R version 2.13.0 (2011-04-13)
Copyright (C) 2011 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-bit)
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.
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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(1972
+ ,33907
+ ,71433
+ ,152
+ ,74272
+ ,99
+ ,765
+ ,1973
+ ,35981
+ ,53655
+ ,99
+ ,78867
+ ,128
+ ,1371
+ ,1974
+ ,36588
+ ,70556
+ ,92
+ ,80176
+ ,57
+ ,1880
+ ,1975
+ ,16967
+ ,74702
+ ,138
+ ,36541
+ ,95
+ ,232
+ ,1976
+ ,25333
+ ,61201
+ ,106
+ ,55107
+ ,205
+ ,230
+ ,1977
+ ,21027
+ ,686
+ ,95
+ ,45527
+ ,51
+ ,828
+ ,1978
+ ,21114
+ ,87586
+ ,145
+ ,46001
+ ,59
+ ,1833
+ ,1979
+ ,28777
+ ,6615
+ ,181
+ ,62854
+ ,194
+ ,906
+ ,1980
+ ,35612
+ ,89725
+ ,190
+ ,78112
+ ,27
+ ,1781
+ ,1981
+ ,24183
+ ,40420
+ ,150
+ ,52653
+ ,9
+ ,1264
+ ,1982
+ ,22262
+ ,49569
+ ,186
+ ,48467
+ ,24
+ ,1123
+ ,1983
+ ,20637
+ ,13963
+ ,174
+ ,44873
+ ,189
+ ,1461
+ ,1984
+ ,29948
+ ,62508
+ ,151
+ ,65605
+ ,37
+ ,820
+ ,1985
+ ,22093
+ ,90901
+ ,112
+ ,48016
+ ,81
+ ,107
+ ,1986
+ ,36997
+ ,89418
+ ,143
+ ,81110
+ ,72
+ ,1349
+ ,1987
+ ,31089
+ ,83237
+ ,120
+ ,68019
+ ,81
+ ,870
+ ,1988
+ ,19477
+ ,22183
+ ,169
+ ,42198
+ ,90
+ ,1471
+ ,1989
+ ,31301
+ ,24346
+ ,135
+ ,68531
+ ,216
+ ,731
+ ,1990
+ ,18497
+ ,74341
+ ,161
+ ,40071
+ ,216
+ ,1945
+ ,1991
+ ,30142
+ ,24188
+ ,98
+ ,65849
+ ,13
+ ,521
+ ,1992
+ ,21326
+ ,11781
+ ,142
+ ,46362
+ ,153
+ ,1920
+ ,1993
+ ,16779
+ ,23072
+ ,190
+ ,36313
+ ,185
+ ,1924
+ ,1994
+ ,38068
+ ,49119
+ ,169
+ ,83521
+ ,131
+ ,100
+ ,1995
+ ,29707
+ ,67776
+ ,130
+ ,64932
+ ,136
+ ,34
+ ,1996
+ ,35016
+ ,86910
+ ,160
+ ,76730
+ ,182
+ ,325
+ ,1997
+ ,26131
+ ,69358
+ ,176
+ ,56982
+ ,139
+ ,1677
+ ,1998
+ ,29251
+ ,16144
+ ,111
+ ,63793
+ ,42
+ ,1779
+ ,1999
+ ,22855
+ ,77863
+ ,165
+ ,49740
+ ,213
+ ,477
+ ,2000
+ ,31806
+ ,89070
+ ,117
+ ,69447
+ ,184
+ ,1007
+ ,2001
+ ,34124
+ ,34790
+ ,122
+ ,74708
+ ,44
+ ,1527)
+ ,dim=c(7
+ ,30)
+ ,dimnames=list(c('t'
+ ,'Y'
+ ,'X1'
+ ,'X2'
+ ,'X3'
+ ,'X4'
+ ,'X5
')
+ ,1:30))
> y <- array(NA,dim=c(7,30),dimnames=list(c('t','Y','X1','X2','X3','X4','X5
'),1:30))
> 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 = 'Do not include Seasonal Dummies'
> par1 = '2'
> library(lattice)
> library(lmtest)
Loading required package: zoo
> 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
Y t X1 X2 X3 X4 X5\r
1 33907 1972 71433 152 74272 99 765
2 35981 1973 53655 99 78867 128 1371
3 36588 1974 70556 92 80176 57 1880
4 16967 1975 74702 138 36541 95 232
5 25333 1976 61201 106 55107 205 230
6 21027 1977 686 95 45527 51 828
7 21114 1978 87586 145 46001 59 1833
8 28777 1979 6615 181 62854 194 906
9 35612 1980 89725 190 78112 27 1781
10 24183 1981 40420 150 52653 9 1264
11 22262 1982 49569 186 48467 24 1123
12 20637 1983 13963 174 44873 189 1461
13 29948 1984 62508 151 65605 37 820
14 22093 1985 90901 112 48016 81 107
15 36997 1986 89418 143 81110 72 1349
16 31089 1987 83237 120 68019 81 870
17 19477 1988 22183 169 42198 90 1471
18 31301 1989 24346 135 68531 216 731
19 18497 1990 74341 161 40071 216 1945
20 30142 1991 24188 98 65849 13 521
21 21326 1992 11781 142 46362 153 1920
22 16779 1993 23072 190 36313 185 1924
23 38068 1994 49119 169 83521 131 100
24 29707 1995 67776 130 64932 136 34
25 35016 1996 86910 160 76730 182 325
26 26131 1997 69358 176 56982 139 1677
27 29251 1998 16144 111 63793 42 1779
28 22855 1999 77863 165 49740 213 477
29 31806 2000 89070 117 69447 184 1007
30 34124 2001 34790 122 74708 44 1527
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) t X1 X2 X3 X4
-4.806e+02 5.337e-01 -1.356e-04 -6.477e-01 4.502e-01 1.962e-02
`X5\r`
-8.267e-03
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-53.967 -18.648 0.863 20.764 46.026
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -4.806e+02 1.248e+03 -0.385 0.70371
t 5.337e-01 6.319e-01 0.845 0.40709
