R version 2.12.0 (2010-10-15)
Copyright (C) 2010 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.
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> x <- array(list(2.0,1.62324929,3,1.8,2.79518459,4,.7,2.255272505,4,3.9,1.544068044,1,1.0,2.593286067,4,3.6,1.799340549,1,1.4,2.361727836,1,1.5,2.049218023,4,.7,2.44870632,5,2.1,1.62324929,1,.0,1.447158031,2,4.1,1.62324929,2,1.2,2.079181246,2,.3,2.602059991,5,.5,2.170261715,5,3.4,1.204119983,2,1.5,2.491361694,1,3.4,1.447158031,3,.8,1.832508913,4,.8,2.526339277,5,1.4,1.322219295,4,2.0,1.698970004,1,1.9,2.426511261,1,2.4,1.477121255,1,2.8,1.653212514,3,1.3,1.278753601,3,2.0,1.477121255,3,5.6,1.079181246,1,3.1,2.079181246,1,1.0,2.643452676,5,1.8,2.146128036,2,.9,2.230448921,4,1.8,1.230448921,2,1.9,2.06069784,4,.9,1.491361694,5,2.6,1.322219295,3,2.4,1.716003344,1,1.2,2.214843848,2,.9,2.352182518,2,.5,2.352182518,3,.6,2.178976947,5,2.3,1.77815125,2,.5,2.301029996,3,2.6,1.662757832,2,.6,2.322219295,4,6.6,1.146128036,1),dim=c(3,46),dimnames=list(c('PS','Tg','D'),1:46))
> y <- array(NA,dim=c(3,46),dimnames=list(c('PS','Tg','D'),1:46))
> 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
PS Tg D
1 2.0 1.623249 3
2 1.8 2.795185 4
3 0.7 2.255273 4
4 3.9 1.544068 1
5 1.0 2.593286 4
6 3.6 1.799341 1
7 1.4 2.361728 1
8 1.5 2.049218 4
9 0.7 2.448706 5
10 2.1 1.623249 1
11 0.0 1.447158 2
12 4.1 1.623249 2
13 1.2 2.079181 2
14 0.3 2.602060 5
15 0.5 2.170262 5
16 3.4 1.204120 2
17 1.5 2.491362 1
18 3.4 1.447158 3
19 0.8 1.832509 4
20 0.8 2.526339 5
21 1.4 1.322219 4
22 2.0 1.698970 1
23 1.9 2.426511 1
24 2.4 1.477121 1
25 2.8 1.653213 3
26 1.3 1.278754 3
27 2.0 1.477121 3
28 5.6 1.079181 1
29 3.1 2.079181 1
30 1.0 2.643453 5
31 1.8 2.146128 2
32 0.9 2.230449 4
33 1.8 1.230449 2
34 1.9 2.060698 4
35 0.9 1.491362 5
36 2.6 1.322219 3
37 2.4 1.716003 1
38 1.2 2.214844 2
39 0.9 2.352183 2
40 0.5 2.352183 3
41 0.6 2.178977 5
42 2.3 1.778151 2
43 0.5 2.301030 3
44 2.6 1.662758 2
45 0.6 2.322219 4
46 6.6 1.146128 1
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Tg D
5.3570 -1.2481 -0.3944
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-2.76197 -0.67495 -0.09253 0.54057 3.06787
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 5.3570 0.6163 8.692 5.08e-11 ***
Tg -1.2481 0.3392 -3.679 0.000646 ***
D -0.3944 0.1116 -3.535 0.000990 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.9846 on 43 degrees of freedom
Multiple R-squared: 0.5007, Adjusted R-squared: 0.4774
F-statistic: 21.56 on 2 and 43 DF, p-value: 3.277e-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,] 0.09477932 0.1895586 0.9052207
[2,] 0.48396257 0.9679251 0.5160374
[3,] 0.33491079 0.6698216 0.6650892
[4,] 0.21749065 0.4349813 0.7825093
[5,] 0.22359123 0.4471825 0.7764088
[6,] 0.76398263 0.4720347 0.2360174
[7,] 0.89562807 0.2087439 0.1043719
[8,] 0.87747770 0.2450446 0.1225223
[9,] 0.82760591 0.3447882 0.1723941
[10,] 0.75987290 0.4802542 0.2401271
[11,] 0.71484400 0.5703120 0.2851560
[12,] 0.64570421 0.7085916 0.3542958
[13,] 0.65015636 0.6996873 0.3498436
[14,] 0.60640589 0.7871882 0.3935941
[15,] 0.55130942 0.8973812 0.4486906
[16,] 0.50059731 0.9988054 0.4994027
[17,] 0.47171305 0.9434261 0.5282869
[18,] 0.38246809 0.7649362 0.6175319
[19,] 0.35134942 0.7026988 0.6486506
[20,] 0.31236315 0.6247263 0.6876369
[21,] 0.37992714 0.7598543 0.6200729
[22,] 0.31688894 0.6337779 0.6831111
[23,] 0.52771974 0.9445605 0.4722803
[24,] 0.48432868 0.9686574 0.5156713
[25,] 0.55530591 0.8893882 0.4446941
[26,] 0.45968627 0.9193725 0.5403137
[27,] 0.37520499 0.7504100 0.6247950
