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.
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(33907
+ ,71433
+ ,152
+ ,74272
+ ,99
+ ,765
+ ,35981
+ ,53655
+ ,99
+ ,78867
+ ,128
+ ,1371
+ ,36588
+ ,70556
+ ,92
+ ,80176
+ ,57
+ ,1880
+ ,16967
+ ,74702
+ ,138
+ ,36541
+ ,95
+ ,232
+ ,25333
+ ,61201
+ ,106
+ ,55107
+ ,205
+ ,230
+ ,21027
+ ,686
+ ,95
+ ,45527
+ ,51
+ ,828
+ ,21114
+ ,87586
+ ,145
+ ,46001
+ ,59
+ ,1833
+ ,28777
+ ,6615
+ ,181
+ ,62854
+ ,194
+ ,906
+ ,35612
+ ,89725
+ ,190
+ ,78112
+ ,27
+ ,1781
+ ,24183
+ ,40420
+ ,150
+ ,52653
+ ,9
+ ,1264
+ ,22262
+ ,49569
+ ,186
+ ,48467
+ ,24
+ ,1123
+ ,20637
+ ,13963
+ ,174
+ ,44873
+ ,189
+ ,1461
+ ,29948
+ ,62508
+ ,151
+ ,65605
+ ,37
+ ,820
+ ,22093
+ ,90901
+ ,112
+ ,48016
+ ,81
+ ,107
+ ,36997
+ ,89418
+ ,143
+ ,81110
+ ,72
+ ,1349
+ ,31089
+ ,83237
+ ,120
+ ,68019
+ ,81
+ ,870
+ ,19477
+ ,22183
+ ,169
+ ,42198
+ ,90
+ ,1471
+ ,31301
+ ,24346
+ ,135
+ ,68531
+ ,216
+ ,731
+ ,18497
+ ,74341
+ ,161
+ ,40071
+ ,216
+ ,1945
+ ,30142
+ ,24188
+ ,98
+ ,65849
+ ,13
+ ,521
+ ,21326
+ ,11781
+ ,142
+ ,46362
+ ,153
+ ,1920
+ ,16779
+ ,23072
+ ,190
+ ,36313
+ ,185
+ ,1924
+ ,38068
+ ,49119
+ ,169
+ ,83521
+ ,131
+ ,100
+ ,29707
+ ,67776
+ ,130
+ ,64932
+ ,136
+ ,34
+ ,35016
+ ,86910
+ ,160
+ ,76730
+ ,182
+ ,325
+ ,26131
+ ,69358
+ ,176
+ ,56982
+ ,139
+ ,1677
+ ,29251
+ ,16144
+ ,111
+ ,63793
+ ,42
+ ,1779
+ ,22855
+ ,77863
+ ,165
+ ,49740
+ ,213
+ ,477
+ ,31806
+ ,89070
+ ,117
+ ,69447
+ ,184
+ ,1007
+ ,34124
+ ,34790
+ ,122
+ ,74708
+ ,44
+ ,1527)
+ ,dim=c(6
+ ,30)
+ ,dimnames=list(c('omzet'
+ ,'uitgaven_voor_promotie'
+ ,'Prijs_product'
+ ,'gem_budget'
+ ,'index_cons_vertriuwen'
+ ,'uitg_lok_promotie')
+ ,1:30))
> y <- array(NA,dim=c(6,30),dimnames=list(c('omzet','uitgaven_voor_promotie','Prijs_product','gem_budget','index_cons_vertriuwen','uitg_lok_promotie'),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 = '5'
> 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
index_cons_vertriuwen omzet uitgaven_voor_promotie Prijs_product gem_budget
1 99 33907 71433 152 74272
2 128 35981 53655 99 78867
3 57 36588 70556 92 80176
4 95 16967 74702 138 36541
5 205 25333 61201 106 55107
6 51 21027 686 95 45527
7 59 21114 87586 145 46001
8 194 28777 6615 181 62854
9 27 35612 89725 190 78112
10 9 24183 40420 150 52653
11 24 22262 49569 186 48467
12 189 20637 13963 174 44873
13 37 29948 62508 151 65605
14 81 22093 90901 112 48016
15 72 36997 89418 143 81110
16 81 31089 83237 120 68019
17 90 19477 22183 169 42198
18 216 31301 24346 135 68531
19 216 18497 74341 161 40071
20 13 30142 24188 98 65849
21 153 21326 11781 142 46362
22 185 16779 23072 190 36313
23 131 38068 49119 169 83521
24 136 29707 67776 130 64932
25 182 35016 86910 160 76730
26 139 26131 69358 176 56982
27 42 29251 16144 111 63793
28 213 22855 77863 165 49740
29 184 31806 89070 117 69447
30 44 34124 34790 122 74708
uitg_lok_promotie
1 765
2 1371
3 1880
4 232
5 230
6 828
7 1833
8 906
9 1781
10 1264
11 1123
12 1461
13 820
14 107
15 1349
16 870
17 1471
18 731
19 1945
20 521
21 1920
22 1924
23 100
24 34
25 325
26 1677
27 1779
28 477
29 1007
30 1527
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) omzet uitgaven_voor_promotie
-3.372e+01 2.272e-01 -2.101e-05
Prijs_product gem_budget uitg_lok_promotie
6.971e-01 -1.029e-01 -2.109e-02
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-117.22 -44.87 -7.85 54.33 112.74
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -3.372e+01 3.075e+02 -0.110 0.914
omzet 2.272e-01 5.065e-01 0.449 0.658
uitgaven_voor_promotie -2.101e-05 4.803e-04 -0.044 0.965
