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.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> x <- array(list(95.1,121.8,97.0,127.6,112.7,129.9,102.9,128.0,97.4,123.5,111.4,124.0,87.4,127.4,96.8,127.6,114.1,128.4,110.3,131.4,103.9,135.1,101.6,134.0,94.6,144.5,95.9,147.3,104.7,150.9,102.8,148.7,98.1,141.4,113.9,138.9,80.9,139.8,95.7,145.6,113.2,147.9,105.9,148.5,108.8,151.1,102.3,157.5,99.0,167.5,100.7,172.3,115.5,173.5,100.7,187.5,109.9,205.5,114.6,195.1,85.4,204.5,100.5,204.5,114.8,201.7,116.5,207.0,112.9,206.6,102.0,210.6,106.0,211.1,105.3,215.0,118.8,223.9,106.1,238.2,109.3,238.9,117.2,229.6,92.5,232.2,104.2,222.1,112.5,221.6,122.4,227.3,113.3,221.0,100.0,213.6,110.7,243.4,112.8,253.8,109.8,265.3,117.3,268.2,109.1,268.5,115.9,266.9,96.0,268.4,99.8,250.8,116.8,231.2,115.7,192.0,99.4,171.4,94.3,160.0),dim=c(2,60),dimnames=list(c('TIP','Grondstofprijzen'),1:60))
> y <- array(NA,dim=c(2,60),dimnames=list(c('TIP','Grondstofprijzen'),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
TIP Grondstofprijzen
1 95.1 121.8
2 97.0 127.6
3 112.7 129.9
4 102.9 128.0
5 97.4 123.5
6 111.4 124.0
7 87.4 127.4
8 96.8 127.6
9 114.1 128.4
10 110.3 131.4
11 103.9 135.1
12 101.6 134.0
13 94.6 144.5
14 95.9 147.3
15 104.7 150.9
16 102.8 148.7
17 98.1 141.4
18 113.9 138.9
19 80.9 139.8
20 95.7 145.6
21 113.2 147.9
22 105.9 148.5
23 108.8 151.1
24 102.3 157.5
25 99.0 167.5
26 100.7 172.3
27 115.5 173.5
28 100.7 187.5
29 109.9 205.5
30 114.6 195.1
31 85.4 204.5
32 100.5 204.5
33 114.8 201.7
34 116.5 207.0
35 112.9 206.6
36 102.0 210.6
37 106.0 211.1
38 105.3 215.0
39 118.8 223.9
40 106.1 238.2
41 109.3 238.9
42 117.2 229.6
43 92.5 232.2
44 104.2 222.1
45 112.5 221.6
46 122.4 227.3
47 113.3 221.0
48 100.0 213.6
49 110.7 243.4
50 112.8 253.8
51 109.8 265.3
52 117.3 268.2
53 109.1 268.5
54 115.9 266.9
55 96.0 268.4
56 99.8 250.8
57 116.8 231.2
58 115.7 192.0
59 99.4 171.4
60 94.3 160.0
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Grondstofprijzen
92.2540 0.0707
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-21.31279 -5.00358 -0.04789 6.61243 14.07518
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 92.25402 4.50132 20.495 < 2e-16 ***
Grondstofprijzen 0.07070 0.02346 3.014 0.00382 **
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 8.44 on 58 degrees of freedom
Multiple R-squared: 0.1354, Adjusted R-squared: 0.1205
F-statistic: 9.085 on 1 and 58 DF, p-value: 0.003817
> 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,] 0.2001971 0.4003941 0.7998029
[2,] 0.4485291 0.8970583 0.5514709
[3,] 0.7281309 0.5437382 0.2718691
[4,] 0.6407552 0.7184896 0.3592448
[5,] 0.7115985 0.5768030 0.2884015
[6,] 0.6362522 0.7274955 0.3637478
[7,] 0.5771160 0.8457680 0.4228840
[8,] 0.5030242 0.9939516 0.4969758
[9,] 0.5409691 0.9180619 0.4590309
[10,] 0.4711094 0.9422188 0.5288906
[11,] 0.4055125 0.8110251 0.5944875
[12,] 0.3222049 0.6444097 0.6777951
[13,] 0.2581006 0.5162012 0.7418994
[14,] 0.3419676 0.6839351 0.6580324
[15,] 0.7215200 0.5569600 0.2784800
[16,] 0.6840096 0.6319809 0.3159904
[17,] 0.7359365 0.5281270 0.2640635
