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.
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(159129,0,157928,0,147768,0,137507,0,136919,0,136151,0,133001,0,125554,0,119647,0,114158,0,116193,0,152803,0,161761,0,160942,0,149470,0,139208,0,134588,0,130322,0,126611,0,122401,0,117352,0,112135,0,112879,0,148729,0,157230,0,157221,0,146681,0,136524,0,132111,0,125326,1,122716,1,116615,1,113719,1,110737,1,112093,1,143565,1,149946,1,149147,1,134339,1,122683,1,115614,1,116566,1,111272,1,104609,1,101802,1,94542,1,93051,1,124129,1,130374,1,123946,1,114971,1,105531,1,104919,1,104782,0,101281,0,94545,0,93248,0,84031,0,87486,0,115867,0,120327,0),dim=c(2,61),dimnames=list(c('jonger_dan_25','plan'),1:61))
> y <- array(NA,dim=c(2,61),dimnames=list(c('jonger_dan_25','plan'),1:61))
> 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
jonger_dan_25 plan
1 159129 0
2 157928 0
3 147768 0
4 137507 0
5 136919 0
6 136151 0
7 133001 0
8 125554 0
9 119647 0
10 114158 0
11 116193 0
12 152803 0
13 161761 0
14 160942 0
15 149470 0
16 139208 0
17 134588 0
18 130322 0
19 126611 0
20 122401 0
21 117352 0
22 112135 0
23 112879 0
24 148729 0
25 157230 0
26 157221 0
27 146681 0
28 136524 0
29 132111 0
30 125326 1
31 122716 1
32 116615 1
33 113719 1
34 110737 1
35 112093 1
36 143565 1
37 149946 1
38 149147 1
39 134339 1
40 122683 1
41 115614 1
42 116566 1
43 111272 1
44 104609 1
45 101802 1
46 94542 1
47 93051 1
48 124129 1
49 130374 1
50 123946 1
51 114971 1
52 105531 1
53 104919 1
54 104782 0
55 101281 0
56 94545 0
57 93248 0
58 84031 0
59 87486 0
60 115867 0
61 120327 0
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) plan
129311 -10885
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-45280 -13118 -1811 11948 32450
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 129310 3192 40.511 <2e-16 ***
plan -10885 5089 -2.139 0.0366 *
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 19420 on 59 degrees of freedom
Multiple R-squared: 0.07197, Adjusted R-squared: 0.05624
F-statistic: 4.575 on 1 and 59 DF, p-value: 0.03658
> 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,] 0.2562968 0.5125936 0.74370321
[2,] 0.1801091 0.3602182 0.81989092
[3,] 0.1376181 0.2752361 0.86238194
[4,] 0.1496662 0.2993324 0.85033382
[5,] 0.1897199 0.3794399 0.81028006
[6,] 0.2545584 0.5091168 0.74544161
[7,] 0.2608240 0.5216480 0.73917601
[8,] 0.2613302 0.5226603 0.73866983
[9,] 0.3547873 0.7095745 0.64521274
[10,] 0.4326985 0.8653971 0.56730147
[11,] 0.3991285 0.7982570 0.60087149
[12,] 0.3310660 0.6621321 0.66893397
[13,] 0.2699367 0.5398735 0.73006327
[14,] 0.2222038 0.4444076 0.77779622
[15,] 0.1884091 0.3768181 0.81159094
[16,] 0.1698149 0.3396297 0.83018515
[17,] 0.1698785 0.3397570 0.83012152
[18,] 0.1915936 0.3831872 0.80840642
[19,] 0.1988120 0.3976240 0.80118798
[20,] 0.2082553 0.4165105 0.79174474
[21,] 0.3115753 0.6231506 0.68842470
[22,] 0.4804988 0.9609976 0.51950119
[23,] 0.5808277 0.8383446 0.41917232
[24,] 0.6317960 0.7364080 0.36820400
[25,] 0.6917756 0.6164488 0.30822442
[26,] 0.6296769 0.7406462 0.37032308
[27,] 0.5600795 0.8798410 0.43992049
[28,] 0.4901399 0.9802798 0.50986010
[29,] 0.4245136 0.8490271 0.57548643
[30,] 0.3691487 0.7382974 0.63085131
[31,] 0.3095411 0.6190822 0.69045890
[32,] 0.4218504 0.8437008 0.57814960
[33,] 0.6580367 0.6839267 0.34196334
[34,] 0.8699456 0.2601088 0.13005439
[35,] 0.9035230 0.1929540 0.09647701
[36,] 0.8865696 0.2268608 0.11343041
[37,] 0.8532100 0.2935801 0.14679004
[38,] 0.8140771 0.3718457 0.18592286
[39,] 0.7653524 0.4692951 0.23464757
[40,] 0.7300758 0.5398485 0.26992424
[41,] 0.7086903 0.5826194 0.29130968
[42,] 0.7710717 0.4578565 0.22892826
[43,] 0.8698289 0.2603423 0.13017114
[44,] 0.8257590 0.3484820 0.17424099
[45,] 0.8405279 0.3189442 0.15947208
