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.
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> x <- array(list(8.9,1.9,9,1.6,9,1.7,9,2,9,2.5,9,2.4,9,2.3,9,2.3,9,2.1,9,2.4,9,2.2,9.1,2.4,9,1.9,9,2.1,9.1,2.1,9,2.1,9,2,9,2.1,9,2.2,8.9,2.2,8.9,2.6,8.9,2.5,8.9,2.3,8.8,2.2,8.8,2.4,8.7,2.3,8.7,2.2,8.5,2.5,8.5,2.5,8.4,2.5,8.2,2.4,8.2,2.3,8.1,1.7,8.1,1.6,8,1.9,7.9,1.9,7.8,1.8,7.7,1.8,7.6,1.9,7.5,1.9,7.5,1.9,7.5,1.9,7.5,1.8,7.5,1.7,7.4,2.1,7.4,2.6,7.3,3.1,7.3,3.1,7.3,3.2,7.2,3.3,7.2,3.6,7.3,3.3,7.4,3.7,7.4,4,7.5,4,7.6,3.8,7.7,3.6,7.9,3.2,8,2.1,8.2,1.6),dim=c(2,60),dimnames=list(c('werkl','infl'),1:60))
> y <- array(NA,dim=c(2,60),dimnames=list(c('werkl','infl'),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
werkl infl
1 8.9 1.9
2 9.0 1.6
3 9.0 1.7
4 9.0 2.0
5 9.0 2.5
6 9.0 2.4
7 9.0 2.3
8 9.0 2.3
9 9.0 2.1
10 9.0 2.4
11 9.0 2.2
12 9.1 2.4
13 9.0 1.9
14 9.0 2.1
15 9.1 2.1
16 9.0 2.1
17 9.0 2.0
18 9.0 2.1
19 9.0 2.2
20 8.9 2.2
21 8.9 2.6
22 8.9 2.5
23 8.9 2.3
24 8.8 2.2
25 8.8 2.4
26 8.7 2.3
27 8.7 2.2
28 8.5 2.5
29 8.5 2.5
30 8.4 2.5
31 8.2 2.4
32 8.2 2.3
33 8.1 1.7
34 8.1 1.6
35 8.0 1.9
36 7.9 1.9
37 7.8 1.8
38 7.7 1.8
39 7.6 1.9
40 7.5 1.9
41 7.5 1.9
42 7.5 1.9
43 7.5 1.8
44 7.5 1.7
45 7.4 2.1
46 7.4 2.6
47 7.3 3.1
48 7.3 3.1
49 7.3 3.2
50 7.2 3.3
51 7.2 3.6
52 7.3 3.3
53 7.4 3.7
54 7.4 4.0
55 7.5 4.0
56 7.6 3.8
57 7.7 3.6
58 7.9 3.2
59 8.0 2.1
60 8.2 1.6
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) infl
9.4012 -0.4729
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-1.09721 -0.55533 0.09667 0.58791 0.83385
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 9.4012 0.3192 29.449 < 2e-16 ***
infl -0.4729 0.1293 -3.657 0.000552 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.6246 on 58 degrees of freedom
Multiple R-squared: 0.1874, Adjusted R-squared: 0.1733
F-statistic: 13.37 on 1 and 58 DF, p-value: 0.0005519
> 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,] 7.578996e-04 1.515799e-03 0.9992421004
[2,] 5.481540e-05 1.096308e-04 0.9999451846
[3,] 3.659975e-06 7.319950e-06 0.9999963400
[4,] 2.302151e-07 4.604303e-07 0.9999997698
[5,] 1.403679e-08 2.807359e-08 0.9999999860
[6,] 8.235921e-10 1.647184e-09 0.9999999992
[7,] 4.732733e-11 9.465466e-11 1.0000000000
[8,] 1.009985e-10 2.019970e-10 0.9999999999
[9,] 7.982592e-12 1.596518e-11 1.0000000000
[10,] 6.303640e-13 1.260728e-12 1.0000000000
[11,] 9.227909e-13 1.845582e-12 1.0000000000
[12,] 9.737634e-14 1.947527e-13 1.0000000000
[13,] 1.043341e-14 2.086682e-14 1.0000000000
[14,] 1.247604e-15 2.495208e-15 1.0000000000
[15,] 1.753948e-16 3.507895e-16 1.0000000000
[16,] 5.117816e-16 1.023563e-15 1.0000000000
[17,] 1.225293e-15 2.450587e-15 1.0000000000
[18,] 1.546526e-15 3.093052e-15 1.0000000000
[19,] 2.031658e-15 4.063315e-15 1.0000000000
[20,] 6.928213e-14 1.385643e-13 1.0000000000
[21,] 8.401820e-13 1.680364e-12 1.0000000000
[22,] 9.646618e-11 1.929324e-10 0.9999999999
[23,] 4.449740e-09 8.899481e-09 0.9999999956
[24,] 1.518729e-06 3.037458e-06 0.9999984813
[25,] 7.355014e-05 1.471003e-04 0.9999264499
[26,] 2.672431e-03 5.344862e-03 0.9973275692
