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
'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.
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> x <- array(list(0,0,104.7,102.8,0,113.9,0,0,113.2,105.9,108.8,102.3,0,100.7,115.5,100.7,109.9,114.6,0,100.5,114.8,116.5,112.9,102,106,105.3,118.8,106.1,109.3,117.2,0,104.2,112.5,122.4,113.3,100,110.7,112.8,109.8,117.3,109.1,115.9,0,0,116.8,115.7,0,0,0,0,103.1,0,0,102.7,0,0,104.5,105.1,0,0,0,0,111.5,0,0,111.7,0,0),dim=c(1,68),dimnames=list(c('productie*dummy'),1:68))
> y <- array(NA,dim=c(1,68),dimnames=list(c('productie*dummy'),1:68))
> 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
> 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
productie*dummy t
1 0.0 1
2 0.0 2
3 104.7 3
4 102.8 4
5 0.0 5
6 113.9 6
7 0.0 7
8 0.0 8
9 113.2 9
10 105.9 10
11 108.8 11
12 102.3 12
13 0.0 13
14 100.7 14
15 115.5 15
16 100.7 16
17 109.9 17
18 114.6 18
19 0.0 19
20 100.5 20
21 114.8 21
22 116.5 22
23 112.9 23
24 102.0 24
25 106.0 25
26 105.3 26
27 118.8 27
28 106.1 28
29 109.3 29
30 117.2 30
31 0.0 31
32 104.2 32
33 112.5 33
34 122.4 34
35 113.3 35
36 100.0 36
37 110.7 37
38 112.8 38
39 109.8 39
40 117.3 40
41 109.1 41
42 115.9 42
43 0.0 43
44 0.0 44
45 116.8 45
46 115.7 46
47 0.0 47
48 0.0 48
49 0.0 49
50 0.0 50
51 103.1 51
52 0.0 52
53 0.0 53
54 102.7 54
55 0.0 55
56 0.0 56
57 104.5 57
58 105.1 58
59 0.0 59
60 0.0 60
61 0.0 61
62 0.0 62
63 111.5 63
64 0.0 64
65 0.0 65
66 111.7 66
67 0.0 67
68 0.0 68
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) t
94.7631 -0.7853
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-93.98 -50.98 23.26 45.06 68.77
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 94.7631 12.7375 7.440 2.66e-10 ***
t -0.7853 0.3209 -2.447 0.0171 *
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 51.94 on 66 degrees of freedom
Multiple R-squared: 0.08319, Adjusted R-squared: 0.0693
F-statistic: 5.989 on 1 and 66 DF, p-value: 0.01706
> 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,] 0.80999677 0.3800065 0.1900032
[2,] 0.71673093 0.5665381 0.2832691
[3,] 0.84499726 0.3100055 0.1550027
[4,] 0.86411935 0.2717613 0.1358806
[5,] 0.86856733 0.2628653 0.1314327
[6,] 0.82127682 0.3574464 0.1787232
[7,] 0.75332006 0.4933599 0.2466799
[8,] 0.66917595 0.6616481 0.3308240
[9,] 0.86268708 0.2746258 0.1373129
[10,] 0.81331830 0.3733634 0.1866817
[11,] 0.75746091 0.4850782 0.2425391
[12,] 0.68733340 0.6253332 0.3126666
[13,] 0.60919237 0.7816153 0.3908076
[14,] 0.52712677 0.9457465 0.4728732
[15,] 0.81489796 0.3702041 0.1851020
[16,] 0.76181571 0.4763686 0.2381843
[17,] 0.70084447 0.5983111 0.2991555
[18,] 0.63244236 0.7351153 0.3675576
[19,] 0.55858106 0.8828379 0.4414189
[20,] 0.48832806 0.9766561 0.5116719
[21,] 0.41649488 0.8329898 0.5835051
[22,] 0.34859750 0.6971950 0.6514025
[23,] 0.28338329 0.5667666 0.7166167
[24,] 0.22794453 0.4558891 0.7720555
[25,] 0.17868459 0.3573692 0.8213154
[26,] 0.13695941 0.2739188 0.8630406
[27,] 0.40645286 0.8129057 0.5935471