[46,] 0.8299557 0.3400887 0.17004434
[47,] 0.7741941 0.4516117 0.22580587
[48,] 0.6821608 0.6356783 0.31783916
[49,] 0.5704982 0.8590035 0.42950175
[50,] 0.4936004 0.9872008 0.50639959
[51,] 0.3950152 0.7900304 0.60498481
[52,] 0.3024075 0.6048151 0.69759247
> postscript(file="/var/www/html/rcomp/tmp/13f3a1227720969.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2f1xa1227720969.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/36u921227720969.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/44lqv1227720969.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5dkoh1227720969.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 = 61
Frequency = 1
1 2 3 4 5 6 7
29818.459 28617.459 18457.459 8196.459 7608.459 6840.459 3690.459
8 9 10 11 12 13 14
-3756.541 -9663.541 -15152.541 -13117.541 23492.459 32450.459 31631.459
15 16 17 18 19 20 21
20159.459 9897.459 5277.459 1011.459 -2699.541 -6909.541 -11958.541
22 23 24 25 26 27 28
-17175.541 -16431.541 19418.459 27919.459 27910.459 17370.459 7213.459
29 30 31 32 33 34 35
2800.459 6900.500 4290.500 -1810.500 -4706.500 -7688.500 -6332.500
36 37 38 39 40 41 42
25139.500 31520.500 30721.500 15913.500 4257.500 -2811.500 -1859.500
43 44 45 46 47 48 49
-7153.500 -13816.500 -16623.500 -23883.500 -25374.500 5703.500 11948.500
50 51 52 53 54 55 56
5520.500 -3454.500 -12894.500 -13506.500 -24528.541 -28029.541 -34765.541
57 58 59 60 61
-36062.541 -45279.541 -41824.541 -13443.541 -8983.541
> postscript(file="/var/www/html/rcomp/tmp/6d5i01227720969.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 = 61
Frequency = 1
lag(myerror, k = 1) myerror
0 29818.459 NA
1 28617.459 29818.459
2 18457.459 28617.459
3 8196.459 18457.459
4 7608.459 8196.459
5 6840.459 7608.459
6 3690.459 6840.459
7 -3756.541 3690.459
8 -9663.541 -3756.541
9 -15152.541 -9663.541
10 -13117.541 -15152.541
11 23492.459 -13117.541
12 32450.459 23492.459
13 31631.459 32450.459
14 20159.459 31631.459
15 9897.459 20159.459
16 5277.459 9897.459
17 1011.459 5277.459
18 -2699.541 1011.459
19 -6909.541 -2699.541
20 -11958.541 -6909.541
21 -17175.541 -11958.541
22 -16431.541 -17175.541
23 19418.459 -16431.541
24 27919.459 19418.459
25 27910.459 27919.459
26 17370.459 27910.459
27 7213.459 17370.459
28 2800.459 7213.459
29 6900.500 2800.459
30 4290.500 6900.500
31 -1810.500 4290.500
32 -4706.500 -1810.500
33 -7688.500 -4706.500
34 -6332.500 -7688.500
35 25139.500 -6332.500
36 31520.500 25139.500
37 30721.500 31520.500
38 15913.500 30721.500
39 4257.500 15913.500
40 -2811.500 4257.500
41 -1859.500 -2811.500
42 -7153.500 -1859.500
43 -13816.500 -7153.500
44 -16623.500 -13816.500
45 -23883.500 -16623.500
46 -25374.500 -23883.500
47 5703.500 -25374.500
48 11948.500 5703.500
49 5520.500 11948.500
50 -3454.500 5520.500
51 -12894.500 -3454.500
52 -13506.500 -12894.500
53 -24528.541 -13506.500
54 -28029.541 -24528.541
55 -34765.541 -28029.541
56 -36062.541 -34765.541
57 -45279.541 -36062.541
58 -41824.541 -45279.541
59 -13443.541 -41824.541
60 -8983.541 -13443.541
61 NA -8983.541
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 28617.459 29818.459
[2,] 18457.459 28617.459
[3,] 8196.459 18457.459
[4,] 7608.459 8196.459
[5,] 6840.459 7608.459
[6,] 3690.459 6840.459
[7,] -3756.541 3690.459
[8,] -9663.541 -3756.541
[9,] -15152.541 -9663.541
[10,] -13117.541 -15152.541
[11,] 23492.459 -13117.541
[12,] 32450.459 23492.459
[13,] 31631.459 32450.459
[14,] 20159.459 31631.459
[15,] 9897.459 20159.459
[16,] 5277.459 9897.459
[17,] 1011.459 5277.459
[18,] -2699.541 1011.459
[19,] -6909.541 -2699.541
[20,] -11958.541 -6909.541
[21,] -17175.541 -11958.541
[22,] -16431.541 -17175.541
[23,] 19418.459 -16431.541
[24,] 27919.459 19418.459
[25,] 27910.459 27919.459
[26,] 17370.459 27910.459
[27,] 7213.459 17370.459
