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(6.3,0,2.1,3.41,9.1,1.02,15.8,-1.7,5.2,2.2,10.9,0.52,8.3,1.72,11,-0.37,3.2,2.67,6.3,-1.1,6.6,-0.1,9.5,-0.7,3.3,1.44,11,-0.92,4.7,1.93,10.4,-1,7.4,0.02,2.1,2.72,17.9,-2,6.1,1.79,11.9,-1.7,13.8,0.23,14.3,0.54,15.2,-0.32,10,1,11.9,0.21,6.5,2.28,7.5,0.4,10.6,-0.55,7.4,0.63,8.4,0.83,5.7,-0.12,4.9,0.56,3.2,1.74,11,-0.05,4.9,0.3,13.2,-1,9.7,0.62,12.8,0.54),dim=c(2,39),dimnames=list(c('SWS','logWb'),1:39))
> y <- array(NA,dim=c(2,39),dimnames=list(c('SWS','logWb'),1:39))
> 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
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
SWS logWb
1 6.3 0.00
2 2.1 3.41
3 9.1 1.02
4 15.8 -1.70
5 5.2 2.20
6 10.9 0.52
7 8.3 1.72
8 11.0 -0.37
9 3.2 2.67
10 6.3 -1.10
11 6.6 -0.10
12 9.5 -0.70
13 3.3 1.44
14 11.0 -0.92
15 4.7 1.93
16 10.4 -1.00
17 7.4 0.02
18 2.1 2.72
19 17.9 -2.00
20 6.1 1.79
21 11.9 -1.70
22 13.8 0.23
23 14.3 0.54
24 15.2 -0.32
25 10.0 1.00
26 11.9 0.21
27 6.5 2.28
28 7.5 0.40
29 10.6 -0.55
30 7.4 0.63
31 8.4 0.83
32 5.7 -0.12
33 4.9 0.56
34 3.2 1.74
35 11.0 -0.05
36 4.9 0.30
37 13.2 -1.00
38 9.7 0.62
39 12.8 0.54
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) logWb
9.717 -2.197
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-5.8337 -1.6981 -0.1253 2.0588 5.7693
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 9.7170 0.4792 20.279 < 2e-16 ***
logWb -2.1970 0.3549 -6.191 3.46e-07 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 2.819 on 37 degrees of freedom
Multiple R-squared: 0.5088, Adjusted R-squared: 0.4955
F-statistic: 38.33 on 1 and 37 DF, p-value: 3.465e-07
> 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,] 0.4711082 0.9422164 0.5288918
[2,] 0.3773114 0.7546228 0.6226886
[3,] 0.3025534 0.6051069 0.6974466
[4,] 0.1902680 0.3805359 0.8097320
[5,] 0.1204212 0.2408425 0.8795788
[6,] 0.4967773 0.9935546 0.5032227
[7,] 0.5014204 0.9971592 0.4985796
[8,] 0.4127565 0.8255130 0.5872435
[9,] 0.4295070 0.8590140 0.5704930
[10,] 0.3384861 0.6769723 0.6615139
[11,] 0.2531681 0.5063362 0.7468319
[12,] 0.1941597 0.3883193 0.8058403
[13,] 0.1630883 0.3261766 0.8369117
[14,] 0.1240609 0.2481219 0.8759391
[15,] 0.2102749 0.4205497 0.7897251
[16,] 0.1510047 0.3020093 0.8489953
[17,] 0.1146950 0.2293899 0.8853050
[18,] 0.2094533 0.4189065 0.7905467
[19,] 0.4516426 0.9032852 0.5483574
[20,] 0.6145971 0.7708058 0.3854029
[21,] 0.5910798 0.8178403 0.4089202
[22,] 0.5915678 0.8168644 0.4084322
[23,] 0.5654848 0.8690303 0.4345152
[24,] 0.4669806 0.9339612 0.5330194
[25,] 0.3570000 0.7140001 0.6430000
[26,] 0.2572710 0.5145420 0.7427290
[27,] 0.1845364 0.3690728 0.8154636
[28,] 0.2655893 0.5311785 0.7344107
[29,] 0.2812846 0.5625693 0.7187154
[30,] 0.2157266 0.4314531 0.7842734
> postscript(file="/var/www/html/rcomp/tmp/1o4v31269597622.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2o4v31269597622.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3zvc51269597622.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4zvc51269597622.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5zvc51269597622.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 = 39
Frequency = 1
1 2 3 4 5 6 7
-3.4170493 -0.1252807 1.6238903 2.3480514 0.3163498 2.3253905 2.3617900
8 9 10 11 12 13 14
0.4700609 -0.6510604 -5.8337488 -3.3367493 -1.7549490 -3.2533699 -0.7382889
15 16 17 18 19 20 21
-0.7768401 -1.5140489 -2.2731093 -1.6412104 3.7889515 0.3155800 -1.5519486
22 23 24 25 26 27 28
4.5882606 5.7693305 4.7799108 2.4799503 2.6443206 1.7921097 -1.3382495
29 30 31 32 33 34 35
-0.3253991 -0.9329396 0.5064604 -4.2806892 -3.5867295 -2.6942700 1.1731007
36 37 38 39
-4.1579494 1.2859511 1.3450904 4.2693305
> postscript(file="/var/www/html/rcomp/tmp/694bq1269597622.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 = 39
Frequency = 1
lag(myerror, k = 1) myerror
0 -3.4170493 NA
1 -0.1252807 -3.4170493
2 1.6238903 -0.1252807
3 2.3480514 1.6238903
4 0.3163498 2.3480514
5 2.3253905 0.3163498
6 2.3617900 2.3253905
7 0.4700609 2.3617900
8 -0.6510604 0.4700609
9 -5.8337488 -0.6510604
10 -3.3367493 -5.8337488
11 -1.7549490 -3.3367493
12 -3.2533699 -1.7549490
13 -0.7382889 -3.2533699
14 -0.7768401 -0.7382889
15 -1.5140489 -0.7768401
16 -2.2731093 -1.5140489
17 -1.6412104 -2.2731093