[28,] 0.33939632 0.6787926 0.6606037
[29,] 0.27726773 0.5545355 0.7227323
[30,] 0.22693445 0.4538689 0.7730656
[31,] 0.18029803 0.3605961 0.8197020
[32,] 0.14120061 0.2824012 0.8587994
[33,] 0.10976368 0.2195274 0.8902363
[34,] 0.08637087 0.1727417 0.9136291
[35,] 0.06871293 0.1374259 0.9312871
[36,] 0.05973346 0.1194669 0.9402665
[37,] 0.05328915 0.1065783 0.9467108
[38,] 0.05695778 0.1139156 0.9430422
[39,] 0.12966432 0.2593286 0.8703357
[40,] 0.20694357 0.4138871 0.7930564
[41,] 0.22411906 0.4482381 0.7758809
[42,] 0.28319879 0.5663976 0.7168012
[43,] 0.33413741 0.6682748 0.6658626
[44,] 0.36520649 0.7304130 0.6347935
[45,] 0.38501395 0.7700279 0.6149861
[46,] 0.40278240 0.8055648 0.5972176
[47,] 0.40907369 0.8181474 0.5909263
[48,] 0.40424921 0.8084984 0.5957508
[49,] 0.40896894 0.8179379 0.5910311
[50,] 0.41065437 0.8213087 0.5893456
[51,] 0.39314365 0.7862873 0.6068563
[52,] 0.40054429 0.8010886 0.5994557
[53,] 0.39535441 0.7907088 0.6046456
[54,] 0.51385937 0.9722813 0.4861406
[55,] 0.42470468 0.8494094 0.5752953
[56,] 0.34107770 0.6821554 0.6589223
[57,] 0.28106421 0.5621284 0.7189358
[58,] 0.28823139 0.5764628 0.7117686
[59,] 0.30704920 0.6140984 0.6929508
> postscript(file="/var/www/rcomp/tmp/1iy4c1292746944.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/2t73f1292746944.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3t73f1292746944.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/4t73f1292746944.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/5t73f1292746944.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 = 68
Frequency = 1
1 2 3 4 5 6 7 8
-93.97775 -93.19242 12.29292 11.17825 -90.83642 23.84891 -89.26576 -88.48042
9 10 11 12 13 14 15 16
25.50491 18.99024 22.67557 16.96091 -84.55376 16.93157 32.51690 18.50223
17 18 19 20 21 22 23 24
28.48757 33.97290 -79.84177 21.44356 36.52890 39.01423 36.19956 26.08489
25 26 27 28 29 30 31 32
30.87023 30.95556 45.24089 33.32622 37.31155 45.99689 -70.41778 34.56755
33 34 35 36 37 38 39 40
43.65288 54.33822 46.02355 33.50888 44.99421 47.87955 45.66488 53.95021
41 42 43 44 45 46 47 48
46.53554 54.12087 -60.99379 -60.20846 57.37687 57.06220 -57.85246 -57.06713
49 50 51 52 53 54 55 56
-56.28180 -55.49647 48.38887 -53.92580 -53.14047 50.34486 -51.56981 -50.78447
57 58 59 60 61 62 63 64
54.50086 55.88619 -48.42848 -47.64314 -46.85781 -46.07248 66.21285 -44.50182
65 66 67 68
-43.71648 68.76885 -42.14582 -41.36049
> postscript(file="/var/www/rcomp/tmp/63h201292746944.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 = 68
Frequency = 1
lag(myerror, k = 1) myerror
0 -93.97775 NA
1 -93.19242 -93.97775
2 12.29292 -93.19242
3 11.17825 12.29292
4 -90.83642 11.17825
5 23.84891 -90.83642
6 -89.26576 23.84891
7 -88.48042 -89.26576
8 25.50491 -88.48042
9 18.99024 25.50491
10 22.67557 18.99024
11 16.96091 22.67557
12 -84.55376 16.96091
13 16.93157 -84.55376
14 32.51690 16.93157
15 18.50223 32.51690
16 28.48757 18.50223
17 33.97290 28.48757
18 -79.84177 33.97290
19 21.44356 -79.84177
