R version 2.7.0 (2008-04-22)
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(147768,0,137507,0,136919,0,136151,0,133001,0,125554,0,119647,0,114158,0,116193,0,152803,0,161761,0,160942,0,149470,0,139208,0,134588,0,130322,0,126611,0,122401,0,117352,0,112135,0,112879,0,148729,0,157230,0,157221,0,146681,0,136524,0,132111,0,125326,0,122716,0,116615,0,113719,0,110737,0,112093,0,143565,0,149946,0,149147,0,134339,0,122683,0,115614,0,116566,0,111272,0,104609,0,101802,0,94542,0,93051,0,124129,0,130374,0,123946,0,114971,0,105531,0,104919,0,104782,0,101281,0,94545,0,93248,0,84031,0,87486,0,115867,0,120327,1,117008,1,108811,1),dim=c(2,61),dimnames=list(c('jonger_dan_25','economische_crisis'),1:61))
> y <- array(NA,dim=c(2,61),dimnames=list(c('jonger_dan_25','economische_crisis'),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 economische_crisis
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 0
26 136524 0
27 132111 0
28 125326 0
29 122716 0
30 116615 0
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 0
41 111272 0
42 104609 0
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 0
53 101281 0
54 94545 0
55 93248 0
56 84031 0
57 87486 0
58 115867 0
59 120327 1
60 117008 1
61 108811 1
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) economische_crisis
123954 -8572
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-39923 -11819 -1238 12570 37807
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 123954 2518 49.221 <2e-16 ***
economische_crisis -8572 11356 -0.755 0.453
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 19180 on 59 degrees of freedom
Multiple R-squared: 0.009565, Adjusted R-squared: -0.007222
F-statistic: 0.5698 on 1 and 59 DF, p-value: 0.4534
> 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,] 0.04603021 0.09206042 0.95396979
[2,] 0.04636659 0.09273318 0.95363341
[3,] 0.06249683 0.12499365 0.93750317
[4,] 0.09134750 0.18269500 0.90865250
[5,] 0.08092529 0.16185058 0.91907471
[6,] 0.13457631 0.26915262 0.86542369
[7,] 0.29044880 0.58089759 0.70955120
[8,] 0.42112027 0.84224054 0.57887973
[9,] 0.40149488 0.80298975 0.59850512
[10,] 0.32915040 0.65830081 0.67084960
[11,] 0.26057795 0.52115590 0.73942205
[12,] 0.20544750 0.41089501 0.79455250
[13,] 0.16575927 0.33151853 0.83424073
[14,] 0.14247655 0.28495310 0.85752345
[15,] 0.13793646 0.27587291 0.86206354
[16,] 0.15398035 0.30796070 0.84601965
[17,] 0.15674203 0.31348406 0.84325797
[18,] 0.17409371 0.34818741 0.82590629
[19,] 0.27975057 0.55950114 0.72024943
[20,] 0.42629290 0.85258580 0.57370710
[21,] 0.47105559 0.94211118 0.52894441
[22,] 0.44884156 0.89768312 0.55115844
[23,] 0.41443611 0.82887222 0.58556389
[24,] 0.37467633 0.74935266 0.62532367
[25,] 0.33850045 0.67700090 0.66149955
[26,] 0.31869606 0.63739212 0.68130394
[27,] 0.30727186 0.61454372 0.69272814
[28,] 0.30537651 0.61075302 0.69462349
[29,] 0.28902308 0.57804616 0.71097692
[30,] 0.35402105 0.70804210 0.64597895
[31,] 0.55685818 0.88628364 0.44314182
[32,] 0.80503320 0.38993360 0.19496680
[33,] 0.87139477 0.25721045 0.12860523
[34,] 0.87626424 0.24747152 0.12373576
[35,] 0.86592531 0.26814937 0.13407469
[36,] 0.85676100 0.28647801 0.14323900
[37,] 0.84021442 0.31957116 0.15978558
[38,] 0.82799519 0.34400963 0.17200481
[39,] 0.81842830 0.36314341 0.18157170
[40,] 0.84229560 0.31540880 0.15770440
[41,] 0.86708048 0.26583903 0.13291952
[42,] 0.87542662 0.24914676 0.12457338
[43,] 0.94371066 0.11257867 0.05628934
[44,] 0.97473459 0.05053082 0.02526541
[45,] 0.98006020 0.03987961 0.01993980
[46,] 0.97072480 0.05855040 0.02927520
[47,] 0.95702245 0.08595511 0.04297755
[48,] 0.93904228 0.12191545 0.06095772
[49,] 0.90396512 0.19206976 0.09603488
[50,] 0.84078452 0.31843097 0.15921548
[51,] 0.74511872 0.50976257 0.25488128
[52,] 0.73834318 0.52331363 0.26165682
