R version 2.12.0 (2010-10-15)
Copyright (C) 2010 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-bit)
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
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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(284
+ ,14.3
+ ,0
+ ,3
+ ,0
+ ,9.3
+ ,164
+ ,14.6
+ ,22
+ ,14
+ ,0
+ ,14.2
+ ,130
+ ,17.5
+ ,19
+ ,17
+ ,0
+ ,17.3
+ ,178
+ ,17.2
+ ,18
+ ,14
+ ,0
+ ,23
+ ,150
+ ,17.2
+ ,13
+ ,10
+ ,0
+ ,16.3
+ ,104
+ ,14.1
+ ,16
+ ,7
+ ,0
+ ,18.4
+ ,111
+ ,10.4
+ ,11
+ ,4
+ ,0
+ ,14.2
+ ,51
+ ,6.8
+ ,22
+ ,1
+ ,1
+ ,9.1
+ ,70
+ ,4.1
+ ,19
+ ,6
+ ,0
+ ,5.9
+ ,42
+ ,6.5
+ ,23
+ ,2
+ ,1
+ ,7.2
+ ,126
+ ,6.1
+ ,11
+ ,2
+ ,0
+ ,6.8
+ ,68
+ ,6.3
+ ,24
+ ,8
+ ,7
+ ,8
+ ,135
+ ,9.3
+ ,14
+ ,10
+ ,0
+ ,14.3
+ ,231
+ ,16.4
+ ,11
+ ,13
+ ,0
+ ,14.6
+ ,185
+ ,16.1
+ ,17
+ ,10
+ ,0
+ ,17.5
+ ,181
+ ,18
+ ,20
+ ,14
+ ,0
+ ,17.2
+ ,138
+ ,17.6
+ ,19
+ ,13
+ ,0
+ ,17.2
+ ,158
+ ,14
+ ,12
+ ,6
+ ,0
+ ,14.1
+ ,122
+ ,10.5
+ ,19
+ ,6
+ ,2
+ ,10.4
+ ,40
+ ,6.9
+ ,26
+ ,9
+ ,3
+ ,6.8
+ ,62
+ ,2.8
+ ,13
+ ,2
+ ,5
+ ,4.1
+ ,89
+ ,0.7
+ ,12
+ ,4
+ ,5
+ ,6.5
+ ,33
+ ,3.6
+ ,20
+ ,3
+ ,7
+ ,6.1
+ ,150
+ ,6.7
+ ,15
+ ,4
+ ,2
+ ,6.3
+ ,196
+ ,12.5
+ ,15
+ ,10
+ ,0
+ ,9.3
+ ,196
+ ,14.4
+ ,17
+ ,15
+ ,0
+ ,16.4
+ ,225
+ ,16.5
+ ,11
+ ,14
+ ,0
+ ,16.1
+ ,213
+ ,18.7
+ ,20
+ ,18
+ ,0
+ ,18
+ ,258
+ ,19.4
+ ,9
+ ,10
+ ,0
+ ,17.6
+ ,156
+ ,15.8
+ ,10
+ ,5
+ ,0
+ ,14
+ ,90
+ ,11.3
+ ,17
+ ,5
+ ,0
+ ,10.5
+ ,48
+ ,9.7
+ ,25
+ ,7
+ ,0
+ ,6.9
+ ,46
+ ,2.9
+ ,19
+ ,2
+ ,7
+ ,2.8
+ ,49
+ ,0.1
+ ,18
+ ,0
+ ,14
+ ,0.7
+ ,29
+ ,2.5
+ ,24
+ ,4
+ ,10
+ ,3.6
+ ,118
+ ,6.7
+ ,13
+ ,7
+ ,2
+ ,6.7
+ ,223
+ ,10.3
+ ,6
+ ,8
+ ,0
+ ,12.5
+ ,172
+ ,11.2
+ ,14
+ ,6
+ ,0
+ ,14.4
+ ,259
+ ,17.4
+ ,9
+ ,3
+ ,0
+ ,16.5
+ ,252
+ ,20.5
+ ,13
+ ,12
+ ,0
+ ,18.7
+ ,136
+ ,17
+ ,23
+ ,15
+ ,0
+ ,19.4
+ ,143
+ ,14.2
+ ,18
+ ,8
+ ,0
+ ,15.8
+ ,119
+ ,10.6
+ ,16
+ ,6
+ ,0
+ ,11.3
+ ,24
+ ,6.1
+ ,21
+ ,1
+ ,6
+ ,9.7)
+ ,dim=c(6
+ ,44)
+ ,dimnames=list(c('UrenZonneschijn'
+ ,'GemiddeldeTemperatuur'
+ ,'Neerslagdagen'
+ ,'Onweersdagen'
+ ,'Sneeuwdagen'
+ ,'GemTemperatuurAuto')
+ ,1:44))
> y <- array(NA,dim=c(6,44),dimnames=list(c('UrenZonneschijn','GemiddeldeTemperatuur','Neerslagdagen','Onweersdagen','Sneeuwdagen','GemTemperatuurAuto'),1:44))
> 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 = '2'
> #'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
> 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
GemiddeldeTemperatuur UrenZonneschijn Neerslagdagen Onweersdagen Sneeuwdagen
1 14.3 284 0 3 0
2 14.6 164 22 14 0
3 17.5 130 19 17 0
4 17.2 178 18 14 0
5 17.2 150 13 10 0
6 14.1 104 16 7 0
7 10.4 111 11 4 0
8 6.8 51 22 1 1
9 4.1 70 19 6 0
10 6.5 42 23 2 1
11 6.1 126 11 2 0
12 6.3 68 24 8 7
13 9.3 135 14 10 0
14 16.4 231 11 13 0
15 16.1 185 17 10 0
16 18.0 181 20 14 0
17 17.6 138 19 13 0
18 14.0 158 12 6 0
19 10.5 122 19 6 2
20 6.9 40 26 9 3
21 2.8 62 13 2 5
22 0.7 89 12 4 5
23 3.6 33 20 3 7
24 6.7 150 15 4 2
25 12.5 196 15 10 0
26 14.4 196 17 15 0
27 16.5 225 11 14 0
28 18.7 213 20 18 0
29 19.4 258 9 10 0
30 15.8 156 10 5 0
31 11.3 90 17 5 0
32 9.7 48 25 7 0
33 2.9 46 19 2 7
34 0.1 49 18 0 14
35 2.5 29 24 4 10
36 6.7 118 13 7 2
37 10.3 223 6 8 0
38 11.2 172 14 6 0
39 17.4 259 9 3 0
40 20.5 252 13 12 0
41 17.0 136 23 15 0
