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(1217,31,48,0,1210,1202,34.4,38,0,1209,1180,35.6,37,0,1207,1167,32.8,48,0,1206,1186,23.3,81,1,1204,1168,20,58,1,1201,1142,16.7,93,1,1199,1147,17.8,86,0,1198,1183,21.2,68,0,1196,1149,23.9,68,0,1195,1197,28.8,68,0,1193,1210,25.6,59,0,1191,1206,29.4,43,0,1190,1196,22.8,59,0,1188,1190,16.1,31,0,1187,1175,16.1,49,0,1185,1186,20,52,0,1183,1172,20.6,75,0,1182,1152,18.3,90,1,1185,1154,21.6,86,1,1179,1168,22.8,87,0,1177,1180,22.8,47,0,1175,1169,17.2,70,0,1174,1166,22.2,61,0,1170,1177,20.6,48,0,1169,1168,18.3,67,0,1167,1160,16.7,74,0,1166,1147,22.8,55,1,1164,1161,13.9,47,0,1162,1161,16.1,28,0,1159,1161,20.6,30,0,1158,1168,19.4,67,0,1156,1172,25.6,32,0,1155),dim=c(5,33),dimnames=list(c('15thbird','Temp','Humidity','Rain','Sunset'),1:33))
> y <- array(NA,dim=c(5,33),dimnames=list(c('15thbird','Temp','Humidity','Rain','Sunset'),1:33))
> 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
15thbird Temp Humidity Rain Sunset
1 1217 31.0 48 0 1210
2 1202 34.4 38 0 1209
3 1180 35.6 37 0 1207
4 1167 32.8 48 0 1206
5 1186 23.3 81 1 1204
6 1168 20.0 58 1 1201
7 1142 16.7 93 1 1199
8 1147 17.8 86 0 1198
9 1183 21.2 68 0 1196
10 1149 23.9 68 0 1195
11 1197 28.8 68 0 1193
12 1210 25.6 59 0 1191
13 1206 29.4 43 0 1190
14 1196 22.8 59 0 1188
15 1190 16.1 31 0 1187
16 1175 16.1 49 0 1185
17 1186 20.0 52 0 1183
18 1172 20.6 75 0 1182
19 1152 18.3 90 1 1185
20 1154 21.6 86 1 1179
21 1168 22.8 87 0 1177
22 1180 22.8 47 0 1175
23 1169 17.2 70 0 1174
24 1166 22.2 61 0 1170
25 1177 20.6 48 0 1169
26 1168 18.3 67 0 1167
27 1160 16.7 74 0 1166
28 1147 22.8 55 1 1164
29 1161 13.9 47 0 1162
30 1161 16.1 28 0 1159
31 1161 20.6 30 0 1158
32 1168 19.4 67 0 1156
33 1172 25.6 32 0 1155
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Temp Humidity Rain Sunset
695.0150 0.7701 -0.2553 -14.6017 0.4053
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-31.3324 -4.6793 0.6607 6.6825 27.6814
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 695.0150 231.3233 3.005 0.00555 **
Temp 0.7701 0.6338 1.215 0.23449
Humidity -0.2553 0.1719 -1.485 0.14863
Rain -14.6017 7.6393 -1.911 0.06624 .
Sunset 0.4053 0.2054 1.973 0.05846 .
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 14.83 on 28 degrees of freedom
Multiple R-squared: 0.472, Adjusted R-squared: 0.3966
F-statistic: 6.258 on 4 and 28 DF, p-value: 0.0009952
> 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,] 0.3932305 7.864611e-01 6.067695e-01
[2,] 0.9785833 4.283339e-02 2.141669e-02
[3,] 0.9999487 1.026928e-04 5.134641e-05
[4,] 0.9999951 9.855043e-06 4.927521e-06
[5,] 0.9999995 1.090920e-06 5.454598e-07
[6,] 0.9999979 4.165417e-06 2.082708e-06
[7,] 0.9999976 4.739381e-06 2.369691e-06
[8,] 0.9999958 8.424153e-06 4.212076e-06
[9,] 0.9999836 3.286653e-05 1.643326e-05
[10,] 0.9999813 3.740184e-05 1.870092e-05
[11,] 0.9999300 1.400343e-04 7.001714e-05
[12,] 0.9997628 4.744188e-04 2.372094e-04
[13,] 0.9993218 1.356390e-03 6.781950e-04
[14,] 0.9987349 2.530104e-03 1.265052e-03
[15,] 0.9968130 6.374052e-03 3.187026e-03
[16,] 0.9889717 2.205653e-02 1.102826e-02
[17,] 0.9840684 3.186327e-02 1.593164e-02
[18,] 0.9797931 4.041384e-02 2.020692e-02
> postscript(file="/var/wessaorg/rcomp/tmp/1hn1q1332176296.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/24vh91332176296.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3lqw41332176296.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/48qf71332176296.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/5d5hv1332176296.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 = 33
Frequency = 1
1 2 3 4 5 6
20.0143636 0.2478963 -22.1210585 -29.7508103 20.4034971 0.2877995
7 8 9 10 11 12
-13.4235357 -25.2544656 4.3416129 -31.3324034 13.7046135 27.6813892
13 14 15 16 17 18
17.0748533 17.0534198 9.4688658 -0.1245451 9.4485854 1.2645549
19 20 21 22 23 24
0.2518068 1.1206339 0.6606505 3.2576261 2.8482096 -4.6793246
25 26 27 28 29 30
4.6386888 3.0718439 -1.5033794 -8.6402015 -3.6202281 -8.9501179
31 32 33
-11.4996361 6.6824971 -2.6237016
> postscript(file="/var/wessaorg/rcomp/tmp/6wo351332176296.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 = 33
Frequency = 1
lag(myerror, k = 1) myerror
0 20.0143636 NA
1 0.2478963 20.0143636
2 -22.1210585 0.2478963
