R version 2.11.1 (2010-05-31)
Copyright (C) 2010 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.
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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(563668,276444,586111,289742,604378,303725,600991,298305,544686,266795,537034,259497,551531,266148,563250,271037,574761,276239,580112,279681,575093,277509,557560,271115,564478,275902,580523,287224,596594,300713,586570,293860,536214,264221,523597,256167,536535,262572,536322,263276,532638,264291,528222,263903,516141,260376,501866,255603,506174,261076,517945,270976,533590,285257,528379,280445,477580,250741,469357,243803,490243,253158,492622,255542,507561,262522,516922,268381,514258,267153,509846,266424,527070,276427,541657,286994,564591,303598,555362,296806,498662,263290,511038,264981,525919,272566,531673,276475,548854,284678,560576,291542,557274,291413,565742,295916,587625,309119,619916,327616),dim=c(2,50),dimnames=list(c('Totaal','vrouwen
'),1:50))
> y <- array(NA,dim=c(2,50),dimnames=list(c('Totaal','vrouwen
'),1:50))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par3 = '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
> 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
Totaal vrouwen\r t
1 563668 276444 1
2 586111 289742 2
3 604378 303725 3
4 600991 298305 4
5 544686 266795 5
6 537034 259497 6
7 551531 266148 7
8 563250 271037 8
9 574761 276239 9
10 580112 279681 10
11 575093 277509 11
12 557560 271115 12
13 564478 275902 13
14 580523 287224 14
15 596594 300713 15
16 586570 293860 16
17 536214 264221 17
18 523597 256167 18
19 536535 262572 19
20 536322 263276 20
21 532638 264291 21
22 528222 263903 22
23 516141 260376 23
24 501866 255603 24
25 506174 261076 25
26 517945 270976 26
27 533590 285257 27
28 528379 280445 28
29 477580 250741 29
30 469357 243803 30
31 490243 253158 31
32 492622 255542 32
33 507561 262522 33
34 516922 268381 34
35 514258 267153 35
36 509846 266424 36
37 527070 276427 37
38 541657 286994 38
39 564591 303598 39
40 555362 296806 40
41 498662 263290 41
42 511038 264981 42
43 525919 272566 43
44 531673 276475 44
45 548854 284678 45
46 560576 291542 46
47 557274 291413 47
48 565742 295916 48
49 587625 309119 49
50 619916 327616 50
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) `vrouwen\r` t
58274.072 1.856 -1074.752
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-25089.7 -6332.6 -279.2 8255.9 13597.2
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 5.827e+04 2.276e+04 2.56 0.0137 *
`vrouwen\r` 1.856e+00 8.352e-02 22.22 < 2e-16 ***
t -1.075e+03 9.872e+01 -10.89 1.92e-14 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 9907 on 47 degrees of freedom
Multiple R-squared: 0.9203, Adjusted R-squared: 0.9169
F-statistic: 271.3 on 2 and 47 DF, p-value: < 2.2e-16
> 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,] 0.035570795 0.0711415905 0.9644292048
[2,] 0.020387771 0.0407755413 0.9796122294
[3,] 0.014971256 0.0299425122 0.9850287439
[4,] 0.009205454 0.0184109089 0.9907945456
[5,] 0.003386527 0.0067730532 0.9966134734
[6,] 0.001432241 0.0028644812 0.9985677594
[7,] 0.004830295 0.0096605903 0.9951697048
[8,] 0.007734815 0.0154696295 0.9922651853
[9,] 0.010114250 0.0202285005 0.9898857498
[10,] 0.014020524 0.0280410486 0.9859794757
[11,] 0.010889763 0.0217795263 0.9891102369
[12,] 0.022266962 0.0445339247 0.9777330376
[13,] 0.030517712 0.0610354239 0.9694822880
[14,] 0.039485791 0.0789715813 0.9605142094
[15,] 0.075582275 0.1511645498 0.9244177251
[16,] 0.188106819 0.3762136384 0.8118931808
[17,] 0.504124287 0.9917514261 0.4958757131
[18,] 0.878516972 0.2429660567 0.1214830284
[19,] 0.986407584 0.0271848326 0.0135924163
[20,] 0.998391419 0.0032171627 0.0016085814
[21,] 0.999597123 0.0008057550 0.0004028775
[22,] 0.999756364 0.0004872730 0.0002436365
