R version 2.12.0 (2010-10-15)
Copyright (C) 2010 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-bit)
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(595,0,597,0,593,0,590,0,580,0,574,0,573,0,573,0,620,0,626,0,620,0,588,0,566,0,557,0,561,0,549,0,532,0,526,0,511,0,499,0,555,0,565,0,542,0,527,0,510,0,514,0,517,0,508,0,493,0,490,0,469,0,478,0,528,0,534,0,518,0,506,0,502,1,516,1,528,1,533,1,536,1,537,1,524,1,536,1,587,1,597,1,581,1,564,1,558,1,575,1,580,1,575,1,563,1,552,1,537,1,545,1,601,1,604,1,586,1,564,1,549,1),dim=c(2,61),dimnames=list(c('werkloosheid','X'),1:61))
> y <- array(NA,dim=c(2,61),dimnames=list(c('werkloosheid','X'),1:61))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par20 = ''
> par19 = ''
> par18 = ''
> par17 = ''
> par16 = ''
> par15 = ''
> par14 = ''
> par13 = ''
> par12 = ''
> par11 = ''
> par10 = ''
> par9 = ''
> par8 = ''
> par7 = ''
> par6 = ''
> par5 = ''
> par4 = ''
> par3 = 'No Linear Trend'
> par2 = 'Do not include Seasonal Dummies'
> par1 = '1'
> ylab = ''
> xlab = ''
> main = ''
> #'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
> 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
werkloosheid X
1 595 0
2 597 0
3 593 0
4 590 0
5 580 0
6 574 0
7 573 0
8 573 0
9 620 0
10 626 0
11 620 0
12 588 0
13 566 0
14 557 0
15 561 0
16 549 0
17 532 0
18 526 0
19 511 0
20 499 0
21 555 0
22 565 0
23 542 0
24 527 0
25 510 0
26 514 0
27 517 0
28 508 0
29 493 0
30 490 0
31 469 0
32 478 0
33 528 0
34 534 0
35 518 0
36 506 0
37 502 1
38 516 1
39 528 1
40 533 1
41 536 1
42 537 1
43 524 1
44 536 1
45 587 1
46 597 1
47 581 1
48 564 1
49 558 1
50 575 1
51 580 1
52 575 1
53 563 1
54 552 1
55 537 1
56 545 1
57 601 1
58 604 1
59 586 1
60 564 1
61 549 1
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X
546.78 10.42
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-77.78 -28.78 0.80 26.22 79.22
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 546.778 6.126 89.261 <2e-16 ***
X 10.422 9.568 1.089 0.280
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 36.75 on 59 degrees of freedom
Multiple R-squared: 0.01971, Adjusted R-squared: 0.003097
F-statistic: 1.186 on 1 and 59 DF, p-value: 0.2805
> 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,] 0.013657228 0.027314456 0.986342772
[2,] 0.012678501 0.025357003 0.987321499
[3,] 0.007840337 0.015680674 0.992159663
[4,] 0.004025432 0.008050864 0.995974568
[5,] 0.025882566 0.051765131 0.974117434
[6,] 0.086895067 0.173790135 0.913104933
[7,] 0.149300716 0.298601433 0.850699284
[8,] 0.131622059 0.263244118 0.868377941
[9,] 0.163733657 0.327467313 0.836266343
[10,] 0.231453875 0.462907750 0.768546125
[11,] 0.271657700 0.543315400 0.728342300
[12,] 0.362985130 0.725970259 0.637014870
[13,] 0.541628787 0.916742426 0.458371213
[14,] 0.687949077 0.624101847 0.312050923
[15,] 0.836007108 0.327985784 0.163992892
[16,] 0.931847656 0.136304688 0.068152344
[17,] 0.929506080 0.140987840 0.070493920
[18,] 0.942008366 0.115983269 0.057991634
[19,] 0.943825551 0.112348899 0.056174449
[20,] 0.947584657 0.104830687 0.052415343
[21,] 0.958521637 0.082956727 0.041478363
[22,] 0.961601028 0.076797944 0.038398972
[23,] 0.961179763 0.077640475 0.038820237
[24,] 0.962645671 0.074708658 0.037354329
[25,] 0.970571584 0.058856833 0.029428416
[26,] 0.976342638 0.047314725 0.023657362
[27,] 0.990710618 0.018578764 0.009289382
[28,] 0.995199162 0.009601675 0.004800838
[29,] 0.992248582 0.015502835 0.007751418
[30,] 0.988522884 0.022954232 0.011477116
[31,] 0.983101152 0.033797697 0.016898848
[32,] 0.976701874 0.046596252 0.023298126
[33,] 0.987061568 0.025876863 0.012938432
[34,] 0.990304183 0.019391635 0.009695817
[35,] 0.990301510 0.019396980 0.009698490
[36,] 0.989397683 0.021204634 0.010602317
[37,] 0.988003984 0.023992032 0.011996016
[38,] 0.986761594 0.026476813 0.013238406
[39,] 0.992822507 0.014354985 0.007177493
[40,] 0.994413629 0.011172742 0.005586371
[41,] 0.992958664 0.014082672 0.007041336
[42,] 0.994072478 0.011855044 0.005927522
[43,] 0.990297475 0.019405049 0.009702525
[44,] 0.981214008 0.037571984 0.018785992
