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(20366,0,22782,0,19169,0,13807,0,29743,0,25591,0,29096,0,26482,0,22405,0,27044,0,17970,0,18730,0,19684,0,19785,0,18479,0,10698,0,31956,0,29506,0,34506,0,27165,0,26736,0,23691,0,18157,0,17328,0,18205,0,20995,0,17382,0,9367,0,31124,0,26551,0,30651,0,25859,0,25100,0,25778,0,20418,0,18688,0,20424,0,24776,0,19814,0,12738,0,31566,0,30111,0,30019,0,31934,1,25826,1,26835,1,20205,1,17789,1,20520,1,22518,1,15572,1,11509,1,25447,1,24090,1,27786,1,26195,1,20516,1,22759,1,19028,1,16971,1,20036,1),dim=c(2,61),dimnames=list(c('Y','X'),1:61))
> y <- array(NA,dim=c(2,61),dimnames=list(c('Y','X'),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
Y X t
1 20366 0 1
2 22782 0 2
3 19169 0 3
4 13807 0 4
5 29743 0 5
6 25591 0 6
7 29096 0 7
8 26482 0 8
9 22405 0 9
10 27044 0 10
11 17970 0 11
12 18730 0 12
13 19684 0 13
14 19785 0 14
15 18479 0 15
16 10698 0 16
17 31956 0 17
18 29506 0 18
19 34506 0 19
20 27165 0 20
21 26736 0 21
22 23691 0 22
23 18157 0 23
24 17328 0 24
25 18205 0 25
26 20995 0 26
27 17382 0 27
28 9367 0 28
29 31124 0 29
30 26551 0 30
31 30651 0 31
32 25859 0 32
33 25100 0 33
34 25778 0 34
35 20418 0 35
36 18688 0 36
37 20424 0 37
38 24776 0 38
39 19814 0 39
40 12738 0 40
41 31566 0 41
42 30111 0 42
43 30019 0 43
44 31934 1 44
45 25826 1 45
46 26835 1 46
47 20205 1 47
48 17789 1 48
49 20520 1 49
50 22518 1 50
51 15572 1 51
52 11509 1 52
53 25447 1 53
54 24090 1 54
55 27786 1 55
56 26195 1 56
57 20516 1 57
58 22759 1 58
59 19028 1 59
60 16971 1 60
61 20036 1 61
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X t
22527.82 -1760.42 22.99
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-13804.5 -4073.7 208.2 4140.3 11541.4
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 22527.82 1750.23 12.871 <2e-16 ***
X -1760.42 2651.69 -0.664 0.509
t 22.99 68.69 0.335 0.739
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 5790 on 58 degrees of freedom
Multiple R-squared: 0.009168, Adjusted R-squared: -0.025
F-statistic: 0.2683 on 2 and 58 DF, p-value: 0.7656
> 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,] 0.6902283 0.61954341 0.30977170
[2,] 0.5607304 0.87853917 0.43926959
[3,] 0.4302175 0.86043503 0.56978249
[4,] 0.4052909 0.81058183 0.59470908
[5,] 0.2952236 0.59044723 0.70477638
[6,] 0.4084833 0.81696669 0.59151665
[7,] 0.3896969 0.77939382 0.61030309
[8,] 0.3208151 0.64163024 0.67918488
[9,] 0.2497812 0.49956233 0.75021884
[10,] 0.2001896 0.40037920 0.79981040
[11,] 0.3734326 0.74686516 0.62656742
[12,] 0.6138109 0.77237821 0.38618911
[13,] 0.6414608 0.71707831 0.35853915
[14,] 0.7895204 0.42095921 0.21047960
[15,] 0.7429772 0.51404563 0.25702281
[16,] 0.6908718 0.61825642 0.30912821
[17,] 0.6271271 0.74574586 0.37287293
[18,] 0.6290677 0.74186452 0.37093226
[19,] 0.6342711 0.73145773 0.36572887
[20,] 0.6108928 0.77821436 0.38910718