[27,] 6.162984e-02 1.232597e-01 0.9383701603
[28,] 3.083995e-01 6.167990e-01 0.6916004977
[29,] 7.240084e-01 5.519831e-01 0.2759915706
[30,] 8.830863e-01 2.338275e-01 0.1169137324
[31,] 9.523939e-01 9.521215e-02 0.0476060756
[32,] 9.782500e-01 4.349999e-02 0.0217499967
[33,] 9.869608e-01 2.607842e-02 0.0130392096
[34,] 9.905841e-01 1.883184e-02 0.0094159216
[35,] 9.930750e-01 1.385003e-02 0.0069250140
[36,] 9.948714e-01 1.025716e-02 0.0051285812
[37,] 9.953949e-01 9.210297e-03 0.0046051484
[38,] 9.952946e-01 9.410748e-03 0.0047053738
[39,] 9.946041e-01 1.079189e-02 0.0053959461
[40,] 9.939951e-01 1.200983e-02 0.0060049136
[41,] 9.965343e-01 6.931367e-03 0.0034656835
[42,] 9.980514e-01 3.897151e-03 0.0019485756
[43,] 9.987666e-01 2.466707e-03 0.0012333533
[44,] 9.988765e-01 2.246970e-03 0.0011234851
[45,] 9.987161e-01 2.567789e-03 0.0012838945
[46,] 9.991902e-01 1.619687e-03 0.0008098437
[47,] 9.993407e-01 1.318510e-03 0.0006592548
[48,] 9.998540e-01 2.919984e-04 0.0001459992
[49,] 9.997973e-01 4.054877e-04 0.0002027438
[50,] 9.995630e-01 8.739983e-04 0.0004369992
[51,] 9.977370e-01 4.526085e-03 0.0022630425
> postscript(file="/var/www/html/rcomp/tmp/12jpk1259343554.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2y7pk1259343554.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3l4fq1259343554.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4bc1s1259343554.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5jf3q1259343554.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
0.397380852 0.355498782 0.402792805 0.544674875 0.781144993 0.733850969
7 8 9 10 11 12
0.686556946 0.686556946 0.591968899 0.733850969 0.639262922 0.833850969
13 14 15 16 17 18
0.497380852 0.591968899 0.691968899 0.591968899 0.544674875 0.591968899
19 20 21 22 23 24
0.639262922 0.539262922 0.728439016 0.681144993 0.586556946 0.439262922
25 26 27 28 29 30
0.533850969 0.386556946 0.339262922 0.281144993 0.281144993 0.181144993
31 32 33 34 35 36
-0.066149031 -0.113443054 -0.497207195 -0.544501218 -0.502619148 -0.602619148
37 38 39 40 41 42
-0.749913171 -0.849913171 -0.902619148 -1.002619148 -1.002619148 -1.002619148
43 44 45 46 47 48
-1.049913171 -1.097207195 -1.008031101 -0.771560984 -0.635090866 -0.635090866
49 50 51 52 53 54
-0.587796843 -0.640502819 -0.498620749 -0.540502819 -0.251326725 -0.109444655
55 56 57 58 59 60
-0.009444655 -0.004032702 0.001379251 0.012203157 -0.408031101 -0.444501218
> postscript(file="/var/www/html/rcomp/tmp/6v79q1259343554.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 0.397380852 NA
1 0.355498782 0.397380852
2 0.402792805 0.355498782
3 0.544674875 0.402792805
4 0.781144993 0.544674875
5 0.733850969 0.781144993
6 0.686556946 0.733850969
7 0.686556946 0.686556946
8 0.591968899 0.686556946
9 0.733850969 0.591968899
10 0.639262922 0.733850969
11 0.833850969 0.639262922
12 0.497380852 0.833850969
13 0.591968899 0.497380852
14 0.691968899 0.591968899
15 0.591968899 0.691968899
16 0.544674875 0.591968899
17 0.591968899 0.544674875
18 0.639262922 0.591968899
19 0.539262922 0.639262922