Prijs_product 6.971e-01 5.515e-01 1.264 0.218
gem_budget -1.029e-01 2.280e-01 -0.451 0.656
uitg_lok_promotie -2.109e-02 2.223e-02 -0.949 0.352
Residual standard error: 70.9 on 24 degrees of freedom
Multiple R-squared: 0.1175, Adjusted R-squared: -0.06636
F-statistic: 0.6391 on 5 and 24 DF, p-value: 0.6721
> 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)$p.value
+ }
+ if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
+ }
+ gqarr
+ }
[,1] [,2] [,3]
[1,] 0.4474551 0.8949101 0.55254494
[2,] 0.4239791 0.8479583 0.57602086
[3,] 0.5278094 0.9443811 0.47219056
[4,] 0.6314176 0.7371648 0.36858240
[5,] 0.7973948 0.4052104 0.20260518
[6,] 0.7580593 0.4838813 0.24194067
[7,] 0.6941274 0.6117452 0.30587258
[8,] 0.7445442 0.5109116 0.25545582
[9,] 0.6273614 0.7452772 0.37263859
[10,] 0.8763622 0.2472757 0.12363783
[11,] 0.9018552 0.1962895 0.09814476
[12,] 0.9025417 0.1949166 0.09745830
[13,] 0.8952475 0.2095050 0.10475252
> postscript(file="/var/wessaorg/rcomp/tmp/1uyyw1323434303.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
> points(x[,1]-mysum$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/22phj1323434303.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/33fu91323434303.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/46kjd1323434303.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/5p69i1323434303.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$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
-15.661554 64.372918 6.148957 -55.347224 86.577747 -56.001641
7 8 9 10 11 12
-30.820011 51.199941 -84.524531 -109.993026 -117.218685 61.856545
13 14 15 16 17 18
-68.461276 -37.209730 -22.013762 -12.160127 -45.015932 112.738310
19 20 21 22 23 24
101.414069 -81.589702 54.499705 52.255777 -3.539301 14.204423
25 26 27 28 29 30
53.802334 14.129195 -44.440389 69.669023 80.003038 -38.875088
> postscript(file="/var/wessaorg/rcomp/tmp/6vcak1323434303.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 -15.661554 NA
1 64.372918 -15.661554
2 6.148957 64.372918
3 -55.347224 6.148957
4 86.577747 -55.347224
5 -56.001641 86.577747
6 -30.820011 -56.001641
7 51.199941 -30.820011
8 -84.524531 51.199941
9 -109.993026 -84.524531
10 -117.218685 -109.993026
11 61.856545 -117.218685
12 -68.461276 61.856545
13 -37.209730 -68.461276
14 -22.013762 -37.209730
15 -12.160127 -22.013762
16 -45.015932 -12.160127
17 112.738310 -45.015932
18 101.414069 112.738310
19 -81.589702 101.414069
20 54.499705 -81.589702
21 52.255777 54.499705
22 -3.539301 52.255777
23 14.204423 -3.539301
24 53.802334 14.204423
25 14.129195 53.802334
26 -44.440389 14.129195
27 69.669023 -44.440389
28 80.003038 69.669023
29 -38.875088 80.003038
30 NA -38.875088
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 64.372918 -15.661554
[2,] 6.148957 64.372918
[3,] -55.347224 6.148957
[4,] 86.577747 -55.347224
[5,] -56.001641 86.577747
[6,] -30.820011 -56.001641
[7,] 51.199941 -30.820011
[8,] -84.524531 51.199941
[9,] -109.993026 -84.524531
[10,] -117.218685 -109.993026
[11,] 61.856545 -117.218685
[12,] -68.461276 61.856545
[13,] -37.209730 -68.461276
[14,] -22.013762 -37.209730
[15,] -12.160127 -22.013762
[16,] -45.015932 -12.160127
[17,] 112.738310 -45.015932
[18,] 101.414069 112.738310
[19,] -81.589702 101.414069
[20,] 54.499705 -81.589702
[21,] 52.255777 54.499705
[22,] -3.539301 52.255777
[23,] 14.204423 -3.539301
[24,] 53.802334 14.204423
[25,] 14.129195 53.802334
[26,] -44.440389 14.129195
[27,] 69.669023 -44.440389
[28,] 80.003038 69.669023
[29,] -38.875088 80.003038
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 64.372918 -15.661554
2 6.148957 64.372918