[45,] 0.966935431 0.066129137 0.033064569
[46,] 0.942219174 0.115561651 0.057780826
[47,] 0.908493189 0.183013622 0.091506811
[48,] 0.851412803 0.297174394 0.148587197
[49,] 0.762342006 0.475315987 0.237657994
[50,] 0.667295807 0.665408386 0.332704193
[51,] 0.665775048 0.668449904 0.334224952
[52,] 0.649153372 0.701693255 0.350846628
> postscript(file="/var/www/rcomp/tmp/10dqz1293210140.ps",horizontal=F,onefile=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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/2b5721293210140.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/rcomp/tmp/3b5721293210140.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/4b5721293210140.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/54w7o1293210140.ps",horizontal=F,onefile=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
48.222222 50.222222 46.222222 43.222222 33.222222 27.222222 26.222222
8 9 10 11 12 13 14
26.222222 73.222222 79.222222 73.222222 41.222222 19.222222 10.222222
15 16 17 18 19 20 21
14.222222 2.222222 -14.777778 -20.777778 -35.777778 -47.777778 8.222222
22 23 24 25 26 27 28
18.222222 -4.777778 -19.777778 -36.777778 -32.777778 -29.777778 -38.777778
29 30 31 32 33 34 35
-53.777778 -56.777778 -77.777778 -68.777778 -18.777778 -12.777778 -28.777778
36 37 38 39 40 41 42
-40.777778 -55.200000 -41.200000 -29.200000 -24.200000 -21.200000 -20.200000
43 44 45 46 47 48 49
-33.200000 -21.200000 29.800000 39.800000 23.800000 6.800000 0.800000
50 51 52 53 54 55 56
17.800000 22.800000 17.800000 5.800000 -5.200000 -20.200000 -12.200000
57 58 59 60 61
43.800000 46.800000 28.800000 6.800000 -8.200000
> postscript(file="/var/www/rcomp/tmp/64w7o1293210140.ps",horizontal=F,onefile=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 48.222222 NA
1 50.222222 48.222222
2 46.222222 50.222222
3 43.222222 46.222222
4 33.222222 43.222222
5 27.222222 33.222222
6 26.222222 27.222222
7 26.222222 26.222222
8 73.222222 26.222222
9 79.222222 73.222222
10 73.222222 79.222222
11 41.222222 73.222222
12 19.222222 41.222222
13 10.222222 19.222222
14 14.222222 10.222222
15 2.222222 14.222222
16 -14.777778 2.222222
17 -20.777778 -14.777778
18 -35.777778 -20.777778
19 -47.777778 -35.777778
20 8.222222 -47.777778
21 18.222222 8.222222
22 -4.777778 18.222222
23 -19.777778 -4.777778
24 -36.777778 -19.777778
25 -32.777778 -36.777778
26 -29.777778 -32.777778
27 -38.777778 -29.777778
28 -53.777778 -38.777778
29 -56.777778 -53.777778
30 -77.777778 -56.777778
31 -68.777778 -77.777778
32 -18.777778 -68.777778
33 -12.777778 -18.777778
34 -28.777778 -12.777778
35 -40.777778 -28.777778
36 -55.200000 -40.777778
37 -41.200000 -55.200000
38 -29.200000 -41.200000
39 -24.200000 -29.200000
40 -21.200000 -24.200000
41 -20.200000 -21.200000
42 -33.200000 -20.200000
43 -21.200000 -33.200000
44 29.800000 -21.200000
45 39.800000 29.800000
46 23.800000 39.800000
47 6.800000 23.800000
48 0.800000 6.800000
49 17.800000 0.800000
50 22.800000 17.800000
51 17.800000 22.800000
52 5.800000 17.800000
53 -5.200000 5.800000
54 -20.200000 -5.200000
55 -12.200000 -20.200000
56 43.800000 -12.200000
57 46.800000 43.800000
58 28.800000 46.800000
59 6.800000 28.800000
60 -8.200000 6.800000
61 NA -8.200000
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 50.222222 48.222222
[2,] 46.222222 50.222222
[3,] 43.222222 46.222222
[4,] 33.222222 43.222222
[5,] 27.222222 33.222222
[6,] 26.222222 27.222222
[7,] 26.222222 26.222222
[8,] 73.222222 26.222222
[9,] 79.222222 73.222222
[10,] 73.222222 79.222222
[11,] 41.222222 73.222222
[12,] 19.222222 41.222222
[13,] 10.222222 19.222222
[14,] 14.222222 10.222222
[15,] 2.222222 14.222222
[16,] -14.777778 2.222222
[17,] -20.777778 -14.777778
[18,] -35.777778 -20.777778
[19,] -47.777778 -35.777778
[20,] 8.222222 -47.777778
[21,] 18.222222 8.222222
[22,] -4.777778 18.222222
[23,] -19.777778 -4.777778
[24,] -36.777778 -19.777778
[25,] -32.777778 -36.777778
[26,] -29.777778 -32.777778
[27,] -38.777778 -29.777778
[28,] -53.777778 -38.777778
[29,] -56.777778 -53.777778
[30,] -77.777778 -56.777778
[31,] -68.777778 -77.777778
