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.
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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(10,24.1,9.2,24.1,9.2,24.1,9.5,21.3,9.6,21.3,9.5,21.3,9.1,19.1,8.9,19.1,9,19.1,10.1,26.2,10.3,26.2,10.2,26.2,9.6,21.7,9.2,21.7,9.3,21.7,9.4,19.4,9.4,19.4,9.2,19.4,9,19.5,9,19.5,9,19.5,9.8,28.7,10,28.7,9.8,28.7,9.3,21.8,9,21.8,9,21.8,9.1,20,9.1,20,9.1,20,9.2,22.6,8.8,22.6,8.3,22.6,8.4,22.4,8.1,22.4,7.7,22.4,7.9,18.6,7.9,18.6,8,18.6,7.9,16.2,7.6,16.2,7.1,16.2,6.8,13.8,6.5,13.8,6.9,13.8,8.2,24.1,8.7,24.1,8.3,24.1,7.9,19.9,7.5,19.9,7.8,19.9,8.3,22.3,8.4,22.3,8.2,22.3,7.7,20.9,7.2,20.9,7.3,20.9,8.1,25.5,8.5,25.5,8.4,25.5),dim=c(2,60),dimnames=list(c('TWV','WV-25'),1:60))
> y <- array(NA,dim=c(2,60),dimnames=list(c('TWV','WV-25'),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'
> #'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
TWV WV-25
1 10.0 24.1
2 9.2 24.1
3 9.2 24.1
4 9.5 21.3
5 9.6 21.3
6 9.5 21.3
7 9.1 19.1
8 8.9 19.1
9 9.0 19.1
10 10.1 26.2
11 10.3 26.2
12 10.2 26.2
13 9.6 21.7
14 9.2 21.7
15 9.3 21.7
16 9.4 19.4
17 9.4 19.4
18 9.2 19.4
19 9.0 19.5
20 9.0 19.5
21 9.0 19.5
22 9.8 28.7
23 10.0 28.7
24 9.8 28.7
25 9.3 21.8
26 9.0 21.8
27 9.0 21.8
28 9.1 20.0
29 9.1 20.0
30 9.1 20.0
31 9.2 22.6
32 8.8 22.6
33 8.3 22.6
34 8.4 22.4
35 8.1 22.4
36 7.7 22.4
37 7.9 18.6
38 7.9 18.6
39 8.0 18.6
40 7.9 16.2
41 7.6 16.2
42 7.1 16.2
43 6.8 13.8
44 6.5 13.8
45 6.9 13.8
46 8.2 24.1
47 8.7 24.1
48 8.3 24.1
49 7.9 19.9
50 7.5 19.9
51 7.8 19.9
52 8.3 22.3
53 8.4 22.3
54 8.2 22.3
55 7.7 20.9
56 7.2 20.9
57 7.3 20.9
58 8.1 25.5
59 8.5 25.5
60 8.4 25.5
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) `WV-25`
5.0770 0.1673
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-1.37384 -0.59108 0.01625 0.66448 1.07713
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 5.07704 0.60420 8.403 1.30e-11 ***
`WV-25` 0.16731 0.02789 5.999 1.37e-07 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.7186 on 58 degrees of freedom
Multiple R-squared: 0.3829, Adjusted R-squared: 0.3722
F-statistic: 35.98 on 1 and 58 DF, p-value: 1.371e-07
> 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,] 0.1598561519 0.3197123039 0.840143848
[2,] 0.0698587674 0.1397175347 0.930141233
[3,] 0.0448097964 0.0896195927 0.955190204
[4,] 0.0295184942 0.0590369884 0.970481506
[5,] 0.0140273828 0.0280547657 0.985972617
[6,] 0.0082895279 0.0165790557 0.991710472
[7,] 0.0065244974 0.0130489947 0.993475503
[8,] 0.0035207565 0.0070415130 0.996479243
[9,] 0.0020824641 0.0041649282 0.997917536
[10,] 0.0011677835 0.0023355670 0.998832217
[11,] 0.0005706064 0.0011412129 0.999429394
[12,] 0.0005962981 0.0011925963 0.999403702
[13,] 0.0006275830 0.0012551660 0.999372417
[14,] 0.0004428106 0.0008856211 0.999557189
[15,] 0.0003247710 0.0006495419 0.999675229
[16,] 0.0002540270 0.0005080540 0.999745973
[17,] 0.0002181780 0.0004363561 0.999781822
[18,] 0.0003486076 0.0006972152 0.999651392
[19,] 0.0002284368 0.0004568736 0.999771563
[20,] 0.0002007716 0.0004015432 0.999799228
