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(70.5,4,370,74,67,53.5,315,6166,53,54,65,4,684,68,62,76.5,17,449,80,73,70,8,643,72,68,71,56,1551,74,68,60.5,15,616,61,60,51.5,503,36660,53,50,78,26,403,82,74,76,26,346,79,73,57.5,44,2471,58,57,61,24,7427,63,59,64.5,23,2992,65,64,78.5,38,233,82,75,79,18,609,82,76,61,96,7615,63,59,70,90,370,73,67,70,49,1066,73,67,72,66,600,76,68,64.5,21,4873,66,63,54.5,592,3485,56,53,56.5,73,2364,57,56,64.5,14,1016,67,62,64.5,88,1062,67,62,73,39,480,77,69,72,6,559,75,69,69,32,259,74,64,64,11,1340,67,61,78.5,26,275,82,75,53,23,12550,54,52,75,32,965,78,72,52.5,NA,25229,55,50,68.5,11,4883,71,66,70,5,1189,72,68,70.5,3,226,75,66,76,3,611,79,73,75.5,13,404,79,72,74.5,56,576,78,71,65,29,3096,67,63,54,NA,23193,56,52),dim=c(5,40),dimnames=list(c('Yt','X1t','X2t','X3t','X4t'),1:40))
> y <- array(NA,dim=c(5,40),dimnames=list(c('Yt','X1t','X2t','X3t','X4t'),1:40))
> 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
Yt X1t X2t X3t X4t
1 70.5 4 370 74 67
2 53.5 315 6166 53 54
3 65.0 4 684 68 62
4 76.5 17 449 80 73
5 70.0 8 643 72 68
6 71.0 56 1551 74 68
7 60.5 15 616 61 60
8 51.5 503 36660 53 50
9 78.0 26 403 82 74
10 76.0 26 346 79 73
11 57.5 44 2471 58 57
12 61.0 24 7427 63 59
13 64.5 23 2992 65 64
14 78.5 38 233 82 75
15 79.0 18 609 82 76
16 61.0 96 7615 63 59
17 70.0 90 370 73 67
18 70.0 49 1066 73 67
19 72.0 66 600 76 68
20 64.5 21 4873 66 63
21 54.5 592 3485 56 53
22 56.5 73 2364 57 56
23 64.5 14 1016 67 62
24 64.5 88 1062 67 62
25 73.0 39 480 77 69
26 72.0 6 559 75 69
27 69.0 32 259 74 64
28 64.0 11 1340 67 61
29 78.5 26 275 82 75
30 53.0 23 12550 54 52
31 75.0 32 965 78 72
32 52.5 NA 25229 55 50
33 68.5 11 4883 71 66
34 70.0 5 1189 72 68
35 70.5 3 226 75 66
36 76.0 3 611 79 73
37 75.5 13 404 79 72
38 74.5 56 576 78 71
39 65.0 29 3096 67 63
40 54.0 NA 23193 56 52
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X1t X2t X3t X4t
4.243e-14 -6.369e-18 -1.757e-19 5.000e-01 5.000e-01
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-2.168e-14 -8.027e-15 -5.337e-15 -2.093e-15 2.059e-13
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 4.243e-14 8.863e-14 4.790e-01 0.635
X1t -6.369e-18 6.300e-17 -1.010e-01 0.920
X2t -1.757e-19 1.324e-18 -1.330e-01 0.895
X3t 5.000e-01 3.361e-15 1.488e+14 <2e-16 ***
X4t 5.000e-01 4.400e-15 1.136e+14 <2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 3.687e-14 on 33 degrees of freedom
(2 observations deleted due to missingness)
Multiple R-squared: 1, Adjusted R-squared: 1
F-statistic: 4.141e+29 on 4 and 33 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,] 1.000000e+00 5.257863e-16 2.628931e-16
[2,] 4.282252e-07 8.564503e-07 9.999996e-01
[3,] 6.840324e-04 1.368065e-03 9.993160e-01
[4,] 1.000000e+00 5.583690e-08 2.791845e-08
[5,] 5.538680e-02 1.107736e-01 9.446132e-01
[6,] 5.594328e-09 1.118866e-08 1.000000e+00
[7,] 7.387280e-01 5.225439e-01 2.612720e-01
[8,] 9.776657e-01 4.466859e-02 2.233429e-02
[9,] 8.336046e-05 1.667209e-04 9.999166e-01
[10,] 1.000000e+00 1.374520e-13 6.872599e-14
[11,] 9.999478e-01 1.044790e-04 5.223948e-05
[12,] 6.626709e-04 1.325342e-03 9.993373e-01
[13,] 8.622292e-01 2.755417e-01 1.377708e-01
[14,] 9.017344e-01 1.965311e-01 9.826557e-02
[15,] 9.999999e-01 1.126272e-07 5.631358e-08
[16,] 5.530643e-01 8.938715e-01 4.469357e-01
[17,] 9.436119e-02 1.887224e-01 9.056388e-01
[18,] 8.043660e-01 3.912680e-01 1.956340e-01
[19,] 8.280693e-02 1.656139e-01 9.171931e-01
[20,] 1.000000e+00 6.601182e-08 3.300591e-08
[21,] 9.999999e-01 2.943955e-07 1.471978e-07
[22,] 9.985696e-01 2.860898e-03 1.430449e-03
[23,] 5.869949e-08 1.173990e-07 9.999999e-01
[24,] 9.982942e-01 3.411575e-03 1.705787e-03
[25,] 9.497165e-01 1.005669e-01 5.028346e-02
> postscript(file="/var/www/html/rcomp/tmp/1ony41290524476.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$resid)
Warning message:
In x[, 1] - mysum$resid :
longer object length is not a multiple of shorter object length
