R version 2.9.0 (2009-04-17)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
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(30
+ ,35
+ ,47
+ ,30
+ ,37
+ ,43
+ ,30
+ ,35
+ ,47
+ ,30
+ ,82
+ ,43
+ ,30
+ ,35
+ ,47
+ ,40
+ ,82
+ ,43
+ ,30
+ ,35
+ ,47
+ ,40
+ ,82
+ ,43
+ ,30
+ ,19
+ ,47
+ ,40
+ ,82
+ ,43
+ ,52
+ ,19
+ ,47
+ ,40
+ ,82
+ ,136
+ ,52
+ ,19
+ ,47
+ ,40
+ ,80
+ ,136
+ ,52
+ ,19
+ ,47
+ ,42
+ ,80
+ ,136
+ ,52
+ ,19
+ ,54
+ ,42
+ ,80
+ ,136
+ ,52
+ ,66
+ ,54
+ ,42
+ ,80
+ ,136
+ ,81
+ ,66
+ ,54
+ ,42
+ ,80
+ ,63
+ ,81
+ ,66
+ ,54
+ ,42
+ ,137
+ ,63
+ ,81
+ ,66
+ ,54
+ ,72
+ ,137
+ ,63
+ ,81
+ ,66
+ ,107
+ ,72
+ ,137
+ ,63
+ ,81
+ ,58
+ ,107
+ ,72
+ ,137
+ ,63
+ ,36
+ ,58
+ ,107
+ ,72
+ ,137
+ ,52
+ ,36
+ ,58
+ ,107
+ ,72
+ ,79
+ ,52
+ ,36
+ ,58
+ ,107
+ ,77
+ ,79
+ ,52
+ ,36
+ ,58
+ ,54
+ ,77
+ ,79
+ ,52
+ ,36
+ ,84
+ ,54
+ ,77
+ ,79
+ ,52
+ ,48
+ ,84
+ ,54
+ ,77
+ ,79
+ ,96
+ ,48
+ ,84
+ ,54
+ ,77
+ ,83
+ ,96
+ ,48
+ ,84
+ ,54
+ ,66
+ ,83
+ ,96
+ ,48
+ ,84
+ ,61
+ ,66
+ ,83
+ ,96
+ ,48
+ ,53
+ ,61
+ ,66
+ ,83
+ ,96
+ ,30
+ ,53
+ ,61
+ ,66
+ ,83
+ ,74
+ ,30
+ ,53
+ ,61
+ ,66
+ ,69
+ ,74
+ ,30
+ ,53
+ ,61
+ ,59
+ ,69
+ ,74
+ ,30
+ ,53
+ ,42
+ ,59
+ ,69
+ ,74
+ ,30
+ ,65
+ ,42
+ ,59
+ ,69
+ ,74
+ ,70
+ ,65
+ ,42
+ ,59
+ ,69
+ ,100
+ ,70
+ ,65
+ ,42
+ ,59
+ ,63
+ ,100
+ ,70
+ ,65
+ ,42
+ ,105
+ ,63
+ ,100
+ ,70
+ ,65
+ ,82
+ ,105
+ ,63
+ ,100
+ ,70
+ ,81
+ ,82
+ ,105
+ ,63
+ ,100
+ ,75
+ ,81
+ ,82
+ ,105
+ ,63
+ ,102
+ ,75
+ ,81
+ ,82
+ ,105
+ ,121
+ ,102
+ ,75
+ ,81
+ ,82
+ ,98
+ ,121
+ ,102
+ ,75
+ ,81
+ ,76
+ ,98
+ ,121
+ ,102
+ ,75
+ ,77
+ ,76
+ ,98
+ ,121
+ ,102
+ ,63
+ ,77
+ ,76
+ ,98
+ ,121
+ ,37
+ ,63
+ ,77
+ ,76
+ ,98
+ ,35
+ ,37
+ ,63
+ ,77
+ ,76
+ ,23
+ ,35
+ ,37
+ ,63
+ ,77
+ ,40
+ ,23
+ ,35
+ ,37
+ ,63
+ ,29
+ ,40
+ ,23
+ ,35
+ ,37
+ ,37
+ ,29
+ ,40
+ ,23
+ ,35
+ ,51
+ ,37
+ ,29
+ ,40
+ ,23
+ ,20
+ ,51
+ ,37
+ ,29
+ ,40
+ ,28
+ ,20
+ ,51
+ ,37
+ ,29
+ ,13
+ ,28
+ ,20
+ ,51
+ ,37
+ ,22
+ ,13
+ ,28
+ ,20
+ ,51
+ ,25
+ ,22
+ ,13
+ ,28
+ ,20
+ ,13
+ ,25
+ ,22
+ ,13
+ ,28
+ ,16
+ ,13
+ ,25
+ ,22
+ ,13
+ ,13
+ ,16
+ ,13
+ ,25
+ ,22
+ ,16
+ ,13
+ ,16
+ ,13
+ ,25
+ ,17
+ ,16
+ ,13
+ ,16
+ ,13
+ ,9
+ ,17
+ ,16
+ ,13
+ ,16
+ ,17
+ ,9
+ ,17
+ ,16