20 36.52890 21.44356
21 39.01423 36.52890
22 36.19956 39.01423
23 26.08489 36.19956
24 30.87023 26.08489
25 30.95556 30.87023
26 45.24089 30.95556
27 33.32622 45.24089
28 37.31155 33.32622
29 45.99689 37.31155
30 -70.41778 45.99689
31 34.56755 -70.41778
32 43.65288 34.56755
33 54.33822 43.65288
34 46.02355 54.33822
35 33.50888 46.02355
36 44.99421 33.50888
37 47.87955 44.99421
38 45.66488 47.87955
39 53.95021 45.66488
40 46.53554 53.95021
41 54.12087 46.53554
42 -60.99379 54.12087
43 -60.20846 -60.99379
44 57.37687 -60.20846
45 57.06220 57.37687
46 -57.85246 57.06220
47 -57.06713 -57.85246
48 -56.28180 -57.06713
49 -55.49647 -56.28180
50 48.38887 -55.49647
51 -53.92580 48.38887
52 -53.14047 -53.92580
53 50.34486 -53.14047
54 -51.56981 50.34486
55 -50.78447 -51.56981
56 54.50086 -50.78447
57 55.88619 54.50086
58 -48.42848 55.88619
59 -47.64314 -48.42848
60 -46.85781 -47.64314
61 -46.07248 -46.85781
62 66.21285 -46.07248
63 -44.50182 66.21285
64 -43.71648 -44.50182
65 68.76885 -43.71648
66 -42.14582 68.76885
67 -41.36049 -42.14582
68 NA -41.36049
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -93.19242 -93.97775
[2,] 12.29292 -93.19242
[3,] 11.17825 12.29292
[4,] -90.83642 11.17825
[5,] 23.84891 -90.83642
[6,] -89.26576 23.84891
[7,] -88.48042 -89.26576
[8,] 25.50491 -88.48042
[9,] 18.99024 25.50491
[10,] 22.67557 18.99024
[11,] 16.96091 22.67557
[12,] -84.55376 16.96091
[13,] 16.93157 -84.55376
[14,] 32.51690 16.93157
[15,] 18.50223 32.51690
[16,] 28.48757 18.50223
[17,] 33.97290 28.48757
[18,] -79.84177 33.97290
[19,] 21.44356 -79.84177
[20,] 36.52890 21.44356
[21,] 39.01423 36.52890
[22,] 36.19956 39.01423
[23,] 26.08489 36.19956
[24,] 30.87023 26.08489
[25,] 30.95556 30.87023
[26,] 45.24089 30.95556
[27,] 33.32622 45.24089
[28,] 37.31155 33.32622
[29,] 45.99689 37.31155
[30,] -70.41778 45.99689
[31,] 34.56755 -70.41778
[32,] 43.65288 34.56755
[33,] 54.33822 43.65288
[34,] 46.02355 54.33822
[35,] 33.50888 46.02355
[36,] 44.99421 33.50888
[37,] 47.87955 44.99421
[38,] 45.66488 47.87955
[39,] 53.95021 45.66488
[40,] 46.53554 53.95021
[41,] 54.12087 46.53554
[42,] -60.99379 54.12087
[43,] -60.20846 -60.99379
[44,] 57.37687 -60.20846
[45,] 57.06220 57.37687
[46,] -57.85246 57.06220
[47,] -57.06713 -57.85246
[48,] -56.28180 -57.06713
[49,] -55.49647 -56.28180
[50,] 48.38887 -55.49647
[51,] -53.92580 48.38887
[52,] -53.14047 -53.92580
[53,] 50.34486 -53.14047
[54,] -51.56981 50.34486
[55,] -50.78447 -51.56981
[56,] 54.50086 -50.78447
[57,] 55.88619 54.50086
[58,] -48.42848 55.88619
[59,] -47.64314 -48.42848
[60,] -46.85781 -47.64314
[61,] -46.07248 -46.85781
[62,] 66.21285 -46.07248
[63,] -44.50182 66.21285
[64,] -43.71648 -44.50182
[65,] 68.76885 -43.71648
[66,] -42.14582 68.76885
[67,] -41.36049 -42.14582
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -93.19242 -93.97775
2 12.29292 -93.19242
3 11.17825 12.29292
4 -90.83642 11.17825
5 23.84891 -90.83642
6 -89.26576 23.84891
7 -88.48042 -89.26576
8 25.50491 -88.48042
9 18.99024 25.50491