[23,] 0.999640398 0.0007192037 0.0003596019
[24,] 0.999676888 0.0006462232 0.0003231116
[25,] 0.999441734 0.0011165318 0.0005582659
[26,] 0.998965152 0.0020696957 0.0010348479
[27,] 0.997817213 0.0043655740 0.0021827870
[28,] 0.997854654 0.0042906914 0.0021453457
[29,] 0.998529914 0.0029401713 0.0014700857
[30,] 0.999167825 0.0016643497 0.0008321749
[31,] 0.998765221 0.0024695586 0.0012347793
[32,] 0.999057070 0.0018858592 0.0009429296
[33,] 0.998575062 0.0028498752 0.0014249376
[34,] 0.995876331 0.0082473385 0.0041236692
[35,] 0.988980964 0.0220380728 0.0110190364
[36,] 0.999785480 0.0004290400 0.0002145200
[37,] 0.999594825 0.0008103501 0.0004051751
[38,] 0.998299947 0.0034001059 0.0017000529
[39,] 0.999097395 0.0018052109 0.0009026055
> postscript(file="/var/www/rcomp/tmp/1bb9c1290622953.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/2bb9c1290622953.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/rcomp/tmp/3bb9c1290622953.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/4m28x1290622953.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/5m28x1290622953.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 = 50
Frequency = 1
1 2 3 4 5 6
-6598.6931 -7761.4190 -14371.4735 -6624.4507 -3373.5856 3593.9190
7 8 9 10 11 12
6821.7200 10541.7120 13472.7905 13510.3481 13597.2320 9005.9541
13 14 15 16 17 18
8114.2535 4220.8929 -3668.3202 101.2848 5828.6598 9234.2656
19 20 21 22 23 24
11359.6313 10914.7912 6421.7495 3800.6113 -659.6870 -5001.4665
25 26 27 28 29 30
-9776.3516 -15304.5455 -25089.6743 -20295.0716 -14890.0596 -9161.6985
31 32 33 34 35 36
-4563.3974 -5534.2403 -2475.0482 -2913.3316 -2223.4684 -4207.7262
37 38 39 40 41 42
-4474.0834 -8424.1987 -15231.7088 -10780.3170 -4201.4080 6110.9253
43 44 45 46 47 48
7989.2651 7563.0922 10594.4524 10651.9351 8664.1048 9849.4952
49 50
8303.0849 7339.2537
> postscript(file="/var/www/rcomp/tmp/6m28x1290622953.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 = 50
Frequency = 1
lag(myerror, k = 1) myerror
0 -6598.6931 NA
1 -7761.4190 -6598.6931
2 -14371.4735 -7761.4190
3 -6624.4507 -14371.4735
4 -3373.5856 -6624.4507
5 3593.9190 -3373.5856
6 6821.7200 3593.9190
7 10541.7120 6821.7200
8 13472.7905 10541.7120
9 13510.3481 13472.7905
10 13597.2320 13510.3481
11 9005.9541 13597.2320
12 8114.2535 9005.9541
13 4220.8929 8114.2535
14 -3668.3202 4220.8929
15 101.2848 -3668.3202
16 5828.6598 101.2848
17 9234.2656 5828.6598
18 11359.6313 9234.2656
19 10914.7912 11359.6313
20 6421.7495 10914.7912
21 3800.6113 6421.7495
22 -659.6870 3800.6113
23 -5001.4665 -659.6870
24 -9776.3516 -5001.4665
25 -15304.5455 -9776.3516
26 -25089.6743 -15304.5455
27 -20295.0716 -25089.6743
28 -14890.0596 -20295.0716
29 -9161.6985 -14890.0596
30 -4563.3974 -9161.6985
31 -5534.2403 -4563.3974
32 -2475.0482 -5534.2403
33 -2913.3316 -2475.0482
34 -2223.4684 -2913.3316
35 -4207.7262 -2223.4684
36 -4474.0834 -4207.7262
37 -8424.1987 -4474.0834
38 -15231.7088 -8424.1987
39 -10780.3170 -15231.7088
40 -4201.4080 -10780.3170
41 6110.9253 -4201.4080
42 7989.2651 6110.9253
43 7563.0922 7989.2651
44 10594.4524 7563.0922
45 10651.9351 10594.4524
46 8664.1048 10651.9351
47 9849.4952 8664.1048
48 8303.0849 9849.4952
49 7339.2537 8303.0849
50 NA 7339.2537
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -7761.4190 -6598.6931
[2,] -14371.4735 -7761.4190
[3,] -6624.4507 -14371.4735
[4,] -3373.5856 -6624.4507
[5,] 3593.9190 -3373.5856
[6,] 6821.7200 3593.9190
[7,] 10541.7120 6821.7200
[8,] 13472.7905 10541.7120
[9,] 13510.3481 13472.7905
[10,] 13597.2320 13510.3481
[11,] 9005.9541 13597.2320
[12,] 8114.2535 9005.9541
[13,] 4220.8929 8114.2535
[14,] -3668.3202 4220.8929
[15,] 101.2848 -3668.3202
[16,] 5828.6598 101.2848
[17,] 9234.2656 5828.6598
[18,] 11359.6313 9234.2656
[19,] 10914.7912 11359.6313
[20,] 6421.7495 10914.7912
