R version 2.9.0 (2009-04-17)
Copyright (C) 2009 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(2360,2,2214,2,2825,2,2355,2,2333,2,3016,2,2155,2,2172,2,2150,2,2533,2,2058,2,2160,2,2260,2,2498,2,2695,2,2799,2,2947,2,2930,2,2318,2,2540,2,2570,2,2669,2,2450,2,2842,2,3440,2,2678,2,2981,2,2260,2.21,2844,2.25,2546,2.25,2456,2.45,2295,2.5,2379,2.5,2479,2.64,2057,2.75,2280,2.93,2351,3,2276,3.17,2548,3.25,2311,3.39,2201,3.5,2725,3.5,2408,3.65,2139,3.75,1898,3.75,2537,3.9,2069,4,2063,4,2524,4,2437,4,2189,4,2793,4,2074,4,2622,4,2278,4,2144,4,2427,4,2139,4,1828,4.18,2072,4.25,1800,4.25),dim=c(2,61),dimnames=list(c('Y','X'),1:61))
> y <- array(NA,dim=c(2,61),dimnames=list(c('Y','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])
+ }
+ }
> 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
Y X
1 2360 2.00
2 2214 2.00
3 2825 2.00
4 2355 2.00
5 2333 2.00
6 3016 2.00
7 2155 2.00
8 2172 2.00
9 2150 2.00
10 2533 2.00
11 2058 2.00
12 2160 2.00
13 2260 2.00
14 2498 2.00
15 2695 2.00
16 2799 2.00
17 2947 2.00
18 2930 2.00
19 2318 2.00
20 2540 2.00
21 2570 2.00
22 2669 2.00
23 2450 2.00
24 2842 2.00
25 3440 2.00
26 2678 2.00
27 2981 2.00
28 2260 2.21
29 2844 2.25
30 2546 2.25
31 2456 2.45
32 2295 2.50
33 2379 2.50
34 2479 2.64
35 2057 2.75
36 2280 2.93
37 2351 3.00
38 2276 3.17
39 2548 3.25
40 2311 3.39
41 2201 3.50
42 2725 3.50
43 2408 3.65
44 2139 3.75
45 1898 3.75
46 2537 3.90
47 2069 4.00
48 2063 4.00
49 2524 4.00
50 2437 4.00
51 2189 4.00
52 2793 4.00
53 2074 4.00
54 2622 4.00
55 2278 4.00
56 2144 4.00
57 2427 4.00
58 2139 4.00
59 1828 4.18
60 2072 4.25
61 1800 4.25
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X
2861.3 -157.8
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-487.74 -185.74 -41.15 199.51 894.26
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 2861.33 123.83 23.106 < 2e-16 ***
X -157.80 41.91 -3.765 0.000386 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 288.5 on 59 degrees of freedom
Multiple R-squared: 0.1937, Adjusted R-squared: 0.18
F-statistic: 14.17 on 1 and 59 DF, p-value: 0.0003863
> 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,] 0.5372874 0.92542520 0.46271260
[2,] 0.8048136 0.39037281 0.19518641
[3,] 0.8119234 0.37615316 0.18807658
[4,] 0.7972935 0.40541308 0.20270654
[5,] 0.7883262 0.42334757 0.21167378
[6,] 0.7141169 0.57176629 0.28588315
[7,] 0.7695895 0.46082105 0.23041053
[8,] 0.7667418 0.46651631 0.23325816
[9,] 0.7311538 0.53769234 0.26884617
[10,] 0.6730808 0.65383850 0.32691925
[11,] 0.6715439 0.65691220 0.32845610
[12,] 0.7098760 0.58024809 0.29012404
[13,] 0.8081701 0.38365981 0.19182991
[14,] 0.8575721 0.28485571 0.14242786
[15,] 0.8393214 0.32135721 0.16067860
[16,] 0.7915176 0.41696490 0.20848245
[17,] 0.7376270 0.52474597 0.26237299
[18,] 0.6882407 0.62351864 0.31175932
[19,] 0.6366700 0.72666001 0.36333001
[20,] 0.6362866 0.72742688 0.36371344
[21,] 0.9655330 0.06893408 0.03446704
[22,] 0.9513231 0.09735372 0.04867686
[23,] 0.9706035 0.05879308 0.02939654
[24,] 0.9622549 0.07549020 0.03774510
[25,] 0.9728526 0.05429473 0.02714737
[26,] 0.9600559 0.07988820 0.03994410
[27,] 0.9417681 0.11646372 0.05823186
[28,] 0.9216773 0.15664547 0.07832274
[29,] 0.8900860 0.21982790 0.10991395
[30,] 0.8533846 0.29323078 0.14661539
[31,] 0.8691398 0.26172044 0.13086022
[32,] 0.8384353 0.32312934 0.16156467
[33,] 0.7998667 0.40026654 0.20013327
[34,] 0.7715822 0.45683564 0.22841782
[35,] 0.7300654 0.53986916 0.26993458
[36,] 0.6796890 0.64062193 0.32031097
[37,] 0.6705226 0.65895480 0.32947740
[38,] 0.6688131 0.66237376 0.33118688
[39,] 0.5909803 0.81803936 0.40901968
[40,] 0.5573669 0.88526610 0.44263305
[41,] 0.8547090 0.29058192 0.14529096
[42,] 0.8110017 0.37799652 0.18899826
[43,] 0.7972465 0.40550700 0.20275350
[44,] 0.7977650 0.40446998 0.20223499
[45,] 0.7641555 0.47168904 0.23584452
[46,] 0.6922705 0.61545892 0.30772946
[47,] 0.6156247 0.76875064 0.38437532
[48,] 0.8466578 0.30668446 0.15334223