10 22.67557 18.99024
11 16.96091 22.67557
12 -84.55376 16.96091
13 16.93157 -84.55376
14 32.51690 16.93157
15 18.50223 32.51690
16 28.48757 18.50223
17 33.97290 28.48757
18 -79.84177 33.97290
19 21.44356 -79.84177
20 36.52890 21.44356
21 39.01423 36.52890
22 36.19956 39.01423
23 26.08489 36.19956
24 30.87023 26.08489
25 30.95556 30.87023
26 45.24089 30.95556
27 33.32622 45.24089
28 37.31155 33.32622
29 45.99689 37.31155
30 -70.41778 45.99689
31 34.56755 -70.41778
32 43.65288 34.56755
33 54.33822 43.65288
34 46.02355 54.33822
35 33.50888 46.02355
36 44.99421 33.50888
37 47.87955 44.99421
38 45.66488 47.87955
39 53.95021 45.66488
40 46.53554 53.95021
41 54.12087 46.53554
42 -60.99379 54.12087
43 -60.20846 -60.99379
44 57.37687 -60.20846
45 57.06220 57.37687
46 -57.85246 57.06220
47 -57.06713 -57.85246
48 -56.28180 -57.06713
49 -55.49647 -56.28180
50 48.38887 -55.49647
51 -53.92580 48.38887
52 -53.14047 -53.92580
53 50.34486 -53.14047
54 -51.56981 50.34486
55 -50.78447 -51.56981
56 54.50086 -50.78447
57 55.88619 54.50086
58 -48.42848 55.88619
59 -47.64314 -48.42848
60 -46.85781 -47.64314
61 -46.07248 -46.85781
62 66.21285 -46.07248
63 -44.50182 66.21285
64 -43.71648 -44.50182
65 68.76885 -43.71648
66 -42.14582 68.76885
67 -41.36049 -42.14582
> 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/7wqkl1292746944.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/8wqkl1292746944.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/9wqkl1292746944.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/rcomp/tmp/10phj51292746944.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11shzt1292746944.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/12d0yz1292746944.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/13aae81292746944.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/14k1db1292746944.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/15okth1292746944.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/162cr81292746944.tab")
+ }
>
> try(system("convert tmp/1iy4c1292746944.ps tmp/1iy4c1292746944.png",intern=TRUE))
character(0)
> try(system("convert tmp/2t73f1292746944.ps tmp/2t73f1292746944.png",intern=TRUE))
character(0)
> try(system("convert tmp/3t73f1292746944.ps tmp/3t73f1292746944.png",intern=TRUE))
character(0)
> try(system("convert tmp/4t73f1292746944.ps tmp/4t73f1292746944.png",intern=TRUE))
character(0)
> try(system("convert tmp/5t73f1292746944.ps tmp/5t73f1292746944.png",intern=TRUE))
character(0)
> try(system("convert tmp/63h201292746944.ps tmp/63h201292746944.png",intern=TRUE))
character(0)
> try(system("convert tmp/7wqkl1292746944.ps tmp/7wqkl1292746944.png",intern=TRUE))
character(0)
> try(system("convert tmp/8wqkl1292746944.ps tmp/8wqkl1292746944.png",intern=TRUE))
character(0)
> try(system("convert tmp/9wqkl1292746944.ps tmp/9wqkl1292746944.png",intern=TRUE))
character(0)
> try(system("convert tmp/10phj51292746944.ps tmp/10phj51292746944.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
3.290 1.580 4.854