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(147768,0,137507,0,136919,0,136151,0,133001,0,125554,0,119647,0,114158,0,116193,0,152803,0,161761,0,160942,0,149470,0,139208,0,134588,0,130322,0,126611,0,122401,0,117352,0,112135,0,112879,0,148729,0,157230,0,157221,0,146681,1,136524,1,132111,1,125326,1,122716,1,116615,1,113719,1,110737,1,112093,1,143565,1,149946,1,149147,1,134339,1,122683,1,115614,1,116566,1,111272,1,104609,1,101802,1,94542,1,93051,1,124129,1,130374,1,123946,1,114971,1,105531,0,104919,0,104782,0,101281,0,94545,0,93248,0,84031,0,87486,0,115867,0,120327,0,117008,0,108811,0),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 147768 0
2 137507 0
3 136919 0
4 136151 0
5 133001 0
6 125554 0
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 0
17 126611 0
18 122401 0
19 117352 0
20 112135 0
21 112879 0
22 148729 0
23 157230 0
24 157221 0
25 146681 1
26 136524 1
27 132111 1
28 125326 1
29 122716 1
30 116615 1
31 113719 1
32 110737 1
33 112093 1
34 143565 1
35 149946 1
36 149147 1
37 134339 1
38 122683 1
39 115614 1
40 116566 1
41 111272 1
42 104609 1
43 101802 1
44 94542 1
45 93051 1
46 124129 1
47 130374 1
48 123946 1
49 114971 1
50 105531 0
51 104919 0
52 104782 0
53 101281 0
54 94545 0
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) plan
124677 -2794
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-40646 -11146 -2276 12456 37084
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 124677 3204 38.920 <2e-16 ***
plan -2794 5004 -0.558 0.579
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 19220 on 59 degrees of freedom
Multiple R-squared: 0.005257, Adjusted R-squared: -0.0116
F-statistic: 0.3118 on 1 and 59 DF, p-value: 0.5787
> 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,] 0.04558382 0.09116765 0.95441618
[2,] 0.04580164 0.09160329 0.95419836
[3,] 0.06161369 0.12322739 0.93838631
[4,] 0.08993549 0.17987098 0.91006451
[5,] 0.07952289 0.15904579 0.92047711
[6,] 0.13230343 0.26460685 0.86769657
[7,] 0.28803419 0.57606839 0.71196581
[8,] 0.42380083 0.84760165 0.57619917
[9,] 0.41171737 0.82343474 0.58828263
[10,] 0.34556606 0.69113213 0.65443394
[11,] 0.28170713 0.56341426 0.71829287
[12,] 0.22939108 0.45878216 0.77060892
[13,] 0.19109137 0.38218274 0.80890863
[14,] 0.16842034 0.33684068 0.83157966
[15,] 0.16455442 0.32910883 0.83544558
[16,] 0.18159647 0.36319293 0.81840353
[17,] 0.18372156 0.36744311 0.81627844
[18,] 0.22967602 0.45935205 0.77032398
[19,] 0.43131412 0.86262824 0.56868588
[20,] 0.74141192 0.51717616 0.25858808
[21,] 0.75459133 0.49081735 0.24540867
[22,] 0.73238663 0.53522674 0.26761337
[23,] 0.69683299 0.60633402 0.30316701
[24,] 0.65320981 0.69358038 0.34679019
[25,] 0.60286173 0.79427654 0.39713827
[26,] 0.56423709 0.87152581 0.43576291
[27,] 0.53010560 0.93978880 0.46989440
[28,] 0.50657459 0.98685082 0.49342541
[29,] 0.46612005 0.93224010 0.53387995
[30,] 0.53779539 0.92440922 0.46220461
[31,] 0.72325038 0.55349925 0.27674962
[32,] 0.88878408 0.22243183 0.11121592
[33,] 0.91090262 0.17819477 0.08909738
[34,] 0.89346586 0.21306828 0.10653414
[35,] 0.86548747 0.26902507 0.13451253
[36,] 0.83141985 0.33716030 0.16858015
[37,] 0.79395704 0.41208592 0.20604296
[38,] 0.77709373 0.44581254 0.22290627
[39,] 0.77821224 0.44357552 0.22178776
[40,] 0.86232100 0.27535799 0.13767900
[41,] 0.96186519 0.07626961 0.03813481
[42,] 0.93710379 0.12579242 0.06289621
[43,] 0.91734438 0.16531124 0.08265562
[44,] 0.88090351 0.23819299 0.11909649
[45,] 0.82167620 0.35664759 0.17832380
[46,] 0.78085109 0.43829781 0.21914891
[47,] 0.72508569 0.54982861 0.27491431
[48,] 0.65211196 0.69577608 0.34788804
[49,] 0.56739260 0.86521481 0.43260740
[50,] 0.50956387 0.98087226 0.49043613
[51,] 0.45428024 0.90856048 0.54571976
[52,] 0.59634207 0.80731585 0.40365793
