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.
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> x <- array(list(19876,45335,48674,156392,100837,101605,532850,294189,80763,105995,25045,90474,48481,50730,68694,207716,99132,104012,422632,364974,82687,66834,28408,97073,40284,24421,116346,72120,108751,91738,402216,390070,106045,110070,70668,167841,28607,95371,30605,131063,81214,85451,455196,454570,63114,74287,42350,113375),dim=c(1,48),dimnames=list(c(''),1:48))
> y <- array(NA,dim=c(1,48),dimnames=list(c(''),1:48))
> 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 = 'Include Monthly 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
M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 19876 1 0 0 0 0 0 0 0 0 0 0 1
2 45335 0 1 0 0 0 0 0 0 0 0 0 2
3 48674 0 0 1 0 0 0 0 0 0 0 0 3
4 156392 0 0 0 1 0 0 0 0 0 0 0 4
5 100837 0 0 0 0 1 0 0 0 0 0 0 5
6 101605 0 0 0 0 0 1 0 0 0 0 0 6
7 532850 0 0 0 0 0 0 1 0 0 0 0 7
8 294189 0 0 0 0 0 0 0 1 0 0 0 8
9 80763 0 0 0 0 0 0 0 0 1 0 0 9
10 105995 0 0 0 0 0 0 0 0 0 1 0 10
11 25045 0 0 0 0 0 0 0 0 0 0 1 11
12 90474 0 0 0 0 0 0 0 0 0 0 0 12
13 48481 1 0 0 0 0 0 0 0 0 0 0 13
14 50730 0 1 0 0 0 0 0 0 0 0 0 14
15 68694 0 0 1 0 0 0 0 0 0 0 0 15
16 207716 0 0 0 1 0 0 0 0 0 0 0 16
17 99132 0 0 0 0 1 0 0 0 0 0 0 17
18 104012 0 0 0 0 0 1 0 0 0 0 0 18
19 422632 0 0 0 0 0 0 1 0 0 0 0 19
20 364974 0 0 0 0 0 0 0 1 0 0 0 20
21 82687 0 0 0 0 0 0 0 0 1 0 0 21
22 66834 0 0 0 0 0 0 0 0 0 1 0 22
23 28408 0 0 0 0 0 0 0 0 0 0 1 23
24 97073 0 0 0 0 0 0 0 0 0 0 0 24
25 40284 1 0 0 0 0 0 0 0 0 0 0 25
26 24421 0 1 0 0 0 0 0 0 0 0 0 26
27 116346 0 0 1 0 0 0 0 0 0 0 0 27
28 72120 0 0 0 1 0 0 0 0 0 0 0 28
29 108751 0 0 0 0 1 0 0 0 0 0 0 29
30 91738 0 0 0 0 0 1 0 0 0 0 0 30
31 402216 0 0 0 0 0 0 1 0 0 0 0 31
32 390070 0 0 0 0 0 0 0 1 0 0 0 32
33 106045 0 0 0 0 0 0 0 0 1 0 0 33
34 110070 0 0 0 0 0 0 0 0 0 1 0 34
35 70668 0 0 0 0 0 0 0 0 0 0 1 35
36 167841 0 0 0 0 0 0 0 0 0 0 0 36
37 28607 1 0 0 0 0 0 0 0 0 0 0 37
38 95371 0 1 0 0 0 0 0 0 0 0 0 38
39 30605 0 0 1 0 0 0 0 0 0 0 0 39
40 131063 0 0 0 1 0 0 0 0 0 0 0 40
41 81214 0 0 0 0 1 0 0 0 0 0 0 41
42 85451 0 0 0 0 0 1 0 0 0 0 0 42
43 455196 0 0 0 0 0 0 1 0 0 0 0 43
44 454570 0 0 0 0 0 0 0 1 0 0 0 44
45 63114 0 0 0 0 0 0 0 0 1 0 0 45
46 74287 0 0 0 0 0 0 0 0 0 1 0 46
47 42350 0 0 0 0 0 0 0 0 0 0 1 47
48 113375 0 0 0 0 0 0 0 0 0 0 0 48
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) M1 M2 M3 M4 M5
112634.5 -81208.1 -61707.7 -49744.1 25847.0 -18644.1
M6 M7 M8 M9 M10 M11
-20578.0 336792.1 259367.5 -33582.9 -27590.5 -75421.1
t
151.9
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-79028 -15440 -2162 13676 82360
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 112634.5 21955.1 5.130 1.08e-05 ***
M1 -81208.1 26449.4 -3.070 0.00412 **
M2 -61707.7 26386.8 -2.339 0.02520 *
M3 -49744.1 26330.0 -1.889 0.06716 .