> postscript(file="/var/www/html/rcomp/tmp/1nxe71227723443.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2erhz1227723443.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/36whk1227723443.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/48zfv1227723443.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5te9c1227723443.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
23814.24138 13553.24138 12965.24138 12197.24138 9047.24138 1600.24138
7 8 9 10 11 12
-4306.75862 -9795.75862 -7760.75862 28849.24138 37807.24138 36988.24138
13 14 15 16 17 18
25516.24138 15254.24138 10634.24138 6368.24138 2657.24138 -1552.75862
19 20 21 22 23 24
-6601.75862 -11818.75862 -11074.75862 24775.24138 33276.24138 33267.24138
25 26 27 28 29 30
22727.24138 12570.24138 8157.24138 1372.24138 -1237.75862 -7338.75862
31 32 33 34 35 36
-10234.75862 -13216.75862 -11860.75862 19611.24138 25992.24138 25193.24138
37 38 39 40 41 42
10385.24138 -1270.75862 -8339.75862 -7387.75862 -12681.75862 -19344.75862
43 44 45 46 47 48
-22151.75862 -29411.75862 -30902.75862 175.24138 6420.24138 -7.75862
49 50 51 52 53 54
-8982.75862 -18422.75862 -19034.75862 -19171.75862 -22672.75862 -29408.75862
55 56 57 58 59 60
-30705.75862 -39922.75862 -36467.75862 -8086.75862 4945.00000 1626.00000
61
-6571.00000
> postscript(file="/var/www/html/rcomp/tmp/6bwry1227723443.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 23814.24138 NA
1 13553.24138 23814.24138
2 12965.24138 13553.24138
3 12197.24138 12965.24138
4 9047.24138 12197.24138
5 1600.24138 9047.24138
6 -4306.75862 1600.24138
7 -9795.75862 -4306.75862
8 -7760.75862 -9795.75862
9 28849.24138 -7760.75862
10 37807.24138 28849.24138
11 36988.24138 37807.24138
12 25516.24138 36988.24138
13 15254.24138 25516.24138
14 10634.24138 15254.24138
15 6368.24138 10634.24138
16 2657.24138 6368.24138
17 -1552.75862 2657.24138
18 -6601.75862 -1552.75862
19 -11818.75862 -6601.75862
20 -11074.75862 -11818.75862
21 24775.24138 -11074.75862
22 33276.24138 24775.24138
23 33267.24138 33276.24138
24 22727.24138 33267.24138
25 12570.24138 22727.24138
26 8157.24138 12570.24138
27 1372.24138 8157.24138
28 -1237.75862 1372.24138
29 -7338.75862 -1237.75862
30 -10234.75862 -7338.75862
31 -13216.75862 -10234.75862
32 -11860.75862 -13216.75862
33 19611.24138 -11860.75862
34 25992.24138 19611.24138
35 25193.24138 25992.24138
36 10385.24138 25193.24138
37 -1270.75862 10385.24138
38 -8339.75862 -1270.75862
39 -7387.75862 -8339.75862
40 -12681.75862 -7387.75862
41 -19344.75862 -12681.75862
42 -22151.75862 -19344.75862
43 -29411.75862 -22151.75862
44 -30902.75862 -29411.75862
45 175.24138 -30902.75862
46 6420.24138 175.24138
47 -7.75862 6420.24138
48 -8982.75862 -7.75862
49 -18422.75862 -8982.75862
50 -19034.75862 -18422.75862
51 -19171.75862 -19034.75862
52 -22672.75862 -19171.75862
53 -29408.75862 -22672.75862
54 -30705.75862 -29408.75862
55 -39922.75862 -30705.75862
56 -36467.75862 -39922.75862
57 -8086.75862 -36467.75862
58 4945.00000 -8086.75862
59 1626.00000 4945.00000
60 -6571.00000 1626.00000
61 NA -6571.00000
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 13553.24138 23814.24138
[2,] 12965.24138 13553.24138
[3,] 12197.24138 12965.24138
[4,] 9047.24138 12197.24138
[5,] 1600.24138 9047.24138
[6,] -4306.75862 1600.24138
[7,] -9795.75862 -4306.75862
[8,] -7760.75862 -9795.75862
[9,] 28849.24138 -7760.75862
[10,] 37807.24138 28849.24138
[11,] 36988.24138 37807.24138
[12,] 25516.24138 36988.24138
[13,] 15254.24138 25516.24138
[14,] 10634.24138 15254.24138
[15,] 6368.24138 10634.24138
[16,] 2657.24138 6368.24138
[17,] -1552.75862 2657.24138
[18,] -6601.75862 -1552.75862
[19,] -11818.75862 -6601.75862
[20,] -11074.75862 -11818.75862
[21,] 24775.24138 -11074.75862
[22,] 33276.24138 24775.24138
[23,] 33267.24138 33276.24138
[24,] 22727.24138 33267.24138
[25,] 12570.24138 22727.24138
[26,] 8157.24138 12570.24138
[27,] 1372.24138 8157.24138
[28,] -1237.75862 1372.24138
[29,] -7338.75862 -1237.75862
[30,] -10234.75862 -7338.75862
[31,] -13216.75862 -10234.75862
[32,] -11860.75862 -13216.75862
[33,] 19611.24138 -11860.75862