+ ,13
+ ,25
+ ,17
+ ,9
+ ,17
+ ,16
+ ,14
+ ,25
+ ,17
+ ,9
+ ,17
+ ,8
+ ,14
+ ,25
+ ,17
+ ,9
+ ,7
+ ,8
+ ,14
+ ,25
+ ,17
+ ,10
+ ,7
+ ,8
+ ,14
+ ,25
+ ,7
+ ,10
+ ,7
+ ,8
+ ,14
+ ,10
+ ,7
+ ,10
+ ,7
+ ,8
+ ,3
+ ,10
+ ,7
+ ,10
+ ,7)
+ ,dim=c(5
+ ,76)
+ ,dimnames=list(c('X'
+ ,'Y1'
+ ,'Y2'
+ ,'Y3'
+ ,'Y4
')
+ ,1:76))
> y <- array(NA,dim=c(5,76),dimnames=list(c('X','Y1','Y2','Y3','Y4
'),1:76))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par3 = 'Linear Trend'
> par2 = 'Include Monthly Dummies'
> par1 = '1'
> #'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.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
X Y1 Y2 Y3 Y4\r M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 30 35 47 30 37 1 0 0 0 0 0 0 0 0 0 0 1
2 43 30 35 47 30 0 1 0 0 0 0 0 0 0 0 0 2
3 82 43 30 35 47 0 0 1 0 0 0 0 0 0 0 0 3
4 40 82 43 30 35 0 0 0 1 0 0 0 0 0 0 0 4
5 47 40 82 43 30 0 0 0 0 1 0 0 0 0 0 0 5
6 19 47 40 82 43 0 0 0 0 0 1 0 0 0 0 0 6
7 52 19 47 40 82 0 0 0 0 0 0 1 0 0 0 0 7
8 136 52 19 47 40 0 0 0 0 0 0 0 1 0 0 0 8
9 80 136 52 19 47 0 0 0 0 0 0 0 0 1 0 0 9
10 42 80 136 52 19 0 0 0 0 0 0 0 0 0 1 0 10
11 54 42 80 136 52 0 0 0 0 0 0 0 0 0 0 1 11
12 66 54 42 80 136 0 0 0 0 0 0 0 0 0 0 0 12
13 81 66 54 42 80 1 0 0 0 0 0 0 0 0 0 0 13
14 63 81 66 54 42 0 1 0 0 0 0 0 0 0 0 0 14
15 137 63 81 66 54 0 0 1 0 0 0 0 0 0 0 0 15
16 72 137 63 81 66 0 0 0 1 0 0 0 0 0 0 0 16
17 107 72 137 63 81 0 0 0 0 1 0 0 0 0 0 0 17
18 58 107 72 137 63 0 0 0 0 0 1 0 0 0 0 0 18
19 36 58 107 72 137 0 0 0 0 0 0 1 0 0 0 0 19
20 52 36 58 107 72 0 0 0 0 0 0 0 1 0 0 0 20
21 79 52 36 58 107 0 0 0 0 0 0 0 0 1 0 0 21
22 77 79 52 36 58 0 0 0 0 0 0 0 0 0 1 0 22
23 54 77 79 52 36 0 0 0 0 0 0 0 0 0 0 1 23
24 84 54 77 79 52 0 0 0 0 0 0 0 0 0 0 0 24
25 48 84 54 77 79 1 0 0 0 0 0 0 0 0 0 0 25
26 96 48 84 54 77 0 1 0 0 0 0 0 0 0 0 0 26
27 83 96 48 84 54 0 0 1 0 0 0 0 0 0 0 0 27
28 66 83 96 48 84 0 0 0 1 0 0 0 0 0 0 0 28
29 61 66 83 96 48 0 0 0 0 1 0 0 0 0 0 0 29
30 53 61 66 83 96 0 0 0 0 0 1 0 0 0 0 0 30
31 30 53 61 66 83 0 0 0 0 0 0 1 0 0 0 0 31
32 74 30 53 61 66 0 0 0 0 0 0 0 1 0 0 0 32
33 69 74 30 53 61 0 0 0 0 0 0 0 0 1 0 0 33
34 59 69 74 30 53 0 0 0 0 0 0 0 0 0 1 0 34
35 42 59 69 74 30 0 0 0 0 0 0 0 0 0 0 1 35
