R version 2.8.0 (2008-10-20)
Copyright (C) 2008 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.
Natural language support but running in an English locale
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(1,2,2,1,2,2,2,1,2,2,4,2,2,2,2,1,2,2,3,2,2,1,4,1,2,1,3,3,3,3,3,1,4,2,3,1,2,1,2,1,3,4,4,2,4,2,4,4,4,3,3,2,2,2,3,1,1,1,4,1,1,1,4,3,3,2,3,2,2,2,3,2,3,2,3,3,4,2,4,3,4,1,2,1,4,2,5,2,4,4,4,2,4,2,2,2,2,2,3,2,3,2,4,3,2,2,4,2,4,2,3,2,3,3,4,2,2,2,4,2,3,1,1,2,4,4,4,3,4,1,5,2,5,2,2,2,3,2,4,2,3,2,3,2,4,2,2,2,2,2,4,1,4,2,5,2,2,2,4,1,3,2,4,2,2,2,4,2,2,2,3,2,2,2,4,2,3,2,2,2,3,1,2,3,2,2,4,2,4,1,2,2,4,2,4,2,4,1,4,4),dim=c(4,50),dimnames=list(c('Upset','punished','highstandards','outstandingperformance'),1:50))
> y <- array(NA,dim=c(4,50),dimnames=list(c('Upset','punished','highstandards','outstandingperformance'),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 = '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
Upset punished highstandards outstandingperformance
1 1 2 2 1
2 2 2 2 1
3 2 2 4 2
4 2 2 2 1
5 2 2 3 2
6 2 1 4 1
7 2 1 3 3
8 3 3 3 1
9 4 2 3 1
10 2 1 2 1
11 3 4 4 2
12 4 2 4 4
13 4 3 3 2
14 2 2 3 1
15 1 1 4 1
16 1 1 4 3
17 3 2 3 2
18 2 2 3 2
19 3 2 3 3
20 4 2 4 3
21 4 1 2 1
22 4 2 5 2
23 4 4 4 2
24 4 2 2 2
25 2 2 3 2
26 3 2 4 3
27 2 2 4 2
28 4 2 3 2
29 3 3 4 2
30 2 2 4 2
31 3 1 1 2
32 4 4 4 3
33 4 1 5 2
34 5 2 2 2
35 3 2 4 2
36 3 2 3 2
37 4 2 2 2
38 2 2 4 1
39 4 2 5 2
40 2 2 4 1
41 3 2 4 2
42 2 2 4 2
43 2 2 3 2
44 2 2 4 2
45 3 2 2 2
46 3 1 2 3
47 2 2 4 2
48 4 1 2 2
49 4 2 4 2
50 4 1 4 4
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) punished highstandards
1.7460 0.3455 -0.1546
outstandingperformance
0.4884
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-1.9383 -0.7954 -0.1227 0.6718 1.8954
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1.7460 0.6148 2.840 0.0067 **
punished 0.3455 0.1900 1.818 0.0756 .
highstandards -0.1546 0.1494 -1.035 0.3062
outstandingperformance 0.4884 0.1870 2.612 0.0121 *
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 0.9414 on 46 degrees of freedom
Multiple R-squared: 0.1728, Adjusted R-squared: 0.1188
F-statistic: 3.202 on 3 and 46 DF, p-value: 0.03182
> 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,] 0.1493784 0.2987568 0.8506216
[2,] 0.1514071 0.3028143 0.8485929
[3,] 0.5741568 0.8516865 0.4258432
[4,] 0.4613516 0.9227031 0.5386484
[5,] 0.3442070 0.6884140 0.6557930
[6,] 0.4221898 0.8443796 0.5778102
[7,] 0.4390046 0.8780091 0.5609954
[8,] 0.3534150 0.7068300 0.6465850
[9,] 0.3532831 0.7065661 0.6467169
[10,] 0.5207708 0.9584584 0.4792292
[11,] 0.4475072 0.8950145 0.5524928
[12,] 0.4215147 0.8430294 0.5784853
[13,] 0.3494399 0.6988798 0.6505601
[14,] 0.3733945 0.7467890 0.6266055
[15,] 0.6674349 0.6651302 0.3325651
[16,] 0.7426305 0.5147391 0.2573695
[17,] 0.6973428 0.6053145 0.3026572
[18,] 0.7093759 0.5812483 0.2906241
[19,] 0.7073811 0.5852378 0.2926189
[20,] 0.6394987 0.7210026 0.3605013
[21,] 0.6229702 0.7540596 0.3770298
[22,] 0.6419427 0.7161147 0.3580573
[23,] 0.5562221 0.8875558 0.4437779
[24,] 0.5420213 0.9159574 0.4579787
[25,] 0.4667813 0.9335625 0.5332187
[26,] 0.4181168 0.8362335 0.5818832
[27,] 0.5312812 0.9374377 0.4687188
[28,] 0.7754101 0.4491798 0.2245899
[29,] 0.6953275 0.6093451 0.3046725
[30,] 0.5989281 0.8021438 0.4010719
[31,] 0.6770313 0.6459375 0.3229687
[32,] 0.5992628 0.8014744 0.4007372
[33,] 0.6956872 0.6086257 0.3043128
[34,] 0.6059982 0.7880036 0.3940018
[35,] 0.4939221 0.9878441 0.5060779
[36,] 0.4025579 0.8051158 0.5974421
[37,] 0.3098126 0.6196252 0.6901874