18 3.7889515 -1.6412104
19 0.3155800 3.7889515
20 -1.5519486 0.3155800
21 4.5882606 -1.5519486
22 5.7693305 4.5882606
23 4.7799108 5.7693305
24 2.4799503 4.7799108
25 2.6443206 2.4799503
26 1.7921097 2.6443206
27 -1.3382495 1.7921097
28 -0.3253991 -1.3382495
29 -0.9329396 -0.3253991
30 0.5064604 -0.9329396
31 -4.2806892 0.5064604
32 -3.5867295 -4.2806892
33 -2.6942700 -3.5867295
34 1.1731007 -2.6942700
35 -4.1579494 1.1731007
36 1.2859511 -4.1579494
37 1.3450904 1.2859511
38 4.2693305 1.3450904
39 NA 4.2693305
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -0.1252807 -3.4170493
[2,] 1.6238903 -0.1252807
[3,] 2.3480514 1.6238903
[4,] 0.3163498 2.3480514
[5,] 2.3253905 0.3163498
[6,] 2.3617900 2.3253905
[7,] 0.4700609 2.3617900
[8,] -0.6510604 0.4700609
[9,] -5.8337488 -0.6510604
[10,] -3.3367493 -5.8337488
[11,] -1.7549490 -3.3367493
[12,] -3.2533699 -1.7549490
[13,] -0.7382889 -3.2533699
[14,] -0.7768401 -0.7382889
[15,] -1.5140489 -0.7768401
[16,] -2.2731093 -1.5140489
[17,] -1.6412104 -2.2731093
[18,] 3.7889515 -1.6412104
[19,] 0.3155800 3.7889515
[20,] -1.5519486 0.3155800
[21,] 4.5882606 -1.5519486
[22,] 5.7693305 4.5882606
[23,] 4.7799108 5.7693305
[24,] 2.4799503 4.7799108
[25,] 2.6443206 2.4799503
[26,] 1.7921097 2.6443206
[27,] -1.3382495 1.7921097
[28,] -0.3253991 -1.3382495
[29,] -0.9329396 -0.3253991
[30,] 0.5064604 -0.9329396
[31,] -4.2806892 0.5064604
[32,] -3.5867295 -4.2806892
[33,] -2.6942700 -3.5867295
[34,] 1.1731007 -2.6942700
[35,] -4.1579494 1.1731007
[36,] 1.2859511 -4.1579494
[37,] 1.3450904 1.2859511
[38,] 4.2693305 1.3450904
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -0.1252807 -3.4170493
2 1.6238903 -0.1252807
3 2.3480514 1.6238903
4 0.3163498 2.3480514
5 2.3253905 0.3163498
6 2.3617900 2.3253905
7 0.4700609 2.3617900
8 -0.6510604 0.4700609
9 -5.8337488 -0.6510604
10 -3.3367493 -5.8337488
11 -1.7549490 -3.3367493
12 -3.2533699 -1.7549490
13 -0.7382889 -3.2533699
14 -0.7768401 -0.7382889
15 -1.5140489 -0.7768401
16 -2.2731093 -1.5140489
17 -1.6412104 -2.2731093
18 3.7889515 -1.6412104
19 0.3155800 3.7889515
20 -1.5519486 0.3155800
21 4.5882606 -1.5519486
22 5.7693305 4.5882606
23 4.7799108 5.7693305
24 2.4799503 4.7799108
25 2.6443206 2.4799503
26 1.7921097 2.6443206
27 -1.3382495 1.7921097
28 -0.3253991 -1.3382495
29 -0.9329396 -0.3253991
30 0.5064604 -0.9329396
31 -4.2806892 0.5064604
32 -3.5867295 -4.2806892
33 -2.6942700 -3.5867295
34 1.1731007 -2.6942700
35 -4.1579494 1.1731007
36 1.2859511 -4.1579494
37 1.3450904 1.2859511
38 4.2693305 1.3450904
> 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/7kebc1269597622.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8kebc1269597622.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9kebc1269597622.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10dnaw1269597622.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11gn8k1269597622.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/12rf851269597622.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/13ggmz1269597622.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/14q7mk1269597622.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/15c7kq1269597622.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/16fq1v1269597622.tab")
+ }
>
> try(system("convert tmp/1o4v31269597622.ps tmp/1o4v31269597622.png",intern=TRUE))
character(0)
> try(system("convert tmp/2o4v31269597622.ps tmp/2o4v31269597622.png",intern=TRUE))
character(0)
> try(system("convert tmp/3zvc51269597622.ps tmp/3zvc51269597622.png",intern=TRUE))
character(0)
> try(system("convert tmp/4zvc51269597622.ps tmp/4zvc51269597622.png",intern=TRUE))
character(0)
> try(system("convert tmp/5zvc51269597622.ps tmp/5zvc51269597622.png",intern=TRUE))
character(0)
> try(system("convert tmp/694bq1269597622.ps tmp/694bq1269597622.png",intern=TRUE))
character(0)
> try(system("convert tmp/7kebc1269597622.ps tmp/7kebc1269597622.png",intern=TRUE))
character(0)
> try(system("convert tmp/8kebc1269597622.ps tmp/8kebc1269597622.png",intern=TRUE))
character(0)
> try(system("convert tmp/9kebc1269597622.ps tmp/9kebc1269597622.png",intern=TRUE))
character(0)
> try(system("convert tmp/10dnaw1269597622.ps tmp/10dnaw1269597622.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
2.321 1.622 87.335