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2ony41290524476.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/3ony41290524476.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4zegp1290524476.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5zegp1290524476.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$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 = 38
Frequency = 1
1 2 3 4 5
2.059225e-13 9.652908e-15 -1.085607e-14 3.050170e-15 -4.339545e-15
6 7 8 9 10
-7.364176e-15 -1.624158e-15 5.913886e-15 -8.252840e-15 -3.690086e-15
11 12 13 14 15
-1.398118e-15 -9.524297e-15 3.928014e-15 -4.791591e-15 -2.083011e-15
16 17 18 19 20
-6.643318e-15 -6.734431e-15 -7.821279e-15 -1.213005e-14 -1.492411e-15
21 22 23 24 25
6.219999e-16 -2.121404e-15 -1.004471e-14 -8.023902e-15 -1.225361e-14
26 27 28 29 30
-7.136255e-15 -2.168076e-14 -1.298196e-14 -5.335496e-15 -5.338224e-15
31 33 34 35 36
-3.835008e-15 -5.495831e-15 -2.198676e-15 -1.815107e-14 -5.306919e-15
37 38 39
-8.027929e-15 -7.633267e-15 -4.779126e-15
> postscript(file="/var/www/html/rcomp/tmp/6zegp1290524476.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 = 38
Frequency = 1
lag(myerror, k = 1) myerror
0 2.059225e-13 NA
1 9.652908e-15 2.059225e-13
2 -1.085607e-14 9.652908e-15
3 3.050170e-15 -1.085607e-14
4 -4.339545e-15 3.050170e-15
5 -7.364176e-15 -4.339545e-15
6 -1.624158e-15 -7.364176e-15
7 5.913886e-15 -1.624158e-15
8 -8.252840e-15 5.913886e-15
9 -3.690086e-15 -8.252840e-15
10 -1.398118e-15 -3.690086e-15
11 -9.524297e-15 -1.398118e-15
12 3.928014e-15 -9.524297e-15
13 -4.791591e-15 3.928014e-15
14 -2.083011e-15 -4.791591e-15
15 -6.643318e-15 -2.083011e-15
16 -6.734431e-15 -6.643318e-15
17 -7.821279e-15 -6.734431e-15
18 -1.213005e-14 -7.821279e-15
19 -1.492411e-15 -1.213005e-14
20 6.219999e-16 -1.492411e-15
21 -2.121404e-15 6.219999e-16
22 -1.004471e-14 -2.121404e-15
23 -8.023902e-15 -1.004471e-14
24 -1.225361e-14 -8.023902e-15
25 -7.136255e-15 -1.225361e-14
26 -2.168076e-14 -7.136255e-15
27 -1.298196e-14 -2.168076e-14
28 -5.335496e-15 -1.298196e-14
29 -5.338224e-15 -5.335496e-15
30 -3.835008e-15 -5.338224e-15
31 -5.495831e-15 -3.835008e-15
32 -2.198676e-15 -5.495831e-15
33 -1.815107e-14 -2.198676e-15
34 -5.306919e-15 -1.815107e-14
35 -8.027929e-15 -5.306919e-15
36 -7.633267e-15 -8.027929e-15
37 -4.779126e-15 -7.633267e-15
38 NA -4.779126e-15
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 9.652908e-15 2.059225e-13
[2,] -1.085607e-14 9.652908e-15
[3,] 3.050170e-15 -1.085607e-14
[4,] -4.339545e-15 3.050170e-15
[5,] -7.364176e-15 -4.339545e-15
[6,] -1.624158e-15 -7.364176e-15
[7,] 5.913886e-15 -1.624158e-15
[8,] -8.252840e-15 5.913886e-15
[9,] -3.690086e-15 -8.252840e-15
[10,] -1.398118e-15 -3.690086e-15
[11,] -9.524297e-15 -1.398118e-15
[12,] 3.928014e-15 -9.524297e-15
[13,] -4.791591e-15 3.928014e-15
[14,] -2.083011e-15 -4.791591e-15
[15,] -6.643318e-15 -2.083011e-15
[16,] -6.734431e-15 -6.643318e-15
[17,] -7.821279e-15 -6.734431e-15
[18,] -1.213005e-14 -7.821279e-15
[19,] -1.492411e-15 -1.213005e-14
[20,] 6.219999e-16 -1.492411e-15
[21,] -2.121404e-15 6.219999e-16
[22,] -1.004471e-14 -2.121404e-15
[23,] -8.023902e-15 -1.004471e-14
[24,] -1.225361e-14 -8.023902e-15
[25,] -7.136255e-15 -1.225361e-14
[26,] -2.168076e-14 -7.136255e-15
[27,] -1.298196e-14 -2.168076e-14
[28,] -5.335496e-15 -1.298196e-14
[29,] -5.338224e-15 -5.335496e-15
[30,] -3.835008e-15 -5.338224e-15
[31,] -5.495831e-15 -3.835008e-15
[32,] -2.198676e-15 -5.495831e-15
[33,] -1.815107e-14 -2.198676e-15
[34,] -5.306919e-15 -1.815107e-14
[35,] -8.027929e-15 -5.306919e-15
[36,] -7.633267e-15 -8.027929e-15
[37,] -4.779126e-15 -7.633267e-15
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 9.652908e-15 2.059225e-13
2 -1.085607e-14 9.652908e-15
3 3.050170e-15 -1.085607e-14
4 -4.339545e-15 3.050170e-15
5 -7.364176e-15 -4.339545e-15
6 -1.624158e-15 -7.364176e-15
