R version 2.13.0 (2011-04-13)
Copyright (C) 2011 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(112.3,0,117.3,0,111.1,1,102.2,1,104.3,1,122.9,1,107.6,1,121.3,1,131.5,1,89,1,104.4,1,128.9,1,135.9,1,133.3,1,121.3,1,120.5,0,120.4,0,137.9,0,126.1,0,133.2,0,151.1,0,105,0,119,0,140.4,0,156.6,0,137.1,0,122.7,0,125.8,0,139.3,0,134.9,0,149.2,0,132.3,0,149,0,117.2,0,119.6,0,152,0,149.4,0,127.3,0,114.1,0,102.1,0,107.7,0,104.4,0,102.1,0,96,1,109.3,0,90,1,83.9,1,112,1,114.3,1,103.6,1,91.7,1,80.8,1,87.2,1,109.2,1,102.7,1,95.1,1,117.5,1,85.1,1,92.1,1,113.5,1),dim=c(2,60),dimnames=list(c('Promet','Dummy'),1:60))
> y <- array(NA,dim=c(2,60),dimnames=list(c('Promet','Dummy'),1:60))
> 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'
> 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
Promet Dummy
1 112.3 0
2 117.3 0
3 111.1 1
4 102.2 1
5 104.3 1
6 122.9 1
7 107.6 1
8 121.3 1
9 131.5 1
10 89.0 1
11 104.4 1
12 128.9 1
13 135.9 1
14 133.3 1
15 121.3 1
16 120.5 0
17 120.4 0
18 137.9 0
19 126.1 0
20 133.2 0
21 151.1 0
22 105.0 0
23 119.0 0
24 140.4 0
25 156.6 0
26 137.1 0
27 122.7 0
28 125.8 0
29 139.3 0
30 134.9 0
31 149.2 0
32 132.3 0
33 149.0 0
34 117.2 0
35 119.6 0
36 152.0 0
37 149.4 0
38 127.3 0
39 114.1 0
40 102.1 0
41 107.7 0
42 104.4 0
43 102.1 0
44 96.0 1
45 109.3 0
46 90.0 1
47 83.9 1
48 112.0 1
49 114.3 1
50 103.6 1
51 91.7 1
52 80.8 1
53 87.2 1
54 109.2 1
55 102.7 1
56 95.1 1
57 117.5 1
58 85.1 1
59 92.1 1
60 113.5 1
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Dummy
126.95 -20.45
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-25.697 -13.233 -1.621 11.341 29.655
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 126.945 2.885 44.003 < 2e-16 ***
Dummy -20.449 4.150 -4.928 7.29e-06 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 16.06 on 58 degrees of freedom
Multiple R-squared: 0.2951, Adjusted R-squared: 0.283
F-statistic: 24.28 on 1 and 58 DF, p-value: 7.292e-06
> 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,] 0.02308078 0.04616155 0.97691922
[2,] 0.09058063 0.18116125 0.90941937
[3,] 0.03836084 0.07672169 0.96163916
[4,] 0.03596145 0.07192291 0.96403855
[5,] 0.09302489 0.18604979 0.90697511
[6,] 0.22234104 0.44468207 0.77765896
[7,] 0.15761089 0.31522178 0.84238911
[8,] 0.19943928 0.39887856 0.80056072
[9,] 0.33605207 0.67210415 0.66394793
[10,] 0.42770922 0.85541845 0.57229078
[11,] 0.38500405 0.77000809 0.61499595
[12,] 0.31138544 0.62277088 0.68861456
[13,] 0.24341079 0.48682158 0.75658921
[14,] 0.26682965 0.53365931 0.73317035
[15,] 0.20462383 0.40924766 0.79537617
[16,] 0.17009588 0.34019177 0.82990412
[17,] 0.28909156 0.57818312 0.71090844
[18,] 0.36732393 0.73464786 0.63267607
[19,] 0.30939708 0.61879416 0.69060292
[20,] 0.30508215 0.61016431 0.69491785
[21,] 0.51999804 0.96000392 0.48000196
[22,] 0.47449196 0.94898392 0.52550804
[23,] 0.40641941 0.81283882 0.59358059
[24,] 0.33490748 0.66981497 0.66509252
[25,] 0.31138996 0.62277991 0.68861004
[26,] 0.26529869 0.53059738 0.73470131
[27,] 0.35373406 0.70746811 0.64626594
[28,] 0.30237362 0.60474723 0.69762638
[29,] 0.42760921 0.85521843 0.57239079
[30,] 0.38470060 0.76940120 0.61529940
[31,] 0.33074548 0.66149096 0.66925452
[32,] 0.59087778 0.81824444 0.40912222
[33,] 0.88092584 0.23814833 0.11907416
[34,] 0.90880021 0.18239958 0.09119979
[35,] 0.90122700 0.19754601 0.09877300
[36,] 0.90664842 0.18670317 0.09335158
