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
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> x <- array(list(1225,31.00,1210,0,1214,34.40,1209,0,1205,35.60,1207,0,1196,32.80,1206,0,1209,23.30,1204,1,1192,17.00,1203,0,1196,20.00,1201,1,1174,16.70,1199,1,1183,17.80,1198,0,1210,21.20,1196,0,1205,23.90,1195,0,1218,28.80,1193,0,1224,25.60,1191,0,1215,29.40,1190,0,1206,22.80,1188,0,1202,16.10,1187,0,1215,16.10,1185,0,1203,20.00,1183,0,1194,20.60,1182,0,1170,18.30,1185,1,1184,21.60,1179,1,1199,22.80,1177,0,1196,22.80,1175,0,1189,17.20,1174,0,1185,22.20,1170,0,1192,20.60,1169,0,1188,18.30,1167,0,1176,16.70,1166,0,1177,13.90,1162,0,1166,10.00,1161,0,1176,16.10,1159,0,1181,20.60,1158,0,1176,19.40,1156,0,1172,25.60,1155,0),dim=c(4,34),dimnames=list(c('50%in','Temp','Sunset','Rain'),1:34))
> y <- array(NA,dim=c(4,34),dimnames=list(c('50%in','Temp','Sunset','Rain'),1:34))
> 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 = '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
> 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
50%in Temp Sunset Rain
1 1225 31.0 1210 0
2 1214 34.4 1209 0
3 1205 35.6 1207 0
4 1196 32.8 1206 0
5 1209 23.3 1204 1
6 1192 17.0 1203 0
7 1196 20.0 1201 1
8 1174 16.7 1199 1
9 1183 17.8 1198 0
10 1210 21.2 1196 0
11 1205 23.9 1195 0
12 1218 28.8 1193 0
13 1224 25.6 1191 0
14 1215 29.4 1190 0
15 1206 22.8 1188 0
16 1202 16.1 1187 0
17 1215 16.1 1185 0
18 1203 20.0 1183 0
19 1194 20.6 1182 0
20 1170 18.3 1185 1
21 1184 21.6 1179 1
22 1199 22.8 1177 0
23 1196 22.8 1175 0
24 1189 17.2 1174 0
25 1185 22.2 1170 0
26 1192 20.6 1169 0
27 1188 18.3 1167 0
28 1176 16.7 1166 0
29 1177 13.9 1162 0
30 1166 10.0 1161 0
31 1176 16.1 1159 0
32 1181 20.6 1158 0
33 1176 19.4 1156 0
34 1172 25.6 1155 0
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Temp Sunset Rain
495.0247 0.6697 0.5805 -14.7336
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-21.1179 -6.8183 0.5676 6.3493 21.2575
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 495.0247 163.0500 3.036 0.004922 **
Temp 0.6697 0.3978 1.683 0.102673
Sunset 0.5805 0.1423 4.081 0.000306 ***
Rain -14.7336 5.6767 -2.595 0.014483 *
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 10.75 on 30 degrees of freedom
Multiple R-squared: 0.6065, Adjusted R-squared: 0.5671
F-statistic: 15.41 on 3 and 30 DF, p-value: 2.989e-06
> 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,] 0.03298365 0.065967308 0.9670163460
[2,] 0.11783766 0.235675328 0.8821623359
[3,] 0.77549493 0.449010147 0.2245050737
[4,] 0.99557350 0.008853006 0.0044265031
[5,] 0.99725132 0.005497366 0.0027486831
[6,] 0.99557651 0.008846970 0.0044234851
[7,] 0.99692441 0.006151172 0.0030755858
[8,] 0.99334910 0.013301806 0.0066509030
[9,] 0.98735682 0.025286355 0.0126431773
[10,] 0.97563175 0.048736503 0.0243682513
[11,] 0.99521160 0.009576807 0.0047884034
[12,] 0.99218298 0.015634037 0.0078170185
[13,] 0.99185597 0.016288069 0.0081440346
[14,] 0.99919493 0.001610141 0.0008050707
[15,] 0.99765914 0.004681729 0.0023408646
[16,] 0.99381824 0.012363516 0.0061817582
[17,] 0.98458884 0.030822321 0.0154111604
[18,] 0.96388134 0.072237328 0.0361186639
[19,] 0.95459380 0.090812398 0.0454061988
[20,] 0.89917979 0.201640420 0.1008202099
[21,] 0.84613838 0.307723237 0.1538616185
> postscript(file="/var/wessaorg/rcomp/tmp/1ibed1333386015.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/2u1eu1333386015.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3wt841333386015.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/4f5041333386015.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/5gxhz1333386015.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 = 34
Frequency = 1
1 2 3 4 5 6
6.76545945 -5.93100958 -14.57358599 -21.11786892 14.13899428 -12.79488269
7 8 9 10 11 12
5.09063758 -13.53825538 -19.42796737 6.45609985 0.22842603 11.10793211
13 14 15 16 17 18
20.41206841 9.44771641 6.02885799 7.09643405 21.25750656 7.80672007
19 20 21 22 23 24
-1.01456814 -10.48227973 4.79090325 5.41475677 3.57582928 0.90672717
25 26 27 28 29 30
-4.11966499 4.53240316 3.23380276 -7.11412909 -1.91680326 -9.72440801
31 32 33 34
-2.64855086 -0.08169806 -3.11697663 -10.68862647
> postscript(file="/var/wessaorg/rcomp/tmp/6ohk91333386015.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 = 34
Frequency = 1
lag(myerror, k = 1) myerror
0 6.76545945 NA
1 -5.93100958 6.76545945
2 -14.57358599 -5.93100958
3 -21.11786892 -14.57358599
4 14.13899428 -21.11786892