7 5.913886e-15 -1.624158e-15
8 -8.252840e-15 5.913886e-15
9 -3.690086e-15 -8.252840e-15
10 -1.398118e-15 -3.690086e-15
11 -9.524297e-15 -1.398118e-15
12 3.928014e-15 -9.524297e-15
13 -4.791591e-15 3.928014e-15
14 -2.083011e-15 -4.791591e-15
15 -6.643318e-15 -2.083011e-15
16 -6.734431e-15 -6.643318e-15
17 -7.821279e-15 -6.734431e-15
18 -1.213005e-14 -7.821279e-15
19 -1.492411e-15 -1.213005e-14
20 6.219999e-16 -1.492411e-15
21 -2.121404e-15 6.219999e-16
22 -1.004471e-14 -2.121404e-15
23 -8.023902e-15 -1.004471e-14
24 -1.225361e-14 -8.023902e-15
25 -7.136255e-15 -1.225361e-14
26 -2.168076e-14 -7.136255e-15
27 -1.298196e-14 -2.168076e-14
28 -5.335496e-15 -1.298196e-14
29 -5.338224e-15 -5.335496e-15
30 -3.835008e-15 -5.338224e-15
31 -5.495831e-15 -3.835008e-15
32 -2.198676e-15 -5.495831e-15
33 -1.815107e-14 -2.198676e-15
34 -5.306919e-15 -1.815107e-14
35 -8.027929e-15 -5.306919e-15
36 -7.633267e-15 -8.027929e-15
37 -4.779126e-15 -7.633267e-15
> 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/7sofa1290524476.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/82fev1290524476.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/92fev1290524476.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/10vody1290524476.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$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
+ }
+ }
> myeq <- paste(myeq, ' + e[t]')
> a<-table.row.start(a)
> a<-table.element(a, myeq)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/11ypum1290524476.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Variable',header=TRUE)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
> a<-table.element(a,'2-tail p-value',header=TRUE)
> a<-table.element(a,'1-tail p-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:k){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(mysum$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$coefficients[i,4]/2,6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/122paa1290524476.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple R',1,TRUE)
> a<-table.element(a, sqrt(mysum$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$sigma)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a, sum(myerror*myerror))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/1398p31290524476.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Time or Index', 1, TRUE)
> a<-table.element(a, 'Actuals', 1, TRUE)
> a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
> a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
> a<-table.row.end(a)
> for (i in 1:n) {
+ a<-table.row.start(a)
+ a<-table.element(a,i, 1, TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]-mysum$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/14jhp61290524476.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/1550nc1290524476.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/161a3l1290524476.tab")
+ }
>
> try(system("convert tmp/1ony41290524476.ps tmp/1ony41290524476.png",intern=TRUE))
character(0)
> try(system("convert tmp/2ony41290524476.ps tmp/2ony41290524476.png",intern=TRUE))
character(0)
> try(system("convert tmp/3ony41290524476.ps tmp/3ony41290524476.png",intern=TRUE))
character(0)
> try(system("convert tmp/4zegp1290524476.ps tmp/4zegp1290524476.png",intern=TRUE))
character(0)
> try(system("convert tmp/5zegp1290524476.ps tmp/5zegp1290524476.png",intern=TRUE))
character(0)
> try(system("convert tmp/6zegp1290524476.ps tmp/6zegp1290524476.png",intern=TRUE))
character(0)
> try(system("convert tmp/7sofa1290524476.ps tmp/7sofa1290524476.png",intern=TRUE))
character(0)
> try(system("convert tmp/82fev1290524476.ps tmp/82fev1290524476.png",intern=TRUE))
character(0)
> try(system("convert tmp/92fev1290524476.ps tmp/92fev1290524476.png",intern=TRUE))
character(0)
> try(system("convert tmp/10vody1290524476.ps tmp/10vody1290524476.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
2.270 1.547 5.097