> postscript(file="/var/www/html/rcomp/tmp/1hbih1227723279.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2xwyt1227723279.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3na3b1227723279.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/474j11227723279.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/53ttb1227723279.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
23090.6111 12829.6111 12241.6111 11473.6111 8323.6111 876.6111
7 8 9 10 11 12
-5030.3889 -10519.3889 -8484.3889 28125.6111 37083.6111 36264.6111
13 14 15 16 17 18
24792.6111 14530.6111 9910.6111 5644.6111 1933.6111 -2276.3889
19 20 21 22 23 24
-7325.3889 -12542.3889 -11798.3889 24051.6111 32552.6111 32543.6111
25 26 27 28 29 30
24797.8800 14640.8800 10227.8800 3442.8800 832.8800 -5268.1200
31 32 33 34 35 36
-8164.1200 -11146.1200 -9790.1200 21681.8800 28062.8800 27263.8800
37 38 39 40 41 42
12455.8800 799.8800 -6269.1200 -5317.1200 -10611.1200 -17274.1200
43 44 45 46 47 48
-20081.1200 -27341.1200 -28832.1200 2245.8800 8490.8800 2062.8800
49 50 51 52 53 54
-6912.1200 -19146.3889 -19758.3889 -19895.3889 -23396.3889 -30132.3889
55 56 57 58 59 60
-31429.3889 -40646.3889 -37191.3889 -8810.3889 -4350.3889 -7669.3889
61
-15866.3889
> postscript(file="/var/www/html/rcomp/tmp/629u81227723279.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 23090.6111 NA
1 12829.6111 23090.6111
2 12241.6111 12829.6111
3 11473.6111 12241.6111
4 8323.6111 11473.6111
5 876.6111 8323.6111
6 -5030.3889 876.6111
7 -10519.3889 -5030.3889
8 -8484.3889 -10519.3889
9 28125.6111 -8484.3889
10 37083.6111 28125.6111
11 36264.6111 37083.6111
12 24792.6111 36264.6111
13 14530.6111 24792.6111
14 9910.6111 14530.6111
15 5644.6111 9910.6111
16 1933.6111 5644.6111
17 -2276.3889 1933.6111
18 -7325.3889 -2276.3889
19 -12542.3889 -7325.3889
20 -11798.3889 -12542.3889
21 24051.6111 -11798.3889
22 32552.6111 24051.6111
23 32543.6111 32552.6111
24 24797.8800 32543.6111
25 14640.8800 24797.8800
26 10227.8800 14640.8800
27 3442.8800 10227.8800
28 832.8800 3442.8800
29 -5268.1200 832.8800
30 -8164.1200 -5268.1200
31 -11146.1200 -8164.1200
32 -9790.1200 -11146.1200
33 21681.8800 -9790.1200
34 28062.8800 21681.8800
35 27263.8800 28062.8800
36 12455.8800 27263.8800
37 799.8800 12455.8800
38 -6269.1200 799.8800
39 -5317.1200 -6269.1200
40 -10611.1200 -5317.1200
41 -17274.1200 -10611.1200
42 -20081.1200 -17274.1200
43 -27341.1200 -20081.1200
44 -28832.1200 -27341.1200
45 2245.8800 -28832.1200
46 8490.8800 2245.8800
47 2062.8800 8490.8800
48 -6912.1200 2062.8800
49 -19146.3889 -6912.1200
50 -19758.3889 -19146.3889
51 -19895.3889 -19758.3889
52 -23396.3889 -19895.3889
53 -30132.3889 -23396.3889
54 -31429.3889 -30132.3889
55 -40646.3889 -31429.3889
56 -37191.3889 -40646.3889
57 -8810.3889 -37191.3889
58 -4350.3889 -8810.3889
59 -7669.3889 -4350.3889
60 -15866.3889 -7669.3889
61 NA -15866.3889
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 12829.6111 23090.6111
[2,] 12241.6111 12829.6111
[3,] 11473.6111 12241.6111
[4,] 8323.6111 11473.6111
[5,] 876.6111 8323.6111
[6,] -5030.3889 876.6111
[7,] -10519.3889 -5030.3889
[8,] -8484.3889 -10519.3889
[9,] 28125.6111 -8484.3889
[10,] 37083.6111 28125.6111
[11,] 36264.6111 37083.6111
[12,] 24792.6111 36264.6111
[13,] 14530.6111 24792.6111
[14,] 9910.6111 14530.6111
[15,] 5644.6111 9910.6111
[16,] 1933.6111 5644.6111
[17,] -2276.3889 1933.6111
[18,] -7325.3889 -2276.3889
[19,] -12542.3889 -7325.3889
[20,] -11798.3889 -12542.3889
[21,] 24051.6111 -11798.3889
[22,] 32552.6111 24051.6111
[23,] 32543.6111 32552.6111
[24,] 24797.8800 32543.6111
[25,] 14640.8800 24797.8800
[26,] 10227.8800 14640.8800
[27,] 3442.8800 10227.8800
[28,] 832.8800 3442.8800
[29,] -5268.1200 832.8800
[30,] -8164.1200 -5268.1200
[31,] -11146.1200 -8164.1200
[32,] -9790.1200 -11146.1200
