R version 2.8.0 (2008-10-20)
Copyright (C) 2008 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.
Natural language support but running in an English locale
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(0.30103000
+ ,3.00000000
+ ,1.62324929
+ ,0.25527251
+ ,4.00000000
+ ,2.79518459
+ ,-0.15490196
+ ,4.00000000
+ ,2.25527251
+ ,0.59106461
+ ,1.00000000
+ ,1.54406804
+ ,0.00000000
+ ,4.00000000
+ ,2.59328607
+ ,0.55630250
+ ,1.00000000
+ ,1.79934055
+ ,0.14612804
+ ,1.00000000
+ ,2.36172784
+ ,0.17609126
+ ,4.00000000
+ ,2.04921802
+ ,-0.15490196
+ ,5.00000000
+ ,2.44870632
+ ,0.32221929
+ ,1.00000000
+ ,1.62324929
+ ,0.61278386
+ ,2.00000000
+ ,1.62324929
+ ,0.07918125
+ ,2.00000000
+ ,2.07918125
+ ,-0.30103000
+ ,5.00000000
+ ,2.17026172
+ ,0.53147892
+ ,2.00000000
+ ,1.20411998
+ ,0.17609126
+ ,1.00000000
+ ,2.49136169
+ ,0.53147892
+ ,3.00000000
+ ,1.44715803
+ ,-0.09691001
+ ,4.00000000
+ ,1.83250891
+ ,-0.09691001
+ ,5.00000000
+ ,2.52633928
+ ,0.30103000
+ ,1.00000000
+ ,1.69897000
+ ,0.27875360
+ ,1.00000000
+ ,2.42651126
+ ,0.11394335
+ ,3.00000000
+ ,1.27875360
+ ,0.74818803
+ ,1.00000000
+ ,1.07918125
+ ,0.49136169
+ ,1.00000000
+ ,2.07918125
+ ,0.25527251
+ ,2.00000000
+ ,2.14612804
+ ,-0.04575749
+ ,4.00000000
+ ,2.23044892
+ ,0.25527251
+ ,2.00000000
+ ,1.23044892
+ ,0.27875360
+ ,4.00000000
+ ,2.06069784
+ ,-0.04575749
+ ,5.00000000
+ ,1.49136169
+ ,0.41497335
+ ,3.00000000
+ ,1.32221929
+ ,0.38021124
+ ,1.00000000
+ ,1.71600334
+ ,0.07918125
+ ,2.00000000
+ ,2.21484385
+ ,-0.04575749
+ ,2.00000000
+ ,2.35218252
+ ,-0.30103000
+ ,3.00000000
+ ,2.35218252
+ ,-0.22184875
+ ,5.00000000
+ ,2.17897695
+ ,0.36172784
+ ,2.00000000
+ ,1.77815125
+ ,-0.30103000
+ ,3.00000000
+ ,2.30103000
+ ,0.41497335
+ ,2.00000000
+ ,1.66275783
+ ,-0.22184875
+ ,4.00000000
+ ,2.32221929
+ ,0.81954394
+ ,1.00000000
+ ,1.14612804)
+ ,dim=c(3
+ ,39)
+ ,dimnames=list(c('LogPS'
+ ,'D'
+ ,'LogTg')
+ ,1:39))
> y <- array(NA,dim=c(3,39),dimnames=list(c('LogPS','D','LogTg'),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
LogPS D LogTg
1 0.30103000 3 1.623249
2 0.25527251 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 0.32221929 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 0.25527251 2 2.146128
25 -0.04575749 4 2.230449
26 0.25527251 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 LogTg
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 ***
LogTg -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 0.80414204 0.40207102
[2,] 0.8058150 0.38837005 0.19418503
[3,] 0.7209818 0.55803637 0.27901819
[4,] 0.6497648 0.70047043 0.35023521
[5,] 0.6130048 0.77399039 0.38699519
[6,] 0.6901072 0.61978562 0.30989281
[7,] 0.6911997 0.61760069 0.30880035
[8,] 0.7378984 0.52420315 0.26210158
[9,] 0.6517731 0.69645381 0.34822690
[10,] 0.5666430 0.86671405 0.43335702
[11,] 0.5946891 0.81062185 0.40531093
[12,] 0.6108801 0.77823971 0.38911986
[13,] 0.6134411 0.77311783 0.38655891
[14,] 0.5892054 0.82158927 0.41079464
[15,] 0.5034278 0.99314435 0.49657218
[16,] 0.5914000 0.81719993 0.40859997
[17,] 0.5262809 0.94743822 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 0.79429033 0.39714517
[22,] 0.9605582 0.07888352 0.03944176
[23,] 0.9705527 0.05889464 0.02944732
[24,] 0.9617218 0.07655638 0.03827819
[25,] 0.9327455 0.13450904 0.06725452