X1 -1.356e-04 1.920e-04 -0.706 0.48699
X2 -6.477e-01 1.912e-01 -3.388 0.00253 **
X3 4.502e-01 3.950e-04 1139.747 < 2e-16 ***
X4 1.962e-02 8.450e-02 0.232 0.81841
`X5\r` -8.267e-03 8.993e-03 -0.919 0.36747
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 28.62 on 23 degrees of freedom
Multiple R-squared: 1, Adjusted R-squared: 1
F-statistic: 2.577e+05 on 6 and 23 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)$p.value
+ }
+ if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
+ }
+ gqarr
+ }
[,1] [,2] [,3]
[1,] 0.5917992 0.8164016 0.4082008
[2,] 0.5666831 0.8666338 0.4333169
[3,] 0.4249090 0.8498180 0.5750910
[4,] 0.8903656 0.2192688 0.1096344
[5,] 0.8149310 0.3701381 0.1850690
[6,] 0.8395966 0.3208068 0.1604034
[7,] 0.8194142 0.3611716 0.1805858
[8,] 0.8995581 0.2008839 0.1004419
[9,] 0.8432448 0.3135103 0.1567552
[10,] 0.7646990 0.4706021 0.2353010
[11,] 0.5929372 0.8141255 0.4070628
> postscript(file="/var/wessaorg/rcomp/tmp/1htyq1321993014.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
> points(x[,1]-mysum$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/2nh0u1321993014.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/33zya1321993014.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/4l1wm1321993014.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/59lia1321993014.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$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 = 30
Frequency = 1
1 2 3 4 5 6
9.6403223 -17.9116998 2.5880120 42.0206252 24.1275604 23.2536182
7 8 9 10 11 12
-51.3582248 25.7113925 18.4630677 14.3507000 0.4991649 -20.0192592
13 14 15 16 17 18
-53.9668628 -18.8940516 15.5910385 -19.0939614 21.5305264 -40.7415776
19 20 21 22 23 24
1.4033930 -15.0786649 -22.7069477 -14.0404714 -3.2495267 -19.1715795
25 26 27 28 29 30
1.2267728 26.4739921 32.9802241 -7.5044291 46.0260766 -2.1492303
> postscript(file="/var/wessaorg/rcomp/tmp/62o1t1321993014.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 = 30
Frequency = 1
lag(myerror, k = 1) myerror
0 9.6403223 NA
1 -17.9116998 9.6403223
2 2.5880120 -17.9116998
3 42.0206252 2.5880120
4 24.1275604 42.0206252
5 23.2536182 24.1275604
6 -51.3582248 23.2536182
7 25.7113925 -51.3582248
8 18.4630677 25.7113925
9 14.3507000 18.4630677
10 0.4991649 14.3507000
11 -20.0192592 0.4991649
12 -53.9668628 -20.0192592
13 -18.8940516 -53.9668628
14 15.5910385 -18.8940516
15 -19.0939614 15.5910385
16 21.5305264 -19.0939614
17 -40.7415776 21.5305264
18 1.4033930 -40.7415776
19 -15.0786649 1.4033930
20 -22.7069477 -15.0786649
21 -14.0404714 -22.7069477
22 -3.2495267 -14.0404714
23 -19.1715795 -3.2495267
24 1.2267728 -19.1715795
25 26.4739921 1.2267728
26 32.9802241 26.4739921
27 -7.5044291 32.9802241
28 46.0260766 -7.5044291
29 -2.1492303 46.0260766
30 NA -2.1492303
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -17.9116998 9.6403223
[2,] 2.5880120 -17.9116998
[3,] 42.0206252 2.5880120
[4,] 24.1275604 42.0206252
[5,] 23.2536182 24.1275604
[6,] -51.3582248 23.2536182
[7,] 25.7113925 -51.3582248
[8,] 18.4630677 25.7113925
[9,] 14.3507000 18.4630677
[10,] 0.4991649 14.3507000
[11,] -20.0192592 0.4991649
[12,] -53.9668628 -20.0192592
[13,] -18.8940516 -53.9668628
[14,] 15.5910385 -18.8940516
[15,] -19.0939614 15.5910385
[16,] 21.5305264 -19.0939614
[17,] -40.7415776 21.5305264
[18,] 1.4033930 -40.7415776
[19,] -15.0786649 1.4033930
[20,] -22.7069477 -15.0786649
[21,] -14.0404714 -22.7069477
[22,] -3.2495267 -14.0404714
[23,] -19.1715795 -3.2495267
[24,] 1.2267728 -19.1715795
[25,] 26.4739921 1.2267728
[26,] 32.9802241 26.4739921
[27,] -7.5044291 32.9802241
[28,] 46.0260766 -7.5044291
[29,] -2.1492303 46.0260766
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -17.9116998 9.6403223
2 2.5880120 -17.9116998
3 42.0206252 2.5880120
4 24.1275604 42.0206252
5 23.2536182 24.1275604
6 -51.3582248 23.2536182
7 25.7113925 -51.3582248
8 18.4630677 25.7113925
