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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Type 'license()' or 'licence()' for distribution details.
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Type 'contributors()' for more information and
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Type 'demo()' for some demos, 'help()' for on-line help, or
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> x <- array(list(8.1,92.9,7.7,107.7,7.5,103.5,7.6,91.1,7.8,79.8,7.8,71.9,7.8,82.9,7.5,90.1,7.5,100.7,7.1,90.7,7.5,108.8,7.5,44.1,7.6,93.6,7.7,107.4,7.7,96.5,7.9,93.6,8.1,76.5,8.2,76.7,8.2,84,8.2,103.3,7.9,88.5,7.3,99,6.9,105.9,6.6,44.7,6.7,94,6.9,107.1,7,104.8,7.1,102.5,7.2,77.7,7.1,85.2,6.9,91.3,7,106.5,6.8,92.4,6.4,97.5,6.7,107,6.6,51.1,6.4,98.6,6.3,102.2,6.2,114.3,6.5,99.4,6.8,72.5,6.8,92.3,6.4,99.4,6.1,85.9,5.8,109.4,6.1,97.6,7.2,104.7,7.3,56.9,6.9,86.7,6.1,108.5,5.8,103.4,6.2,86.2,7.1,71,7.7,75.9,7.9,87.1,7.7,102,7.4,88.5,7.5,87.8,8,100.8,8.1,50.6,8,85.9),dim=c(2,61),dimnames=list(c('Werkloosheidsgraad','Bruto_index'),1:61))
> y <- array(NA,dim=c(2,61),dimnames=list(c('Werkloosheidsgraad','Bruto_index'),1:61))
> 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 = '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
Werkloosheidsgraad Bruto_index t
1 8.1 92.9 1
2 7.7 107.7 2
3 7.5 103.5 3
4 7.6 91.1 4
5 7.8 79.8 5
6 7.8 71.9 6
7 7.8 82.9 7
8 7.5 90.1 8
9 7.5 100.7 9
10 7.1 90.7 10
11 7.5 108.8 11
12 7.5 44.1 12
13 7.6 93.6 13
14 7.7 107.4 14
15 7.7 96.5 15
16 7.9 93.6 16
17 8.1 76.5 17
18 8.2 76.7 18
19 8.2 84.0 19
20 8.2 103.3 20
21 7.9 88.5 21
22 7.3 99.0 22
23 6.9 105.9 23
24 6.6 44.7 24
25 6.7 94.0 25
26 6.9 107.1 26
27 7.0 104.8 27
28 7.1 102.5 28
29 7.2 77.7 29
30 7.1 85.2 30
31 6.9 91.3 31
32 7.0 106.5 32
33 6.8 92.4 33
34 6.4 97.5 34
35 6.7 107.0 35
36 6.6 51.1 36
37 6.4 98.6 37
38 6.3 102.2 38
39 6.2 114.3 39
40 6.5 99.4 40
41 6.8 72.5 41
42 6.8 92.3 42
43 6.4 99.4 43
44 6.1 85.9 44
45 5.8 109.4 45
46 6.1 97.6 46
47 7.2 104.7 47
48 7.3 56.9 48
49 6.9 86.7 49
50 6.1 108.5 50
51 5.8 103.4 51
52 6.2 86.2 52
53 7.1 71.0 53
54 7.7 75.9 54
55 7.9 87.1 55
56 7.7 102.0 56
57 7.4 88.5 57
58 7.5 87.8 58
59 8.0 100.8 59
60 8.1 50.6 60
61 8.0 85.9 61
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Bruto_index t
8.54364 -0.01014 -0.01419
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-1.150103 -0.427163 -0.007493 0.443575 1.315031
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 8.543643 0.469041 18.215 < 2e-16 ***
Bruto_index -0.010136 0.004804 -2.110 0.03917 *
t -0.014186 0.004404 -3.221 0.00209 **
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.6047 on 58 degrees of freedom
Multiple R-squared: 0.1958, Adjusted R-squared: 0.1681
F-statistic: 7.063 on 2 and 58 DF, p-value: 0.001798
> 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,] 2.166959e-03 0.0043339179 0.9978330
[2,] 6.922696e-03 0.0138453913 0.9930773
[3,] 1.546820e-03 0.0030936407 0.9984532
[4,] 6.043792e-04 0.0012087583 0.9993956
[5,] 5.809191e-04 0.0011618382 0.9994191
[6,] 6.664171e-04 0.0013328341 0.9993336
[7,] 2.023476e-04 0.0004046952 0.9997977
[8,] 1.560914e-04 0.0003121828 0.9998439
[9,] 1.661408e-04 0.0003322815 0.9998339
[10,] 9.576628e-05 0.0001915326 0.9999042
[11,] 1.178626e-04 0.0002357251 0.9998821
[12,] 2.232092e-04 0.0004464185 0.9997768
[13,] 3.773188e-04 0.0007546375 0.9996227