[26,] 0.9136053 0.17278946 0.08639473
[27,] 0.9363536 0.12729271 0.06364636
[28,] 0.8803570 0.23928600 0.11964300
> postscript(file="/var/www/html/freestat/rcomp/tmp/1prwd1292272203.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/2prwd1292272203.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/html/freestat/rcomp/tmp/3z0dy1292272203.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/4z0dy1292272203.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/5srcj1292272203.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
0.050773410 0.471254336 -0.102804436 0.095752433 0.154697778 0.138475452
7 8 9 10 11 12
-0.100992606 0.165643237 0.066420744 -0.149058300 0.252016770 -0.143192768
13 14 15 16 17 18
-0.164226055 0.043489794 -0.031680473 0.227771789 -0.173137671 0.147977315
19 20 21 22 23 24
-0.147263411 0.051297240 -0.240881072 0.111764643 0.158477172 0.053219445
25 26 27 28 29 30
-0.001194890 -0.224724760 0.271790149 -0.115026092 0.073342455 -0.062911890
31 32 33 34 35 36
-0.102013896 -0.185265011 -0.330027021 -0.082399394 0.047979516 -0.345553799
37 38 39
0.066198638 -0.149430276 0.203441506
> postscript(file="/var/www/html/freestat/rcomp/tmp/63ib41292272203.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 0.050773410 NA
1 0.471254336 0.050773410
2 -0.102804436 0.471254336
3 0.095752433 -0.102804436
4 0.154697778 0.095752433
5 0.138475452 0.154697778
6 -0.100992606 0.138475452
7 0.165643237 -0.100992606
8 0.066420744 0.165643237
9 -0.149058300 0.066420744
10 0.252016770 -0.149058300
11 -0.143192768 0.252016770
12 -0.164226055 -0.143192768
13 0.043489794 -0.164226055
14 -0.031680473 0.043489794
15 0.227771789 -0.031680473
16 -0.173137671 0.227771789
17 0.147977315 -0.173137671
18 -0.147263411 0.147977315
19 0.051297240 -0.147263411
20 -0.240881072 0.051297240
21 0.111764643 -0.240881072
22 0.158477172 0.111764643
23 0.053219445 0.158477172
24 -0.001194890 0.053219445
25 -0.224724760 -0.001194890
26 0.271790149 -0.224724760
27 -0.115026092 0.271790149
28 0.073342455 -0.115026092
29 -0.062911890 0.073342455
30 -0.102013896 -0.062911890
31 -0.185265011 -0.102013896
32 -0.330027021 -0.185265011
33 -0.082399394 -0.330027021
34 0.047979516 -0.082399394
35 -0.345553799 0.047979516
36 0.066198638 -0.345553799
37 -0.149430276 0.066198638
38 0.203441506 -0.149430276
39 NA 0.203441506
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 0.471254336 0.050773410
[2,] -0.102804436 0.471254336
[3,] 0.095752433 -0.102804436
[4,] 0.154697778 0.095752433
[5,] 0.138475452 0.154697778
[6,] -0.100992606 0.138475452
[7,] 0.165643237 -0.100992606
[8,] 0.066420744 0.165643237
[9,] -0.149058300 0.066420744
[10,] 0.252016770 -0.149058300
[11,] -0.143192768 0.252016770
[12,] -0.164226055 -0.143192768
[13,] 0.043489794 -0.164226055
[14,] -0.031680473 0.043489794
[15,] 0.227771789 -0.031680473
[16,] -0.173137671 0.227771789
[17,] 0.147977315 -0.173137671
[18,] -0.147263411 0.147977315
[19,] 0.051297240 -0.147263411
[20,] -0.240881072 0.051297240
[21,] 0.111764643 -0.240881072
[22,] 0.158477172 0.111764643
[23,] 0.053219445 0.158477172
[24,] -0.001194890 0.053219445
[25,] -0.224724760 -0.001194890
[26,] 0.271790149 -0.224724760
[27,] -0.115026092 0.271790149
[28,] 0.073342455 -0.115026092
[29,] -0.062911890 0.073342455
[30,] -0.102013896 -0.062911890