3 -55.347224 6.148957
4 86.577747 -55.347224
5 -56.001641 86.577747
6 -30.820011 -56.001641
7 51.199941 -30.820011
8 -84.524531 51.199941
9 -109.993026 -84.524531
10 -117.218685 -109.993026
11 61.856545 -117.218685
12 -68.461276 61.856545
13 -37.209730 -68.461276
14 -22.013762 -37.209730
15 -12.160127 -22.013762
16 -45.015932 -12.160127
17 112.738310 -45.015932
18 101.414069 112.738310
19 -81.589702 101.414069
20 54.499705 -81.589702
21 52.255777 54.499705
22 -3.539301 52.255777
23 14.204423 -3.539301
24 53.802334 14.204423
25 14.129195 53.802334
26 -44.440389 14.129195
27 69.669023 -44.440389
28 80.003038 69.669023
29 -38.875088 80.003038
> 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/76fv91323434303.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/8wz5q1323434303.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/9y4n11323434303.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/10t5kx1323434303.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$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
+ }
+ }
> myeq <- paste(myeq, ' + e[t]')
> a<-table.row.start(a)
> a<-table.element(a, myeq)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/11kf6q1323434303.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Variable',header=TRUE)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
> a<-table.element(a,'2-tail p-value',header=TRUE)
> a<-table.element(a,'1-tail p-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:k){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(mysum$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$coefficients[i,4]/2,6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/12zp4p1323434303.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple R',1,TRUE)
> a<-table.element(a, sqrt(mysum$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$sigma)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a, sum(myerror*myerror))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/13we8r1323434303.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Time or Index', 1, TRUE)
> a<-table.element(a, 'Actuals', 1, TRUE)
> a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
> a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
> a<-table.row.end(a)
> for (i in 1:n) {
+ a<-table.row.start(a)
+ a<-table.element(a,i, 1, TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]-mysum$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/14qjcw1323434303.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/15z86v1323434303.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/167cm61323434303.tab")
+ }
>
> try(system("convert tmp/1uyyw1323434303.ps tmp/1uyyw1323434303.png",intern=TRUE))
character(0)
> try(system("convert tmp/22phj1323434303.ps tmp/22phj1323434303.png",intern=TRUE))
character(0)
> try(system("convert tmp/33fu91323434303.ps tmp/33fu91323434303.png",intern=TRUE))
character(0)
> try(system("convert tmp/46kjd1323434303.ps tmp/46kjd1323434303.png",intern=TRUE))
character(0)
> try(system("convert tmp/5p69i1323434303.ps tmp/5p69i1323434303.png",intern=TRUE))
character(0)
> try(system("convert tmp/6vcak1323434303.ps tmp/6vcak1323434303.png",intern=TRUE))
character(0)
> try(system("convert tmp/76fv91323434303.ps tmp/76fv91323434303.png",intern=TRUE))
character(0)
> try(system("convert tmp/8wz5q1323434303.ps tmp/8wz5q1323434303.png",intern=TRUE))
character(0)
> try(system("convert tmp/9y4n11323434303.ps tmp/9y4n11323434303.png",intern=TRUE))
character(0)
> try(system("convert tmp/10t5kx1323434303.ps tmp/10t5kx1323434303.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
3.010 0.524 3.550