[37,] 0.89133411 0.21733177 0.10866589
[38,] 0.87644982 0.24710035 0.12355018
[39,] 0.86525427 0.26949147 0.13474573
[40,] 0.83124648 0.33750703 0.16875352
[41,] 0.78410046 0.43179909 0.21589954
[42,] 0.76556985 0.46886030 0.23443015
[43,] 0.80301877 0.39396246 0.19698123
[44,] 0.77132808 0.45734383 0.22867192
[45,] 0.77095790 0.45808421 0.22904210
[46,] 0.69294182 0.61411635 0.30705818
[47,] 0.61632768 0.76734465 0.38367232
[48,] 0.68988137 0.62023725 0.31011863
[49,] 0.68030900 0.63938200 0.31969100
[50,] 0.56608004 0.86783991 0.43391996
[51,] 0.39765428 0.79530857 0.60234572
> postscript(file="/var/wessaorg/rcomp/tmp/1nsda1322331008.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/wessaorg/rcomp/tmp/2zn1d1322331008.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/3fsc11322331008.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/4vw7n1322331008.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/59ci31322331008.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$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 = 60
Frequency = 1
1 2 3 4 5 6
-14.6451613 -9.6451613 4.6034483 -4.2965517 -2.1965517 16.4034483
7 8 9 10 11 12
1.1034483 14.8034483 25.0034483 -17.4965517 -2.0965517 22.4034483
13 14 15 16 17 18
29.4034483 26.8034483 14.8034483 -6.4451613 -6.5451613 10.9548387
19 20 21 22 23 24
-0.8451613 6.2548387 24.1548387 -21.9451613 -7.9451613 13.4548387
25 26 27 28 29 30
29.6548387 10.1548387 -4.2451613 -1.1451613 12.3548387 7.9548387
31 32 33 34 35 36
22.2548387 5.3548387 22.0548387 -9.7451613 -7.3451613 25.0548387
37 38 39 40 41 42
22.4548387 0.3548387 -12.8451613 -24.8451613 -19.2451613 -22.5451613
43 44 45 46 47 48
-24.8451613 -10.4965517 -17.6451613 -16.4965517 -22.5965517 5.5034483
49 50 51 52 53 54
7.8034483 -2.8965517 -14.7965517 -25.6965517 -19.2965517 2.7034483
55 56 57 58 59 60
-3.7965517 -11.3965517 11.0034483 -21.3965517 -14.3965517 7.0034483
> postscript(file="/var/wessaorg/rcomp/tmp/6hek81322331008.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 = 60
Frequency = 1
lag(myerror, k = 1) myerror
0 -14.6451613 NA
1 -9.6451613 -14.6451613
2 4.6034483 -9.6451613
3 -4.2965517 4.6034483
4 -2.1965517 -4.2965517
5 16.4034483 -2.1965517
6 1.1034483 16.4034483
7 14.8034483 1.1034483
8 25.0034483 14.8034483
9 -17.4965517 25.0034483
10 -2.0965517 -17.4965517
11 22.4034483 -2.0965517
12 29.4034483 22.4034483
13 26.8034483 29.4034483
14 14.8034483 26.8034483
15 -6.4451613 14.8034483
16 -6.5451613 -6.4451613
17 10.9548387 -6.5451613
18 -0.8451613 10.9548387
19 6.2548387 -0.8451613
20 24.1548387 6.2548387
21 -21.9451613 24.1548387
22 -7.9451613 -21.9451613
23 13.4548387 -7.9451613
24 29.6548387 13.4548387
25 10.1548387 29.6548387
26 -4.2451613 10.1548387
27 -1.1451613 -4.2451613
28 12.3548387 -1.1451613
29 7.9548387 12.3548387
30 22.2548387 7.9548387
31 5.3548387 22.2548387
32 22.0548387 5.3548387
33 -9.7451613 22.0548387
34 -7.3451613 -9.7451613
35 25.0548387 -7.3451613
36 22.4548387 25.0548387
37 0.3548387 22.4548387
38 -12.8451613 0.3548387
39 -24.8451613 -12.8451613
40 -19.2451613 -24.8451613
41 -22.5451613 -19.2451613
42 -24.8451613 -22.5451613
43 -10.4965517 -24.8451613
44 -17.6451613 -10.4965517
45 -16.4965517 -17.6451613
46 -22.5965517 -16.4965517
47 5.5034483 -22.5965517
48 7.8034483 5.5034483
49 -2.8965517 7.8034483
50 -14.7965517 -2.8965517