[28,] 0.62476195 0.7504761 0.3752381
[29,] 0.65831571 0.6833686 0.3416843
[30,] 0.68305606 0.6338879 0.3169439
[31,] 0.84440518 0.3111896 0.1555948
[32,] 0.87309899 0.2538020 0.1269010
[33,] 0.78383251 0.4323350 0.2161675
[34,] 0.69514802 0.6097040 0.3048520
[35,] 0.57179190 0.8564162 0.4282081
> postscript(file="/var/www/rcomp/tmp/1mhpf1292316812.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/2x8oi1292316812.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/3x8oi1292316812.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/4x8oi1292316812.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/5x8oi1292316812.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 = 46
Frequency = 1
1 2 3 4 5 6
-0.14774203 1.50938149 -0.26447422 0.86453377 0.45739514 0.88313534
7 8 9 10 11 12
-0.61495802 0.27835245 0.37139712 -0.83664137 -2.76196841 1.55780830
13 14 15 16 17 18
-0.77315026 0.16279541 -0.17612517 0.33469966 -0.35316406 1.03248126
19 20 21 22 23 24
-0.69211875 0.56828959 -0.72900312 -0.84213555 -0.03410285 -0.71902145
25 26 27 28 29 30
0.68965459 -1.27770163 -0.33012211 1.98431594 0.73240007 0.91445696
31 32 33 34 35 36
-0.08959504 -0.09545614 -1.23243961 0.69268023 -0.62344951 0.07654721
37 38 39 40 41 42
-0.42087651 -0.60383192 -0.73242171 -0.73797204 -0.06524782 -0.04886102
43 44 45 46
-0.80181469 0.10711828 -0.28091899 3.06787117
> postscript(file="/var/www/rcomp/tmp/6qh631292316812.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 = 46
Frequency = 1
lag(myerror, k = 1) myerror
0 -0.14774203 NA
1 1.50938149 -0.14774203
2 -0.26447422 1.50938149
3 0.86453377 -0.26447422
4 0.45739514 0.86453377
5 0.88313534 0.45739514
6 -0.61495802 0.88313534
7 0.27835245 -0.61495802
8 0.37139712 0.27835245
9 -0.83664137 0.37139712
10 -2.76196841 -0.83664137
11 1.55780830 -2.76196841
12 -0.77315026 1.55780830
13 0.16279541 -0.77315026
14 -0.17612517 0.16279541
15 0.33469966 -0.17612517
16 -0.35316406 0.33469966
17 1.03248126 -0.35316406
18 -0.69211875 1.03248126
19 0.56828959 -0.69211875
20 -0.72900312 0.56828959
21 -0.84213555 -0.72900312
22 -0.03410285 -0.84213555
23 -0.71902145 -0.03410285
24 0.68965459 -0.71902145
25 -1.27770163 0.68965459
26 -0.33012211 -1.27770163
27 1.98431594 -0.33012211
28 0.73240007 1.98431594
29 0.91445696 0.73240007
30 -0.08959504 0.91445696
31 -0.09545614 -0.08959504
32 -1.23243961 -0.09545614
33 0.69268023 -1.23243961
34 -0.62344951 0.69268023
35 0.07654721 -0.62344951
36 -0.42087651 0.07654721
37 -0.60383192 -0.42087651
38 -0.73242171 -0.60383192
39 -0.73797204 -0.73242171
40 -0.06524782 -0.73797204
41 -0.04886102 -0.06524782
42 -0.80181469 -0.04886102
43 0.10711828 -0.80181469
44 -0.28091899 0.10711828
45 3.06787117 -0.28091899
46 NA 3.06787117
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 1.50938149 -0.14774203
[2,] -0.26447422 1.50938149
[3,] 0.86453377 -0.26447422
[4,] 0.45739514 0.86453377
[5,] 0.88313534 0.45739514
[6,] -0.61495802 0.88313534
[7,] 0.27835245 -0.61495802
[8,] 0.37139712 0.27835245
[9,] -0.83664137 0.37139712
[10,] -2.76196841 -0.83664137
[11,] 1.55780830 -2.76196841
[12,] -0.77315026 1.55780830
[13,] 0.16279541 -0.77315026
[14,] -0.17612517 0.16279541
[15,] 0.33469966 -0.17612517
[16,] -0.35316406 0.33469966
[17,] 1.03248126 -0.35316406
[18,] -0.69211875 1.03248126
[19,] 0.56828959 -0.69211875
[20,] -0.72900312 0.56828959
[21,] -0.84213555 -0.72900312
[22,] -0.03410285 -0.84213555
[23,] -0.71902145 -0.03410285
[24,] 0.68965459 -0.71902145
[25,] -1.27770163 0.68965459
[26,] -0.33012211 -1.27770163
[27,] 1.98431594 -0.33012211