M4 25847.0 26279.1 0.984 0.33208
M5 -18644.1 26234.1 -0.711 0.48199
M6 -20578.0 26195.0 -0.786 0.43741
M7 336792.1 26161.9 12.873 7.79e-15 ***
M8 259367.5 26134.8 9.924 1.03e-11 ***
M9 -33582.9 26113.7 -1.286 0.20688
M10 -27590.5 26098.6 -1.057 0.29768
M11 -75421.1 26089.6 -2.891 0.00656 **
t 151.9 396.9 0.383 0.70429
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 36890 on 35 degrees of freedom
Multiple R-squared: 0.9431, Adjusted R-squared: 0.9237
F-statistic: 48.39 on 12 and 35 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,] 0.09362683 0.18725366 0.90637317
[2,] 0.06815995 0.13631989 0.93184005
[3,] 0.03589997 0.07179995 0.96410003
[4,] 0.62597091 0.74805819 0.37402909
[5,] 0.67911521 0.64176959 0.32088479
[6,] 0.55653576 0.88692848 0.44346424
[7,] 0.49199172 0.98398344 0.50800828
[8,] 0.37935006 0.75870012 0.62064994
[9,] 0.31194647 0.62389294 0.68805353
[10,] 0.21176428 0.42352856 0.78823572
[11,] 0.24414208 0.48828415 0.75585792
[12,] 0.38336644 0.76673287 0.61663356
[13,] 0.68431712 0.63136576 0.31568288
[14,] 0.56806850 0.86386299 0.43193150
[15,] 0.42175001 0.84350001 0.57824999
[16,] 0.52484949 0.95030102 0.47515051
[17,] 0.98822911 0.02354177 0.01177089
> postscript(file="/var/www/rcomp/tmp/1ou7z1292767917.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/2h4o21292767917.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3h4o21292767917.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/4h4o21292767917.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/5rd651292767917.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 = 48
Frequency = 1
1 2 3 4 5 6
-11702.2375 -5895.4875 -14671.9875 17303.0125 6087.2625 8637.2625
7 8 9 10 11 12
82360.2625 -79027.9875 344.5125 19432.2625 -13838.9875 -23982.9875
13 14 15 16 17 18
15080.2542 -2322.9958 3525.5042 66804.5042 2559.7542 9221.7542
19 20 21 22 23 24
-29680.2458 -10065.4958 446.0042 -21551.2458 -12298.4958 -19206.4958
25 26 27 28 29 30
5060.7458 -30454.5042 49354.9958 -70614.0042 10356.2458 -4874.7542
31 32 33 34 35 36
-51918.7542 13207.9958 21981.4958 19862.2458 28138.9958 49738.9958
37 38 39 40 41 42
-8438.7625 38672.9875 -38208.5125 -13493.5125 -19003.2625 -12984.2625
43 44 45 46 47 48
-761.2625 75885.4875 -22772.0125 -17743.2625 -2001.5125 -6549.5125
> postscript(file="/var/www/rcomp/tmp/6rd651292767917.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 = 48
Frequency = 1
lag(myerror, k = 1) myerror
0 -11702.2375 NA
1 -5895.4875 -11702.2375
2 -14671.9875 -5895.4875
3 17303.0125 -14671.9875
4 6087.2625 17303.0125
5 8637.2625 6087.2625
6 82360.2625 8637.2625
7 -79027.9875 82360.2625
8 344.5125 -79027.9875
9 19432.2625 344.5125
10 -13838.9875 19432.2625
11 -23982.9875 -13838.9875
12 15080.2542 -23982.9875
13 -2322.9958 15080.2542
14 3525.5042 -2322.9958
15 66804.5042 3525.5042
16 2559.7542 66804.5042
17 9221.7542 2559.7542
18 -29680.2458 9221.7542
19 -10065.4958 -29680.2458
20 446.0042 -10065.4958
21 -21551.2458 446.0042
22 -12298.4958 -21551.2458
23 -19206.4958 -12298.4958
24 5060.7458 -19206.4958
25 -30454.5042 5060.7458
26 49354.9958 -30454.5042
27 -70614.0042 49354.9958
28 10356.2458 -70614.0042
29 -4874.7542 10356.2458
30 -51918.7542 -4874.7542
31 13207.9958 -51918.7542
32 21981.4958 13207.9958
33 19862.2458 21981.4958
34 28138.9958 19862.2458
35 49738.9958 28138.9958
36 -8438.7625 49738.9958
37 38672.9875 -8438.7625
38 -38208.5125 38672.9875
39 -13493.5125 -38208.5125
40 -19003.2625 -13493.5125
41 -12984.2625 -19003.2625
42 -761.2625 -12984.2625
43 75885.4875 -761.2625
44 -22772.0125 75885.4875
45 -17743.2625 -22772.0125
46 -2001.5125 -17743.2625
47 -6549.5125 -2001.5125
48 NA -6549.5125
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -5895.4875 -11702.2375
[2,] -14671.9875 -5895.4875
[3,] 17303.0125 -14671.9875
[4,] 6087.2625 17303.0125
[5,] 8637.2625 6087.2625
[6,] 82360.2625 8637.2625
[7,] -79027.9875 82360.2625
[8,] 344.5125 -79027.9875
[9,] 19432.2625 344.5125
[10,] -13838.9875 19432.2625
[11,] -23982.9875 -13838.9875
