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(147768,0,137507,0,136919,0,136151,1,133001,1,125554,1,119647,0,114158,0,116193,0,152803,0,161761,0,160942,0,149470,0,139208,0,134588,0,130322,1,126611,1,122401,1,117352,0,112135,0,112879,0,148729,0,157230,0,157221,0,146681,0,136524,0,132111,0,125326,1,122716,1,116615,1,113719,0,110737,0,112093,0,143565,0,149946,0,149147,0,134339,0,122683,0,115614,0,116566,1,111272,1,104609,1,101802,0,94542,0,93051,0,124129,0,130374,0,123946,0,114971,0,105531,0,104919,0,104782,1,101281,1,94545,1,93248,0,84031,0,87486,0,115867,0,120327,0,117008,0,108811,0),dim=c(2,61),dimnames=list(c('jonger_dan_25','winter'),1:61))
> y <- array(NA,dim=c(2,61),dimnames=list(c('jonger_dan_25','winter'),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 winter
1 147768 0
2 137507 0
3 136919 0
4 136151 1
5 133001 1
6 125554 1
7 119647 0
8 114158 0
9 116193 0
10 152803 0
11 161761 0
12 160942 0
13 149470 0
14 139208 0
15 134588 0
16 130322 1
17 126611 1
18 122401 1
19 117352 0
20 112135 0
21 112879 0
22 148729 0
23 157230 0
24 157221 0
25 146681 0
26 136524 0
27 132111 0
28 125326 1
29 122716 1
30 116615 1
31 113719 0
32 110737 0
33 112093 0
34 143565 0
35 149946 0
36 149147 0
37 134339 0
38 122683 0
39 115614 0
40 116566 1
41 111272 1
42 104609 1
43 101802 0
44 94542 0
45 93051 0
46 124129 0
47 130374 0
48 123946 0
49 114971 0
50 105531 0
51 104919 0
52 104782 1
53 101281 1
54 94545 1
55 93248 0
56 84031 0
57 87486 0
58 115867 0
59 120327 0
60 117008 0
61 108811 0
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) winter
125298 -7181
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-41267 -13163 -1502 12209 36463
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 125298 2803 44.70 <2e-16 ***
winter -7181 5653 -1.27 0.209
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 19010 on 59 degrees of freedom
Multiple R-squared: 0.02662, Adjusted R-squared: 0.01012
F-statistic: 1.614 on 1 and 59 DF, p-value: 0.2090
> 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,] 0.02527749 0.05055497 0.97472251
[2,] 0.01469423 0.02938845 0.98530577
[3,] 0.06013771 0.12027542 0.93986229
[4,] 0.09902375 0.19804749 0.90097625
[5,] 0.08556507 0.17113013 0.91443493
[6,] 0.14630192 0.29260384 0.85369808
[7,] 0.29824594 0.59649187 0.70175406
[8,] 0.41103596 0.82207192 0.58896404
[9,] 0.37903675 0.75807350 0.62096325
[10,] 0.30553060 0.61106121 0.69446940
[11,] 0.24074543 0.48149085 0.75925457
[12,] 0.18440960 0.36881921 0.81559040
[13,] 0.13859907 0.27719815 0.86140093
[14,] 0.10458212 0.20916425 0.89541788
[15,] 0.11967613 0.23935226 0.88032387
[16,] 0.15415312 0.30830625 0.84584688
[17,] 0.17005762 0.34011524 0.82994238
[18,] 0.17960751 0.35921503 0.82039249
[19,] 0.27165596 0.54331191 0.72834404
[20,] 0.39798844 0.79597689 0.60201156
[21,] 0.42843539 0.85687079 0.57156461
[22,] 0.40120862 0.80241725 0.59879138
[23,] 0.36641780 0.73283561 0.63358220
[24,] 0.32492824 0.64985647 0.67507176
[25,] 0.28677174 0.57354349 0.71322826
[26,] 0.25177207 0.50354413 0.74822793
[27,] 0.26620175 0.53240349 0.73379825
[28,] 0.28833340 0.57666680 0.71166660
[29,] 0.28888259 0.57776518 0.71111741
[30,] 0.33675165 0.67350330 0.66324835
[31,] 0.51131374 0.97737253 0.48868626
[32,] 0.74348816 0.51302368 0.25651184
[33,] 0.80454819 0.39090363 0.19545181
[34,] 0.80355625 0.39288750 0.19644375
[35,] 0.79024156 0.41951688 0.20975844
[36,] 0.76919552 0.46160895 0.23080448
[37,] 0.73853148 0.52293704 0.26146852
[38,] 0.70210854 0.59578292 0.29789146
[39,] 0.72230558 0.55538884 0.27769442
[40,] 0.79170994 0.41658013 0.20829006
[41,] 0.85276177 0.29447646 0.14723823
[42,] 0.84041834 0.31916332 0.15958166
[43,] 0.88789518 0.22420964 0.11210482
[44,] 0.90445688 0.19108625 0.09554312
[45,] 0.88371983 0.23256033 0.11628017