42 14.2 143 18 8 0
43 10.6 119 16 6 0
44 6.1 24 21 1 6
GemTemperatuurAuto
1 9.3
2 14.2
3 17.3
4 23.0
5 16.3
6 18.4
7 14.2
8 9.1
9 5.9
10 7.2
11 6.8
12 8.0
13 14.3
14 14.6
15 17.5
16 17.2
17 17.2
18 14.1
19 10.4
20 6.8
21 4.1
22 6.5
23 6.1
24 6.3
25 9.3
26 16.4
27 16.1
28 18.0
29 17.6
30 14.0
31 10.5
32 6.9
33 2.8
34 0.7
35 3.6
36 6.7
37 12.5
38 14.4
39 16.5
40 18.7
41 19.4
42 15.8
43 11.3
44 9.7
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) UrenZonneschijn Neerslagdagen Onweersdagen
-4.045302 0.038144 0.213147 0.001013
Sneeuwdagen GemTemperatuurAuto
-0.208606 0.587554
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-3.9874 -0.6995 0.0338 0.9501 3.5326
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -4.045302 2.255823 -1.793 0.080892 .
UrenZonneschijn 0.038144 0.009171 4.159 0.000176 ***
Neerslagdagen 0.213147 0.098636 2.161 0.037069 *
Onweersdagen 0.001013 0.107129 0.009 0.992505
Sneeuwdagen -0.208606 0.123561 -1.688 0.099550 .
GemTemperatuurAuto 0.587554 0.094520 6.216 2.88e-07 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 1.79 on 38 degrees of freedom
Multiple R-squared: 0.9118, Adjusted R-squared: 0.9002
F-statistic: 78.59 on 5 and 38 DF, p-value: < 2.2e-16
> if (n > n25) {
+ kp3 <- k + 3
+ nmkm3 <- n - k - 3
+ gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
+ numgqtests <- 0
+ numsignificant1 <- 0
+ numsignificant5 <- 0
+ numsignificant10 <- 0
+ for (mypoint in kp3:nmkm3) {
+ j <- 0
+ numgqtests <- numgqtests + 1
+ for (myalt in c('greater', 'two.sided', 'less')) {
+ j <- j + 1
+ gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
+ }
+ if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
+ }
+ gqarr
+ }
[,1] [,2] [,3]
[1,] 0.7191151 0.5617697 0.2808849
[2,] 0.5684284 0.8631433 0.4315716
[3,] 0.4308323 0.8616646 0.5691677
[4,] 0.7323767 0.5352466 0.2676233
[5,] 0.8958348 0.2083304 0.1041652
[6,] 0.8442469 0.3115062 0.1557531
[7,] 0.7801296 0.4397409 0.2198704
[8,] 0.7156615 0.5686769 0.2843385
[9,] 0.7456493 0.5087015 0.2543507
[10,] 0.6876133 0.6247734 0.3123867
[11,] 0.5964877 0.8070246 0.4035123
[12,] 0.5076158 0.9847684 0.4923842
[13,] 0.4122105 0.8244210 0.5877895
[14,] 0.7164042 0.5671916 0.2835958
[15,] 0.6528116 0.6943769 0.3471884
[16,] 0.6281020 0.7437961 0.3718980
[17,] 0.5285475 0.9429049 0.4714525
[18,] 0.5801142 0.8397717 0.4198858
[19,] 0.4776218 0.9552436 0.5223782
[20,] 0.3722442 0.7444883 0.6277558
[21,] 0.3533236 0.7066472 0.6466764
[22,] 0.7689990 0.4620020 0.2310010
[23,] 0.8448552 0.3102895 0.1551448
[24,] 0.7954763 0.4090473 0.2045237
[25,] 0.7060552 0.5878896 0.2939448
[26,] 0.5745694 0.8508612 0.4254306
[27,] 0.6971986 0.6056028 0.3028014
> postscript(file="/var/www/rcomp/tmp/1rkw91293195438.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
> points(x[,1]-mysum$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/2rkw91293195438.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/3jceu1293195438.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/4jceu1293195438.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/5jceu1293195438.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
> qqline(mysum$resid)
> grid()
> dev.off()
null device
1
> (myerror <- as.ts(mysum$resid))
Time Series:
Start = 1
End = 44
Frequency = 1
1 2 3 4 5 6