36 65 42 59 69 74 0 0 0 0 0 0 0 0 0 0 0 36
37 70 65 42 59 69 1 0 0 0 0 0 0 0 0 0 0 37
38 100 70 65 42 59 0 1 0 0 0 0 0 0 0 0 0 38
39 63 100 70 65 42 0 0 1 0 0 0 0 0 0 0 0 39
40 105 63 100 70 65 0 0 0 1 0 0 0 0 0 0 0 40
41 82 105 63 100 70 0 0 0 0 1 0 0 0 0 0 0 41
42 81 82 105 63 100 0 0 0 0 0 1 0 0 0 0 0 42
43 75 81 82 105 63 0 0 0 0 0 0 1 0 0 0 0 43
44 102 75 81 82 105 0 0 0 0 0 0 0 1 0 0 0 44
45 121 102 75 81 82 0 0 0 0 0 0 0 0 1 0 0 45
46 98 121 102 75 81 0 0 0 0 0 0 0 0 0 1 0 46
47 76 98 121 102 75 0 0 0 0 0 0 0 0 0 0 1 47
48 77 76 98 121 102 0 0 0 0 0 0 0 0 0 0 0 48
49 63 77 76 98 121 1 0 0 0 0 0 0 0 0 0 0 49
50 37 63 77 76 98 0 1 0 0 0 0 0 0 0 0 0 50
51 35 37 63 77 76 0 0 1 0 0 0 0 0 0 0 0 51
52 23 35 37 63 77 0 0 0 1 0 0 0 0 0 0 0 52
53 40 23 35 37 63 0 0 0 0 1 0 0 0 0 0 0 53
54 29 40 23 35 37 0 0 0 0 0 1 0 0 0 0 0 54
55 37 29 40 23 35 0 0 0 0 0 0 1 0 0 0 0 55
56 51 37 29 40 23 0 0 0 0 0 0 0 1 0 0 0 56
57 20 51 37 29 40 0 0 0 0 0 0 0 0 1 0 0 57
58 28 20 51 37 29 0 0 0 0 0 0 0 0 0 1 0 58
59 13 28 20 51 37 0 0 0 0 0 0 0 0 0 0 1 59
60 22 13 28 20 51 0 0 0 0 0 0 0 0 0 0 0 60
61 25 22 13 28 20 1 0 0 0 0 0 0 0 0 0 0 61
62 13 25 22 13 28 0 1 0 0 0 0 0 0 0 0 0 62
63 16 13 25 22 13 0 0 1 0 0 0 0 0 0 0 0 63
64 13 16 13 25 22 0 0 0 1 0 0 0 0 0 0 0 64
65 16 13 16 13 25 0 0 0 0 1 0 0 0 0 0 0 65
66 17 16 13 16 13 0 0 0 0 0 1 0 0 0 0 0 66
67 9 17 16 13 16 0 0 0 0 0 0 1 0 0 0 0 67
68 17 9 17 16 13 0 0 0 0 0 0 0 1 0 0 0 68
69 25 17 9 17 16 0 0 0 0 0 0 0 0 1 0 0 69
70 14 25 17 9 17 0 0 0 0 0 0 0 0 0 1 0 70
71 8 14 25 17 9 0 0 0 0 0 0 0 0 0 0 1 71
72 7 8 14 25 17 0 0 0 0 0 0 0 0 0 0 0 72
73 10 7 8 14 25 1 0 0 0 0 0 0 0 0 0 0 73
74 7 10 7 8 14 0 1 0 0 0 0 0 0 0 0 0 74
75 10 7 10 7 8 0 0 1 0 0 0 0 0 0 0 0 75
76 3 10 7 10 7 0 0 0 1 0 0 0 0 0 0 0 76
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Y1 Y2 Y3 `Y4\r` M1
27.28342 0.39713 0.24163 -0.07212 0.19455 -8.55124
M2 M3 M4 M5 M6 M7
-2.43346 8.75388 -12.74014 -2.18969 -16.60868 -17.57429
M8 M9 M10 M11 t
23.49448 3.14624 -11.59046 -13.66912 -0.29072
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-38.5345 -10.2488 -0.4374 8.9409 57.9137
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 27.28342 13.82700 1.973 0.05316 .