20 0.728439016 0.539262922
21 0.681144993 0.728439016
22 0.586556946 0.681144993
23 0.439262922 0.586556946
24 0.533850969 0.439262922
25 0.386556946 0.533850969
26 0.339262922 0.386556946
27 0.281144993 0.339262922
28 0.281144993 0.281144993
29 0.181144993 0.281144993
30 -0.066149031 0.181144993
31 -0.113443054 -0.066149031
32 -0.497207195 -0.113443054
33 -0.544501218 -0.497207195
34 -0.502619148 -0.544501218
35 -0.602619148 -0.502619148
36 -0.749913171 -0.602619148
37 -0.849913171 -0.749913171
38 -0.902619148 -0.849913171
39 -1.002619148 -0.902619148
40 -1.002619148 -1.002619148
41 -1.002619148 -1.002619148
42 -1.049913171 -1.002619148
43 -1.097207195 -1.049913171
44 -1.008031101 -1.097207195
45 -0.771560984 -1.008031101
46 -0.635090866 -0.771560984
47 -0.635090866 -0.635090866
48 -0.587796843 -0.635090866
49 -0.640502819 -0.587796843
50 -0.498620749 -0.640502819
51 -0.540502819 -0.498620749
52 -0.251326725 -0.540502819
53 -0.109444655 -0.251326725
54 -0.009444655 -0.109444655
55 -0.004032702 -0.009444655
56 0.001379251 -0.004032702
57 0.012203157 0.001379251
58 -0.408031101 0.012203157
59 -0.444501218 -0.408031101
60 NA -0.444501218
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 0.355498782 0.397380852
[2,] 0.402792805 0.355498782
[3,] 0.544674875 0.402792805
[4,] 0.781144993 0.544674875
[5,] 0.733850969 0.781144993
[6,] 0.686556946 0.733850969
[7,] 0.686556946 0.686556946
[8,] 0.591968899 0.686556946
[9,] 0.733850969 0.591968899
[10,] 0.639262922 0.733850969
[11,] 0.833850969 0.639262922
[12,] 0.497380852 0.833850969
[13,] 0.591968899 0.497380852
[14,] 0.691968899 0.591968899
[15,] 0.591968899 0.691968899
[16,] 0.544674875 0.591968899
[17,] 0.591968899 0.544674875
[18,] 0.639262922 0.591968899
[19,] 0.539262922 0.639262922
[20,] 0.728439016 0.539262922
[21,] 0.681144993 0.728439016
[22,] 0.586556946 0.681144993
[23,] 0.439262922 0.586556946
[24,] 0.533850969 0.439262922
[25,] 0.386556946 0.533850969
[26,] 0.339262922 0.386556946
[27,] 0.281144993 0.339262922
[28,] 0.281144993 0.281144993
[29,] 0.181144993 0.281144993
[30,] -0.066149031 0.181144993
[31,] -0.113443054 -0.066149031
[32,] -0.497207195 -0.113443054
[33,] -0.544501218 -0.497207195
[34,] -0.502619148 -0.544501218
[35,] -0.602619148 -0.502619148
[36,] -0.749913171 -0.602619148
[37,] -0.849913171 -0.749913171
[38,] -0.902619148 -0.849913171
[39,] -1.002619148 -0.902619148
[40,] -1.002619148 -1.002619148
[41,] -1.002619148 -1.002619148
[42,] -1.049913171 -1.002619148
[43,] -1.097207195 -1.049913171
[44,] -1.008031101 -1.097207195
[45,] -0.771560984 -1.008031101
[46,] -0.635090866 -0.771560984
[47,] -0.635090866 -0.635090866
[48,] -0.587796843 -0.635090866
[49,] -0.640502819 -0.587796843
[50,] -0.498620749 -0.640502819
[51,] -0.540502819 -0.498620749
[52,] -0.251326725 -0.540502819
[53,] -0.109444655 -0.251326725
[54,] -0.009444655 -0.109444655
[55,] -0.004032702 -0.009444655
[56,] 0.001379251 -0.004032702
[57,] 0.012203157 0.001379251
[58,] -0.408031101 0.012203157
[59,] -0.444501218 -0.408031101
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 0.355498782 0.397380852