[28,] 2800.459 7213.459
[29,] 6900.500 2800.459
[30,] 4290.500 6900.500
[31,] -1810.500 4290.500
[32,] -4706.500 -1810.500
[33,] -7688.500 -4706.500
[34,] -6332.500 -7688.500
[35,] 25139.500 -6332.500
[36,] 31520.500 25139.500
[37,] 30721.500 31520.500
[38,] 15913.500 30721.500
[39,] 4257.500 15913.500
[40,] -2811.500 4257.500
[41,] -1859.500 -2811.500
[42,] -7153.500 -1859.500
[43,] -13816.500 -7153.500
[44,] -16623.500 -13816.500
[45,] -23883.500 -16623.500
[46,] -25374.500 -23883.500
[47,] 5703.500 -25374.500
[48,] 11948.500 5703.500
[49,] 5520.500 11948.500
[50,] -3454.500 5520.500
[51,] -12894.500 -3454.500
[52,] -13506.500 -12894.500
[53,] -24528.541 -13506.500
[54,] -28029.541 -24528.541
[55,] -34765.541 -28029.541
[56,] -36062.541 -34765.541
[57,] -45279.541 -36062.541
[58,] -41824.541 -45279.541
[59,] -13443.541 -41824.541
[60,] -8983.541 -13443.541
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 28617.459 29818.459
2 18457.459 28617.459
3 8196.459 18457.459
4 7608.459 8196.459
5 6840.459 7608.459
6 3690.459 6840.459
7 -3756.541 3690.459
8 -9663.541 -3756.541
9 -15152.541 -9663.541
10 -13117.541 -15152.541
11 23492.459 -13117.541
12 32450.459 23492.459
13 31631.459 32450.459
14 20159.459 31631.459
15 9897.459 20159.459
16 5277.459 9897.459
17 1011.459 5277.459
18 -2699.541 1011.459
19 -6909.541 -2699.541
20 -11958.541 -6909.541
21 -17175.541 -11958.541
22 -16431.541 -17175.541
23 19418.459 -16431.541
24 27919.459 19418.459
25 27910.459 27919.459
26 17370.459 27910.459
27 7213.459 17370.459
28 2800.459 7213.459
29 6900.500 2800.459
30 4290.500 6900.500
31 -1810.500 4290.500
32 -4706.500 -1810.500
33 -7688.500 -4706.500
34 -6332.500 -7688.500
35 25139.500 -6332.500
36 31520.500 25139.500
37 30721.500 31520.500
38 15913.500 30721.500
39 4257.500 15913.500
40 -2811.500 4257.500
41 -1859.500 -2811.500
42 -7153.500 -1859.500
43 -13816.500 -7153.500
44 -16623.500 -13816.500
45 -23883.500 -16623.500
46 -25374.500 -23883.500
47 5703.500 -25374.500
48 11948.500 5703.500
49 5520.500 11948.500
50 -3454.500 5520.500
51 -12894.500 -3454.500
52 -13506.500 -12894.500
53 -24528.541 -13506.500
54 -28029.541 -24528.541
55 -34765.541 -28029.541
56 -36062.541 -34765.541
57 -45279.541 -36062.541
58 -41824.541 -45279.541
59 -13443.541 -41824.541
60 -8983.541 -13443.541
> 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/7riwf1227720969.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8h2911227720969.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9l2jq1227720969.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10k5u31227720969.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11h9ei1227720969.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/12rneq1227720969.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/13uwd11227720969.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/14ac7m1227720969.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/158t4m1227720969.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/16hkpv1227720969.tab")
+ }
>
> system("convert tmp/13f3a1227720969.ps tmp/13f3a1227720969.png")
> system("convert tmp/2f1xa1227720969.ps tmp/2f1xa1227720969.png")
> system("convert tmp/36u921227720969.ps tmp/36u921227720969.png")
> system("convert tmp/44lqv1227720969.ps tmp/44lqv1227720969.png")
> system("convert tmp/5dkoh1227720969.ps tmp/5dkoh1227720969.png")
> system("convert tmp/6d5i01227720969.ps tmp/6d5i01227720969.png")
> system("convert tmp/7riwf1227720969.ps tmp/7riwf1227720969.png")
> system("convert tmp/8h2911227720969.ps tmp/8h2911227720969.png")
> system("convert tmp/9l2jq1227720969.ps tmp/9l2jq1227720969.png")
> system("convert tmp/10k5u31227720969.ps tmp/10k5u31227720969.png")
>
>
> proc.time()
user system elapsed
2.488 1.550 3.036