> postscript(file="/var/www/html/freestat/rcomp/tmp/1zn631290518083.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/2rw6o1290518083.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/freestat/rcomp/tmp/3rw6o1290518083.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/4rw6o1290518083.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/5k55q1290518083.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
-1.61615660 -0.61615660 -0.79537426 -0.61615660 -0.94996309 0.03848445
7 8 9 10 11 12
-1.09289503 0.19296885 1.53843223 -0.27069321 -0.48630103 0.22783509
13 14 15 16 17 18
0.70457353 -0.46156777 -0.96151555 -1.93830620 0.05003691 -0.94996309
19 20 21 22 23 24
-0.43835841 0.71623042 1.72930679 1.35921457 0.51369897 0.89544808
25 26 27 28 29 30
-0.94996309 -0.28376958 -0.79537426 1.05003691 -0.14083765 -0.79537426
31 32 33 34 35 36
0.08632264 0.02530365 1.70467795 1.89544808 0.20462574 0.05003691
37 38 39 40 41 42
0.89544808 -0.30697894 1.35921457 -0.30697894 0.20462574 -0.79537426
43 44 45 46 47 48
-0.94996309 -0.79537426 -0.10455192 -0.24748386 -0.79537426 1.24091146
49 50
1.20462574 0.57329848
> postscript(file="/var/www/html/freestat/rcomp/tmp/6k55q1290518083.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 -1.61615660 NA
1 -0.61615660 -1.61615660
2 -0.79537426 -0.61615660
3 -0.61615660 -0.79537426
4 -0.94996309 -0.61615660
5 0.03848445 -0.94996309
6 -1.09289503 0.03848445
7 0.19296885 -1.09289503
8 1.53843223 0.19296885
9 -0.27069321 1.53843223
10 -0.48630103 -0.27069321
11 0.22783509 -0.48630103
12 0.70457353 0.22783509
13 -0.46156777 0.70457353
14 -0.96151555 -0.46156777
15 -1.93830620 -0.96151555
16 0.05003691 -1.93830620
17 -0.94996309 0.05003691
18 -0.43835841 -0.94996309
19 0.71623042 -0.43835841
20 1.72930679 0.71623042
21 1.35921457 1.72930679
22 0.51369897 1.35921457
23 0.89544808 0.51369897
24 -0.94996309 0.89544808
25 -0.28376958 -0.94996309
26 -0.79537426 -0.28376958
27 1.05003691 -0.79537426
28 -0.14083765 1.05003691
29 -0.79537426 -0.14083765
30 0.08632264 -0.79537426
31 0.02530365 0.08632264
32 1.70467795 0.02530365
33 1.89544808 1.70467795
34 0.20462574 1.89544808
35 0.05003691 0.20462574
36 0.89544808 0.05003691
37 -0.30697894 0.89544808
38 1.35921457 -0.30697894
39 -0.30697894 1.35921457
40 0.20462574 -0.30697894
41 -0.79537426 0.20462574
42 -0.94996309 -0.79537426
43 -0.79537426 -0.94996309
44 -0.10455192 -0.79537426
45 -0.24748386 -0.10455192
46 -0.79537426 -0.24748386
47 1.24091146 -0.79537426
48 1.20462574 1.24091146
49 0.57329848 1.20462574
50 NA 0.57329848
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -0.61615660 -1.61615660
[2,] -0.79537426 -0.61615660
[3,] -0.61615660 -0.79537426
[4,] -0.94996309 -0.61615660
[5,] 0.03848445 -0.94996309
[6,] -1.09289503 0.03848445
[7,] 0.19296885 -1.09289503
[8,] 1.53843223 0.19296885
[9,] -0.27069321 1.53843223
[10,] -0.48630103 -0.27069321
[11,] 0.22783509 -0.48630103
[12,] 0.70457353 0.22783509
[13,] -0.46156777 0.70457353
[14,] -0.96151555 -0.46156777
[15,] -1.93830620 -0.96151555
[16,] 0.05003691 -1.93830620
[17,] -0.94996309 0.05003691
[18,] -0.43835841 -0.94996309
[19,] 0.71623042 -0.43835841
[20,] 1.72930679 0.71623042
[21,] 1.35921457 1.72930679
[22,] 0.51369897 1.35921457
[23,] 0.89544808 0.51369897
[24,] -0.94996309 0.89544808
[25,] -0.28376958 -0.94996309
[26,] -0.79537426 -0.28376958
[27,] 1.05003691 -0.79537426
[28,] -0.14083765 1.05003691
[29,] -0.79537426 -0.14083765
[30,] 0.08632264 -0.79537426
[31,] 0.02530365 0.08632264
[32,] 1.70467795 0.02530365
[33,] 1.89544808 1.70467795
[34,] 0.20462574 1.89544808
