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.
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(0.301029996
+ ,3
+ ,1.62324929
+ ,0.255272505
+ ,4
+ ,2.79518459
+ ,-0.15490196
+ ,4
+ ,2.255272505
+ ,0.591064607
+ ,1
+ ,1.544068044
+ ,0
+ ,4
+ ,2.593286067
+ ,0.556302501
+ ,1
+ ,1.799340549
+ ,0.146128036
+ ,1
+ ,2.361727836
+ ,0.176091259
+ ,4
+ ,2.049218023
+ ,-0.15490196
+ ,5
+ ,2.44870632
+ ,0.322219295
+ ,1
+ ,1.62324929
+ ,0.612783857
+ ,2
+ ,1.62324929
+ ,0.079181246
+ ,2
+ ,2.079181246
+ ,-0.301029996
+ ,5
+ ,2.170261715
+ ,0.531478917
+ ,2
+ ,1.204119983
+ ,0.176091259
+ ,1
+ ,2.491361694
+ ,0.531478917
+ ,3
+ ,1.447158031
+ ,-0.096910013
+ ,4
+ ,1.832508913
+ ,-0.096910013
+ ,5
+ ,2.526339277
+ ,0.301029996
+ ,1
+ ,1.698970004
+ ,0.278753601
+ ,1
+ ,2.426511261
+ ,0.113943352
+ ,3
+ ,1.278753601
+ ,0.748188027
+ ,1
+ ,1.079181246
+ ,0.491361694
+ ,1
+ ,2.079181246
+ ,0.255272505
+ ,2
+ ,2.146128036
+ ,-0.045757491
+ ,4
+ ,2.230448921
+ ,0.255272505
+ ,2
+ ,1.230448921
+ ,0.278753601
+ ,4
+ ,2.06069784
+ ,-0.045757491
+ ,5
+ ,1.491361694
+ ,0.414973348
+ ,3
+ ,1.322219295
+ ,0.380211242
+ ,1
+ ,1.716003344
+ ,0.079181246
+ ,2
+ ,2.214843848
+ ,-0.045757491
+ ,2
+ ,2.352182518
+ ,-0.301029996
+ ,3
+ ,2.352182518
+ ,-0.22184875
+ ,5
+ ,2.178976947
+ ,0.361727836
+ ,2
+ ,1.77815125
+ ,-0.301029996
+ ,3
+ ,2.301029996
+ ,0.414973348
+ ,2
+ ,1.662757832
+ ,-0.22184875
+ ,4
+ ,2.322219295
+ ,0.819543936
+ ,1
+ ,1.146128036)
+ ,dim=c(3
+ ,39)
+ ,dimnames=list(c('Log_PS'
+ ,'D'
+ ,'Log_tg')
+ ,1:39))
> y <- array(NA,dim=c(3,39),dimnames=list(c('Log_PS','D','Log_tg'),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
> 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
Log_PS D Log_tg
1 0.30103000 3 1.623249
2 0.25527250 4 2.795185
3 -0.15490196 4 2.255273
4 0.59106461 1 1.544068
5 0.00000000 4 2.593286
6 0.55630250 1 1.799341
7 0.14612804 1 2.361728
8 0.17609126 4 2.049218
9 -0.15490196 5 2.448706
10 0.32221930 1 1.623249
11 0.61278386 2 1.623249
12 0.07918125 2 2.079181
13 -0.30103000 5 2.170262
14 0.53147892 2 1.204120
15 0.17609126 1 2.491362
16 0.53147892 3 1.447158
17 -0.09691001 4 1.832509
18 -0.09691001 5 2.526339
19 0.30103000 1 1.698970
20 0.27875360 1 2.426511
21 0.11394335 3 1.278754
22 0.74818803 1 1.079181
23 0.49136169 1 2.079181
24 0.25527250 2 2.146128
25 -0.04575749 4 2.230449
26 0.25527250 2 1.230449
27 0.27875360 4 2.060698
28 -0.04575749 5 1.491362
29 0.41497335 3 1.322219
30 0.38021124 1 1.716003
31 0.07918125 2 2.214844
32 -0.04575749 2 2.352183
33 -0.30103000 3 2.352183
34 -0.22184875 5 2.178977
35 0.36172784 2 1.778151
36 -0.30103000 3 2.301030
37 0.41497335 2 1.662758
38 -0.22184875 4 2.322219
39 0.81954394 1 1.146128
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) D Log_tg
1.0745 -0.1105 -0.3035
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-0.34555 -0.14523 0.04349 0.12512 0.47125
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1.07451 0.12875 8.346 6.16e-10 ***
D -0.11051 0.02219 -4.980 1.60e-05 ***
Log_tg -0.30354 0.06890 -4.405 9.09e-05 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.1818 on 36 degrees of freedom
Multiple R-squared: 0.6546, Adjusted R-squared: 0.6354
F-statistic: 34.12 on 2 and 36 DF, p-value: 4.888e-09
> 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,] 0.5979290 0.80414206 0.40207103
[2,] 0.8058150 0.38837005 0.19418502
[3,] 0.7209818 0.55803636 0.27901818
[4,] 0.6497648 0.70047042 0.35023521
[5,] 0.6130048 0.77399039 0.38699520
[6,] 0.6901072 0.61978563 0.30989281
[7,] 0.6911997 0.61760069 0.30880034