[12,] 15080.2542 -23982.9875
[13,] -2322.9958 15080.2542
[14,] 3525.5042 -2322.9958
[15,] 66804.5042 3525.5042
[16,] 2559.7542 66804.5042
[17,] 9221.7542 2559.7542
[18,] -29680.2458 9221.7542
[19,] -10065.4958 -29680.2458
[20,] 446.0042 -10065.4958
[21,] -21551.2458 446.0042
[22,] -12298.4958 -21551.2458
[23,] -19206.4958 -12298.4958
[24,] 5060.7458 -19206.4958
[25,] -30454.5042 5060.7458
[26,] 49354.9958 -30454.5042
[27,] -70614.0042 49354.9958
[28,] 10356.2458 -70614.0042
[29,] -4874.7542 10356.2458
[30,] -51918.7542 -4874.7542
[31,] 13207.9958 -51918.7542
[32,] 21981.4958 13207.9958
[33,] 19862.2458 21981.4958
[34,] 28138.9958 19862.2458
[35,] 49738.9958 28138.9958
[36,] -8438.7625 49738.9958
[37,] 38672.9875 -8438.7625
[38,] -38208.5125 38672.9875
[39,] -13493.5125 -38208.5125
[40,] -19003.2625 -13493.5125
[41,] -12984.2625 -19003.2625
[42,] -761.2625 -12984.2625
[43,] 75885.4875 -761.2625
[44,] -22772.0125 75885.4875
[45,] -17743.2625 -22772.0125
[46,] -2001.5125 -17743.2625
[47,] -6549.5125 -2001.5125
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -5895.4875 -11702.2375
2 -14671.9875 -5895.4875
3 17303.0125 -14671.9875
4 6087.2625 17303.0125
5 8637.2625 6087.2625
6 82360.2625 8637.2625
7 -79027.9875 82360.2625
8 344.5125 -79027.9875
9 19432.2625 344.5125
10 -13838.9875 19432.2625
11 -23982.9875 -13838.9875
12 15080.2542 -23982.9875
13 -2322.9958 15080.2542
14 3525.5042 -2322.9958
15 66804.5042 3525.5042
16 2559.7542 66804.5042
17 9221.7542 2559.7542
18 -29680.2458 9221.7542
19 -10065.4958 -29680.2458
20 446.0042 -10065.4958
21 -21551.2458 446.0042
22 -12298.4958 -21551.2458
23 -19206.4958 -12298.4958
24 5060.7458 -19206.4958
25 -30454.5042 5060.7458
26 49354.9958 -30454.5042
27 -70614.0042 49354.9958
28 10356.2458 -70614.0042
29 -4874.7542 10356.2458
30 -51918.7542 -4874.7542
31 13207.9958 -51918.7542
32 21981.4958 13207.9958
33 19862.2458 21981.4958
34 28138.9958 19862.2458
35 49738.9958 28138.9958
36 -8438.7625 49738.9958
37 38672.9875 -8438.7625
38 -38208.5125 38672.9875
39 -13493.5125 -38208.5125
40 -19003.2625 -13493.5125
41 -12984.2625 -19003.2625
42 -761.2625 -12984.2625
43 75885.4875 -761.2625
44 -22772.0125 75885.4875
45 -17743.2625 -22772.0125
46 -2001.5125 -17743.2625
47 -6549.5125 -2001.5125
> 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/7k4nq1292767917.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/8k4nq1292767917.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/9dd4t1292767917.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/rcomp/tmp/10dd4t1292767917.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11ywlz1292767917.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/122wj51292767917.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/13qxgh1292767917.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/1417yk1292767917.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/15m7e71292767917.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/16jhug1292767917.tab")
+ }
>
> try(system("convert tmp/1ou7z1292767917.ps tmp/1ou7z1292767917.png",intern=TRUE))
character(0)
> try(system("convert tmp/2h4o21292767917.ps tmp/2h4o21292767917.png",intern=TRUE))
character(0)
> try(system("convert tmp/3h4o21292767917.ps tmp/3h4o21292767917.png",intern=TRUE))
character(0)
> try(system("convert tmp/4h4o21292767917.ps tmp/4h4o21292767917.png",intern=TRUE))
character(0)
> try(system("convert tmp/5rd651292767917.ps tmp/5rd651292767917.png",intern=TRUE))
character(0)
> try(system("convert tmp/6rd651292767917.ps tmp/6rd651292767917.png",intern=TRUE))
character(0)
> try(system("convert tmp/7k4nq1292767917.ps tmp/7k4nq1292767917.png",intern=TRUE))
character(0)
> try(system("convert tmp/8k4nq1292767917.ps tmp/8k4nq1292767917.png",intern=TRUE))
character(0)
> try(system("convert tmp/9dd4t1292767917.ps tmp/9dd4t1292767917.png",intern=TRUE))
character(0)
> try(system("convert tmp/10dd4t1292767917.ps tmp/10dd4t1292767917.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
2.870 1.620 4.527