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.
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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(16198.9,16896.2,16554.2,16698,19554.2,19691.6,15903.8,15930.7,18003.8,17444.6,18329.6,17699.4,16260.7,15189.8,14851.9,15672.7,18174.1,17180.8,18406.6,17664.9,18466.5,17862.9,16016.5,16162.3,17428.5,17463.6,17167.2,16772.1,19630,19106.9,17183.6,16721.3,18344.7,18161.3,19301.4,18509.9,18147.5,17802.7,16192.9,16409.9,18374.4,17967.7,20515.2,20286.6,18957.2,19537.3,16471.5,18021.9,18746.8,20194.3,19009.5,19049.6,19211.2,20244.7,20547.7,21473.3,19325.8,19673.6,20605.5,21053.2,20056.9,20159.5,16141.4,18203.6,20359.8,21289.5,19711.6,20432.3,15638.6,17180.4,14384.5,15816.8,13855.6,15071.8,14308.3,14521.1,15290.6,15668.8,14423.8,14346.9,13779.7,13881,15686.3,15465.9,14733.8,14238.2,12522.5,13557.7,16189.4,16127.6,16059.1,16793.9,16007.1,16014,15806.8,16867.9,15160,16014.6,15692.1,15878.6,18908.9,18664.9,16969.9,17962.5,16997.5,17332.7,19858.9,19542.1,17681.2,17203.6),dim=c(2,55),dimnames=list(c('uitvoer','invoer'),1:55))
> y <- array(NA,dim=c(2,55),dimnames=list(c('uitvoer','invoer'),1:55))
> 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
uitvoer invoer
1 16198.9 16896.2
2 16554.2 16698.0
3 19554.2 19691.6
4 15903.8 15930.7
5 18003.8 17444.6
6 18329.6 17699.4
7 16260.7 15189.8
8 14851.9 15672.7
9 18174.1 17180.8
10 18406.6 17664.9
11 18466.5 17862.9
12 16016.5 16162.3
13 17428.5 17463.6
14 17167.2 16772.1
15 19630.0 19106.9
16 17183.6 16721.3
17 18344.7 18161.3
18 19301.4 18509.9
19 18147.5 17802.7
20 16192.9 16409.9
21 18374.4 17967.7
22 20515.2 20286.6
23 18957.2 19537.3
24 16471.5 18021.9
25 18746.8 20194.3
26 19009.5 19049.6
27 19211.2 20244.7
28 20547.7 21473.3
29 19325.8 19673.6
30 20605.5 21053.2
31 20056.9 20159.5
32 16141.4 18203.6
33 20359.8 21289.5
34 19711.6 20432.3
35 15638.6 17180.4
36 14384.5 15816.8
37 13855.6 15071.8
38 14308.3 14521.1
39 15290.6 15668.8
40 14423.8 14346.9
41 13779.7 13881.0
42 15686.3 15465.9
43 14733.8 14238.2
44 12522.5 13557.7
45 16189.4 16127.6
46 16059.1 16793.9
47 16007.1 16014.0
48 15806.8 16867.9
49 15160.0 16014.6
50 15692.1 15878.6
51 18908.9 18664.9
52 16969.9 17962.5
53 16997.5 17332.7
54 19858.9 19542.1
55 17681.2 17203.6
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) invoer
461.7169 0.9604
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-1802.6 -533.8 56.1 593.2 1212.3
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 461.71691 876.96205 0.526 0.601
invoer 0.96038 0.04989 19.249 <2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 721 on 53 degrees of freedom
Multiple R-squared: 0.8749, Adjusted R-squared: 0.8725
F-statistic: 370.5 on 1 and 53 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,] 0.3011147 0.60222948 0.69888526
[2,] 0.3011816 0.60236318 0.69881841
[3,] 0.4054232 0.81084639 0.59457681
[4,] 0.5308493 0.93830144 0.46915072
[5,] 0.6066603 0.78667933 0.39333967
[6,] 0.5836622 0.83267568 0.41633784
[7,] 0.5286432 0.94271365 0.47135683
[8,] 0.4448271 0.88965424 0.55517288
[9,] 0.3618901 0.72378011 0.63810995
[10,] 0.2983020 0.59660392 0.70169804
[11,] 0.2554002 0.51080041 0.74459980
[12,] 0.2163425 0.43268498 0.78365751
[13,] 0.1681446 0.33628923 0.83185538
[14,] 0.1884482 0.37689649 0.81155175
[15,] 0.1575738 0.31514758 0.84242621
[16,] 0.1273440 0.25468798 0.87265601
[17,] 0.1123359 0.22467182 0.88766409
[18,] 0.1048430 0.20968599 0.89515700
[19,] 0.1344200 0.26884007 0.86557996
[20,] 0.4515680 0.90313608 0.54843196
[21,] 0.6266490 0.74670209 0.37335104
[22,] 0.5727040 0.85459195 0.42729598
[23,] 0.5640603 0.87187939 0.43593969
[24,] 0.5060667 0.98786655 0.49393328
[25,] 0.4304843 0.86096850 0.56951575
[26,] 0.3562714 0.71254282 0.64372859
[27,] 0.3130866 0.62617316 0.68691342
[28,] 0.7329999 0.53400010 0.26700005
[29,] 0.6844637 0.63107267 0.31553633
[30,] 0.6232500 0.75350003 0.37675002