2 0.402792805 0.355498782
3 0.544674875 0.402792805
4 0.781144993 0.544674875
5 0.733850969 0.781144993
6 0.686556946 0.733850969
7 0.686556946 0.686556946
8 0.591968899 0.686556946
9 0.733850969 0.591968899
10 0.639262922 0.733850969
11 0.833850969 0.639262922
12 0.497380852 0.833850969
13 0.591968899 0.497380852
14 0.691968899 0.591968899
15 0.591968899 0.691968899
16 0.544674875 0.591968899
17 0.591968899 0.544674875
18 0.639262922 0.591968899
19 0.539262922 0.639262922
20 0.728439016 0.539262922
21 0.681144993 0.728439016
22 0.586556946 0.681144993
23 0.439262922 0.586556946
24 0.533850969 0.439262922
25 0.386556946 0.533850969
26 0.339262922 0.386556946
27 0.281144993 0.339262922
28 0.281144993 0.281144993
29 0.181144993 0.281144993
30 -0.066149031 0.181144993
31 -0.113443054 -0.066149031
32 -0.497207195 -0.113443054
33 -0.544501218 -0.497207195
34 -0.502619148 -0.544501218
35 -0.602619148 -0.502619148
36 -0.749913171 -0.602619148
37 -0.849913171 -0.749913171
38 -0.902619148 -0.849913171
39 -1.002619148 -0.902619148
40 -1.002619148 -1.002619148
41 -1.002619148 -1.002619148
42 -1.049913171 -1.002619148
43 -1.097207195 -1.049913171
44 -1.008031101 -1.097207195
45 -0.771560984 -1.008031101
46 -0.635090866 -0.771560984
47 -0.635090866 -0.635090866
48 -0.587796843 -0.635090866
49 -0.640502819 -0.587796843
50 -0.498620749 -0.640502819
51 -0.540502819 -0.498620749
52 -0.251326725 -0.540502819
53 -0.109444655 -0.251326725
54 -0.009444655 -0.109444655
55 -0.004032702 -0.009444655
56 0.001379251 -0.004032702
57 0.012203157 0.001379251
58 -0.408031101 0.012203157
59 -0.444501218 -0.408031101
> 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/72z221259343554.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8z5h01259343554.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/91dpd1259343554.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10vvmw1259343554.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11ciiu1259343554.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/12rftm1259343554.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/1374qd1259343554.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/146a971259343554.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/15fhcp1259343554.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/16a7d71259343555.tab")
+ }
>
> system("convert tmp/12jpk1259343554.ps tmp/12jpk1259343554.png")
> system("convert tmp/2y7pk1259343554.ps tmp/2y7pk1259343554.png")
> system("convert tmp/3l4fq1259343554.ps tmp/3l4fq1259343554.png")
> system("convert tmp/4bc1s1259343554.ps tmp/4bc1s1259343554.png")
> system("convert tmp/5jf3q1259343554.ps tmp/5jf3q1259343554.png")
> system("convert tmp/6v79q1259343554.ps tmp/6v79q1259343554.png")
> system("convert tmp/72z221259343554.ps tmp/72z221259343554.png")
> system("convert tmp/8z5h01259343554.ps tmp/8z5h01259343554.png")
> system("convert tmp/91dpd1259343554.ps tmp/91dpd1259343554.png")
> system("convert tmp/10vvmw1259343554.ps tmp/10vvmw1259343554.png")
>
>
> proc.time()
user system elapsed
2.453 1.588 2.923