2.045238951 -0.656914562 2.354951244 -2.908811178 3.165604110 -0.050055589
7 8 9 10 11 12
-0.480562682 -0.928392439 -2.047178997 0.017092274 -1.002792443 -0.612272392
13 14 15 16 17 18
-3.200281418 0.698070658 -0.827071984 0.758276695 2.212609862 1.170272289
19 20 21 22 23 24
0.142575175 0.499082184 0.341527668 -3.987357075 -0.003243893 -1.461861890
25 26 27 28 29 30
0.397582936 -2.305406887 0.144588478 -0.236412421 1.334865060 3.532621046
31 32 33 34 35 36
2.114508465 2.524532999 0.953976717 0.948822967 0.290433083 -0.053034687
37 38 39 40 41 42
-2.792119876 -2.766297127 -0.049878692 1.162804866 -0.458333765 -0.337321308
43 44
0.050435566 0.305128011
> postscript(file="/var/www/rcomp/tmp/6c3dx1293195438.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> dum <- cbind(lag(myerror,k=1),myerror)
> dum
Time Series:
Start = 0
End = 44
Frequency = 1
lag(myerror, k = 1) myerror
0 2.045238951 NA
1 -0.656914562 2.045238951
2 2.354951244 -0.656914562
3 -2.908811178 2.354951244
4 3.165604110 -2.908811178
5 -0.050055589 3.165604110
6 -0.480562682 -0.050055589
7 -0.928392439 -0.480562682
8 -2.047178997 -0.928392439
9 0.017092274 -2.047178997
10 -1.002792443 0.017092274
11 -0.612272392 -1.002792443
12 -3.200281418 -0.612272392
13 0.698070658 -3.200281418
14 -0.827071984 0.698070658
15 0.758276695 -0.827071984
16 2.212609862 0.758276695
17 1.170272289 2.212609862
18 0.142575175 1.170272289
19 0.499082184 0.142575175
20 0.341527668 0.499082184
21 -3.987357075 0.341527668
22 -0.003243893 -3.987357075
23 -1.461861890 -0.003243893
24 0.397582936 -1.461861890
25 -2.305406887 0.397582936
26 0.144588478 -2.305406887
27 -0.236412421 0.144588478
28 1.334865060 -0.236412421
29 3.532621046 1.334865060
30 2.114508465 3.532621046
31 2.524532999 2.114508465
32 0.953976717 2.524532999
33 0.948822967 0.953976717
34 0.290433083 0.948822967
35 -0.053034687 0.290433083
36 -2.792119876 -0.053034687
37 -2.766297127 -2.792119876
38 -0.049878692 -2.766297127
39 1.162804866 -0.049878692
40 -0.458333765 1.162804866
41 -0.337321308 -0.458333765
42 0.050435566 -0.337321308
43 0.305128011 0.050435566
44 NA 0.305128011
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -0.656914562 2.045238951
[2,] 2.354951244 -0.656914562
[3,] -2.908811178 2.354951244
[4,] 3.165604110 -2.908811178
[5,] -0.050055589 3.165604110
[6,] -0.480562682 -0.050055589
[7,] -0.928392439 -0.480562682
[8,] -2.047178997 -0.928392439
[9,] 0.017092274 -2.047178997
[10,] -1.002792443 0.017092274
[11,] -0.612272392 -1.002792443
[12,] -3.200281418 -0.612272392
[13,] 0.698070658 -3.200281418
[14,] -0.827071984 0.698070658
[15,] 0.758276695 -0.827071984
[16,] 2.212609862 0.758276695
[17,] 1.170272289 2.212609862
[18,] 0.142575175 1.170272289
[19,] 0.499082184 0.142575175
[20,] 0.341527668 0.499082184
[21,] -3.987357075 0.341527668
[22,] -0.003243893 -3.987357075
[23,] -1.461861890 -0.003243893
[24,] 0.397582936 -1.461861890
[25,] -2.305406887 0.397582936
[26,] 0.144588478 -2.305406887
[27,] -0.236412421 0.144588478
[28,] 1.334865060 -0.236412421
[29,] 3.532621046 1.334865060
[30,] 2.114508465 3.532621046
[31,] 2.524532999 2.114508465
[32,] 0.953976717 2.524532999
[33,] 0.948822967 0.953976717
[34,] 0.290433083 0.948822967
[35,] -0.053034687 0.290433083
[36,] -2.792119876 -0.053034687