[21,] 0.5440321 0.91193585 0.45596792
[22,] 0.5393416 0.92131677 0.46065839
[23,] 0.8499099 0.30018016 0.15009008
[24,] 0.8816153 0.23676940 0.11838470
[25,] 0.8519107 0.29617869 0.14808934
[26,] 0.8642587 0.27148260 0.13574130
[27,] 0.8226864 0.35462714 0.17731357
[28,] 0.7697925 0.46041508 0.23020754
[29,] 0.7132945 0.57341102 0.28670551
[30,] 0.6668462 0.66630767 0.33315384
[31,] 0.6538921 0.69221574 0.34610787
[32,] 0.6143238 0.77135240 0.38567620
[33,] 0.5387257 0.92254861 0.46127430
[34,] 0.5221123 0.95577541 0.47788771
[35,] 0.8882999 0.22340014 0.11170007
[36,] 0.8742939 0.25141219 0.12570610
[37,] 0.8421105 0.31577906 0.15788953
[38,] 0.7988433 0.40231338 0.20115669
[39,] 0.8520552 0.29588962 0.14794481
[40,] 0.8256696 0.34866081 0.17433041
[41,] 0.8352352 0.32952960 0.16476480
[42,] 0.7833011 0.43339779 0.21669890
[43,] 0.7371090 0.52578194 0.26289097
[44,] 0.6482443 0.70351130 0.35175565
[45,] 0.5529841 0.89403171 0.44701585
[46,] 0.5542137 0.89157270 0.44578635
[47,] 0.9845304 0.03093921 0.01546961
[48,] 0.9664842 0.06703170 0.03351585
[49,] 0.9510626 0.09787484 0.04893742
[50,] 0.8926352 0.21472959 0.10736479
> postscript(file="/var/www/html/rcomp/tmp/1gv2b1258728868.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2x35h1258728868.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3eoc51258728868.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4vzn81258728868.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5qfys1258728868.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
-2184.8053 208.2076 -3427.7795 -8812.7666 7100.2462 2925.2591
7 8 9 10 11 12
6407.2720 3770.2849 -329.7023 4286.3106 -4810.6765 -4073.6636
13 14 15 16 17 18
-3142.6508 -3064.6379 -4393.6250 -12197.6121 9037.4007 6564.4136
19 20 21 22 23 24
11541.4265 4177.4394 3725.4522 657.4651 -4899.5220 -5751.5091
25 26 27 28 29 30
-4897.4963 -2130.4834 -5766.4705 -13804.4576 7929.5552 3333.5681
31 32 33 34 35 36
7410.5810 2595.5939 1813.6067 2468.6196 -2914.3675 -4667.3546
37 38 39 40 41 42
-2954.3418 1374.6711 -3610.3160 -10709.3031 8095.7098 6617.7226
43 44 45 46 47 48
6502.7355 10155.1683 4024.1812 5010.1941 -1642.7930 -4081.7802
49 50 51 52 53 54
-1373.7673 601.2456 -6367.7415 -10453.7287 3461.2842 2081.2971
55 56 57 58 59 60
5754.3100 4140.3228 -1561.6643 658.3486 -3095.6385 -5175.6257
61
-2133.6128
> postscript(file="/var/www/html/rcomp/tmp/6pzyv1258728868.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 -2184.8053 NA
1 208.2076 -2184.8053
2 -3427.7795 208.2076
3 -8812.7666 -3427.7795
4 7100.2462 -8812.7666
5 2925.2591 7100.2462
6 6407.2720 2925.2591
7 3770.2849 6407.2720
8 -329.7023 3770.2849
9 4286.3106 -329.7023
10 -4810.6765 4286.3106
11 -4073.6636 -4810.6765
12 -3142.6508 -4073.6636
13 -3064.6379 -3142.6508
14 -4393.6250 -3064.6379
15 -12197.6121 -4393.6250
16 9037.4007 -12197.6121