[21,] 0.0002150931 0.0004301861 0.999784907
[22,] 0.0003412365 0.0006824731 0.999658763
[23,] 0.0005379083 0.0010758166 0.999462092
[24,] 0.0010579504 0.0021159007 0.998942050
[25,] 0.0030431850 0.0060863700 0.996956815
[26,] 0.0145282261 0.0290564522 0.985471774
[27,] 0.0558636250 0.1117272501 0.944136375
[28,] 0.1768090537 0.3536181075 0.823190946
[29,] 0.5011301622 0.9977396757 0.498869838
[30,] 0.6895039854 0.6209920291 0.310496015
[31,] 0.8476777070 0.3046445859 0.152322293
[32,] 0.9643015914 0.0713968172 0.035698409
[33,] 0.9726748351 0.0546503299 0.027325165
[34,] 0.9769405515 0.0461188969 0.023059448
[35,] 0.9816223339 0.0367553322 0.018377666
[36,] 0.9933845194 0.0132309611 0.006615481
[37,] 0.9958798011 0.0082403978 0.004120199
[38,] 0.9954298400 0.0091403200 0.004570160
[39,] 0.9936576622 0.0126846756 0.006342338
[40,] 0.9931978498 0.0136043003 0.006802150
[41,] 0.9885744728 0.0228510544 0.011425527
[42,] 0.9859647409 0.0280705183 0.014035259
[43,] 0.9872295419 0.0255409163 0.012770458
[44,] 0.9803703091 0.0392593818 0.019629691
[45,] 0.9729584658 0.0540830683 0.027041534
[46,] 0.9559055772 0.0881888456 0.044094423
[47,] 0.9330834256 0.1338331488 0.066916574
[48,] 0.9226342308 0.1547315383 0.077365769
[49,] 0.9526145984 0.0947708031 0.047385402
[50,] 0.9678466579 0.0643066843 0.032153342
[51,] 0.9746472940 0.0507054120 0.025352706
> postscript(file="/var/www/html/rcomp/tmp/10g7p1258661727.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2yyva1258661727.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3ob1f1258661727.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/44pny1258661727.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5ad7q1258661727.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 = 60
Frequency = 1
1 2 3 4 5 6
0.89076306 0.09076306 0.09076306 0.85923434 0.95923434 0.85923434
7 8 9 10 11 12
0.82731892 0.62731892 0.72731892 0.63940960 0.83940960 0.73940960
13 14 15 16 17 18
0.89230987 0.49230987 0.59230987 1.07712556 1.07712556 0.87712556
19 20 21 22 23 24
0.66039445 0.66039445 0.66039445 -0.07886832 0.12113168 -0.07886832
25 26 27 28 29 30
0.57557875 0.27557875 0.27557875 0.67673886 0.67673886 0.67673886
31 32 33 34 35 36
0.34172982 -0.05827018 -0.55827018 -0.42480795 -0.72480795 -1.12480795
37 38 39 40 41 42
-0.28902550 -0.28902550 -0.18902550 0.11252131 -0.18747869 -0.68747869
43 44 45 46 47 48
-0.58593188 -0.88593188 -0.48593188 -0.90923694 -0.40923694 -0.80923694
49 50 51 52 53 54
-0.50653002 -0.90653002 -0.60653002 -0.50807683 -0.40807683 -0.60807683
55 56 57 58 59 60
-0.87384119 -1.37384119 -1.27384119 -1.24347258 -0.84347258 -0.94347258
> postscript(file="/var/www/html/rcomp/tmp/6o1671258661727.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 = 60
Frequency = 1
lag(myerror, k = 1) myerror
0 0.89076306 NA
1 0.09076306 0.89076306
2 0.09076306 0.09076306
3 0.85923434 0.09076306
4 0.95923434 0.85923434
5 0.85923434 0.95923434
6 0.82731892 0.85923434
7 0.62731892 0.82731892
8 0.72731892 0.62731892
9 0.63940960 0.72731892
10 0.83940960 0.63940960