[35,] 0.05003691 0.20462574
[36,] 0.89544808 0.05003691
[37,] -0.30697894 0.89544808
[38,] 1.35921457 -0.30697894
[39,] -0.30697894 1.35921457
[40,] 0.20462574 -0.30697894
[41,] -0.79537426 0.20462574
[42,] -0.94996309 -0.79537426
[43,] -0.79537426 -0.94996309
[44,] -0.10455192 -0.79537426
[45,] -0.24748386 -0.10455192
[46,] -0.79537426 -0.24748386
[47,] 1.24091146 -0.79537426
[48,] 1.20462574 1.24091146
[49,] 0.57329848 1.20462574
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -0.61615660 -1.61615660
2 -0.79537426 -0.61615660
3 -0.61615660 -0.79537426
4 -0.94996309 -0.61615660
5 0.03848445 -0.94996309
6 -1.09289503 0.03848445
7 0.19296885 -1.09289503
8 1.53843223 0.19296885
9 -0.27069321 1.53843223
10 -0.48630103 -0.27069321
11 0.22783509 -0.48630103
12 0.70457353 0.22783509
13 -0.46156777 0.70457353
14 -0.96151555 -0.46156777
15 -1.93830620 -0.96151555
16 0.05003691 -1.93830620
17 -0.94996309 0.05003691
18 -0.43835841 -0.94996309
19 0.71623042 -0.43835841
20 1.72930679 0.71623042
21 1.35921457 1.72930679
22 0.51369897 1.35921457
23 0.89544808 0.51369897
24 -0.94996309 0.89544808
25 -0.28376958 -0.94996309
26 -0.79537426 -0.28376958
27 1.05003691 -0.79537426
28 -0.14083765 1.05003691
29 -0.79537426 -0.14083765
30 0.08632264 -0.79537426
31 0.02530365 0.08632264
32 1.70467795 0.02530365
33 1.89544808 1.70467795
34 0.20462574 1.89544808
35 0.05003691 0.20462574
36 0.89544808 0.05003691
37 -0.30697894 0.89544808
38 1.35921457 -0.30697894
39 -0.30697894 1.35921457
40 0.20462574 -0.30697894
41 -0.79537426 0.20462574
42 -0.94996309 -0.79537426
43 -0.79537426 -0.94996309
44 -0.10455192 -0.79537426
45 -0.24748386 -0.10455192
46 -0.79537426 -0.24748386
47 1.24091146 -0.79537426
48 1.20462574 1.24091146
49 0.57329848 1.20462574
> 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/7dx4t1290518083.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/8dx4t1290518083.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/9o64f1290518083.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/freestat/rcomp/tmp/10o64f1290518083.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/freestat/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/1197kk1290518083.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/12cpiq1290518083.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/13j8gk1290518083.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/14uzx51290518083.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/15x0dt1290518083.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/16tst21290518083.tab")
+ }
>
> try(system("convert tmp/1zn631290518083.ps tmp/1zn631290518083.png",intern=TRUE))
character(0)
> try(system("convert tmp/2rw6o1290518083.ps tmp/2rw6o1290518083.png",intern=TRUE))
character(0)
> try(system("convert tmp/3rw6o1290518083.ps tmp/3rw6o1290518083.png",intern=TRUE))
character(0)
> try(system("convert tmp/4rw6o1290518083.ps tmp/4rw6o1290518083.png",intern=TRUE))
character(0)
> try(system("convert tmp/5k55q1290518083.ps tmp/5k55q1290518083.png",intern=TRUE))
character(0)
> try(system("convert tmp/6k55q1290518083.ps tmp/6k55q1290518083.png",intern=TRUE))
character(0)
> try(system("convert tmp/7dx4t1290518083.ps tmp/7dx4t1290518083.png",intern=TRUE))
character(0)
> try(system("convert tmp/8dx4t1290518083.ps tmp/8dx4t1290518083.png",intern=TRUE))
character(0)
> try(system("convert tmp/9o64f1290518083.ps tmp/9o64f1290518083.png",intern=TRUE))
character(0)
> try(system("convert tmp/10o64f1290518083.ps tmp/10o64f1290518083.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
3.863 2.557 17.357