[49,] 0.8274435 0.34511292 0.17255646
[50,] 0.9200105 0.15997890 0.07998945
[51,] 0.8397518 0.32049637 0.16024819
[52,] 0.7234957 0.55300856 0.27650428
> postscript(file="/var/www/html/rcomp/tmp/1akuu1258652704.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2usio1258652704.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3zci71258652704.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4xosu1258652704.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/56mwo1258652704.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
-185.736686 -331.736686 279.263314 -190.736686 -212.736686 470.263314
7 8 9 10 11 12
-390.736686 -373.736686 -395.736686 -12.736686 -487.736686 -385.736686
13 14 15 16 17 18
-285.736686 -47.736686 149.263314 253.263314 401.263314 384.263314
19 20 21 22 23 24
-227.736686 -5.736686 24.263314 123.263314 -95.736686 296.263314
25 26 27 28 29 30
894.263314 132.263314 435.263314 -252.599602 337.712224 39.712224
31 32 33 34 35 36
-18.728649 -171.838867 -87.838867 34.252523 -370.389957 -118.986742
37 38 39 40 41 42
-36.941047 -85.115789 199.507862 -15.400748 -108.043228 415.956772
43 44 45 46 47 48
122.626118 -130.594318 -371.594318 291.075028 -161.145409 -167.145409
49 50 51 52 53 54
293.854591 206.854591 -41.145409 562.854591 -156.145409 391.854591
55 56 57 58 59 60
47.854591 -86.145409 196.854591 -91.145409 -373.742194 -118.696499
61
-390.696499
> postscript(file="/var/www/html/rcomp/tmp/606n41258652704.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 -185.736686 NA
1 -331.736686 -185.736686
2 279.263314 -331.736686
3 -190.736686 279.263314
4 -212.736686 -190.736686
5 470.263314 -212.736686
6 -390.736686 470.263314
7 -373.736686 -390.736686
8 -395.736686 -373.736686
9 -12.736686 -395.736686
10 -487.736686 -12.736686
11 -385.736686 -487.736686
12 -285.736686 -385.736686
13 -47.736686 -285.736686
14 149.263314 -47.736686
15 253.263314 149.263314
16 401.263314 253.263314
17 384.263314 401.263314
18 -227.736686 384.263314
19 -5.736686 -227.736686
20 24.263314 -5.736686
21 123.263314 24.263314
22 -95.736686 123.263314
23 296.263314 -95.736686
24 894.263314 296.263314
25 132.263314 894.263314
26 435.263314 132.263314
27 -252.599602 435.263314
28 337.712224 -252.599602
29 39.712224 337.712224
30 -18.728649 39.712224
31 -171.838867 -18.728649
32 -87.838867 -171.838867
33 34.252523 -87.838867
34 -370.389957 34.252523
35 -118.986742 -370.389957
36 -36.941047 -118.986742
37 -85.115789 -36.941047
38 199.507862 -85.115789
39 -15.400748 199.507862
40 -108.043228 -15.400748
41 415.956772 -108.043228
42 122.626118 415.956772
43 -130.594318 122.626118
44 -371.594318 -130.594318
45 291.075028 -371.594318
46 -161.145409 291.075028
47 -167.145409 -161.145409
48 293.854591 -167.145409
49 206.854591 293.854591
50 -41.145409 206.854591
51 562.854591 -41.145409
52 -156.145409 562.854591
53 391.854591 -156.145409
54 47.854591 391.854591
55 -86.145409 47.854591
56 196.854591 -86.145409
57 -91.145409 196.854591
58 -373.742194 -91.145409
59 -118.696499 -373.742194
60 -390.696499 -118.696499
61 NA -390.696499
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -331.736686 -185.736686
[2,] 279.263314 -331.736686
[3,] -190.736686 279.263314
[4,] -212.736686 -190.736686
[5,] 470.263314 -212.736686
[6,] -390.736686 470.263314
[7,] -373.736686 -390.736686
[8,] -395.736686 -373.736686
[9,] -12.736686 -395.736686
[10,] -487.736686 -12.736686
[11,] -385.736686 -487.736686
[12,] -285.736686 -385.736686
[13,] -47.736686 -285.736686
[14,] 149.263314 -47.736686
[15,] 253.263314 149.263314
[16,] 401.263314 253.263314
[17,] 384.263314 401.263314
[18,] -227.736686 384.263314
[19,] -5.736686 -227.736686
[20,] 24.263314 -5.736686
[21,] 123.263314 24.263314
[22,] -95.736686 123.263314
[23,] 296.263314 -95.736686
[24,] 894.263314 296.263314
[25,] 132.263314 894.263314
[26,] 435.263314 132.263314
[27,] -252.599602 435.263314
[28,] 337.712224 -252.599602