11 0.73940960 0.83940960
12 0.89230987 0.73940960
13 0.49230987 0.89230987
14 0.59230987 0.49230987
15 1.07712556 0.59230987
16 1.07712556 1.07712556
17 0.87712556 1.07712556
18 0.66039445 0.87712556
19 0.66039445 0.66039445
20 0.66039445 0.66039445
21 -0.07886832 0.66039445
22 0.12113168 -0.07886832
23 -0.07886832 0.12113168
24 0.57557875 -0.07886832
25 0.27557875 0.57557875
26 0.27557875 0.27557875
27 0.67673886 0.27557875
28 0.67673886 0.67673886
29 0.67673886 0.67673886
30 0.34172982 0.67673886
31 -0.05827018 0.34172982
32 -0.55827018 -0.05827018
33 -0.42480795 -0.55827018
34 -0.72480795 -0.42480795
35 -1.12480795 -0.72480795
36 -0.28902550 -1.12480795
37 -0.28902550 -0.28902550
38 -0.18902550 -0.28902550
39 0.11252131 -0.18902550
40 -0.18747869 0.11252131
41 -0.68747869 -0.18747869
42 -0.58593188 -0.68747869
43 -0.88593188 -0.58593188
44 -0.48593188 -0.88593188
45 -0.90923694 -0.48593188
46 -0.40923694 -0.90923694
47 -0.80923694 -0.40923694
48 -0.50653002 -0.80923694
49 -0.90653002 -0.50653002
50 -0.60653002 -0.90653002
51 -0.50807683 -0.60653002
52 -0.40807683 -0.50807683
53 -0.60807683 -0.40807683
54 -0.87384119 -0.60807683
55 -1.37384119 -0.87384119
56 -1.27384119 -1.37384119
57 -1.24347258 -1.27384119
58 -0.84347258 -1.24347258
59 -0.94347258 -0.84347258
60 NA -0.94347258
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 0.09076306 0.89076306
[2,] 0.09076306 0.09076306
[3,] 0.85923434 0.09076306
[4,] 0.95923434 0.85923434
[5,] 0.85923434 0.95923434
[6,] 0.82731892 0.85923434
[7,] 0.62731892 0.82731892
[8,] 0.72731892 0.62731892
[9,] 0.63940960 0.72731892
[10,] 0.83940960 0.63940960
[11,] 0.73940960 0.83940960
[12,] 0.89230987 0.73940960
[13,] 0.49230987 0.89230987
[14,] 0.59230987 0.49230987
[15,] 1.07712556 0.59230987
[16,] 1.07712556 1.07712556
[17,] 0.87712556 1.07712556
[18,] 0.66039445 0.87712556
[19,] 0.66039445 0.66039445
[20,] 0.66039445 0.66039445
[21,] -0.07886832 0.66039445
[22,] 0.12113168 -0.07886832
[23,] -0.07886832 0.12113168
[24,] 0.57557875 -0.07886832
[25,] 0.27557875 0.57557875
[26,] 0.27557875 0.27557875
[27,] 0.67673886 0.27557875
[28,] 0.67673886 0.67673886
[29,] 0.67673886 0.67673886
[30,] 0.34172982 0.67673886
[31,] -0.05827018 0.34172982
[32,] -0.55827018 -0.05827018
[33,] -0.42480795 -0.55827018
[34,] -0.72480795 -0.42480795
[35,] -1.12480795 -0.72480795
[36,] -0.28902550 -1.12480795
[37,] -0.28902550 -0.28902550
[38,] -0.18902550 -0.28902550
[39,] 0.11252131 -0.18902550
[40,] -0.18747869 0.11252131
[41,] -0.68747869 -0.18747869
[42,] -0.58593188 -0.68747869
[43,] -0.88593188 -0.58593188
[44,] -0.48593188 -0.88593188
[45,] -0.90923694 -0.48593188
[46,] -0.40923694 -0.90923694
[47,] -0.80923694 -0.40923694
[48,] -0.50653002 -0.80923694
[49,] -0.90653002 -0.50653002
[50,] -0.60653002 -0.90653002
[51,] -0.50807683 -0.60653002
[52,] -0.40807683 -0.50807683
[53,] -0.60807683 -0.40807683
[54,] -0.87384119 -0.60807683
[55,] -1.37384119 -0.87384119
[56,] -1.27384119 -1.37384119
[57,] -1.24347258 -1.27384119
[58,] -0.84347258 -1.24347258