[46,] 0.83892971 0.32214058 0.16107029
[47,] 0.77872449 0.44255102 0.22127551
[48,] 0.70150983 0.59698034 0.29849017
[49,] 0.60579656 0.78840688 0.39420344
[50,] 0.49221354 0.98442708 0.50778646
[51,] 0.43880987 0.87761975 0.56119013
[52,] 0.58554467 0.82891067 0.41445533
> postscript(file="/var/www/html/rcomp/tmp/1rs7y1227723576.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2oeka1227723576.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3ld2s1227723576.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4fthv1227723576.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/54lsp1227723576.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
22469.913 12208.913 11620.913 18034.200 14884.200 7437.200 -5651.087
8 9 10 11 12 13 14
-11140.087 -9105.087 27504.913 36462.913 35643.913 24171.913 13909.913
15 16 17 18 19 20 21
9289.913 12205.200 8494.200 4284.200 -7946.087 -13163.087 -12419.087
22 23 24 25 26 27 28
23430.913 31931.913 31922.913 21382.913 11225.913 6812.913 7209.200
29 30 31 32 33 34 35
4599.200 -1501.800 -11579.087 -14561.087 -13205.087 18266.913 24647.913
36 37 38 39 40 41 42
23848.913 9040.913 -2615.087 -9684.087 -1550.800 -6844.800 -13507.800
43 44 45 46 47 48 49
-23496.087 -30756.087 -32247.087 -1169.087 5075.913 -1352.087 -10327.087
50 51 52 53 54 55 56
-19767.087 -20379.087 -13334.800 -16835.800 -23571.800 -32050.087 -41267.087
57 58 59 60 61
-37812.087 -9431.087 -4971.087 -8290.087 -16487.087
> postscript(file="/var/www/html/rcomp/tmp/6dftk1227723576.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 22469.913 NA
1 12208.913 22469.913
2 11620.913 12208.913
3 18034.200 11620.913
4 14884.200 18034.200
5 7437.200 14884.200
6 -5651.087 7437.200
7 -11140.087 -5651.087
8 -9105.087 -11140.087
9 27504.913 -9105.087
10 36462.913 27504.913
11 35643.913 36462.913
12 24171.913 35643.913
13 13909.913 24171.913
14 9289.913 13909.913
15 12205.200 9289.913
16 8494.200 12205.200
17 4284.200 8494.200
18 -7946.087 4284.200
19 -13163.087 -7946.087
20 -12419.087 -13163.087
21 23430.913 -12419.087
22 31931.913 23430.913
23 31922.913 31931.913
24 21382.913 31922.913
25 11225.913 21382.913
26 6812.913 11225.913
27 7209.200 6812.913
28 4599.200 7209.200
29 -1501.800 4599.200
30 -11579.087 -1501.800
31 -14561.087 -11579.087
32 -13205.087 -14561.087
33 18266.913 -13205.087
34 24647.913 18266.913
35 23848.913 24647.913
36 9040.913 23848.913
37 -2615.087 9040.913
38 -9684.087 -2615.087
39 -1550.800 -9684.087
40 -6844.800 -1550.800
41 -13507.800 -6844.800
42 -23496.087 -13507.800
43 -30756.087 -23496.087
44 -32247.087 -30756.087
45 -1169.087 -32247.087
46 5075.913 -1169.087
47 -1352.087 5075.913
48 -10327.087 -1352.087
49 -19767.087 -10327.087
50 -20379.087 -19767.087
51 -13334.800 -20379.087
52 -16835.800 -13334.800
53 -23571.800 -16835.800
54 -32050.087 -23571.800
55 -41267.087 -32050.087
56 -37812.087 -41267.087
57 -9431.087 -37812.087
58 -4971.087 -9431.087
59 -8290.087 -4971.087
60 -16487.087 -8290.087
61 NA -16487.087
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 12208.913 22469.913
[2,] 11620.913 12208.913
[3,] 18034.200 11620.913
[4,] 14884.200 18034.200
[5,] 7437.200 14884.200
[6,] -5651.087 7437.200
[7,] -11140.087 -5651.087
[8,] -9105.087 -11140.087
[9,] 27504.913 -9105.087
[10,] 36462.913 27504.913
[11,] 35643.913 36462.913
[12,] 24171.913 35643.913
[13,] 13909.913 24171.913
[14,] 9289.913 13909.913
[15,] 12205.200 9289.913
[16,] 8494.200 12205.200
[17,] 4284.200 8494.200
[18,] -7946.087 4284.200
[19,] -13163.087 -7946.087
[20,] -12419.087 -13163.087
[21,] 23430.913 -12419.087
[22,] 31931.913 23430.913
[23,] 31922.913 31931.913
[24,] 21382.913 31922.913
[25,] 11225.913 21382.913
[26,] 6812.913 11225.913
[27,] 7209.200 6812.913
[28,] 4599.200 7209.200