17 6564.4136 9037.4007
18 11541.4265 6564.4136
19 4177.4394 11541.4265
20 3725.4522 4177.4394
21 657.4651 3725.4522
22 -4899.5220 657.4651
23 -5751.5091 -4899.5220
24 -4897.4963 -5751.5091
25 -2130.4834 -4897.4963
26 -5766.4705 -2130.4834
27 -13804.4576 -5766.4705
28 7929.5552 -13804.4576
29 3333.5681 7929.5552
30 7410.5810 3333.5681
31 2595.5939 7410.5810
32 1813.6067 2595.5939
33 2468.6196 1813.6067
34 -2914.3675 2468.6196
35 -4667.3546 -2914.3675
36 -2954.3418 -4667.3546
37 1374.6711 -2954.3418
38 -3610.3160 1374.6711
39 -10709.3031 -3610.3160
40 8095.7098 -10709.3031
41 6617.7226 8095.7098
42 6502.7355 6617.7226
43 10155.1683 6502.7355
44 4024.1812 10155.1683
45 5010.1941 4024.1812
46 -1642.7930 5010.1941
47 -4081.7802 -1642.7930
48 -1373.7673 -4081.7802
49 601.2456 -1373.7673
50 -6367.7415 601.2456
51 -10453.7287 -6367.7415
52 3461.2842 -10453.7287
53 2081.2971 3461.2842
54 5754.3100 2081.2971
55 4140.3228 5754.3100
56 -1561.6643 4140.3228
57 658.3486 -1561.6643
58 -3095.6385 658.3486
59 -5175.6257 -3095.6385
60 -2133.6128 -5175.6257
61 NA -2133.6128
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 208.2076 -2184.8053
[2,] -3427.7795 208.2076
[3,] -8812.7666 -3427.7795
[4,] 7100.2462 -8812.7666
[5,] 2925.2591 7100.2462
[6,] 6407.2720 2925.2591
[7,] 3770.2849 6407.2720
[8,] -329.7023 3770.2849
[9,] 4286.3106 -329.7023
[10,] -4810.6765 4286.3106
[11,] -4073.6636 -4810.6765
[12,] -3142.6508 -4073.6636
[13,] -3064.6379 -3142.6508
[14,] -4393.6250 -3064.6379
[15,] -12197.6121 -4393.6250
[16,] 9037.4007 -12197.6121
[17,] 6564.4136 9037.4007
[18,] 11541.4265 6564.4136
[19,] 4177.4394 11541.4265
[20,] 3725.4522 4177.4394
[21,] 657.4651 3725.4522
[22,] -4899.5220 657.4651
[23,] -5751.5091 -4899.5220
[24,] -4897.4963 -5751.5091
[25,] -2130.4834 -4897.4963
[26,] -5766.4705 -2130.4834
[27,] -13804.4576 -5766.4705
[28,] 7929.5552 -13804.4576
[29,] 3333.5681 7929.5552
[30,] 7410.5810 3333.5681
[31,] 2595.5939 7410.5810
[32,] 1813.6067 2595.5939
[33,] 2468.6196 1813.6067
[34,] -2914.3675 2468.6196
[35,] -4667.3546 -2914.3675
[36,] -2954.3418 -4667.3546
[37,] 1374.6711 -2954.3418
[38,] -3610.3160 1374.6711
[39,] -10709.3031 -3610.3160
[40,] 8095.7098 -10709.3031
[41,] 6617.7226 8095.7098
[42,] 6502.7355 6617.7226
[43,] 10155.1683 6502.7355
[44,] 4024.1812 10155.1683
[45,] 5010.1941 4024.1812
[46,] -1642.7930 5010.1941
[47,] -4081.7802 -1642.7930
[48,] -1373.7673 -4081.7802
[49,] 601.2456 -1373.7673
[50,] -6367.7415 601.2456
[51,] -10453.7287 -6367.7415
[52,] 3461.2842 -10453.7287
[53,] 2081.2971 3461.2842
[54,] 5754.3100 2081.2971
[55,] 4140.3228 5754.3100
[56,] -1561.6643 4140.3228
[57,] 658.3486 -1561.6643
[58,] -3095.6385 658.3486
[59,] -5175.6257 -3095.6385
[60,] -2133.6128 -5175.6257
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 208.2076 -2184.8053
2 -3427.7795 208.2076