3 -29.7508103 -22.1210585
4 20.4034971 -29.7508103
5 0.2877995 20.4034971
6 -13.4235357 0.2877995
7 -25.2544656 -13.4235357
8 4.3416129 -25.2544656
9 -31.3324034 4.3416129
10 13.7046135 -31.3324034
11 27.6813892 13.7046135
12 17.0748533 27.6813892
13 17.0534198 17.0748533
14 9.4688658 17.0534198
15 -0.1245451 9.4688658
16 9.4485854 -0.1245451
17 1.2645549 9.4485854
18 0.2518068 1.2645549
19 1.1206339 0.2518068
20 0.6606505 1.1206339
21 3.2576261 0.6606505
22 2.8482096 3.2576261
23 -4.6793246 2.8482096
24 4.6386888 -4.6793246
25 3.0718439 4.6386888
26 -1.5033794 3.0718439
27 -8.6402015 -1.5033794
28 -3.6202281 -8.6402015
29 -8.9501179 -3.6202281
30 -11.4996361 -8.9501179
31 6.6824971 -11.4996361
32 -2.6237016 6.6824971
33 NA -2.6237016
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 0.2478963 20.0143636
[2,] -22.1210585 0.2478963
[3,] -29.7508103 -22.1210585
[4,] 20.4034971 -29.7508103
[5,] 0.2877995 20.4034971
[6,] -13.4235357 0.2877995
[7,] -25.2544656 -13.4235357
[8,] 4.3416129 -25.2544656
[9,] -31.3324034 4.3416129
[10,] 13.7046135 -31.3324034
[11,] 27.6813892 13.7046135
[12,] 17.0748533 27.6813892
[13,] 17.0534198 17.0748533
[14,] 9.4688658 17.0534198
[15,] -0.1245451 9.4688658
[16,] 9.4485854 -0.1245451
[17,] 1.2645549 9.4485854
[18,] 0.2518068 1.2645549
[19,] 1.1206339 0.2518068
[20,] 0.6606505 1.1206339
[21,] 3.2576261 0.6606505
[22,] 2.8482096 3.2576261
[23,] -4.6793246 2.8482096
[24,] 4.6386888 -4.6793246
[25,] 3.0718439 4.6386888
[26,] -1.5033794 3.0718439
[27,] -8.6402015 -1.5033794
[28,] -3.6202281 -8.6402015
[29,] -8.9501179 -3.6202281
[30,] -11.4996361 -8.9501179
[31,] 6.6824971 -11.4996361
[32,] -2.6237016 6.6824971
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 0.2478963 20.0143636
2 -22.1210585 0.2478963
3 -29.7508103 -22.1210585
4 20.4034971 -29.7508103
5 0.2877995 20.4034971
6 -13.4235357 0.2877995
7 -25.2544656 -13.4235357
8 4.3416129 -25.2544656
9 -31.3324034 4.3416129
10 13.7046135 -31.3324034
11 27.6813892 13.7046135
12 17.0748533 27.6813892
13 17.0534198 17.0748533
14 9.4688658 17.0534198
15 -0.1245451 9.4688658
16 9.4485854 -0.1245451
17 1.2645549 9.4485854
18 0.2518068 1.2645549
19 1.1206339 0.2518068
20 0.6606505 1.1206339
21 3.2576261 0.6606505
22 2.8482096 3.2576261
23 -4.6793246 2.8482096
24 4.6386888 -4.6793246
25 3.0718439 4.6386888
26 -1.5033794 3.0718439
27 -8.6402015 -1.5033794
28 -3.6202281 -8.6402015
29 -8.9501179 -3.6202281
30 -11.4996361 -8.9501179
31 6.6824971 -11.4996361
32 -2.6237016 6.6824971
> 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/73ydc1332176296.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/8crfu1332176296.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/9fgkk1332176296.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/wessaorg/rcomp/tmp/10b2tx1332176296.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11sp101332176296.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/12gh8t1332176296.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/13mppj1332176296.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/14esoh1332176296.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/15q2t31332176296.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/16u8x91332176296.tab")
+ }
>
> try(system("convert tmp/1hn1q1332176296.ps tmp/1hn1q1332176296.png",intern=TRUE))
character(0)
> try(system("convert tmp/24vh91332176296.ps tmp/24vh91332176296.png",intern=TRUE))
character(0)
> try(system("convert tmp/3lqw41332176296.ps tmp/3lqw41332176296.png",intern=TRUE))
character(0)
> try(system("convert tmp/48qf71332176296.ps tmp/48qf71332176296.png",intern=TRUE))
character(0)
> try(system("convert tmp/5d5hv1332176296.ps tmp/5d5hv1332176296.png",intern=TRUE))
character(0)
> try(system("convert tmp/6wo351332176296.ps tmp/6wo351332176296.png",intern=TRUE))
character(0)
> try(system("convert tmp/73ydc1332176296.ps tmp/73ydc1332176296.png",intern=TRUE))
character(0)
> try(system("convert tmp/8crfu1332176296.ps tmp/8crfu1332176296.png",intern=TRUE))
character(0)
> try(system("convert tmp/9fgkk1332176296.ps tmp/9fgkk1332176296.png",intern=TRUE))
character(0)
> try(system("convert tmp/10b2tx1332176296.ps tmp/10b2tx1332176296.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
3.112 0.656 3.790