[18,] 0.6797422 0.6405156 0.3202578
[19,] 0.6430046 0.7139908 0.3569954
[20,] 0.5681490 0.8637019 0.4318510
[21,] 0.5114509 0.9770982 0.4885491
[22,] 0.4438087 0.8876174 0.5561913
[23,] 0.5004402 0.9991196 0.4995598
[24,] 0.4455803 0.8911606 0.5544197
[25,] 0.3821609 0.7643219 0.6178391
[26,] 0.3739157 0.7478315 0.6260843
[27,] 0.7355758 0.5288485 0.2644242
[28,] 0.6994948 0.6010105 0.3005052
[29,] 0.7055896 0.5888209 0.2944104
[30,] 0.7266702 0.5466596 0.2733298
[31,] 0.6938899 0.6122202 0.3061101
[32,] 0.6473323 0.7053354 0.3526677
[33,] 0.5724997 0.8550006 0.4275003
[34,] 0.4976952 0.9953904 0.5023048
[35,] 0.5409314 0.9181373 0.4590686
[36,] 0.4695883 0.9391767 0.5304117
[37,] 0.3885957 0.7771914 0.6114043
[38,] 0.3899753 0.7799506 0.6100247
[39,] 0.5959595 0.8080811 0.4040405
[40,] 0.5256227 0.9487546 0.4743773
[41,] 0.4600916 0.9201832 0.5399084
[42,] 0.6252976 0.7494048 0.3747024
[43,] 0.5854018 0.8291964 0.4145982
[44,] 0.5400383 0.9199234 0.4599617
[45,] 0.4414004 0.8828009 0.5585996
[46,] 0.3529140 0.7058280 0.6470860
[47,] 0.2558645 0.5117290 0.7441355
[48,] 0.2269013 0.4538026 0.7730987
[49,] 0.1454707 0.2909415 0.8545293
[50,] 0.1345382 0.2690764 0.8654618
[51,] 0.1736741 0.3473481 0.8263259
> postscript(file="/var/www/html/rcomp/tmp/15h5z1260783623.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2wkgb1260783623.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3ow8n1260783623.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/45sk01260783623.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/57eni1260783623.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
-5.76564716 -4.27572476 11.26165826 1.59599403 -3.58584232 10.37880616
7 8 9 10 11 12
-13.86158415 -4.47572476 12.76771281 8.75560371 2.09400249 -0.12822417
13 14 15 16 17 18
-7.87060603 -6.76857452 1.77689456 0.03244123 -4.15142662 11.82533096
19 20 21 22 23 24
-21.23830177 -6.84837936 10.48900366 3.14658184 5.86275395 -1.08974546
25 26 27 28 29 30
-5.09677580 -3.73615036 10.97900600 -4.81083647 3.11650893 8.55182048
31 32 33 34 35 36
-21.31278804 -6.21278804 8.28518045 9.61045438 6.03873559 -5.14407654
37 38 39 40 41 42
-1.17942806 -2.15516989 10.71557311 -2.99548027 0.15502761 8.71256582
43 44 45 46 47 48
-16.17126207 -3.75716143 4.57819009 14.07518280 5.42061191 -7.35618564
49 50 51 52 53 54
1.23686396 2.60155241 -1.21153248 6.08342872 -2.13778219 4.77534267
55 56 57 58 59 60
-15.23071188 -10.18633849 8.19944097 9.87099988 -4.97251763 -9.26650305
> postscript(file="/var/www/html/rcomp/tmp/6p8il1260783623.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 -5.76564716 NA
1 -4.27572476 -5.76564716
2 11.26165826 -4.27572476
3 1.59599403 11.26165826
4 -3.58584232 1.59599403
5 10.37880616 -3.58584232
6 -13.86158415 10.37880616
7 -4.47572476 -13.86158415
8 12.76771281 -4.47572476
9 8.75560371 12.76771281
10 2.09400249 8.75560371
11 -0.12822417 2.09400249
12 -7.87060603 -0.12822417
13 -6.76857452 -7.87060603
14 1.77689456 -6.76857452
15 0.03244123 1.77689456
16 -4.15142662 0.03244123
17 11.82533096 -4.15142662
18 -21.23830177 11.82533096
19 -6.84837936 -21.23830177