[8,] 0.7378984 0.52420315 0.26210158
[9,] 0.6517731 0.69645381 0.34822690
[10,] 0.5666430 0.86671405 0.43335703
[11,] 0.5946891 0.81062186 0.40531093
[12,] 0.6108801 0.77823971 0.38911985
[13,] 0.6134411 0.77311783 0.38655892
[14,] 0.5892054 0.82158927 0.41079464
[15,] 0.5034278 0.99314435 0.49657218
[16,] 0.5914000 0.81719994 0.40859997
[17,] 0.5262809 0.94743823 0.47371911
[18,] 0.5343516 0.93129677 0.46564839
[19,] 0.4829137 0.96582748 0.51708626
[20,] 0.4143011 0.82860226 0.58569887
[21,] 0.6028548 0.79429032 0.39714516
[22,] 0.9605582 0.07888351 0.03944176
[23,] 0.9705527 0.05889463 0.02944732
[24,] 0.9617218 0.07655637 0.03827818
[25,] 0.9327455 0.13450903 0.06725451
[26,] 0.9136053 0.17278945 0.08639473
[27,] 0.9363536 0.12729272 0.06364636
[28,] 0.8803570 0.23928601 0.11964301
> postscript(file="/var/www/rcomp/tmp/19aw21291923292.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/29aw21291923292.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/311d51291923292.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/411d51291923292.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/511d51291923292.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 = 39
Frequency = 1
1 2 3 4 5 6
0.050773408 0.471254332 -0.102804437 0.095752433 0.154697777 0.138475455
7 8 9 10 11 12
-0.100992610 0.165643238 0.066420745 -0.149058293 0.252016769 -0.143192772
13 14 15 16 17 18
-0.164226052 0.043489793 -0.031680472 0.227771787 -0.173137672 0.147977311
19 20 21 22 23 24
-0.147263412 0.051297243 -0.240881068 0.111764641 0.158477176 0.053219440
25 26 27 28 29 30
-0.001194890 -0.224724763 0.271790151 -0.115026091 0.073342456 -0.062911885
31 32 33 34 35 36
-0.102013899 -0.185265012 -0.330027017 -0.082399394 0.047979514 -0.345553796
37 38 39
0.066198638 -0.149430274 0.203441502
> postscript(file="/var/www/rcomp/tmp/6cac81291923292.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 = 39
Frequency = 1
lag(myerror, k = 1) myerror
0 0.050773408 NA
1 0.471254332 0.050773408
2 -0.102804437 0.471254332
3 0.095752433 -0.102804437
4 0.154697777 0.095752433
5 0.138475455 0.154697777
6 -0.100992610 0.138475455
7 0.165643238 -0.100992610
8 0.066420745 0.165643238
9 -0.149058293 0.066420745
10 0.252016769 -0.149058293
11 -0.143192772 0.252016769
12 -0.164226052 -0.143192772
13 0.043489793 -0.164226052
14 -0.031680472 0.043489793
15 0.227771787 -0.031680472
16 -0.173137672 0.227771787
17 0.147977311 -0.173137672
18 -0.147263412 0.147977311
19 0.051297243 -0.147263412
20 -0.240881068 0.051297243
21 0.111764641 -0.240881068
22 0.158477176 0.111764641
23 0.053219440 0.158477176
24 -0.001194890 0.053219440
25 -0.224724763 -0.001194890
26 0.271790151 -0.224724763
27 -0.115026091 0.271790151
28 0.073342456 -0.115026091
29 -0.062911885 0.073342456
30 -0.102013899 -0.062911885
31 -0.185265012 -0.102013899
32 -0.330027017 -0.185265012
33 -0.082399394 -0.330027017
34 0.047979514 -0.082399394
35 -0.345553796 0.047979514
36 0.066198638 -0.345553796
37 -0.149430274 0.066198638
38 0.203441502 -0.149430274
39 NA 0.203441502
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 0.471254332 0.050773408
[2,] -0.102804437 0.471254332
[3,] 0.095752433 -0.102804437
[4,] 0.154697777 0.095752433
[5,] 0.138475455 0.154697777
[6,] -0.100992610 0.138475455
[7,] 0.165643238 -0.100992610
[8,] 0.066420745 0.165643238
[9,] -0.149058293 0.066420745
[10,] 0.252016769 -0.149058293
[11,] -0.143192772 0.252016769
[12,] -0.164226052 -0.143192772
[13,] 0.043489793 -0.164226052
[14,] -0.031680472 0.043489793
[15,] 0.227771787 -0.031680472