[33,] 21681.8800 -9790.1200
[34,] 28062.8800 21681.8800
[35,] 27263.8800 28062.8800
[36,] 12455.8800 27263.8800
[37,] 799.8800 12455.8800
[38,] -6269.1200 799.8800
[39,] -5317.1200 -6269.1200
[40,] -10611.1200 -5317.1200
[41,] -17274.1200 -10611.1200
[42,] -20081.1200 -17274.1200
[43,] -27341.1200 -20081.1200
[44,] -28832.1200 -27341.1200
[45,] 2245.8800 -28832.1200
[46,] 8490.8800 2245.8800
[47,] 2062.8800 8490.8800
[48,] -6912.1200 2062.8800
[49,] -19146.3889 -6912.1200
[50,] -19758.3889 -19146.3889
[51,] -19895.3889 -19758.3889
[52,] -23396.3889 -19895.3889
[53,] -30132.3889 -23396.3889
[54,] -31429.3889 -30132.3889
[55,] -40646.3889 -31429.3889
[56,] -37191.3889 -40646.3889
[57,] -8810.3889 -37191.3889
[58,] -4350.3889 -8810.3889
[59,] -7669.3889 -4350.3889
[60,] -15866.3889 -7669.3889
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 12829.6111 23090.6111
2 12241.6111 12829.6111
3 11473.6111 12241.6111
4 8323.6111 11473.6111
5 876.6111 8323.6111
6 -5030.3889 876.6111
7 -10519.3889 -5030.3889
8 -8484.3889 -10519.3889
9 28125.6111 -8484.3889
10 37083.6111 28125.6111
11 36264.6111 37083.6111
12 24792.6111 36264.6111
13 14530.6111 24792.6111
14 9910.6111 14530.6111
15 5644.6111 9910.6111
16 1933.6111 5644.6111
17 -2276.3889 1933.6111
18 -7325.3889 -2276.3889
19 -12542.3889 -7325.3889
20 -11798.3889 -12542.3889
21 24051.6111 -11798.3889
22 32552.6111 24051.6111
23 32543.6111 32552.6111
24 24797.8800 32543.6111
25 14640.8800 24797.8800
26 10227.8800 14640.8800
27 3442.8800 10227.8800
28 832.8800 3442.8800
29 -5268.1200 832.8800
30 -8164.1200 -5268.1200
31 -11146.1200 -8164.1200
32 -9790.1200 -11146.1200
33 21681.8800 -9790.1200
34 28062.8800 21681.8800
35 27263.8800 28062.8800
36 12455.8800 27263.8800
37 799.8800 12455.8800
38 -6269.1200 799.8800
39 -5317.1200 -6269.1200
40 -10611.1200 -5317.1200
41 -17274.1200 -10611.1200
42 -20081.1200 -17274.1200
43 -27341.1200 -20081.1200
44 -28832.1200 -27341.1200
45 2245.8800 -28832.1200
46 8490.8800 2245.8800
47 2062.8800 8490.8800
48 -6912.1200 2062.8800
49 -19146.3889 -6912.1200
50 -19758.3889 -19146.3889
51 -19895.3889 -19758.3889
52 -23396.3889 -19895.3889
53 -30132.3889 -23396.3889
54 -31429.3889 -30132.3889
55 -40646.3889 -31429.3889
56 -37191.3889 -40646.3889
57 -8810.3889 -37191.3889
58 -4350.3889 -8810.3889
59 -7669.3889 -4350.3889
60 -15866.3889 -7669.3889
> 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/78his1227723279.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8wzs11227723279.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9rusg1227723279.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10gm3a1227723279.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11482v1227723279.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/12z1sp1227723279.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/13xpg11227723279.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/147k9o1227723279.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/15a00d1227723279.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/160wwc1227723279.tab")
+ }
>
> system("convert tmp/1hbih1227723279.ps tmp/1hbih1227723279.png")
> system("convert tmp/2xwyt1227723279.ps tmp/2xwyt1227723279.png")
> system("convert tmp/3na3b1227723279.ps tmp/3na3b1227723279.png")
> system("convert tmp/474j11227723279.ps tmp/474j11227723279.png")
> system("convert tmp/53ttb1227723279.ps tmp/53ttb1227723279.png")
> system("convert tmp/629u81227723279.ps tmp/629u81227723279.png")
> system("convert tmp/78his1227723279.ps tmp/78his1227723279.png")
> system("convert tmp/8wzs11227723279.ps tmp/8wzs11227723279.png")
> system("convert tmp/9rusg1227723279.ps tmp/9rusg1227723279.png")
> system("convert tmp/10gm3a1227723279.ps tmp/10gm3a1227723279.png")
>
>
> proc.time()
user system elapsed
2.460 1.557 2.867