Y1 0.39713 0.12633 3.144 0.00261 **
Y2 0.24163 0.13573 1.780 0.08018 .
Y3 -0.07212 0.13495 -0.534 0.59509
`Y4\r` 0.19455 0.12345 1.576 0.12037
M1 -8.55124 12.08055 -0.708 0.48182
M2 -2.43346 12.23900 -0.199 0.84308
M3 8.75388 12.31178 0.711 0.47988
M4 -12.74014 12.46660 -1.022 0.31098
M5 -2.18969 12.73441 -0.172 0.86406
M6 -16.60868 12.47235 -1.332 0.18810
M7 -17.57429 12.33230 -1.425 0.15941
M8 23.49448 12.33227 1.905 0.06164 .
M9 3.14624 13.50924 0.233 0.81665
M10 -11.59046 13.78116 -0.841 0.40372
M11 -13.66912 13.15108 -1.039 0.30286
t -0.29072 0.13498 -2.154 0.03535 *
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 21.05 on 59 degrees of freedom
Multiple R-squared: 0.671, Adjusted R-squared: 0.5818
F-statistic: 7.521 on 16 and 59 DF, p-value: 3.647e-09
> 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,] 0.9960993 0.0078013281 0.0039006641
[2,] 0.9970242 0.0059515098 0.0029757549
[3,] 0.9970102 0.0059795977 0.0029897988
[4,] 0.9979756 0.0040487255 0.0020243628
[5,] 0.9968934 0.0062132858 0.0031066429
[6,] 0.9982857 0.0034286470 0.0017143235
[7,] 0.9986466 0.0027068789 0.0013534394
[8,] 0.9989825 0.0020350940 0.0010175470
[9,] 0.9989892 0.0020215843 0.0010107922
[10,] 0.9986225 0.0027549268 0.0013774634
[11,] 0.9973382 0.0053235408 0.0026617704
[12,] 0.9975492 0.0049016449 0.0024508224
[13,] 0.9965722 0.0068556899 0.0034278449
[14,] 0.9934910 0.0130179116 0.0065089558
[15,] 0.9915275 0.0169450092 0.0084725046
[16,] 0.9905750 0.0188500234 0.0094250117
[17,] 0.9832028 0.0335944699 0.0167972349
[18,] 0.9746837 0.0506325429 0.0253162714
[19,] 0.9874621 0.0250757602 0.0125378801
[20,] 0.9939527 0.0120945038 0.0060472519
[21,] 0.9986173 0.0027654650 0.0013827325
[22,] 0.9977995 0.0044010641 0.0022005321
[23,] 0.9956442 0.0087115193 0.0043557597
[24,] 0.9942915 0.0114170251 0.0057085125
[25,] 0.9954019 0.0091961872 0.0045980936
[26,] 0.9998960 0.0002079003 0.0001039501
[27,] 0.9998623 0.0002754050 0.0001377025
[28,] 0.9996216 0.0007567590 0.0003783795
[29,] 0.9994282 0.0011435396 0.0005717698
[30,] 0.9992981 0.0014038938 0.0007019469
[31,] 0.9988153 0.0023694395 0.0011847198
[32,] 0.9975886 0.0048227259 0.0024113629
[33,] 0.9936887 0.0126226836 0.0063113418
[34,] 0.9869473 0.0261053290 0.0130526645
[35,] 0.9645165 0.0709670569 0.0354835285
[36,] 0.9486502 0.1026996818 0.0513498409
[37,] 0.9953251 0.0093498991 0.0046749495
> postscript(file="/var/www/html/rcomp/tmp/1g3e31291022852.ps",horizontal=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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2qdeo1291022852.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/3qdeo1291022852.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4qdeo1291022852.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5qdeo1291022852.ps",horizontal=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 = 76
Frequency = 1
1 2 3 4 5 6
-18.7324280 -4.0864699 15.8896318 -20.9806139 -15.0743383 -20.7127912
7 8 9 10 11 12
12.3551972 57.9136990 -22.1607198 -35.3637957 7.2649875 -10.0780078