[16,] -0.173137672 0.227771787
[17,] 0.147977311 -0.173137672
[18,] -0.147263412 0.147977311
[19,] 0.051297243 -0.147263412
[20,] -0.240881068 0.051297243
[21,] 0.111764641 -0.240881068
[22,] 0.158477176 0.111764641
[23,] 0.053219440 0.158477176
[24,] -0.001194890 0.053219440
[25,] -0.224724763 -0.001194890
[26,] 0.271790151 -0.224724763
[27,] -0.115026091 0.271790151
[28,] 0.073342456 -0.115026091
[29,] -0.062911885 0.073342456
[30,] -0.102013899 -0.062911885
[31,] -0.185265012 -0.102013899
[32,] -0.330027017 -0.185265012
[33,] -0.082399394 -0.330027017
[34,] 0.047979514 -0.082399394
[35,] -0.345553796 0.047979514
[36,] 0.066198638 -0.345553796
[37,] -0.149430274 0.066198638
[38,] 0.203441502 -0.149430274
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 0.471254332 0.050773408
2 -0.102804437 0.471254332
3 0.095752433 -0.102804437
4 0.154697777 0.095752433
5 0.138475455 0.154697777
6 -0.100992610 0.138475455
7 0.165643238 -0.100992610
8 0.066420745 0.165643238
9 -0.149058293 0.066420745
10 0.252016769 -0.149058293
11 -0.143192772 0.252016769
12 -0.164226052 -0.143192772
13 0.043489793 -0.164226052
14 -0.031680472 0.043489793
15 0.227771787 -0.031680472
16 -0.173137672 0.227771787
17 0.147977311 -0.173137672
18 -0.147263412 0.147977311
19 0.051297243 -0.147263412
20 -0.240881068 0.051297243
21 0.111764641 -0.240881068
22 0.158477176 0.111764641
23 0.053219440 0.158477176
24 -0.001194890 0.053219440
25 -0.224724763 -0.001194890
26 0.271790151 -0.224724763
27 -0.115026091 0.271790151
28 0.073342456 -0.115026091
29 -0.062911885 0.073342456
30 -0.102013899 -0.062911885
31 -0.185265012 -0.102013899
32 -0.330027017 -0.185265012
33 -0.082399394 -0.330027017
34 0.047979514 -0.082399394
35 -0.345553796 0.047979514
36 0.066198638 -0.345553796
37 -0.149430274 0.066198638
38 0.203441502 -0.149430274
> 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/751tt1291923292.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/851tt1291923292.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/951tt1291923292.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/rcomp/tmp/10xttw1291923292.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11jt9k1291923292.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/12mc881291923292.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/13bdnk1291923292.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/14m4mn1291923292.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/15pm2s1291923292.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/163e0j1291923292.tab")
+ }
>
> try(system("convert tmp/19aw21291923292.ps tmp/19aw21291923292.png",intern=TRUE))
character(0)
> try(system("convert tmp/29aw21291923292.ps tmp/29aw21291923292.png",intern=TRUE))
character(0)
> try(system("convert tmp/311d51291923292.ps tmp/311d51291923292.png",intern=TRUE))
character(0)
> try(system("convert tmp/411d51291923292.ps tmp/411d51291923292.png",intern=TRUE))
character(0)
> try(system("convert tmp/511d51291923292.ps tmp/511d51291923292.png",intern=TRUE))
character(0)
> try(system("convert tmp/6cac81291923292.ps tmp/6cac81291923292.png",intern=TRUE))
character(0)
> try(system("convert tmp/751tt1291923292.ps tmp/751tt1291923292.png",intern=TRUE))
character(0)
> try(system("convert tmp/851tt1291923292.ps tmp/851tt1291923292.png",intern=TRUE))
character(0)
> try(system("convert tmp/951tt1291923292.ps tmp/951tt1291923292.png",intern=TRUE))
character(0)
> try(system("convert tmp/10xttw1291923292.ps tmp/10xttw1291923292.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
2.940 1.570 4.759