[14,] 5.302848e-04 0.0010605697 0.9994697
[15,] 1.039210e-03 0.0020784203 0.9989608
[16,] 1.047578e-03 0.0020951550 0.9989524
[17,] 3.155591e-03 0.0063111817 0.9968444
[18,] 1.445657e-02 0.0289131314 0.9855434
[19,] 7.308408e-02 0.1461681698 0.9269159
[20,] 1.023311e-01 0.2046622598 0.8976689
[21,] 1.018791e-01 0.2037581680 0.8981209
[22,] 9.474569e-02 0.1894913781 0.9052543
[23,] 9.321987e-02 0.1864397377 0.9067801
[24,] 8.081806e-02 0.1616361242 0.9191819
[25,] 7.515217e-02 0.1503043304 0.9248478
[26,] 7.047829e-02 0.1409565709 0.9295217
[27,] 9.448833e-02 0.1889766624 0.9055117
[28,] 9.890246e-02 0.1978049293 0.9010975
[29,] 1.039420e-01 0.2078840100 0.8960580
[30,] 1.299449e-01 0.2598898113 0.8700551
[31,] 9.889091e-02 0.1977818100 0.9011091
[32,] 8.975977e-02 0.1795195413 0.9102402
[33,] 7.912338e-02 0.1582467672 0.9208766
[34,] 7.303721e-02 0.1460744144 0.9269628
[35,] 6.535406e-02 0.1307081194 0.9346459
[36,] 5.673434e-02 0.1134686749 0.9432657
[37,] 7.986120e-02 0.1597223915 0.9201388
[38,] 7.166912e-02 0.1433382348 0.9283309
[39,] 5.244941e-02 0.1048988125 0.9475506
[40,] 4.444325e-02 0.0888864934 0.9555568
[41,] 2.986916e-02 0.0597383155 0.9701308
[42,] 1.601176e-01 0.3202351310 0.8398824
[43,] 2.357348e-01 0.4714696800 0.7642652
[44,] 3.161637e-01 0.6323273595 0.6838363
[45,] 2.312205e-01 0.4624410201 0.7687795
[46,] 3.803099e-01 0.7606198512 0.6196901
[47,] 8.120002e-01 0.3759996593 0.1879998
[48,] 8.655764e-01 0.2688472361 0.1344236
[49,] 8.130749e-01 0.3738502744 0.1869251
[50,] 8.559544e-01 0.2880912323 0.1440456
> postscript(file="/var/www/html/rcomp/tmp/1emmb1261134723.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2g8ew1261134723.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/32cqg1261134723.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4powo1261134723.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5frb21261134723.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 = 61
Frequency = 1
1 2 3 4 5 6
0.512187714 0.276387786 0.048001772 0.036499658 0.136147265 0.070257645
7 8 9 10 11 12
0.195940500 -0.016893862 0.104734549 -0.382440902 0.215208333 -0.426412324
13 14 15 16 17 18
0.189510758 0.443574721 0.347276771 0.532067700 0.572925870 0.689138739
19 20 21 22 23 24
0.777317988 0.987130554 0.551301777 0.071916577 -0.243958618 -1.150102891
25 26 27 28 29 30
-0.536207030 -0.189238345 -0.098365750 -0.007493155 -0.144683031 -0.154476560
31 32 33 34 35 36
-0.278460643 -0.010206127 -0.338939628 -0.673059821 -0.262581130 -0.915004021
37 38 39 40 41 42
-0.619353158 -0.668677515 -0.631844939 -0.468687328 -0.427163035 -0.212282413
43 44 45 46 47 48
-0.526130386 -0.948782221 -0.996397994 -0.801818442 0.384333585 0.014013183
49 50 51 52 53 54
-0.069745097 -0.634592256 -0.972100769 -0.732256210 0.027860568 0.691713153
55 56 57 58 59 60
1.019423230 0.984636914 0.561985079 0.669075449 1.315030524 0.920383459
61
1.192373782
> postscript(file="/var/www/html/rcomp/tmp/6rlsz1261134723.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 = 61
Frequency = 1
lag(myerror, k = 1) myerror
0 0.512187714 NA
1 0.276387786 0.512187714
2 0.048001772 0.276387786
3 0.036499658 0.048001772
4 0.136147265 0.036499658
5 0.070257645 0.136147265
6 0.195940500 0.070257645
7 -0.016893862 0.195940500
8 0.104734549 -0.016893862
9 -0.382440902 0.104734549
10 0.215208333 -0.382440902
11 -0.426412324 0.215208333