[29,] -1501.800 4599.200
[30,] -11579.087 -1501.800
[31,] -14561.087 -11579.087
[32,] -13205.087 -14561.087
[33,] 18266.913 -13205.087
[34,] 24647.913 18266.913
[35,] 23848.913 24647.913
[36,] 9040.913 23848.913
[37,] -2615.087 9040.913
[38,] -9684.087 -2615.087
[39,] -1550.800 -9684.087
[40,] -6844.800 -1550.800
[41,] -13507.800 -6844.800
[42,] -23496.087 -13507.800
[43,] -30756.087 -23496.087
[44,] -32247.087 -30756.087
[45,] -1169.087 -32247.087
[46,] 5075.913 -1169.087
[47,] -1352.087 5075.913
[48,] -10327.087 -1352.087
[49,] -19767.087 -10327.087
[50,] -20379.087 -19767.087
[51,] -13334.800 -20379.087
[52,] -16835.800 -13334.800
[53,] -23571.800 -16835.800
[54,] -32050.087 -23571.800
[55,] -41267.087 -32050.087
[56,] -37812.087 -41267.087
[57,] -9431.087 -37812.087
[58,] -4971.087 -9431.087
[59,] -8290.087 -4971.087
[60,] -16487.087 -8290.087
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 12208.913 22469.913
2 11620.913 12208.913
3 18034.200 11620.913
4 14884.200 18034.200
5 7437.200 14884.200
6 -5651.087 7437.200
7 -11140.087 -5651.087
8 -9105.087 -11140.087
9 27504.913 -9105.087
10 36462.913 27504.913
11 35643.913 36462.913
12 24171.913 35643.913
13 13909.913 24171.913
14 9289.913 13909.913
15 12205.200 9289.913
16 8494.200 12205.200
17 4284.200 8494.200
18 -7946.087 4284.200
19 -13163.087 -7946.087
20 -12419.087 -13163.087
21 23430.913 -12419.087
22 31931.913 23430.913
23 31922.913 31931.913
24 21382.913 31922.913
25 11225.913 21382.913
26 6812.913 11225.913
27 7209.200 6812.913
28 4599.200 7209.200
29 -1501.800 4599.200
30 -11579.087 -1501.800
31 -14561.087 -11579.087
32 -13205.087 -14561.087
33 18266.913 -13205.087
34 24647.913 18266.913
35 23848.913 24647.913
36 9040.913 23848.913
37 -2615.087 9040.913
38 -9684.087 -2615.087
39 -1550.800 -9684.087
40 -6844.800 -1550.800
41 -13507.800 -6844.800
42 -23496.087 -13507.800
43 -30756.087 -23496.087
44 -32247.087 -30756.087
45 -1169.087 -32247.087
46 5075.913 -1169.087
47 -1352.087 5075.913
48 -10327.087 -1352.087
49 -19767.087 -10327.087
50 -20379.087 -19767.087
51 -13334.800 -20379.087
52 -16835.800 -13334.800
53 -23571.800 -16835.800
54 -32050.087 -23571.800
55 -41267.087 -32050.087
56 -37812.087 -41267.087
57 -9431.087 -37812.087
58 -4971.087 -9431.087
59 -8290.087 -4971.087
60 -16487.087 -8290.087
> 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/7bswm1227723576.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8txmh1227723576.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/99hu21227723576.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10f6191227723576.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11vj0e1227723576.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/12oelf1227723576.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/132pey1227723576.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/14d3lp1227723576.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/1583nn1227723576.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/16lgmh1227723577.tab")
+ }
>
> system("convert tmp/1rs7y1227723576.ps tmp/1rs7y1227723576.png")
> system("convert tmp/2oeka1227723576.ps tmp/2oeka1227723576.png")
> system("convert tmp/3ld2s1227723576.ps tmp/3ld2s1227723576.png")
> system("convert tmp/4fthv1227723576.ps tmp/4fthv1227723576.png")
> system("convert tmp/54lsp1227723576.ps tmp/54lsp1227723576.png")
> system("convert tmp/6dftk1227723576.ps tmp/6dftk1227723576.png")
> system("convert tmp/7bswm1227723576.ps tmp/7bswm1227723576.png")
> system("convert tmp/8txmh1227723576.ps tmp/8txmh1227723576.png")
> system("convert tmp/99hu21227723576.ps tmp/99hu21227723576.png")
> system("convert tmp/10f6191227723576.ps tmp/10f6191227723576.png")
>
>
> proc.time()
user system elapsed
2.484 1.562 2.950