[31,] -0.185265011 -0.102013896
[32,] -0.330027021 -0.185265011
[33,] -0.082399394 -0.330027021
[34,] 0.047979516 -0.082399394
[35,] -0.345553799 0.047979516
[36,] 0.066198638 -0.345553799
[37,] -0.149430276 0.066198638
[38,] 0.203441506 -0.149430276
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 0.471254336 0.050773410
2 -0.102804436 0.471254336
3 0.095752433 -0.102804436
4 0.154697778 0.095752433
5 0.138475452 0.154697778
6 -0.100992606 0.138475452
7 0.165643237 -0.100992606
8 0.066420744 0.165643237
9 -0.149058300 0.066420744
10 0.252016770 -0.149058300
11 -0.143192768 0.252016770
12 -0.164226055 -0.143192768
13 0.043489794 -0.164226055
14 -0.031680473 0.043489794
15 0.227771789 -0.031680473
16 -0.173137671 0.227771789
17 0.147977315 -0.173137671
18 -0.147263411 0.147977315
19 0.051297240 -0.147263411
20 -0.240881072 0.051297240
21 0.111764643 -0.240881072
22 0.158477172 0.111764643
23 0.053219445 0.158477172
24 -0.001194890 0.053219445
25 -0.224724760 -0.001194890
26 0.271790149 -0.224724760
27 -0.115026092 0.271790149
28 0.073342455 -0.115026092
29 -0.062911890 0.073342455
30 -0.102013896 -0.062911890
31 -0.185265011 -0.102013896
32 -0.330027021 -0.185265011
33 -0.082399394 -0.330027021
34 0.047979516 -0.082399394
35 -0.345553799 0.047979516
36 0.066198638 -0.345553799
37 -0.149430276 0.066198638
38 0.203441506 -0.149430276
> 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/freestat/rcomp/tmp/7vrb61292272203.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/8vrb61292272203.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/9o1s91292272203.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/freestat/rcomp/tmp/10o1s91292272203.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/freestat/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/freestat/rcomp/tmp/11r18x1292272203.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/freestat/rcomp/tmp/12ncay1292272204.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/freestat/rcomp/tmp/13uvps1292272204.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/freestat/rcomp/tmp/14n4od1292272204.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/freestat/rcomp/tmp/1585401292272204.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/freestat/rcomp/tmp/164wkr1292272204.tab")
+ }
>
> try(system("convert tmp/1prwd1292272203.ps tmp/1prwd1292272203.png",intern=TRUE))
character(0)
> try(system("convert tmp/2prwd1292272203.ps tmp/2prwd1292272203.png",intern=TRUE))
character(0)
> try(system("convert tmp/3z0dy1292272203.ps tmp/3z0dy1292272203.png",intern=TRUE))
character(0)
> try(system("convert tmp/4z0dy1292272203.ps tmp/4z0dy1292272203.png",intern=TRUE))
character(0)
> try(system("convert tmp/5srcj1292272203.ps tmp/5srcj1292272203.png",intern=TRUE))
character(0)
> try(system("convert tmp/63ib41292272203.ps tmp/63ib41292272203.png",intern=TRUE))
character(0)
> try(system("convert tmp/7vrb61292272203.ps tmp/7vrb61292272203.png",intern=TRUE))
character(0)
> try(system("convert tmp/8vrb61292272203.ps tmp/8vrb61292272203.png",intern=TRUE))
character(0)
> try(system("convert tmp/9o1s91292272203.ps tmp/9o1s91292272203.png",intern=TRUE))
character(0)
> try(system("convert tmp/10o1s91292272203.ps tmp/10o1s91292272203.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
3.766 2.530 4.452