12 0.189510758 -0.426412324
13 0.443574721 0.189510758
14 0.347276771 0.443574721
15 0.532067700 0.347276771
16 0.572925870 0.532067700
17 0.689138739 0.572925870
18 0.777317988 0.689138739
19 0.987130554 0.777317988
20 0.551301777 0.987130554
21 0.071916577 0.551301777
22 -0.243958618 0.071916577
23 -1.150102891 -0.243958618
24 -0.536207030 -1.150102891
25 -0.189238345 -0.536207030
26 -0.098365750 -0.189238345
27 -0.007493155 -0.098365750
28 -0.144683031 -0.007493155
29 -0.154476560 -0.144683031
30 -0.278460643 -0.154476560
31 -0.010206127 -0.278460643
32 -0.338939628 -0.010206127
33 -0.673059821 -0.338939628
34 -0.262581130 -0.673059821
35 -0.915004021 -0.262581130
36 -0.619353158 -0.915004021
37 -0.668677515 -0.619353158
38 -0.631844939 -0.668677515
39 -0.468687328 -0.631844939
40 -0.427163035 -0.468687328
41 -0.212282413 -0.427163035
42 -0.526130386 -0.212282413
43 -0.948782221 -0.526130386
44 -0.996397994 -0.948782221
45 -0.801818442 -0.996397994
46 0.384333585 -0.801818442
47 0.014013183 0.384333585
48 -0.069745097 0.014013183
49 -0.634592256 -0.069745097
50 -0.972100769 -0.634592256
51 -0.732256210 -0.972100769
52 0.027860568 -0.732256210
53 0.691713153 0.027860568
54 1.019423230 0.691713153
55 0.984636914 1.019423230
56 0.561985079 0.984636914
57 0.669075449 0.561985079
58 1.315030524 0.669075449
59 0.920383459 1.315030524
60 1.192373782 0.920383459
61 NA 1.192373782
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 0.276387786 0.512187714
[2,] 0.048001772 0.276387786
[3,] 0.036499658 0.048001772
[4,] 0.136147265 0.036499658
[5,] 0.070257645 0.136147265
[6,] 0.195940500 0.070257645
[7,] -0.016893862 0.195940500
[8,] 0.104734549 -0.016893862
[9,] -0.382440902 0.104734549
[10,] 0.215208333 -0.382440902
[11,] -0.426412324 0.215208333
[12,] 0.189510758 -0.426412324
[13,] 0.443574721 0.189510758
[14,] 0.347276771 0.443574721
[15,] 0.532067700 0.347276771
[16,] 0.572925870 0.532067700
[17,] 0.689138739 0.572925870
[18,] 0.777317988 0.689138739
[19,] 0.987130554 0.777317988
[20,] 0.551301777 0.987130554
[21,] 0.071916577 0.551301777
[22,] -0.243958618 0.071916577
[23,] -1.150102891 -0.243958618
[24,] -0.536207030 -1.150102891
[25,] -0.189238345 -0.536207030
[26,] -0.098365750 -0.189238345
[27,] -0.007493155 -0.098365750
[28,] -0.144683031 -0.007493155
[29,] -0.154476560 -0.144683031
[30,] -0.278460643 -0.154476560
[31,] -0.010206127 -0.278460643
[32,] -0.338939628 -0.010206127
[33,] -0.673059821 -0.338939628
[34,] -0.262581130 -0.673059821
[35,] -0.915004021 -0.262581130
[36,] -0.619353158 -0.915004021
[37,] -0.668677515 -0.619353158
[38,] -0.631844939 -0.668677515
[39,] -0.468687328 -0.631844939
[40,] -0.427163035 -0.468687328
[41,] -0.212282413 -0.427163035
[42,] -0.526130386 -0.212282413
[43,] -0.948782221 -0.526130386
[44,] -0.996397994 -0.948782221
[45,] -0.801818442 -0.996397994
[46,] 0.384333585 -0.801818442
[47,] 0.014013183 0.384333585
[48,] -0.069745097 0.014013183
[49,] -0.634592256 -0.069745097
[50,] -0.972100769 -0.634592256
[51,] -0.732256210 -0.972100769
[52,] 0.027860568 -0.732256210
[53,] 0.691713153 0.027860568
[54,] 1.019423230 0.691713153
[55,] 0.984636914 1.019423230
[56,] 0.561985079 0.984636914
[57,] 0.669075449 0.561985079
[58,] 1.315030524 0.669075449
[59,] 0.920383459 1.315030524
[60,] 1.192373782 0.920383459
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 0.276387786 0.512187714