[21,] 3800.6113 6421.7495
[22,] -659.6870 3800.6113
[23,] -5001.4665 -659.6870
[24,] -9776.3516 -5001.4665
[25,] -15304.5455 -9776.3516
[26,] -25089.6743 -15304.5455
[27,] -20295.0716 -25089.6743
[28,] -14890.0596 -20295.0716
[29,] -9161.6985 -14890.0596
[30,] -4563.3974 -9161.6985
[31,] -5534.2403 -4563.3974
[32,] -2475.0482 -5534.2403
[33,] -2913.3316 -2475.0482
[34,] -2223.4684 -2913.3316
[35,] -4207.7262 -2223.4684
[36,] -4474.0834 -4207.7262
[37,] -8424.1987 -4474.0834
[38,] -15231.7088 -8424.1987
[39,] -10780.3170 -15231.7088
[40,] -4201.4080 -10780.3170
[41,] 6110.9253 -4201.4080
[42,] 7989.2651 6110.9253
[43,] 7563.0922 7989.2651
[44,] 10594.4524 7563.0922
[45,] 10651.9351 10594.4524
[46,] 8664.1048 10651.9351
[47,] 9849.4952 8664.1048
[48,] 8303.0849 9849.4952
[49,] 7339.2537 8303.0849
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -7761.4190 -6598.6931
2 -14371.4735 -7761.4190
3 -6624.4507 -14371.4735
4 -3373.5856 -6624.4507
5 3593.9190 -3373.5856
6 6821.7200 3593.9190
7 10541.7120 6821.7200
8 13472.7905 10541.7120
9 13510.3481 13472.7905
10 13597.2320 13510.3481
11 9005.9541 13597.2320
12 8114.2535 9005.9541
13 4220.8929 8114.2535
14 -3668.3202 4220.8929
15 101.2848 -3668.3202
16 5828.6598 101.2848
17 9234.2656 5828.6598
18 11359.6313 9234.2656
19 10914.7912 11359.6313
20 6421.7495 10914.7912
21 3800.6113 6421.7495
22 -659.6870 3800.6113
23 -5001.4665 -659.6870
24 -9776.3516 -5001.4665
25 -15304.5455 -9776.3516
26 -25089.6743 -15304.5455
27 -20295.0716 -25089.6743
28 -14890.0596 -20295.0716
29 -9161.6985 -14890.0596
30 -4563.3974 -9161.6985
31 -5534.2403 -4563.3974
32 -2475.0482 -5534.2403
33 -2913.3316 -2475.0482
34 -2223.4684 -2913.3316
35 -4207.7262 -2223.4684
36 -4474.0834 -4207.7262
37 -8424.1987 -4474.0834
38 -15231.7088 -8424.1987
39 -10780.3170 -15231.7088
40 -4201.4080 -10780.3170
41 6110.9253 -4201.4080
42 7989.2651 6110.9253
43 7563.0922 7989.2651
44 10594.4524 7563.0922
45 10651.9351 10594.4524
46 8664.1048 10651.9351
47 9849.4952 8664.1048
48 8303.0849 9849.4952
49 7339.2537 8303.0849
> 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/7xbp01290622953.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/8qlp31290622953.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/9qlp31290622953.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/rcomp/tmp/10iuoo1290622953.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11lcmu1290622953.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/127dl01290622953.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/1335j91290622953.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/14o5zw1290622953.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/15aog21290622953.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/16vow81290622953.tab")
+ }
>
> try(system("convert tmp/1bb9c1290622953.ps tmp/1bb9c1290622953.png",intern=TRUE))
character(0)
> try(system("convert tmp/2bb9c1290622953.ps tmp/2bb9c1290622953.png",intern=TRUE))
character(0)
> try(system("convert tmp/3bb9c1290622953.ps tmp/3bb9c1290622953.png",intern=TRUE))
character(0)
> try(system("convert tmp/4m28x1290622953.ps tmp/4m28x1290622953.png",intern=TRUE))
character(0)
> try(system("convert tmp/5m28x1290622953.ps tmp/5m28x1290622953.png",intern=TRUE))
character(0)
> try(system("convert tmp/6m28x1290622953.ps tmp/6m28x1290622953.png",intern=TRUE))
character(0)
> try(system("convert tmp/7xbp01290622953.ps tmp/7xbp01290622953.png",intern=TRUE))
character(0)
> try(system("convert tmp/8qlp31290622953.ps tmp/8qlp31290622953.png",intern=TRUE))
character(0)
> try(system("convert tmp/9qlp31290622953.ps tmp/9qlp31290622953.png",intern=TRUE))
character(0)
> try(system("convert tmp/10iuoo1290622953.ps tmp/10iuoo1290622953.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
3.51 2.13 5.61