[31,] 0.8168194 0.36636112 0.18318056
[32,] 0.9221719 0.15565620 0.07782810
[33,] 0.9574861 0.08502783 0.04251392
[34,] 0.9326581 0.13468384 0.06734192
[35,] 0.8991686 0.20166288 0.10083144
[36,] 0.8625559 0.27488811 0.13744405
[37,] 0.8092996 0.38140085 0.19070043
[38,] 0.7784982 0.44300353 0.22150176
[39,] 0.8765074 0.24698518 0.12349259
[40,] 0.8371891 0.32562180 0.16281090
[41,] 0.8041277 0.39174462 0.19587231
[42,] 0.7424854 0.51502917 0.25751458
[43,] 0.6947218 0.61055648 0.30527824
[44,] 0.7055147 0.58897052 0.29448526
[45,] 0.6381287 0.72374261 0.36187130
[46,] 0.4695688 0.93913751 0.53043125
> postscript(file="/var/www/html/rcomp/tmp/1w27s1290248148.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2obod1290248148.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3obod1290248148.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4obod1290248148.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5zk5g1290248148.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 = 55
Frequency = 1
1 2 3 4 5 6
-489.54834 56.09849 181.11221 142.59620 788.68060 869.77639
7 8 9 10 11 12
1211.03994 -661.52639 1212.32820 979.90942 849.65466 32.87275
13 14 15 16 17 18
195.13342 597.93451 818.44497 663.12169 441.27800 1063.19038
19 20 21 22 23 24
588.46939 -28.51673 656.90709 570.68755 -267.70153 -1298.04537
25 26 27 28 29 30
-1109.06960 252.97460 -693.07263 -536.49250 -30.00100 -75.23789
31 32 33 34 35 36
234.45154 -1802.64597 -547.87511 -372.83946 -1322.78765 -1267.31680
37 38 39 40 41 42
-1080.73551 -99.15559 -219.08092 183.64219 -13.01791 371.47969
43 44 45 46 47 48
598.03523 -959.72784 239.09785 -531.10172 165.89675 -854.46966
49 50 51 52 53 54
-681.77948 -19.06813 521.83185 -742.59894 -110.15315 629.38865
55
697.53159
> postscript(file="/var/www/html/rcomp/tmp/6zk5g1290248148.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 = 55
Frequency = 1
lag(myerror, k = 1) myerror
0 -489.54834 NA
1 56.09849 -489.54834
2 181.11221 56.09849
3 142.59620 181.11221
4 788.68060 142.59620
5 869.77639 788.68060
6 1211.03994 869.77639
7 -661.52639 1211.03994
8 1212.32820 -661.52639
9 979.90942 1212.32820
10 849.65466 979.90942
11 32.87275 849.65466
12 195.13342 32.87275
13 597.93451 195.13342
14 818.44497 597.93451
15 663.12169 818.44497
16 441.27800 663.12169
17 1063.19038 441.27800
18 588.46939 1063.19038
19 -28.51673 588.46939
20 656.90709 -28.51673
21 570.68755 656.90709
22 -267.70153 570.68755
23 -1298.04537 -267.70153
24 -1109.06960 -1298.04537
25 252.97460 -1109.06960
26 -693.07263 252.97460
27 -536.49250 -693.07263
28 -30.00100 -536.49250
29 -75.23789 -30.00100
30 234.45154 -75.23789
31 -1802.64597 234.45154
32 -547.87511 -1802.64597
33 -372.83946 -547.87511
34 -1322.78765 -372.83946
35 -1267.31680 -1322.78765
36 -1080.73551 -1267.31680
37 -99.15559 -1080.73551
38 -219.08092 -99.15559
39 183.64219 -219.08092
40 -13.01791 183.64219
41 371.47969 -13.01791
42 598.03523 371.47969
43 -959.72784 598.03523
44 239.09785 -959.72784
45 -531.10172 239.09785
46 165.89675 -531.10172
47 -854.46966 165.89675
48 -681.77948 -854.46966
49 -19.06813 -681.77948
50 521.83185 -19.06813
51 -742.59894 521.83185
52 -110.15315 -742.59894
53 629.38865 -110.15315
54 697.53159 629.38865
55 NA 697.53159
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 56.09849 -489.54834
[2,] 181.11221 56.09849
[3,] 142.59620 181.11221
[4,] 788.68060 142.59620
[5,] 869.77639 788.68060
[6,] 1211.03994 869.77639
[7,] -661.52639 1211.03994
[8,] 1212.32820 -661.52639
[9,] 979.90942 1212.32820
[10,] 849.65466 979.90942
[11,] 32.87275 849.65466
[12,] 195.13342 32.87275
[13,] 597.93451 195.13342
[14,] 818.44497 597.93451
[15,] 663.12169 818.44497
[16,] 441.27800 663.12169
[17,] 1063.19038 441.27800
[18,] 588.46939 1063.19038
[19,] -28.51673 588.46939
[20,] 656.90709 -28.51673
[21,] 570.68755 656.90709
[22,] -267.70153 570.68755
[23,] -1298.04537 -267.70153
[24,] -1109.06960 -1298.04537
