R version 2.8.0 (2008-10-20)
Copyright (C) 2008 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
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> x <- array(list(104.31,103.88,103.88,103.86,103.89,103.98,103.98,104.29,104.29,104.24,103.98,103.54,103.44,103.32,103.3,103.26,103.14,103.11,102.91,103.23,103.23,103.14,102.91,102.42,102.1,102.07,102.06,101.98,101.83,101.75,101.56,101.66,101.65,101.61,101.52,101.31,101.19,101.11,101.1,101.07,100.98,100.93,100.92,101.02,101.01,100.97,100.89,100.62,100.53,100.48,100.48,100.47,100.52,100.49,100.47,100.44),dim=c(1,56),dimnames=list(c('kleding/schoeisel'),1:56))
> y <- array(NA,dim=c(1,56),dimnames=list(c('kleding/schoeisel'),1:56))
> 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
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
kleding/schoeisel M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 104.31 1 0 0 0 0 0 0 0 0 0 0 1
2 103.88 0 1 0 0 0 0 0 0 0 0 0 2
3 103.88 0 0 1 0 0 0 0 0 0 0 0 3
4 103.86 0 0 0 1 0 0 0 0 0 0 0 4
5 103.89 0 0 0 0 1 0 0 0 0 0 0 5
6 103.98 0 0 0 0 0 1 0 0 0 0 0 6
7 103.98 0 0 0 0 0 0 1 0 0 0 0 7
8 104.29 0 0 0 0 0 0 0 1 0 0 0 8
9 104.29 0 0 0 0 0 0 0 0 1 0 0 9
10 104.24 0 0 0 0 0 0 0 0 0 1 0 10
11 103.98 0 0 0 0 0 0 0 0 0 0 1 11
12 103.54 0 0 0 0 0 0 0 0 0 0 0 12
13 103.44 1 0 0 0 0 0 0 0 0 0 0 13
14 103.32 0 1 0 0 0 0 0 0 0 0 0 14
15 103.30 0 0 1 0 0 0 0 0 0 0 0 15
16 103.26 0 0 0 1 0 0 0 0 0 0 0 16
17 103.14 0 0 0 0 1 0 0 0 0 0 0 17
18 103.11 0 0 0 0 0 1 0 0 0 0 0 18
19 102.91 0 0 0 0 0 0 1 0 0 0 0 19
20 103.23 0 0 0 0 0 0 0 1 0 0 0 20
21 103.23 0 0 0 0 0 0 0 0 1 0 0 21
22 103.14 0 0 0 0 0 0 0 0 0 1 0 22
23 102.91 0 0 0 0 0 0 0 0 0 0 1 23
24 102.42 0 0 0 0 0 0 0 0 0 0 0 24
25 102.10 1 0 0 0 0 0 0 0 0 0 0 25
26 102.07 0 1 0 0 0 0 0 0 0 0 0 26
27 102.06 0 0 1 0 0 0 0 0 0 0 0 27
28 101.98 0 0 0 1 0 0 0 0 0 0 0 28
29 101.83 0 0 0 0 1 0 0 0 0 0 0 29
30 101.75 0 0 0 0 0 1 0 0 0 0 0 30
31 101.56 0 0 0 0 0 0 1 0 0 0 0 31
32 101.66 0 0 0 0 0 0 0 1 0 0 0 32
33 101.65 0 0 0 0 0 0 0 0 1 0 0 33
34 101.61 0 0 0 0 0 0 0 0 0 1 0 34
35 101.52 0 0 0 0 0 0 0 0 0 0 1 35
36 101.31 0 0 0 0 0 0 0 0 0 0 0 36
37 101.19 1 0 0 0 0 0 0 0 0 0 0 37
38 101.11 0 1 0 0 0 0 0 0 0 0 0 38
39 101.10 0 0 1 0 0 0 0 0 0 0 0 39
40 101.07 0 0 0 1 0 0 0 0 0 0 0 40
41 100.98 0 0 0 0 1 0 0 0 0 0 0 41
42 100.93 0 0 0 0 0 1 0 0 0 0 0 42
43 100.92 0 0 0 0 0 0 1 0 0 0 0 43
44 101.02 0 0 0 0 0 0 0 1 0 0 0 44
45 101.01 0 0 0 0 0 0 0 0 1 0 0 45
46 100.97 0 0 0 0 0 0 0 0 0 1 0 46
47 100.89 0 0 0 0 0 0 0 0 0 0 1 47
48 100.62 0 0 0 0 0 0 0 0 0 0 0 48
49 100.53 1 0 0 0 0 0 0 0 0 0 0 49
50 100.48 0 1 0 0 0 0 0 0 0 0 0 50
51 100.48 0 0 1 0 0 0 0 0 0 0 0 51
52 100.47 0 0 0 1 0 0 0 0 0 0 0 52
53 100.52 0 0 0 0 1 0 0 0 0 0 0 53
54 100.49 0 0 0 0 0 1 0 0 0 0 0 54
55 100.47 0 0 0 0 0 0 1 0 0 0 0 55
56 100.44 0 0 0 0 0 0 0 1 0 0 0 56
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) M1 M2 M3 M4 M5
104.357875 -0.056062 -0.118550 -0.047038 -0.003525 0.019987
M6 M7 M8 M9 M10 M11
0.079500 0.075012 0.314525 0.333963 0.358475 0.272987
t