20 10.48900366 -6.84837936
21 3.14658184 10.48900366
22 5.86275395 3.14658184
23 -1.08974546 5.86275395
24 -5.09677580 -1.08974546
25 -3.73615036 -5.09677580
26 10.97900600 -3.73615036
27 -4.81083647 10.97900600
28 3.11650893 -4.81083647
29 8.55182048 3.11650893
30 -21.31278804 8.55182048
31 -6.21278804 -21.31278804
32 8.28518045 -6.21278804
33 9.61045438 8.28518045
34 6.03873559 9.61045438
35 -5.14407654 6.03873559
36 -1.17942806 -5.14407654
37 -2.15516989 -1.17942806
38 10.71557311 -2.15516989
39 -2.99548027 10.71557311
40 0.15502761 -2.99548027
41 8.71256582 0.15502761
42 -16.17126207 8.71256582
43 -3.75716143 -16.17126207
44 4.57819009 -3.75716143
45 14.07518280 4.57819009
46 5.42061191 14.07518280
47 -7.35618564 5.42061191
48 1.23686396 -7.35618564
49 2.60155241 1.23686396
50 -1.21153248 2.60155241
51 6.08342872 -1.21153248
52 -2.13778219 6.08342872
53 4.77534267 -2.13778219
54 -15.23071188 4.77534267
55 -10.18633849 -15.23071188
56 8.19944097 -10.18633849
57 9.87099988 8.19944097
58 -4.97251763 9.87099988
59 -9.26650305 -4.97251763
60 NA -9.26650305
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -4.27572476 -5.76564716
[2,] 11.26165826 -4.27572476
[3,] 1.59599403 11.26165826
[4,] -3.58584232 1.59599403
[5,] 10.37880616 -3.58584232
[6,] -13.86158415 10.37880616
[7,] -4.47572476 -13.86158415
[8,] 12.76771281 -4.47572476
[9,] 8.75560371 12.76771281
[10,] 2.09400249 8.75560371
[11,] -0.12822417 2.09400249
[12,] -7.87060603 -0.12822417
[13,] -6.76857452 -7.87060603
[14,] 1.77689456 -6.76857452
[15,] 0.03244123 1.77689456
[16,] -4.15142662 0.03244123
[17,] 11.82533096 -4.15142662
[18,] -21.23830177 11.82533096
[19,] -6.84837936 -21.23830177
[20,] 10.48900366 -6.84837936
[21,] 3.14658184 10.48900366
[22,] 5.86275395 3.14658184
[23,] -1.08974546 5.86275395
[24,] -5.09677580 -1.08974546
[25,] -3.73615036 -5.09677580
[26,] 10.97900600 -3.73615036
[27,] -4.81083647 10.97900600
[28,] 3.11650893 -4.81083647
[29,] 8.55182048 3.11650893
[30,] -21.31278804 8.55182048
[31,] -6.21278804 -21.31278804
[32,] 8.28518045 -6.21278804
[33,] 9.61045438 8.28518045
[34,] 6.03873559 9.61045438
[35,] -5.14407654 6.03873559
[36,] -1.17942806 -5.14407654
[37,] -2.15516989 -1.17942806
[38,] 10.71557311 -2.15516989
[39,] -2.99548027 10.71557311
[40,] 0.15502761 -2.99548027
[41,] 8.71256582 0.15502761
[42,] -16.17126207 8.71256582
[43,] -3.75716143 -16.17126207
[44,] 4.57819009 -3.75716143
[45,] 14.07518280 4.57819009
[46,] 5.42061191 14.07518280
[47,] -7.35618564 5.42061191
[48,] 1.23686396 -7.35618564
[49,] 2.60155241 1.23686396
[50,] -1.21153248 2.60155241
[51,] 6.08342872 -1.21153248
[52,] -2.13778219 6.08342872
[53,] 4.77534267 -2.13778219
[54,] -15.23071188 4.77534267
[55,] -10.18633849 -15.23071188
[56,] 8.19944097 -10.18633849
[57,] 9.87099988 8.19944097
[58,] -4.97251763 9.87099988
[59,] -9.26650305 -4.97251763
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -4.27572476 -5.76564716
2 11.26165826 -4.27572476
3 1.59599403 11.26165826
4 -3.58584232 1.59599403
5 10.37880616 -3.58584232
6 -13.86158415 10.37880616
7 -4.47572476 -13.86158415