3 -8812.7666 -3427.7795
4 7100.2462 -8812.7666
5 2925.2591 7100.2462
6 6407.2720 2925.2591
7 3770.2849 6407.2720
8 -329.7023 3770.2849
9 4286.3106 -329.7023
10 -4810.6765 4286.3106
11 -4073.6636 -4810.6765
12 -3142.6508 -4073.6636
13 -3064.6379 -3142.6508
14 -4393.6250 -3064.6379
15 -12197.6121 -4393.6250
16 9037.4007 -12197.6121
17 6564.4136 9037.4007
18 11541.4265 6564.4136
19 4177.4394 11541.4265
20 3725.4522 4177.4394
21 657.4651 3725.4522
22 -4899.5220 657.4651
23 -5751.5091 -4899.5220
24 -4897.4963 -5751.5091
25 -2130.4834 -4897.4963
26 -5766.4705 -2130.4834
27 -13804.4576 -5766.4705
28 7929.5552 -13804.4576
29 3333.5681 7929.5552
30 7410.5810 3333.5681
31 2595.5939 7410.5810
32 1813.6067 2595.5939
33 2468.6196 1813.6067
34 -2914.3675 2468.6196
35 -4667.3546 -2914.3675
36 -2954.3418 -4667.3546
37 1374.6711 -2954.3418
38 -3610.3160 1374.6711
39 -10709.3031 -3610.3160
40 8095.7098 -10709.3031
41 6617.7226 8095.7098
42 6502.7355 6617.7226
43 10155.1683 6502.7355
44 4024.1812 10155.1683
45 5010.1941 4024.1812
46 -1642.7930 5010.1941
47 -4081.7802 -1642.7930
48 -1373.7673 -4081.7802
49 601.2456 -1373.7673
50 -6367.7415 601.2456
51 -10453.7287 -6367.7415
52 3461.2842 -10453.7287
53 2081.2971 3461.2842
54 5754.3100 2081.2971
55 4140.3228 5754.3100
56 -1561.6643 4140.3228
57 658.3486 -1561.6643
58 -3095.6385 658.3486
59 -5175.6257 -3095.6385
60 -2133.6128 -5175.6257
> 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/7mcy81258728868.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/80ztv1258728868.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9z3uz1258728868.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10nn8b1258728868.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/114vet1258728868.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/127np31258728868.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/13ummj1258728868.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/14j7h51258728868.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/15xnz01258728868.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/16ys1p1258728868.tab")
+ }
>
> system("convert tmp/1gv2b1258728868.ps tmp/1gv2b1258728868.png")
> system("convert tmp/2x35h1258728868.ps tmp/2x35h1258728868.png")
> system("convert tmp/3eoc51258728868.ps tmp/3eoc51258728868.png")
> system("convert tmp/4vzn81258728868.ps tmp/4vzn81258728868.png")
> system("convert tmp/5qfys1258728868.ps tmp/5qfys1258728868.png")
> system("convert tmp/6pzyv1258728868.ps tmp/6pzyv1258728868.png")
> system("convert tmp/7mcy81258728868.ps tmp/7mcy81258728868.png")
> system("convert tmp/80ztv1258728868.ps tmp/80ztv1258728868.png")
> system("convert tmp/9z3uz1258728868.ps tmp/9z3uz1258728868.png")
> system("convert tmp/10nn8b1258728868.ps tmp/10nn8b1258728868.png")
>
>
> proc.time()
user system elapsed
2.467 1.566 2.851