-0.079513
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-0.468000 -0.157350 -0.007963 0.178850 0.410300
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 104.357875 0.138550 753.216 <2e-16 ***
M1 -0.056062 0.166580 -0.337 0.7381
M2 -0.118550 0.166465 -0.712 0.4802
M3 -0.047038 0.166375 -0.283 0.7787
M4 -0.003525 0.166311 -0.021 0.9832
M5 0.019987 0.166272 0.120 0.9049
M6 0.079500 0.166260 0.478 0.6350
M7 0.075012 0.166272 0.451 0.6542
M8 0.314525 0.166311 1.891 0.0653 .
M9 0.333963 0.175363 1.904 0.0636 .
M10 0.358475 0.175302 2.045 0.0470 *
M11 0.272987 0.175265 1.558 0.1267
t -0.079513 0.002065 -38.498 <2e-16 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 0.2478 on 43 degrees of freedom
Multiple R-squared: 0.9723, Adjusted R-squared: 0.9646
F-statistic: 125.8 on 12 and 43 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,] 0.08339426 0.1667885263 0.9166057368
[2,] 0.03477509 0.0695501895 0.9652249053
[3,] 0.02760397 0.0552079338 0.9723960331
[4,] 0.06308849 0.1261769848 0.9369115076
[5,] 0.09494863 0.1898972672 0.9050513664
[6,] 0.17165206 0.3433041285 0.8283479357
[7,] 0.38942354 0.7788470725 0.6105764637
[8,] 0.70164246 0.5967150843 0.2983575422
[9,] 0.86911470 0.2617705933 0.1308852967
[10,] 0.95602220 0.0879556041 0.0439778021
[11,] 0.97270366 0.0545926757 0.0272963379
[12,] 0.99141078 0.0171784456 0.0085892228
[13,] 0.99859631 0.0028073757 0.0014036878
[14,] 0.99940021 0.0011995794 0.0005997897
[15,] 0.99979668 0.0004066340 0.0002033170
[16,] 0.99972977 0.0005404647 0.0002702324
[17,] 0.99981405 0.0003718980 0.0001859490
[18,] 0.99978022 0.0004395679 0.0002197840
[19,] 0.99961889 0.0007622204 0.0003811102
[20,] 0.99899755 0.0020048924 0.0010024462
[21,] 0.99845588 0.0030882409 0.0015441205
[22,] 0.99736798 0.0052640326 0.0026320163
[23,] 0.99493129 0.0101374209 0.0050687104
[24,] 0.99093130 0.0181373945 0.0090686972
[25,] 0.98514050 0.0297189972 0.0148594986
> postscript(file="/var/www/html/freestat/rcomp/tmp/158ef1292676566.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/258ef1292676566.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/html/freestat/rcomp/tmp/3yzdi1292676566.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/4yzdi1292676566.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/5yzdi1292676566.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 = 56
Frequency = 1
1 2 3 4 5 6 7 8
0.087700 -0.200300 -0.192300 -0.176300 -0.090300 0.019700 0.103700 0.253700
9 10 11 12 13 14 15 16
0.313775 0.318775 0.223775 0.136275 0.171850 0.193850 0.181850 0.177850
17 18 19 20 21 22 23 24
0.113850 0.103850 -0.012150 0.147850 0.207925 0.172925 0.107925 -0.029575
25 26 27 28 29 30 31 32
-0.214000 -0.102000 -0.104000 -0.148000 -0.242000 -0.302000 -0.408000 -0.468000
33 34 35 36 37 38 39 40
-0.417925 -0.402925 -0.327925 -0.185425 -0.169850 -0.107850 -0.109850 -0.103850
41 42 43 44 45 46 47 48
-0.137850 -0.167850 -0.093850 -0.153850 -0.103775 -0.088775 -0.003775 0.078725
49 50 51 52 53 54 55 56
0.124300 0.216300 0.224300 0.250300 0.356300 0.346300 0.410300 0.220300
