281041 27.73489671
274 16.03045092 39.62281041
275 -3.24497623 16.03045092
276 32.19854938 -3.24497623
277 52.84150604 32.19854938
278 49.97435570 52.84150604
279 50.41110264 49.97435570
280 46.08899341 50.41110264
281 43.62682711 46.08899341
282 36.87404835 43.62682711
283 42.60058203 36.87404835
284 37.34932043 42.60058203
285 35.96042176 37.34932043
286 33.47780335 35.96042176
287 35.68457275 33.47780335
288 41.86495804 35.68457275
289 50.43356893 41.86495804
290 52.40367917 50.43356893
291 36.32836877 52.40367917
292 24.79201122 36.32836877
293 48.03480315 24.79201122
294 34.01226102 48.03480315
295 26.26178190 34.01226102
296 26.17320961 26.26178190
297 39.00797464 26.17320961
298 38.09967694 39.00797464
299 34.80873754 38.09967694
300 32.07950703 34.80873754
301 33.28736904 32.07950703
302 18.52928329 33.28736904
303 22.09584093 18.52928329
304 35.48563871 22.09584093
305 30.51400694 35.48563871
306 38.42207727 30.51400694
307 35.54848568 38.42207727
308 28.33174246 35.54848568
309 26.36384045 28.33174246
310 28.46714910 26.36384045
311 39.81145468 28.46714910
312 46.99373030 39.81145468
313 39.53414520 46.99373030
314 49.98585065 39.53414520
315 50.22685428 49.98585065
316 39.15575285 50.22685428
317 42.44696072 39.15575285
318 27.49393140 42.44696072
319 29.14831029 27.49393140
320 31.75976306 29.14831029
321 27.54309435 31.75976306
322 28.75352716 27.54309435
323 38.06012117 28.75352716
324 26.82366627 38.06012117
325 20.17561236 26.82366627
326 26.87117639 20.17561236
327 25.82640328 26.87117639
328 14.02506522 25.82640328
329 -6.64935887 14.02506522
330 12.98670701 -6.64935887
331 9.66643948 12.98670701
332 0.30077922 9.66643948
333 1.97247911 0.30077922
334 -12.14775066 1.97247911
335 -27.78581700 -12.14775066
336 -2.98473571 -27.78581700
337 -41.86380297 -2.98473571
338 -57.35728403 -41.86380297
339 -22.81802040 -57.35728403
340 -9.72142417 -22.81802040
341 9.23277368 -9.72142417
342 10.43636183 9.23277368
343 23.85103861 10.43636183
344 32.89302867 23.85103861
345 17.64781321 32.89302867
346 2.60691250 17.64781321
347 -0.84455029 2.60691250
348 -30.69547900 -0.84455029
349 -21.51506132 -30.69547900
350 6.00192531 -21.51506132
351 0.50347737 6.00192531
352 11.49778239 0.50347737
353 2.91245351 11.49778239
354 -8.64274174 2.91245351
355 -17.34470470 -8.64274174
356 -9.05626419 -17.34470470
357 -6.98222299 -9.05626419
358 -20.28873059 -6.98222299
359 -36.78482867 -20.28873059
> 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/fisher/rcomp/tmp/7po1o1351781052.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/87tuq1351781052.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/9i5xb1351781052.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/fisher/rcomp/tmp/10f2e71351781052.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/fisher/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/fisher/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
+ myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ')
+ if (rownames(mysum$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.end(a)
> table.save(a,file="/var/fisher/rcomp/tmp/11ds4d1351781052.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$coefficients)[i],header=TRUE)
+ a<-table.element(a,mysum$coefficients[i,1])
+ a<-table.element(a, round(mysum$coefficients[i,2],6))
+ a<-table.element(a, round(mysum$coefficients[i,3],4))
+ a<-table.element(a, round(mysum$coefficients[i,4],6))
+ a<-table.element(a, round(mysum$coefficients[i,4]/2,6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/fisher/rcomp/tmp/12cvi41351781052.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, sqrt(mysum$r.squared))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'R-squared',1,TRUE)
> a<-table.element(a, mysum$r.squared)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Adjusted R-squared',1,TRUE)
> a<-table.element(a, mysum$adj.r.squared)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (value)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[1])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[2])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[3])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'p-value',1,TRUE)
> a<-table.element(a, 1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
> a<-table.element(a, mysum$sigma)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a, sum(myerror*myerror))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/fisher/rcomp/tmp/137bt41351781052.tab")
> 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,x[i])
+ a<-table.element(a,x[i]-mysum$resid[i])
+ a<-table.element(a,mysum$resid[i])
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/fisher/rcomp/tmp/14m3631351781052.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,gqarr[mypoint-kp3+1,1])
+ a<-table.element(a,gqarr[mypoint-kp3+1,2])
+ a<-table.element(a,gqarr[mypoint-kp3+1,3])
+ a<-table.row.end(a)
+ }
+ a<-table.end(a)
+ table.save(a,file="/var/fisher/rcomp/tmp/15g2ah1351781052.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,numsignificant1)
+ a<-table.element(a,numsignificant1/numgqtests)
+ 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,numsignificant5)
+ a<-table.element(a,numsignificant5/numgqtests)
+ 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,numsignificant10)
+ a<-table.element(a,numsignificant10/numgqtests)
+ 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/fisher/rcomp/tmp/16i3pv1351781052.tab")
+ }
>
> try(system("convert tmp/12kj21351781052.ps tmp/12kj21351781052.png",intern=TRUE))
character(0)
> try(system("convert tmp/2br651351781052.ps tmp/2br651351781052.png",intern=TRUE))
character(0)
> try(system("convert tmp/3ple41351781052.ps tmp/3ple41351781052.png",intern=TRUE))
character(0)
> try(system("convert tmp/4u9u01351781052.ps tmp/4u9u01351781052.png",intern=TRUE))
character(0)
> try(system("convert tmp/5o95r1351781052.ps tmp/5o95r1351781052.png",intern=TRUE))
character(0)
> try(system("convert tmp/60rmm1351781052.ps tmp/60rmm1351781052.png",intern=TRUE))
character(0)
> try(system("convert tmp/7po1o1351781052.ps tmp/7po1o1351781052.png",intern=TRUE))
character(0)
> try(system("convert tmp/87tuq1351781052.ps tmp/87tuq1351781052.png",intern=TRUE))
character(0)
> try(system("convert tmp/9i5xb1351781052.ps tmp/9i5xb1351781052.png",intern=TRUE))
character(0)
> try(system("convert tmp/10f2e71351781052.ps tmp/10f2e71351781052.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
14.007 1.102 15.117