[37,] -2.766297127 -2.792119876
[38,] -0.049878692 -2.766297127
[39,] 1.162804866 -0.049878692
[40,] -0.458333765 1.162804866
[41,] -0.337321308 -0.458333765
[42,] 0.050435566 -0.337321308
[43,] 0.305128011 0.050435566
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -0.656914562 2.045238951
2 2.354951244 -0.656914562
3 -2.908811178 2.354951244
4 3.165604110 -2.908811178
5 -0.050055589 3.165604110
6 -0.480562682 -0.050055589
7 -0.928392439 -0.480562682
8 -2.047178997 -0.928392439
9 0.017092274 -2.047178997
10 -1.002792443 0.017092274
11 -0.612272392 -1.002792443
12 -3.200281418 -0.612272392
13 0.698070658 -3.200281418
14 -0.827071984 0.698070658
15 0.758276695 -0.827071984
16 2.212609862 0.758276695
17 1.170272289 2.212609862
18 0.142575175 1.170272289
19 0.499082184 0.142575175
20 0.341527668 0.499082184
21 -3.987357075 0.341527668
22 -0.003243893 -3.987357075
23 -1.461861890 -0.003243893
24 0.397582936 -1.461861890
25 -2.305406887 0.397582936
26 0.144588478 -2.305406887
27 -0.236412421 0.144588478
28 1.334865060 -0.236412421
29 3.532621046 1.334865060
30 2.114508465 3.532621046
31 2.524532999 2.114508465
32 0.953976717 2.524532999
33 0.948822967 0.953976717
34 0.290433083 0.948822967
35 -0.053034687 0.290433083
36 -2.792119876 -0.053034687
37 -2.766297127 -2.792119876
38 -0.049878692 -2.766297127
39 1.162804866 -0.049878692
40 -0.458333765 1.162804866
41 -0.337321308 -0.458333765
42 0.050435566 -0.337321308
43 0.305128011 0.050435566
> 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/rcomp/tmp/7nuu01293195438.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/8nuu01293195438.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/9nuu01293195438.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/rcomp/tmp/10gmul1293195438.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/rcomp/tmp/1114ar1293195438.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/rcomp/tmp/12mn9x1293195438.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/rcomp/tmp/13bo911293195439.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/rcomp/tmp/14ep7o1293195439.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/rcomp/tmp/150poc1293195439.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/rcomp/tmp/1638401293195439.tab")
+ }
>
> try(system("convert tmp/1rkw91293195438.ps tmp/1rkw91293195438.png",intern=TRUE))
character(0)
> try(system("convert tmp/2rkw91293195438.ps tmp/2rkw91293195438.png",intern=TRUE))
character(0)
> try(system("convert tmp/3jceu1293195438.ps tmp/3jceu1293195438.png",intern=TRUE))
character(0)
> try(system("convert tmp/4jceu1293195438.ps tmp/4jceu1293195438.png",intern=TRUE))
character(0)
> try(system("convert tmp/5jceu1293195438.ps tmp/5jceu1293195438.png",intern=TRUE))
character(0)
> try(system("convert tmp/6c3dx1293195438.ps tmp/6c3dx1293195438.png",intern=TRUE))
character(0)
> try(system("convert tmp/7nuu01293195438.ps tmp/7nuu01293195438.png",intern=TRUE))
character(0)
> try(system("convert tmp/8nuu01293195438.ps tmp/8nuu01293195438.png",intern=TRUE))
character(0)
> try(system("convert tmp/9nuu01293195438.ps tmp/9nuu01293195438.png",intern=TRUE))
character(0)
> try(system("convert tmp/10gmul1293195438.ps tmp/10gmul1293195438.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
2.89 1.66 4.55