> postscript(file="/var/www/html/freestat/rcomp/tmp/68rc31292676566.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 = 56
Frequency = 1
lag(myerror, k = 1) myerror
0 0.087700 NA
1 -0.200300 0.087700
2 -0.192300 -0.200300
3 -0.176300 -0.192300
4 -0.090300 -0.176300
5 0.019700 -0.090300
6 0.103700 0.019700
7 0.253700 0.103700
8 0.313775 0.253700
9 0.318775 0.313775
10 0.223775 0.318775
11 0.136275 0.223775
12 0.171850 0.136275
13 0.193850 0.171850
14 0.181850 0.193850
15 0.177850 0.181850
16 0.113850 0.177850
17 0.103850 0.113850
18 -0.012150 0.103850
19 0.147850 -0.012150
20 0.207925 0.147850
21 0.172925 0.207925
22 0.107925 0.172925
23 -0.029575 0.107925
24 -0.214000 -0.029575
25 -0.102000 -0.214000
26 -0.104000 -0.102000
27 -0.148000 -0.104000
28 -0.242000 -0.148000
29 -0.302000 -0.242000
30 -0.408000 -0.302000
31 -0.468000 -0.408000
32 -0.417925 -0.468000
33 -0.402925 -0.417925
34 -0.327925 -0.402925
35 -0.185425 -0.327925
36 -0.169850 -0.185425
37 -0.107850 -0.169850
38 -0.109850 -0.107850
39 -0.103850 -0.109850
40 -0.137850 -0.103850
41 -0.167850 -0.137850
42 -0.093850 -0.167850
43 -0.153850 -0.093850
44 -0.103775 -0.153850
45 -0.088775 -0.103775
46 -0.003775 -0.088775
47 0.078725 -0.003775
48 0.124300 0.078725
49 0.216300 0.124300
50 0.224300 0.216300
51 0.250300 0.224300
52 0.356300 0.250300
53 0.346300 0.356300
54 0.410300 0.346300
55 0.220300 0.410300
56 NA 0.220300
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -0.200300 0.087700
[2,] -0.192300 -0.200300
[3,] -0.176300 -0.192300
[4,] -0.090300 -0.176300
[5,] 0.019700 -0.090300
[6,] 0.103700 0.019700
[7,] 0.253700 0.103700
[8,] 0.313775 0.253700
[9,] 0.318775 0.313775
[10,] 0.223775 0.318775
[11,] 0.136275 0.223775
[12,] 0.171850 0.136275
[13,] 0.193850 0.171850
[14,] 0.181850 0.193850
[15,] 0.177850 0.181850
[16,] 0.113850 0.177850
[17,] 0.103850 0.113850
[18,] -0.012150 0.103850
[19,] 0.147850 -0.012150
[20,] 0.207925 0.147850
[21,] 0.172925 0.207925
[22,] 0.107925 0.172925
[23,] -0.029575 0.107925
[24,] -0.214000 -0.029575
[25,] -0.102000 -0.214000
[26,] -0.104000 -0.102000
[27,] -0.148000 -0.104000
[28,] -0.242000 -0.148000
[29,] -0.302000 -0.242000
[30,] -0.408000 -0.302000
[31,] -0.468000 -0.408000
[32,] -0.417925 -0.468000
[33,] -0.402925 -0.417925
[34,] -0.327925 -0.402925
[35,] -0.185425 -0.327925
[36,] -0.169850 -0.185425
[37,] -0.107850 -0.169850
[38,] -0.109850 -0.107850
[39,] -0.103850 -0.109850
[40,] -0.137850 -0.103850
[41,] -0.167850 -0.137850
[42,] -0.093850 -0.167850
[43,] -0.153850 -0.093850
[44,] -0.103775 -0.153850
[45,] -0.088775 -0.103775
[46,] -0.003775 -0.088775
[47,] 0.078725 -0.003775
[48,] 0.124300 0.078725
[49,] 0.216300 0.124300
[50,] 0.224300 0.216300
[51,] 0.250300 0.224300
[52,] 0.356300 0.250300
[53,] 0.346300 0.356300
[54,] 0.410300 0.346300
[55,] 0.220300 0.410300
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -0.200300 0.087700
2 -0.192300 -0.200300
3 -0.176300 -0.192300
4 -0.090300 -0.176300
5 0.019700 -0.090300
6 0.103700 0.019700