2 0.048001772 0.276387786
3 0.036499658 0.048001772
4 0.136147265 0.036499658
5 0.070257645 0.136147265
6 0.195940500 0.070257645
7 -0.016893862 0.195940500
8 0.104734549 -0.016893862
9 -0.382440902 0.104734549
10 0.215208333 -0.382440902
11 -0.426412324 0.215208333
12 0.189510758 -0.426412324
13 0.443574721 0.189510758
14 0.347276771 0.443574721
15 0.532067700 0.347276771
16 0.572925870 0.532067700
17 0.689138739 0.572925870
18 0.777317988 0.689138739
19 0.987130554 0.777317988
20 0.551301777 0.987130554
21 0.071916577 0.551301777
22 -0.243958618 0.071916577
23 -1.150102891 -0.243958618
24 -0.536207030 -1.150102891
25 -0.189238345 -0.536207030
26 -0.098365750 -0.189238345
27 -0.007493155 -0.098365750
28 -0.144683031 -0.007493155
29 -0.154476560 -0.144683031
30 -0.278460643 -0.154476560
31 -0.010206127 -0.278460643
32 -0.338939628 -0.010206127
33 -0.673059821 -0.338939628
34 -0.262581130 -0.673059821
35 -0.915004021 -0.262581130
36 -0.619353158 -0.915004021
37 -0.668677515 -0.619353158
38 -0.631844939 -0.668677515
39 -0.468687328 -0.631844939
40 -0.427163035 -0.468687328
41 -0.212282413 -0.427163035
42 -0.526130386 -0.212282413
43 -0.948782221 -0.526130386
44 -0.996397994 -0.948782221
45 -0.801818442 -0.996397994
46 0.384333585 -0.801818442
47 0.014013183 0.384333585
48 -0.069745097 0.014013183
49 -0.634592256 -0.069745097
50 -0.972100769 -0.634592256
51 -0.732256210 -0.972100769
52 0.027860568 -0.732256210
53 0.691713153 0.027860568
54 1.019423230 0.691713153
55 0.984636914 1.019423230
56 0.561985079 0.984636914
57 0.669075449 0.561985079
58 1.315030524 0.669075449
59 0.920383459 1.315030524
60 1.192373782 0.920383459
> 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/7nyk01261134723.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8gs3i1261134723.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9j0ta1261134723.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10laam1261134723.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11e2e71261134723.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/125itr1261134723.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/13rt531261134723.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/14x2if1261134723.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/156vef1261134723.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/16erep1261134723.tab")
+ }
>
> try(system("convert tmp/1emmb1261134723.ps tmp/1emmb1261134723.png",intern=TRUE))
character(0)
> try(system("convert tmp/2g8ew1261134723.ps tmp/2g8ew1261134723.png",intern=TRUE))
character(0)
> try(system("convert tmp/32cqg1261134723.ps tmp/32cqg1261134723.png",intern=TRUE))
character(0)
> try(system("convert tmp/4powo1261134723.ps tmp/4powo1261134723.png",intern=TRUE))
character(0)
> try(system("convert tmp/5frb21261134723.ps tmp/5frb21261134723.png",intern=TRUE))
character(0)
> try(system("convert tmp/6rlsz1261134723.ps tmp/6rlsz1261134723.png",intern=TRUE))
character(0)
> try(system("convert tmp/7nyk01261134723.ps tmp/7nyk01261134723.png",intern=TRUE))
character(0)
> try(system("convert tmp/8gs3i1261134723.ps tmp/8gs3i1261134723.png",intern=TRUE))
character(0)
> try(system("convert tmp/9j0ta1261134723.ps tmp/9j0ta1261134723.png",intern=TRUE))
character(0)
> try(system("convert tmp/10laam1261134723.ps tmp/10laam1261134723.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
2.456 1.561 3.491