51 -25.6965517 -14.7965517
52 -19.2965517 -25.6965517
53 2.7034483 -19.2965517
54 -3.7965517 2.7034483
55 -11.3965517 -3.7965517
56 11.0034483 -11.3965517
57 -21.3965517 11.0034483
58 -14.3965517 -21.3965517
59 7.0034483 -14.3965517
60 NA 7.0034483
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -9.6451613 -14.6451613
[2,] 4.6034483 -9.6451613
[3,] -4.2965517 4.6034483
[4,] -2.1965517 -4.2965517
[5,] 16.4034483 -2.1965517
[6,] 1.1034483 16.4034483
[7,] 14.8034483 1.1034483
[8,] 25.0034483 14.8034483
[9,] -17.4965517 25.0034483
[10,] -2.0965517 -17.4965517
[11,] 22.4034483 -2.0965517
[12,] 29.4034483 22.4034483
[13,] 26.8034483 29.4034483
[14,] 14.8034483 26.8034483
[15,] -6.4451613 14.8034483
[16,] -6.5451613 -6.4451613
[17,] 10.9548387 -6.5451613
[18,] -0.8451613 10.9548387
[19,] 6.2548387 -0.8451613
[20,] 24.1548387 6.2548387
[21,] -21.9451613 24.1548387
[22,] -7.9451613 -21.9451613
[23,] 13.4548387 -7.9451613
[24,] 29.6548387 13.4548387
[25,] 10.1548387 29.6548387
[26,] -4.2451613 10.1548387
[27,] -1.1451613 -4.2451613
[28,] 12.3548387 -1.1451613
[29,] 7.9548387 12.3548387
[30,] 22.2548387 7.9548387
[31,] 5.3548387 22.2548387
[32,] 22.0548387 5.3548387
[33,] -9.7451613 22.0548387
[34,] -7.3451613 -9.7451613
[35,] 25.0548387 -7.3451613
[36,] 22.4548387 25.0548387
[37,] 0.3548387 22.4548387
[38,] -12.8451613 0.3548387
[39,] -24.8451613 -12.8451613
[40,] -19.2451613 -24.8451613
[41,] -22.5451613 -19.2451613
[42,] -24.8451613 -22.5451613
[43,] -10.4965517 -24.8451613
[44,] -17.6451613 -10.4965517
[45,] -16.4965517 -17.6451613
[46,] -22.5965517 -16.4965517
[47,] 5.5034483 -22.5965517
[48,] 7.8034483 5.5034483
[49,] -2.8965517 7.8034483
[50,] -14.7965517 -2.8965517
[51,] -25.6965517 -14.7965517
[52,] -19.2965517 -25.6965517
[53,] 2.7034483 -19.2965517
[54,] -3.7965517 2.7034483
[55,] -11.3965517 -3.7965517
[56,] 11.0034483 -11.3965517
[57,] -21.3965517 11.0034483
[58,] -14.3965517 -21.3965517
[59,] 7.0034483 -14.3965517
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -9.6451613 -14.6451613
2 4.6034483 -9.6451613
3 -4.2965517 4.6034483
4 -2.1965517 -4.2965517
5 16.4034483 -2.1965517
6 1.1034483 16.4034483
7 14.8034483 1.1034483
8 25.0034483 14.8034483
9 -17.4965517 25.0034483
10 -2.0965517 -17.4965517
11 22.4034483 -2.0965517
12 29.4034483 22.4034483
13 26.8034483 29.4034483
14 14.8034483 26.8034483
15 -6.4451613 14.8034483
16 -6.5451613 -6.4451613
17 10.9548387 -6.5451613
18 -0.8451613 10.9548387
19 6.2548387 -0.8451613
20 24.1548387 6.2548387
21 -21.9451613 24.1548387
22 -7.9451613 -21.9451613
23 13.4548387 -7.9451613
24 29.6548387 13.4548387
25 10.1548387 29.6548387
26 -4.2451613 10.1548387
27 -1.1451613 -4.2451613
28 12.3548387 -1.1451613
29 7.9548387 12.3548387
30 22.2548387 7.9548387
31 5.3548387 22.2548387
32 22.0548387 5.3548387
33 -9.7451613 22.0548387
34 -7.3451613 -9.7451613
35 25.0548387 -7.3451613
36 22.4548387 25.0548387
37 0.3548387 22.4548387
38 -12.8451613 0.3548387
39 -24.8451613 -12.8451613
40 -19.2451613 -24.8451613
41 -22.5451613 -19.2451613
42 -24.8451613 -22.5451613
43 -10.4965517 -24.8451613
44 -17.6451613 -10.4965517
45 -16.4965517 -17.6451613
46 -22.5965517 -16.4965517
47 5.5034483 -22.5965517
48 7.8034483 5.5034483
49 -2.8965517 7.8034483
50 -14.7965517 -2.8965517
51 -25.6965517 -14.7965517
52 -19.2965517 -25.6965517
53 2.7034483 -19.2965517
54 -3.7965517 2.7034483