[28,] 0.73240007 1.98431594
[29,] 0.91445696 0.73240007
[30,] -0.08959504 0.91445696
[31,] -0.09545614 -0.08959504
[32,] -1.23243961 -0.09545614
[33,] 0.69268023 -1.23243961
[34,] -0.62344951 0.69268023
[35,] 0.07654721 -0.62344951
[36,] -0.42087651 0.07654721
[37,] -0.60383192 -0.42087651
[38,] -0.73242171 -0.60383192
[39,] -0.73797204 -0.73242171
[40,] -0.06524782 -0.73797204
[41,] -0.04886102 -0.06524782
[42,] -0.80181469 -0.04886102
[43,] 0.10711828 -0.80181469
[44,] -0.28091899 0.10711828
[45,] 3.06787117 -0.28091899
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 1.50938149 -0.14774203
2 -0.26447422 1.50938149
3 0.86453377 -0.26447422
4 0.45739514 0.86453377
5 0.88313534 0.45739514
6 -0.61495802 0.88313534
7 0.27835245 -0.61495802
8 0.37139712 0.27835245
9 -0.83664137 0.37139712
10 -2.76196841 -0.83664137
11 1.55780830 -2.76196841
12 -0.77315026 1.55780830
13 0.16279541 -0.77315026
14 -0.17612517 0.16279541
15 0.33469966 -0.17612517
16 -0.35316406 0.33469966
17 1.03248126 -0.35316406
18 -0.69211875 1.03248126
19 0.56828959 -0.69211875
20 -0.72900312 0.56828959
21 -0.84213555 -0.72900312
22 -0.03410285 -0.84213555
23 -0.71902145 -0.03410285
24 0.68965459 -0.71902145
25 -1.27770163 0.68965459
26 -0.33012211 -1.27770163
27 1.98431594 -0.33012211
28 0.73240007 1.98431594
29 0.91445696 0.73240007
30 -0.08959504 0.91445696
31 -0.09545614 -0.08959504
32 -1.23243961 -0.09545614
33 0.69268023 -1.23243961
34 -0.62344951 0.69268023
35 0.07654721 -0.62344951
36 -0.42087651 0.07654721
37 -0.60383192 -0.42087651
38 -0.73242171 -0.60383192
39 -0.73797204 -0.73242171
40 -0.06524782 -0.73797204
41 -0.04886102 -0.06524782
42 -0.80181469 -0.04886102
43 0.10711828 -0.80181469
44 -0.28091899 0.10711828
45 3.06787117 -0.28091899
> 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/rcomp/tmp/71qn61292316812.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/81qn61292316812.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/9bim91292316812.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/rcomp/tmp/10m9mu1292316812.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/rcomp/tmp/11f03f1292316812.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/rcomp/tmp/12ij131292316812.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/rcomp/tmp/13pkgx1292316812.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/rcomp/tmp/14akf21292316812.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/rcomp/tmp/153ten1292316812.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/rcomp/tmp/16z3uw1292316812.tab")
+ }
>
> try(system("convert tmp/1mhpf1292316812.ps tmp/1mhpf1292316812.png",intern=TRUE))
character(0)
> try(system("convert tmp/2x8oi1292316812.ps tmp/2x8oi1292316812.png",intern=TRUE))
character(0)
> try(system("convert tmp/3x8oi1292316812.ps tmp/3x8oi1292316812.png",intern=TRUE))
character(0)
> try(system("convert tmp/4x8oi1292316812.ps tmp/4x8oi1292316812.png",intern=TRUE))
character(0)
> try(system("convert tmp/5x8oi1292316812.ps tmp/5x8oi1292316812.png",intern=TRUE))
character(0)
> try(system("convert tmp/6qh631292316812.ps tmp/6qh631292316812.png",intern=TRUE))
character(0)
> try(system("convert tmp/71qn61292316812.ps tmp/71qn61292316812.png",intern=TRUE))
character(0)
> try(system("convert tmp/81qn61292316812.ps tmp/81qn61292316812.png",intern=TRUE))
character(0)
> try(system("convert tmp/9bim91292316812.ps tmp/9bim91292316812.png",intern=TRUE))
character(0)
> try(system("convert tmp/10m9mu1292316812.ps tmp/10m9mu1292316812.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
3.040 1.830 4.923