[32,] -18.777778 -68.777778
[33,] -12.777778 -18.777778
[34,] -28.777778 -12.777778
[35,] -40.777778 -28.777778
[36,] -55.200000 -40.777778
[37,] -41.200000 -55.200000
[38,] -29.200000 -41.200000
[39,] -24.200000 -29.200000
[40,] -21.200000 -24.200000
[41,] -20.200000 -21.200000
[42,] -33.200000 -20.200000
[43,] -21.200000 -33.200000
[44,] 29.800000 -21.200000
[45,] 39.800000 29.800000
[46,] 23.800000 39.800000
[47,] 6.800000 23.800000
[48,] 0.800000 6.800000
[49,] 17.800000 0.800000
[50,] 22.800000 17.800000
[51,] 17.800000 22.800000
[52,] 5.800000 17.800000
[53,] -5.200000 5.800000
[54,] -20.200000 -5.200000
[55,] -12.200000 -20.200000
[56,] 43.800000 -12.200000
[57,] 46.800000 43.800000
[58,] 28.800000 46.800000
[59,] 6.800000 28.800000
[60,] -8.200000 6.800000
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 50.222222 48.222222
2 46.222222 50.222222
3 43.222222 46.222222
4 33.222222 43.222222
5 27.222222 33.222222
6 26.222222 27.222222
7 26.222222 26.222222
8 73.222222 26.222222
9 79.222222 73.222222
10 73.222222 79.222222
11 41.222222 73.222222
12 19.222222 41.222222
13 10.222222 19.222222
14 14.222222 10.222222
15 2.222222 14.222222
16 -14.777778 2.222222
17 -20.777778 -14.777778
18 -35.777778 -20.777778
19 -47.777778 -35.777778
20 8.222222 -47.777778
21 18.222222 8.222222
22 -4.777778 18.222222
23 -19.777778 -4.777778
24 -36.777778 -19.777778
25 -32.777778 -36.777778
26 -29.777778 -32.777778
27 -38.777778 -29.777778
28 -53.777778 -38.777778
29 -56.777778 -53.777778
30 -77.777778 -56.777778
31 -68.777778 -77.777778
32 -18.777778 -68.777778
33 -12.777778 -18.777778
34 -28.777778 -12.777778
35 -40.777778 -28.777778
36 -55.200000 -40.777778
37 -41.200000 -55.200000
38 -29.200000 -41.200000
39 -24.200000 -29.200000
40 -21.200000 -24.200000
41 -20.200000 -21.200000
42 -33.200000 -20.200000
43 -21.200000 -33.200000
44 29.800000 -21.200000
45 39.800000 29.800000
46 23.800000 39.800000
47 6.800000 23.800000
48 0.800000 6.800000
49 17.800000 0.800000
50 22.800000 17.800000
51 17.800000 22.800000
52 5.800000 17.800000
53 -5.200000 5.800000
54 -20.200000 -5.200000
55 -12.200000 -20.200000
56 43.800000 -12.200000
57 46.800000 43.800000
58 28.800000 46.800000
59 6.800000 28.800000
60 -8.200000 6.800000
> 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/rcomp/tmp/7f5or1293210140.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/8pe5b1293210140.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/9pe5b1293210140.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/rcomp/tmp/10pe5b1293210140.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/rcomp/tmp/11ax3h1293210140.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/rcomp/tmp/12efk51293210140.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/rcomp/tmp/13kghh1293210140.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/rcomp/tmp/14dqyk1293210140.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/rcomp/tmp/15hqxq1293210140.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/rcomp/tmp/16krdv1293210140.tab")
+ }
>
> try(system("convert tmp/10dqz1293210140.ps tmp/10dqz1293210140.png",intern=TRUE))
character(0)
> try(system("convert tmp/2b5721293210140.ps tmp/2b5721293210140.png",intern=TRUE))
character(0)
> try(system("convert tmp/3b5721293210140.ps tmp/3b5721293210140.png",intern=TRUE))
character(0)
> try(system("convert tmp/4b5721293210140.ps tmp/4b5721293210140.png",intern=TRUE))
character(0)
> try(system("convert tmp/54w7o1293210140.ps tmp/54w7o1293210140.png",intern=TRUE))
character(0)
> try(system("convert tmp/64w7o1293210140.ps tmp/64w7o1293210140.png",intern=TRUE))
character(0)
> try(system("convert tmp/7f5or1293210140.ps tmp/7f5or1293210140.png",intern=TRUE))
character(0)
> try(system("convert tmp/8pe5b1293210140.ps tmp/8pe5b1293210140.png",intern=TRUE))
character(0)
> try(system("convert tmp/9pe5b1293210140.ps tmp/9pe5b1293210140.png",intern=TRUE))
character(0)
> try(system("convert tmp/10pe5b1293210140.ps tmp/10pe5b1293210140.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
3.110 0.810 3.866