7 0.253700 0.103700
8 0.313775 0.253700
9 0.318775 0.313775
10 0.223775 0.318775
11 0.136275 0.223775
12 0.171850 0.136275
13 0.193850 0.171850
14 0.181850 0.193850
15 0.177850 0.181850
16 0.113850 0.177850
17 0.103850 0.113850
18 -0.012150 0.103850
19 0.147850 -0.012150
20 0.207925 0.147850
21 0.172925 0.207925
22 0.107925 0.172925
23 -0.029575 0.107925
24 -0.214000 -0.029575
25 -0.102000 -0.214000
26 -0.104000 -0.102000
27 -0.148000 -0.104000
28 -0.242000 -0.148000
29 -0.302000 -0.242000
30 -0.408000 -0.302000
31 -0.468000 -0.408000
32 -0.417925 -0.468000
33 -0.402925 -0.417925
34 -0.327925 -0.402925
35 -0.185425 -0.327925
36 -0.169850 -0.185425
37 -0.107850 -0.169850
38 -0.109850 -0.107850
39 -0.103850 -0.109850
40 -0.137850 -0.103850
41 -0.167850 -0.137850
42 -0.093850 -0.167850
43 -0.153850 -0.093850
44 -0.103775 -0.153850
45 -0.088775 -0.103775
46 -0.003775 -0.088775
47 0.078725 -0.003775
48 0.124300 0.078725
49 0.216300 0.124300
50 0.224300 0.216300
51 0.250300 0.224300
52 0.356300 0.250300
53 0.346300 0.356300
54 0.410300 0.346300
55 0.220300 0.410300
> 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/freestat/rcomp/tmp/78rc31292676566.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/8j0t61292676566.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/9j0t61292676566.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/freestat/rcomp/tmp/10urtr1292676566.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/freestat/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/freestat/rcomp/tmp/11xsrf1292676566.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/freestat/rcomp/tmp/121s8k1292676566.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/freestat/rcomp/tmp/13x2ot1292676566.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/freestat/rcomp/tmp/140l4z1292676566.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/freestat/rcomp/tmp/1533ln1292676566.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/freestat/rcomp/tmp/167mjt1292676566.tab")
+ }
>
> try(system("convert tmp/158ef1292676566.ps tmp/158ef1292676566.png",intern=TRUE))
character(0)
> try(system("convert tmp/258ef1292676566.ps tmp/258ef1292676566.png",intern=TRUE))
character(0)
> try(system("convert tmp/3yzdi1292676566.ps tmp/3yzdi1292676566.png",intern=TRUE))
character(0)
> try(system("convert tmp/4yzdi1292676566.ps tmp/4yzdi1292676566.png",intern=TRUE))
character(0)
> try(system("convert tmp/5yzdi1292676566.ps tmp/5yzdi1292676566.png",intern=TRUE))
character(0)
> try(system("convert tmp/68rc31292676566.ps tmp/68rc31292676566.png",intern=TRUE))
character(0)
> try(system("convert tmp/78rc31292676566.ps tmp/78rc31292676566.png",intern=TRUE))
character(0)
> try(system("convert tmp/8j0t61292676566.ps tmp/8j0t61292676566.png",intern=TRUE))
character(0)
> try(system("convert tmp/9j0t61292676566.ps tmp/9j0t61292676566.png",intern=TRUE))
character(0)
> try(system("convert tmp/10urtr1292676566.ps tmp/10urtr1292676566.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
3.932 2.535 4.456