55 -11.3965517 -3.7965517
56 11.0034483 -11.3965517
57 -21.3965517 11.0034483
58 -14.3965517 -21.3965517
59 7.0034483 -14.3965517
> 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/wessaorg/rcomp/tmp/7jfo81322331009.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/wessaorg/rcomp/tmp/8nasa1322331009.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/wessaorg/rcomp/tmp/925k21322331009.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/wessaorg/rcomp/tmp/10smf81322331009.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/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/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$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
+ }
+ }
> myeq <- paste(myeq, ' + e[t]')
> a<-table.row.start(a)
> a<-table.element(a, myeq)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/11fraa1322331009.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Variable',header=TRUE)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
> a<-table.element(a,'2-tail p-value',header=TRUE)
> a<-table.element(a,'1-tail p-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:k){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(mysum$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$coefficients[i,4]/2,6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/12ohxy1322331009.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple R',1,TRUE)
> a<-table.element(a, sqrt(mysum$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$sigma)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a, sum(myerror*myerror))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/13tg1b1322331009.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Time or Index', 1, TRUE)
> a<-table.element(a, 'Actuals', 1, TRUE)
> a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
> a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
> a<-table.row.end(a)
> for (i in 1:n) {
+ a<-table.row.start(a)
+ a<-table.element(a,i, 1, TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]-mysum$resid[i])
+ a<-table.element(a,mysum$resid[i])
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/14umkd1322331009.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/wessaorg/rcomp/tmp/1529lp1322331009.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/wessaorg/rcomp/tmp/16jd0m1322331009.tab")
+ }
>
> try(system("convert tmp/1nsda1322331008.ps tmp/1nsda1322331008.png",intern=TRUE))
character(0)
> try(system("convert tmp/2zn1d1322331008.ps tmp/2zn1d1322331008.png",intern=TRUE))
character(0)
> try(system("convert tmp/3fsc11322331008.ps tmp/3fsc11322331008.png",intern=TRUE))
character(0)
> try(system("convert tmp/4vw7n1322331008.ps tmp/4vw7n1322331008.png",intern=TRUE))
character(0)
> try(system("convert tmp/59ci31322331008.ps tmp/59ci31322331008.png",intern=TRUE))
character(0)
> try(system("convert tmp/6hek81322331008.ps tmp/6hek81322331008.png",intern=TRUE))
character(0)
> try(system("convert tmp/7jfo81322331009.ps tmp/7jfo81322331009.png",intern=TRUE))
character(0)
> try(system("convert tmp/8nasa1322331009.ps tmp/8nasa1322331009.png",intern=TRUE))
character(0)
> try(system("convert tmp/925k21322331009.ps tmp/925k21322331009.png",intern=TRUE))
character(0)
> try(system("convert tmp/10smf81322331009.ps tmp/10smf81322331009.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
3.288 0.508 3.806