5 -12.79488269 14.13899428
6 5.09063758 -12.79488269
7 -13.53825538 5.09063758
8 -19.42796737 -13.53825538
9 6.45609985 -19.42796737
10 0.22842603 6.45609985
11 11.10793211 0.22842603
12 20.41206841 11.10793211
13 9.44771641 20.41206841
14 6.02885799 9.44771641
15 7.09643405 6.02885799
16 21.25750656 7.09643405
17 7.80672007 21.25750656
18 -1.01456814 7.80672007
19 -10.48227973 -1.01456814
20 4.79090325 -10.48227973
21 5.41475677 4.79090325
22 3.57582928 5.41475677
23 0.90672717 3.57582928
24 -4.11966499 0.90672717
25 4.53240316 -4.11966499
26 3.23380276 4.53240316
27 -7.11412909 3.23380276
28 -1.91680326 -7.11412909
29 -9.72440801 -1.91680326
30 -2.64855086 -9.72440801
31 -0.08169806 -2.64855086
32 -3.11697663 -0.08169806
33 -10.68862647 -3.11697663
34 NA -10.68862647
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -5.93100958 6.76545945
[2,] -14.57358599 -5.93100958
[3,] -21.11786892 -14.57358599
[4,] 14.13899428 -21.11786892
[5,] -12.79488269 14.13899428
[6,] 5.09063758 -12.79488269
[7,] -13.53825538 5.09063758
[8,] -19.42796737 -13.53825538
[9,] 6.45609985 -19.42796737
[10,] 0.22842603 6.45609985
[11,] 11.10793211 0.22842603
[12,] 20.41206841 11.10793211
[13,] 9.44771641 20.41206841
[14,] 6.02885799 9.44771641
[15,] 7.09643405 6.02885799
[16,] 21.25750656 7.09643405
[17,] 7.80672007 21.25750656
[18,] -1.01456814 7.80672007
[19,] -10.48227973 -1.01456814
[20,] 4.79090325 -10.48227973
[21,] 5.41475677 4.79090325
[22,] 3.57582928 5.41475677
[23,] 0.90672717 3.57582928
[24,] -4.11966499 0.90672717
[25,] 4.53240316 -4.11966499
[26,] 3.23380276 4.53240316
[27,] -7.11412909 3.23380276
[28,] -1.91680326 -7.11412909
[29,] -9.72440801 -1.91680326
[30,] -2.64855086 -9.72440801
[31,] -0.08169806 -2.64855086
[32,] -3.11697663 -0.08169806
[33,] -10.68862647 -3.11697663
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -5.93100958 6.76545945
2 -14.57358599 -5.93100958
3 -21.11786892 -14.57358599
4 14.13899428 -21.11786892
5 -12.79488269 14.13899428
6 5.09063758 -12.79488269
7 -13.53825538 5.09063758
8 -19.42796737 -13.53825538
9 6.45609985 -19.42796737
10 0.22842603 6.45609985
11 11.10793211 0.22842603
12 20.41206841 11.10793211
13 9.44771641 20.41206841
14 6.02885799 9.44771641
15 7.09643405 6.02885799
16 21.25750656 7.09643405
17 7.80672007 21.25750656
18 -1.01456814 7.80672007
19 -10.48227973 -1.01456814
20 4.79090325 -10.48227973
21 5.41475677 4.79090325
22 3.57582928 5.41475677
23 0.90672717 3.57582928
24 -4.11966499 0.90672717
25 4.53240316 -4.11966499
26 3.23380276 4.53240316
27 -7.11412909 3.23380276
28 -1.91680326 -7.11412909
29 -9.72440801 -1.91680326
30 -2.64855086 -9.72440801
31 -0.08169806 -2.64855086
32 -3.11697663 -0.08169806
33 -10.68862647 -3.11697663
> 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/7n0531333386015.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/82k7k1333386015.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/9vlxq1333386015.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/wessaorg/rcomp/tmp/10nbkk1333386015.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/115spl1333386015.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/12ypqe1333386015.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/13m7ea1333386015.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/14oykb1333386015.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/15zpf11333386015.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/16amm51333386015.tab")
+ }
>
> try(system("convert tmp/1ibed1333386015.ps tmp/1ibed1333386015.png",intern=TRUE))
character(0)
> try(system("convert tmp/2u1eu1333386015.ps tmp/2u1eu1333386015.png",intern=TRUE))
character(0)
> try(system("convert tmp/3wt841333386015.ps tmp/3wt841333386015.png",intern=TRUE))
character(0)
> try(system("convert tmp/4f5041333386015.ps tmp/4f5041333386015.png",intern=TRUE))
character(0)
> try(system("convert tmp/5gxhz1333386015.ps tmp/5gxhz1333386015.png",intern=TRUE))
character(0)
> try(system("convert tmp/6ohk91333386015.ps tmp/6ohk91333386015.png",intern=TRUE))
character(0)
> try(system("convert tmp/7n0531333386015.ps tmp/7n0531333386015.png",intern=TRUE))
character(0)
> try(system("convert tmp/82k7k1333386015.ps tmp/82k7k1333386015.png",intern=TRUE))
character(0)
> try(system("convert tmp/9vlxq1333386015.ps tmp/9vlxq1333386015.png",intern=TRUE))
character(0)
> try(system("convert tmp/10nbkk1333386015.ps tmp/10nbkk1333386015.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
2.996 0.670 3.678