[59,] -0.94347258 -0.84347258
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 0.09076306 0.89076306
2 0.09076306 0.09076306
3 0.85923434 0.09076306
4 0.95923434 0.85923434
5 0.85923434 0.95923434
6 0.82731892 0.85923434
7 0.62731892 0.82731892
8 0.72731892 0.62731892
9 0.63940960 0.72731892
10 0.83940960 0.63940960
11 0.73940960 0.83940960
12 0.89230987 0.73940960
13 0.49230987 0.89230987
14 0.59230987 0.49230987
15 1.07712556 0.59230987
16 1.07712556 1.07712556
17 0.87712556 1.07712556
18 0.66039445 0.87712556
19 0.66039445 0.66039445
20 0.66039445 0.66039445
21 -0.07886832 0.66039445
22 0.12113168 -0.07886832
23 -0.07886832 0.12113168
24 0.57557875 -0.07886832
25 0.27557875 0.57557875
26 0.27557875 0.27557875
27 0.67673886 0.27557875
28 0.67673886 0.67673886
29 0.67673886 0.67673886
30 0.34172982 0.67673886
31 -0.05827018 0.34172982
32 -0.55827018 -0.05827018
33 -0.42480795 -0.55827018
34 -0.72480795 -0.42480795
35 -1.12480795 -0.72480795
36 -0.28902550 -1.12480795
37 -0.28902550 -0.28902550
38 -0.18902550 -0.28902550
39 0.11252131 -0.18902550
40 -0.18747869 0.11252131
41 -0.68747869 -0.18747869
42 -0.58593188 -0.68747869
43 -0.88593188 -0.58593188
44 -0.48593188 -0.88593188
45 -0.90923694 -0.48593188
46 -0.40923694 -0.90923694
47 -0.80923694 -0.40923694
48 -0.50653002 -0.80923694
49 -0.90653002 -0.50653002
50 -0.60653002 -0.90653002
51 -0.50807683 -0.60653002
52 -0.40807683 -0.50807683
53 -0.60807683 -0.40807683
54 -0.87384119 -0.60807683
55 -1.37384119 -0.87384119
56 -1.27384119 -1.37384119
57 -1.24347258 -1.27384119
58 -0.84347258 -1.24347258
59 -0.94347258 -0.84347258
> 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/77aik1258661727.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8jsxs1258661727.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/997q01258661727.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10ft6r1258661727.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/110kpj1258661727.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/12erkn1258661727.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/13uokd1258661727.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/14dk4h1258661727.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/151dan1258661727.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/16kcyt1258661727.tab")
+ }
>
> system("convert tmp/10g7p1258661727.ps tmp/10g7p1258661727.png")
> system("convert tmp/2yyva1258661727.ps tmp/2yyva1258661727.png")
> system("convert tmp/3ob1f1258661727.ps tmp/3ob1f1258661727.png")
> system("convert tmp/44pny1258661727.ps tmp/44pny1258661727.png")
> system("convert tmp/5ad7q1258661727.ps tmp/5ad7q1258661727.png")
> system("convert tmp/6o1671258661727.ps tmp/6o1671258661727.png")
> system("convert tmp/77aik1258661727.ps tmp/77aik1258661727.png")
> system("convert tmp/8jsxs1258661727.ps tmp/8jsxs1258661727.png")
> system("convert tmp/997q01258661727.ps tmp/997q01258661727.png")
> system("convert tmp/10ft6r1258661727.ps tmp/10ft6r1258661727.png")
>
>
> proc.time()
user system elapsed
2.355 1.532 2.820