8 12.76771281 -4.47572476
9 8.75560371 12.76771281
10 2.09400249 8.75560371
11 -0.12822417 2.09400249
12 -7.87060603 -0.12822417
13 -6.76857452 -7.87060603
14 1.77689456 -6.76857452
15 0.03244123 1.77689456
16 -4.15142662 0.03244123
17 11.82533096 -4.15142662
18 -21.23830177 11.82533096
19 -6.84837936 -21.23830177
20 10.48900366 -6.84837936
21 3.14658184 10.48900366
22 5.86275395 3.14658184
23 -1.08974546 5.86275395
24 -5.09677580 -1.08974546
25 -3.73615036 -5.09677580
26 10.97900600 -3.73615036
27 -4.81083647 10.97900600
28 3.11650893 -4.81083647
29 8.55182048 3.11650893
30 -21.31278804 8.55182048
31 -6.21278804 -21.31278804
32 8.28518045 -6.21278804
33 9.61045438 8.28518045
34 6.03873559 9.61045438
35 -5.14407654 6.03873559
36 -1.17942806 -5.14407654
37 -2.15516989 -1.17942806
38 10.71557311 -2.15516989
39 -2.99548027 10.71557311
40 0.15502761 -2.99548027
41 8.71256582 0.15502761
42 -16.17126207 8.71256582
43 -3.75716143 -16.17126207
44 4.57819009 -3.75716143
45 14.07518280 4.57819009
46 5.42061191 14.07518280
47 -7.35618564 5.42061191
48 1.23686396 -7.35618564
49 2.60155241 1.23686396
50 -1.21153248 2.60155241
51 6.08342872 -1.21153248
52 -2.13778219 6.08342872
53 4.77534267 -2.13778219
54 -15.23071188 4.77534267
55 -10.18633849 -15.23071188
56 8.19944097 -10.18633849
57 9.87099988 8.19944097
58 -4.97251763 9.87099988
59 -9.26650305 -4.97251763
> 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/7unkw1260783623.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/808nr1260783623.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9n3g41260783623.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/1073ui1260783623.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/110sdl1260783623.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/12wnr01260783623.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/13p4hn1260783623.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/14hhdc1260783623.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/15wzl31260783623.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/16ov911260783623.tab")
+ }
>
> try(system("convert tmp/15h5z1260783623.ps tmp/15h5z1260783623.png",intern=TRUE))
character(0)
> try(system("convert tmp/2wkgb1260783623.ps tmp/2wkgb1260783623.png",intern=TRUE))
character(0)
> try(system("convert tmp/3ow8n1260783623.ps tmp/3ow8n1260783623.png",intern=TRUE))
character(0)
> try(system("convert tmp/45sk01260783623.ps tmp/45sk01260783623.png",intern=TRUE))
character(0)
> try(system("convert tmp/57eni1260783623.ps tmp/57eni1260783623.png",intern=TRUE))
character(0)
> try(system("convert tmp/6p8il1260783623.ps tmp/6p8il1260783623.png",intern=TRUE))
character(0)
> try(system("convert tmp/7unkw1260783623.ps tmp/7unkw1260783623.png",intern=TRUE))
character(0)
> try(system("convert tmp/808nr1260783623.ps tmp/808nr1260783623.png",intern=TRUE))
character(0)
> try(system("convert tmp/9n3g41260783623.ps tmp/9n3g41260783623.png",intern=TRUE))
character(0)
> try(system("convert tmp/1073ui1260783623.ps tmp/1073ui1260783623.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
2.475 1.557 3.028