13 14 15 16 17 18
14.2535349 -10.1715109 54.9864345 -14.5196820 13.9368065 -9.7084772
19 20 21 22 23 24
-38.5345089 -27.5659438 8.6918052 15.0773831 -5.8489240 19.2240686
25 26 27 28 29 30
-19.6874471 28.2635923 0.6418108 -9.4417768 -4.3437192 -1.8167802
31 32 33 34 35 36
-17.8720618 -0.6363588 3.4824020 -0.2384464 -2.0418419 7.8262278
37 38 39 40 41 42
16.8936156 34.2430478 -21.8093951 45.3059519 5.4979293 9.6882175
43 44 45 46 47 48
21.1264835 0.1428998 34.9118759 12.6317991 0.6585599 -1.3083827
49 50 51 52 53 54
-6.9028901 -30.5236211 -25.3598753 -9.7027018 3.1350840 7.9073808
55 56 57 58 59 60
16.9481244 -6.7883964 -28.7429062 5.9296068 -2.9343250 -8.2482109
61 62 63 64 65 66
10.2521506 -13.5791015 -13.8677526 5.0905225 -3.1517623 14.6424504
67 68 69 70 71 72
5.9767655 -23.0658997 3.8175430 1.9634531 2.9015434 -7.4156950
73 74 75 76
3.9234641 -4.1459367 -10.4808539 4.2483001
> postscript(file="/var/www/html/rcomp/tmp/61mdr1291022852.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> dum <- cbind(lag(myerror,k=1),myerror)
> dum
Time Series:
Start = 0
End = 76
Frequency = 1
lag(myerror, k = 1) myerror
0 -18.7324280 NA
1 -4.0864699 -18.7324280
2 15.8896318 -4.0864699
3 -20.9806139 15.8896318
4 -15.0743383 -20.9806139
5 -20.7127912 -15.0743383
6 12.3551972 -20.7127912
7 57.9136990 12.3551972
8 -22.1607198 57.9136990
9 -35.3637957 -22.1607198
10 7.2649875 -35.3637957
11 -10.0780078 7.2649875
12 14.2535349 -10.0780078
13 -10.1715109 14.2535349
14 54.9864345 -10.1715109
15 -14.5196820 54.9864345
16 13.9368065 -14.5196820
17 -9.7084772 13.9368065
18 -38.5345089 -9.7084772
19 -27.5659438 -38.5345089
20 8.6918052 -27.5659438
21 15.0773831 8.6918052
22 -5.8489240 15.0773831
23 19.2240686 -5.8489240
24 -19.6874471 19.2240686
25 28.2635923 -19.6874471
26 0.6418108 28.2635923
27 -9.4417768 0.6418108
28 -4.3437192 -9.4417768
29 -1.8167802 -4.3437192
30 -17.8720618 -1.8167802
31 -0.6363588 -17.8720618
32 3.4824020 -0.6363588
33 -0.2384464 3.4824020
34 -2.0418419 -0.2384464
35 7.8262278 -2.0418419
36 16.8936156 7.8262278
37 34.2430478 16.8936156
38 -21.8093951 34.2430478
39 45.3059519 -21.8093951
40 5.4979293 45.3059519
41 9.6882175 5.4979293
42 21.1264835 9.6882175
43 0.1428998 21.1264835
44 34.9118759 0.1428998
45 12.6317991 34.9118759
46 0.6585599 12.6317991
47 -1.3083827 0.6585599
48 -6.9028901 -1.3083827
49 -30.5236211 -6.9028901
50 -25.3598753 -30.5236211
51 -9.7027018 -25.3598753
52 3.1350840 -9.7027018
53 7.9073808 3.1350840
54 16.9481244 7.9073808
55 -6.7883964 16.9481244
56 -28.7429062 -6.7883964
57 5.9296068 -28.7429062
58 -2.9343250 5.9296068
59 -8.2482109 -2.9343250
60 10.2521506 -8.2482109
61 -13.5791015 10.2521506
62 -13.8677526 -13.5791015
63 5.0905225 -13.8677526
64 -3.1517623 5.0905225
65 14.6424504 -3.1517623
66 5.9767655 14.6424504
67 -23.0658997 5.9767655
68 3.8175430 -23.0658997
69 1.9634531 3.8175430
70 2.9015434 1.9634531
71 -7.4156950 2.9015434
72 3.9234641 -7.4156950
73 -4.1459367 3.9234641