9 14.3507000 18.4630677
10 0.4991649 14.3507000
11 -20.0192592 0.4991649
12 -53.9668628 -20.0192592
13 -18.8940516 -53.9668628
14 15.5910385 -18.8940516
15 -19.0939614 15.5910385
16 21.5305264 -19.0939614
17 -40.7415776 21.5305264
18 1.4033930 -40.7415776
19 -15.0786649 1.4033930
20 -22.7069477 -15.0786649
21 -14.0404714 -22.7069477
22 -3.2495267 -14.0404714
23 -19.1715795 -3.2495267
24 1.2267728 -19.1715795
25 26.4739921 1.2267728
26 32.9802241 26.4739921
27 -7.5044291 32.9802241
28 46.0260766 -7.5044291
29 -2.1492303 46.0260766
> plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
> lines(lowess(z))
> abline(lm(z))
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/7c8tr1321993014.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/8tsca1321993014.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/9la191321993014.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/wessaorg/rcomp/tmp/10r14v1321993014.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
+ myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ')
+ if (rownames(mysum$coefficients)[i] != '(Intercept)') {
+ myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
+ if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
+ }
+ }
> myeq <- paste(myeq, ' + e[t]')
> a<-table.row.start(a)
> a<-table.element(a, myeq)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/11126m1321993014.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Variable',header=TRUE)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
> a<-table.element(a,'2-tail p-value',header=TRUE)
> a<-table.element(a,'1-tail p-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:k){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(mysum$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$coefficients[i,4]/2,6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/12428d1321993014.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple R',1,TRUE)
> a<-table.element(a, sqrt(mysum$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$sigma)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a, sum(myerror*myerror))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/13nroq1321993014.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Time or Index', 1, TRUE)
> a<-table.element(a, 'Actuals', 1, TRUE)
> a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
> a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
> a<-table.row.end(a)
> for (i in 1:n) {
+ a<-table.row.start(a)
+ a<-table.element(a,i, 1, TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]-mysum$resid[i])
+ a<-table.element(a,mysum$resid[i])
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/14gpjs1321993014.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/wessaorg/rcomp/tmp/15ydkr1321993014.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/wessaorg/rcomp/tmp/166x2r1321993014.tab")
+ }
>
> try(system("convert tmp/1htyq1321993014.ps tmp/1htyq1321993014.png",intern=TRUE))
character(0)
> try(system("convert tmp/2nh0u1321993014.ps tmp/2nh0u1321993014.png",intern=TRUE))
character(0)
> try(system("convert tmp/33zya1321993014.ps tmp/33zya1321993014.png",intern=TRUE))
character(0)
> try(system("convert tmp/4l1wm1321993014.ps tmp/4l1wm1321993014.png",intern=TRUE))
character(0)
> try(system("convert tmp/59lia1321993014.ps tmp/59lia1321993014.png",intern=TRUE))
character(0)
> try(system("convert tmp/62o1t1321993014.ps tmp/62o1t1321993014.png",intern=TRUE))
character(0)
> try(system("convert tmp/7c8tr1321993014.ps tmp/7c8tr1321993014.png",intern=TRUE))
character(0)
> try(system("convert tmp/8tsca1321993014.ps tmp/8tsca1321993014.png",intern=TRUE))
character(0)
> try(system("convert tmp/9la191321993014.ps tmp/9la191321993014.png",intern=TRUE))
character(0)
> try(system("convert tmp/10r14v1321993014.ps tmp/10r14v1321993014.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
2.944 0.444 3.426