[29,] 39.712224 337.712224
[30,] -18.728649 39.712224
[31,] -171.838867 -18.728649
[32,] -87.838867 -171.838867
[33,] 34.252523 -87.838867
[34,] -370.389957 34.252523
[35,] -118.986742 -370.389957
[36,] -36.941047 -118.986742
[37,] -85.115789 -36.941047
[38,] 199.507862 -85.115789
[39,] -15.400748 199.507862
[40,] -108.043228 -15.400748
[41,] 415.956772 -108.043228
[42,] 122.626118 415.956772
[43,] -130.594318 122.626118
[44,] -371.594318 -130.594318
[45,] 291.075028 -371.594318
[46,] -161.145409 291.075028
[47,] -167.145409 -161.145409
[48,] 293.854591 -167.145409
[49,] 206.854591 293.854591
[50,] -41.145409 206.854591
[51,] 562.854591 -41.145409
[52,] -156.145409 562.854591
[53,] 391.854591 -156.145409
[54,] 47.854591 391.854591
[55,] -86.145409 47.854591
[56,] 196.854591 -86.145409
[57,] -91.145409 196.854591
[58,] -373.742194 -91.145409
[59,] -118.696499 -373.742194
[60,] -390.696499 -118.696499
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -331.736686 -185.736686
2 279.263314 -331.736686
3 -190.736686 279.263314
4 -212.736686 -190.736686
5 470.263314 -212.736686
6 -390.736686 470.263314
7 -373.736686 -390.736686
8 -395.736686 -373.736686
9 -12.736686 -395.736686
10 -487.736686 -12.736686
11 -385.736686 -487.736686
12 -285.736686 -385.736686
13 -47.736686 -285.736686
14 149.263314 -47.736686
15 253.263314 149.263314
16 401.263314 253.263314
17 384.263314 401.263314
18 -227.736686 384.263314
19 -5.736686 -227.736686
20 24.263314 -5.736686
21 123.263314 24.263314
22 -95.736686 123.263314
23 296.263314 -95.736686
24 894.263314 296.263314
25 132.263314 894.263314
26 435.263314 132.263314
27 -252.599602 435.263314
28 337.712224 -252.599602
29 39.712224 337.712224
30 -18.728649 39.712224
31 -171.838867 -18.728649
32 -87.838867 -171.838867
33 34.252523 -87.838867
34 -370.389957 34.252523
35 -118.986742 -370.389957
36 -36.941047 -118.986742
37 -85.115789 -36.941047
38 199.507862 -85.115789
39 -15.400748 199.507862
40 -108.043228 -15.400748
41 415.956772 -108.043228
42 122.626118 415.956772
43 -130.594318 122.626118
44 -371.594318 -130.594318
45 291.075028 -371.594318
46 -161.145409 291.075028
47 -167.145409 -161.145409
48 293.854591 -167.145409
49 206.854591 293.854591
50 -41.145409 206.854591
51 562.854591 -41.145409
52 -156.145409 562.854591
53 391.854591 -156.145409
54 47.854591 391.854591
55 -86.145409 47.854591
56 196.854591 -86.145409
57 -91.145409 196.854591
58 -373.742194 -91.145409
59 -118.696499 -373.742194
60 -390.696499 -118.696499
> 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/7eigt1258652704.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8pcdo1258652704.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9vy9e1258652704.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10kot81258652704.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/118ipb1258652704.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/126ye91258652704.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/13qso41258652704.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/14seop1258652704.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/15rv2x1258652704.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/16vgbq1258652704.tab")
+ }
> system("convert tmp/1akuu1258652704.ps tmp/1akuu1258652704.png")
> system("convert tmp/2usio1258652704.ps tmp/2usio1258652704.png")
> system("convert tmp/3zci71258652704.ps tmp/3zci71258652704.png")
> system("convert tmp/4xosu1258652704.ps tmp/4xosu1258652704.png")
> system("convert tmp/56mwo1258652704.ps tmp/56mwo1258652704.png")
> system("convert tmp/606n41258652704.ps tmp/606n41258652704.png")
> system("convert tmp/7eigt1258652704.ps tmp/7eigt1258652704.png")
> system("convert tmp/8pcdo1258652704.ps tmp/8pcdo1258652704.png")
> system("convert tmp/9vy9e1258652704.ps tmp/9vy9e1258652704.png")
> system("convert tmp/10kot81258652704.ps tmp/10kot81258652704.png")
>
>
> proc.time()
user system elapsed
2.556 1.616 5.769