74 -10.4808539 -4.1459367
75 4.2483001 -10.4808539
76 NA 4.2483001
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -4.0864699 -18.7324280
[2,] 15.8896318 -4.0864699
[3,] -20.9806139 15.8896318
[4,] -15.0743383 -20.9806139
[5,] -20.7127912 -15.0743383
[6,] 12.3551972 -20.7127912
[7,] 57.9136990 12.3551972
[8,] -22.1607198 57.9136990
[9,] -35.3637957 -22.1607198
[10,] 7.2649875 -35.3637957
[11,] -10.0780078 7.2649875
[12,] 14.2535349 -10.0780078
[13,] -10.1715109 14.2535349
[14,] 54.9864345 -10.1715109
[15,] -14.5196820 54.9864345
[16,] 13.9368065 -14.5196820
[17,] -9.7084772 13.9368065
[18,] -38.5345089 -9.7084772
[19,] -27.5659438 -38.5345089
[20,] 8.6918052 -27.5659438
[21,] 15.0773831 8.6918052
[22,] -5.8489240 15.0773831
[23,] 19.2240686 -5.8489240
[24,] -19.6874471 19.2240686
[25,] 28.2635923 -19.6874471
[26,] 0.6418108 28.2635923
[27,] -9.4417768 0.6418108
[28,] -4.3437192 -9.4417768
[29,] -1.8167802 -4.3437192
[30,] -17.8720618 -1.8167802
[31,] -0.6363588 -17.8720618
[32,] 3.4824020 -0.6363588
[33,] -0.2384464 3.4824020
[34,] -2.0418419 -0.2384464
[35,] 7.8262278 -2.0418419
[36,] 16.8936156 7.8262278
[37,] 34.2430478 16.8936156
[38,] -21.8093951 34.2430478
[39,] 45.3059519 -21.8093951
[40,] 5.4979293 45.3059519
[41,] 9.6882175 5.4979293
[42,] 21.1264835 9.6882175
[43,] 0.1428998 21.1264835
[44,] 34.9118759 0.1428998
[45,] 12.6317991 34.9118759
[46,] 0.6585599 12.6317991
[47,] -1.3083827 0.6585599
[48,] -6.9028901 -1.3083827
[49,] -30.5236211 -6.9028901
[50,] -25.3598753 -30.5236211
[51,] -9.7027018 -25.3598753
[52,] 3.1350840 -9.7027018
[53,] 7.9073808 3.1350840
[54,] 16.9481244 7.9073808
[55,] -6.7883964 16.9481244
[56,] -28.7429062 -6.7883964
[57,] 5.9296068 -28.7429062
[58,] -2.9343250 5.9296068
[59,] -8.2482109 -2.9343250
[60,] 10.2521506 -8.2482109
[61,] -13.5791015 10.2521506
[62,] -13.8677526 -13.5791015
[63,] 5.0905225 -13.8677526
[64,] -3.1517623 5.0905225
[65,] 14.6424504 -3.1517623
[66,] 5.9767655 14.6424504
[67,] -23.0658997 5.9767655
[68,] 3.8175430 -23.0658997
[69,] 1.9634531 3.8175430
[70,] 2.9015434 1.9634531
[71,] -7.4156950 2.9015434
[72,] 3.9234641 -7.4156950
[73,] -4.1459367 3.9234641
[74,] -10.4808539 -4.1459367
[75,] 4.2483001 -10.4808539
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -4.0864699 -18.7324280
2 15.8896318 -4.0864699
3 -20.9806139 15.8896318
4 -15.0743383 -20.9806139
5 -20.7127912 -15.0743383
6 12.3551972 -20.7127912
7 57.9136990 12.3551972
8 -22.1607198 57.9136990
9 -35.3637957 -22.1607198
10 7.2649875 -35.3637957
11 -10.0780078 7.2649875
12 14.2535349 -10.0780078
13 -10.1715109 14.2535349
14 54.9864345 -10.1715109
15 -14.5196820 54.9864345
16 13.9368065 -14.5196820
17 -9.7084772 13.9368065
18 -38.5345089 -9.7084772
19 -27.5659438 -38.5345089
20 8.6918052 -27.5659438
21 15.0773831 8.6918052
22 -5.8489240 15.0773831
23 19.2240686 -5.8489240
24 -19.6874471 19.2240686
25 28.2635923 -19.6874471
26 0.6418108 28.2635923
27 -9.4417768 0.6418108
28 -4.3437192 -9.4417768
29 -1.8167802 -4.3437192