[25,] 252.97460 -1109.06960
[26,] -693.07263 252.97460
[27,] -536.49250 -693.07263
[28,] -30.00100 -536.49250
[29,] -75.23789 -30.00100
[30,] 234.45154 -75.23789
[31,] -1802.64597 234.45154
[32,] -547.87511 -1802.64597
[33,] -372.83946 -547.87511
[34,] -1322.78765 -372.83946
[35,] -1267.31680 -1322.78765
[36,] -1080.73551 -1267.31680
[37,] -99.15559 -1080.73551
[38,] -219.08092 -99.15559
[39,] 183.64219 -219.08092
[40,] -13.01791 183.64219
[41,] 371.47969 -13.01791
[42,] 598.03523 371.47969
[43,] -959.72784 598.03523
[44,] 239.09785 -959.72784
[45,] -531.10172 239.09785
[46,] 165.89675 -531.10172
[47,] -854.46966 165.89675
[48,] -681.77948 -854.46966
[49,] -19.06813 -681.77948
[50,] 521.83185 -19.06813
[51,] -742.59894 521.83185
[52,] -110.15315 -742.59894
[53,] 629.38865 -110.15315
[54,] 697.53159 629.38865
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 56.09849 -489.54834
2 181.11221 56.09849
3 142.59620 181.11221
4 788.68060 142.59620
5 869.77639 788.68060
6 1211.03994 869.77639
7 -661.52639 1211.03994
8 1212.32820 -661.52639
9 979.90942 1212.32820
10 849.65466 979.90942
11 32.87275 849.65466
12 195.13342 32.87275
13 597.93451 195.13342
14 818.44497 597.93451
15 663.12169 818.44497
16 441.27800 663.12169
17 1063.19038 441.27800
18 588.46939 1063.19038
19 -28.51673 588.46939
20 656.90709 -28.51673
21 570.68755 656.90709
22 -267.70153 570.68755
23 -1298.04537 -267.70153
24 -1109.06960 -1298.04537
25 252.97460 -1109.06960
26 -693.07263 252.97460
27 -536.49250 -693.07263
28 -30.00100 -536.49250
29 -75.23789 -30.00100
30 234.45154 -75.23789
31 -1802.64597 234.45154
32 -547.87511 -1802.64597
33 -372.83946 -547.87511
34 -1322.78765 -372.83946
35 -1267.31680 -1322.78765
36 -1080.73551 -1267.31680
37 -99.15559 -1080.73551
38 -219.08092 -99.15559
39 183.64219 -219.08092
40 -13.01791 183.64219
41 371.47969 -13.01791
42 598.03523 371.47969
43 -959.72784 598.03523
44 239.09785 -959.72784
45 -531.10172 239.09785
46 165.89675 -531.10172
47 -854.46966 165.89675
48 -681.77948 -854.46966
49 -19.06813 -681.77948
50 521.83185 -19.06813
51 -742.59894 521.83185
52 -110.15315 -742.59894
53 629.38865 -110.15315
54 697.53159 629.38865
> 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/7st5j1290248148.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8st5j1290248148.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9kk4l1290248148.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10kk4l1290248148.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11o32r1290248148.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/129l1x1290248148.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/13g4g91290248148.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/149efu1290248148.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/15cwei1290248148.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/16q6bq1290248148.tab")
+ }
>
> try(system("convert tmp/1w27s1290248148.ps tmp/1w27s1290248148.png",intern=TRUE))
character(0)
> try(system("convert tmp/2obod1290248148.ps tmp/2obod1290248148.png",intern=TRUE))
character(0)
> try(system("convert tmp/3obod1290248148.ps tmp/3obod1290248148.png",intern=TRUE))
character(0)
> try(system("convert tmp/4obod1290248148.ps tmp/4obod1290248148.png",intern=TRUE))
character(0)
> try(system("convert tmp/5zk5g1290248148.ps tmp/5zk5g1290248148.png",intern=TRUE))
character(0)
> try(system("convert tmp/6zk5g1290248148.ps tmp/6zk5g1290248148.png",intern=TRUE))
character(0)
> try(system("convert tmp/7st5j1290248148.ps tmp/7st5j1290248148.png",intern=TRUE))
character(0)
> try(system("convert tmp/8st5j1290248148.ps tmp/8st5j1290248148.png",intern=TRUE))
character(0)
> try(system("convert tmp/9kk4l1290248148.ps tmp/9kk4l1290248148.png",intern=TRUE))
character(0)
> try(system("convert tmp/10kk4l1290248148.ps tmp/10kk4l1290248148.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
2.363 1.539 5.716