[34,] 25992.24138 19611.24138
[35,] 25193.24138 25992.24138
[36,] 10385.24138 25193.24138
[37,] -1270.75862 10385.24138
[38,] -8339.75862 -1270.75862
[39,] -7387.75862 -8339.75862
[40,] -12681.75862 -7387.75862
[41,] -19344.75862 -12681.75862
[42,] -22151.75862 -19344.75862
[43,] -29411.75862 -22151.75862
[44,] -30902.75862 -29411.75862
[45,] 175.24138 -30902.75862
[46,] 6420.24138 175.24138
[47,] -7.75862 6420.24138
[48,] -8982.75862 -7.75862
[49,] -18422.75862 -8982.75862
[50,] -19034.75862 -18422.75862
[51,] -19171.75862 -19034.75862
[52,] -22672.75862 -19171.75862
[53,] -29408.75862 -22672.75862
[54,] -30705.75862 -29408.75862
[55,] -39922.75862 -30705.75862
[56,] -36467.75862 -39922.75862
[57,] -8086.75862 -36467.75862
[58,] 4945.00000 -8086.75862
[59,] 1626.00000 4945.00000
[60,] -6571.00000 1626.00000
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 13553.24138 23814.24138
2 12965.24138 13553.24138
3 12197.24138 12965.24138
4 9047.24138 12197.24138
5 1600.24138 9047.24138
6 -4306.75862 1600.24138
7 -9795.75862 -4306.75862
8 -7760.75862 -9795.75862
9 28849.24138 -7760.75862
10 37807.24138 28849.24138
11 36988.24138 37807.24138
12 25516.24138 36988.24138
13 15254.24138 25516.24138
14 10634.24138 15254.24138
15 6368.24138 10634.24138
16 2657.24138 6368.24138
17 -1552.75862 2657.24138
18 -6601.75862 -1552.75862
19 -11818.75862 -6601.75862
20 -11074.75862 -11818.75862
21 24775.24138 -11074.75862
22 33276.24138 24775.24138
23 33267.24138 33276.24138
24 22727.24138 33267.24138
25 12570.24138 22727.24138
26 8157.24138 12570.24138
27 1372.24138 8157.24138
28 -1237.75862 1372.24138
29 -7338.75862 -1237.75862
30 -10234.75862 -7338.75862
31 -13216.75862 -10234.75862
32 -11860.75862 -13216.75862
33 19611.24138 -11860.75862
34 25992.24138 19611.24138
35 25193.24138 25992.24138
36 10385.24138 25193.24138
37 -1270.75862 10385.24138
38 -8339.75862 -1270.75862
39 -7387.75862 -8339.75862
40 -12681.75862 -7387.75862
41 -19344.75862 -12681.75862
42 -22151.75862 -19344.75862
43 -29411.75862 -22151.75862
44 -30902.75862 -29411.75862
45 175.24138 -30902.75862
46 6420.24138 175.24138
47 -7.75862 6420.24138
48 -8982.75862 -7.75862
49 -18422.75862 -8982.75862
50 -19034.75862 -18422.75862
51 -19171.75862 -19034.75862
52 -22672.75862 -19171.75862
53 -29408.75862 -22672.75862
54 -30705.75862 -29408.75862
55 -39922.75862 -30705.75862
56 -36467.75862 -39922.75862
57 -8086.75862 -36467.75862
58 4945.00000 -8086.75862
59 1626.00000 4945.00000
60 -6571.00000 1626.00000
> 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/77of11227723443.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/86zb91227723443.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9gedp1227723443.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/1092kw1227723443.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11ovoe1227723443.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/12sxhr1227723443.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/136ltw1227723443.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/141ftj1227723443.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/157hlt1227723444.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/16r27h1227723444.tab")
+ }
>
> system("convert tmp/1nxe71227723443.ps tmp/1nxe71227723443.png")
> system("convert tmp/2erhz1227723443.ps tmp/2erhz1227723443.png")
> system("convert tmp/36whk1227723443.ps tmp/36whk1227723443.png")
> system("convert tmp/48zfv1227723443.ps tmp/48zfv1227723443.png")
> system("convert tmp/5te9c1227723443.ps tmp/5te9c1227723443.png")
> system("convert tmp/6bwry1227723443.ps tmp/6bwry1227723443.png")
> system("convert tmp/77of11227723443.ps tmp/77of11227723443.png")
> system("convert tmp/86zb91227723443.ps tmp/86zb91227723443.png")
> system("convert tmp/9gedp1227723443.ps tmp/9gedp1227723443.png")
> system("convert tmp/1092kw1227723443.ps tmp/1092kw1227723443.png")
>
>
> proc.time()
user system elapsed
5.065 2.724 5.449