30 -17.8720618 -1.8167802
31 -0.6363588 -17.8720618
32 3.4824020 -0.6363588
33 -0.2384464 3.4824020
34 -2.0418419 -0.2384464
35 7.8262278 -2.0418419
36 16.8936156 7.8262278
37 34.2430478 16.8936156
38 -21.8093951 34.2430478
39 45.3059519 -21.8093951
40 5.4979293 45.3059519
41 9.6882175 5.4979293
42 21.1264835 9.6882175
43 0.1428998 21.1264835
44 34.9118759 0.1428998
45 12.6317991 34.9118759
46 0.6585599 12.6317991
47 -1.3083827 0.6585599
48 -6.9028901 -1.3083827
49 -30.5236211 -6.9028901
50 -25.3598753 -30.5236211
51 -9.7027018 -25.3598753
52 3.1350840 -9.7027018
53 7.9073808 3.1350840
54 16.9481244 7.9073808
55 -6.7883964 16.9481244
56 -28.7429062 -6.7883964
57 5.9296068 -28.7429062
58 -2.9343250 5.9296068
59 -8.2482109 -2.9343250
60 10.2521506 -8.2482109
61 -13.5791015 10.2521506
62 -13.8677526 -13.5791015
63 5.0905225 -13.8677526
64 -3.1517623 5.0905225
65 14.6424504 -3.1517623
66 5.9767655 14.6424504
67 -23.0658997 5.9767655
68 3.8175430 -23.0658997
69 1.9634531 3.8175430
70 2.9015434 1.9634531
71 -7.4156950 2.9015434
72 3.9234641 -7.4156950
73 -4.1459367 3.9234641
74 -10.4808539 -4.1459367
75 4.2483001 -10.4808539
> 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/www/html/rcomp/tmp/7uvuc1291022852.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8uvuc1291022852.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9uvuc1291022852.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10mmcx1291022852.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/www/html/rcomp/tmp/11qna31291022852.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/www/html/rcomp/tmp/12tor91291022852.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/www/html/rcomp/tmp/138gpi1291022852.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/www/html/rcomp/tmp/14tg551291022852.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/www/html/rcomp/tmp/15eg3b1291022852.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/www/html/rcomp/tmp/16sr5c1291022853.tab")
+ }
>
> try(system("convert tmp/1g3e31291022852.ps tmp/1g3e31291022852.png",intern=TRUE))
character(0)
> try(system("convert tmp/2qdeo1291022852.ps tmp/2qdeo1291022852.png",intern=TRUE))
character(0)
> try(system("convert tmp/3qdeo1291022852.ps tmp/3qdeo1291022852.png",intern=TRUE))
character(0)
> try(system("convert tmp/4qdeo1291022852.ps tmp/4qdeo1291022852.png",intern=TRUE))
character(0)
> try(system("convert tmp/5qdeo1291022852.ps tmp/5qdeo1291022852.png",intern=TRUE))
character(0)
> try(system("convert tmp/61mdr1291022852.ps tmp/61mdr1291022852.png",intern=TRUE))
character(0)
> try(system("convert tmp/7uvuc1291022852.ps tmp/7uvuc1291022852.png",intern=TRUE))
character(0)
> try(system("convert tmp/8uvuc1291022852.ps tmp/8uvuc1291022852.png",intern=TRUE))
character(0)
> try(system("convert tmp/9uvuc1291022852.ps tmp/9uvuc1291022852.png",intern=TRUE))
character(0)
> try(system("convert tmp/10mmcx1291022852.ps tmp/10mmcx1291022852.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
2.625 1.611 32.528