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(562000,4814,561000,3908,555000,5250,544000,3937,537000,4004,543000,5560,594000,3922,611000,3759,613000,4138,611000,4634,594000,3996,595000,4308,591000,4143,589000,4429,584000,5219,573000,4929,567000,5755,569000,5592,621000,4163,629000,4962,628000,5208,612000,4755,595000,4491,597000,5732,593000,5731,590000,5040,580000,6102,574000,4904,573000,5369,573000,5578,620000,4619,626000,4731,620000,5011,588000,5299,566000,4146,557000,4625,561000,4736,549000,4219,532000,5116,526000,4205,511000,4121,499000,5103,555000,4300,565000,4578,542000,3809,527000,5526,510000,4247,514000,3830,517000,4394,508000,4826,493000,4409,490000,4569,469000,4106,478000,4794,528000,3914,534000,3793,518000,4405,506000,4022,502000,4100,516000,4788),dim=c(2,60),dimnames=list(c('werkloos','bouw'),1:60))
> y <- array(NA,dim=c(2,60),dimnames=list(c('werkloos','bouw'),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
werkloos bouw
1 562000 4814
2 561000 3908
3 555000 5250
4 544000 3937
5 537000 4004
6 543000 5560
7 594000 3922
8 611000 3759
9 613000 4138
10 611000 4634
11 594000 3996
12 595000 4308
13 591000 4143
14 589000 4429
15 584000 5219
16 573000 4929
17 567000 5755
18 569000 5592
19 621000 4163
20 629000 4962
21 628000 5208
22 612000 4755
23 595000 4491
24 597000 5732
25 593000 5731
26 590000 5040
27 580000 6102
28 574000 4904
29 573000 5369
30 573000 5578
31 620000 4619
32 626000 4731
33 620000 5011
34 588000 5299
35 566000 4146
36 557000 4625
37 561000 4736
38 549000 4219
39 532000 5116
40 526000 4205
41 511000 4121
42 499000 5103
43 555000 4300
44 565000 4578
45 542000 3809
46 527000 5526
47 510000 4247
48 514000 3830
49 517000 4394
50 508000 4826
51 493000 4409
52 490000 4569
53 469000 4106
54 478000 4794
55 528000 3914
56 534000 3793
57 518000 4405
58 506000 4022
59 502000 4100
60 516000 4788
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) bouw
488516.20 15.34
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-84042.1 -33688.1 -707.6 33818.2 68635.6
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 4.885e+05 4.197e+04 11.641 <2e-16 ***
bouw 1.534e+01 8.962e+00 1.711 0.0924 .
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 41300 on 58 degrees of freedom
Multiple R-squared: 0.04806, Adjusted R-squared: 0.03165
F-statistic: 2.928 on 1 and 58 DF, p-value: 0.09238
> 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,] 0.023861208 0.04772242 0.97613879
[2,] 0.009727995 0.01945599 0.99027201
[3,] 0.046496583 0.09299317 0.95350342
[4,] 0.098212521 0.19642504 0.90178748
[5,] 0.144884928 0.28976986 0.85511507
[6,] 0.191852430 0.38370486 0.80814757
[7,] 0.143848269 0.28769654 0.85615173
[8,] 0.111438789 0.22287758 0.88856121
[9,] 0.080399458 0.16079892 0.91960054
[10,] 0.056641880 0.11328376 0.94335812
[11,] 0.039314084 0.07862817 0.96068592
[12,] 0.022705246 0.04541049 0.97729475
[13,] 0.012967344 0.02593469 0.98703266
[14,] 0.007015183 0.01403037 0.99298482
[15,] 0.014957264 0.02991453 0.98504274
[16,] 0.043462431 0.08692486 0.95653757
[17,] 0.084843985 0.16968797 0.91515601
[18,] 0.098514719 0.19702944 0.90148528
[19,] 0.091606942 0.18321388 0.90839306
[20,] 0.070534984 0.14106997 0.92946502
[21,] 0.050604516 0.10120903 0.94939548
[22,] 0.039166690 0.07833338 0.96083331
[23,] 0.025095313 0.05019063 0.97490469
[24,] 0.018074767 0.03614953 0.98192523
[25,] 0.011838966 0.02367793 0.98816103
[26,] 0.007394546 0.01478909 0.99260545
[27,] 0.020864784 0.04172957 0.97913522
[28,] 0.085479610 0.17095922 0.91452039
[29,] 0.265182206 0.53036441 0.73481779
[30,] 0.382606671 0.76521334 0.61739333
[31,] 0.459418523 0.91883705 0.54058148
[32,] 0.524749839 0.95050032 0.47525016
[33,] 0.624291003 0.75141799 0.37570900
[34,] 0.687487493 0.62502501 0.31251251
[35,] 0.736128547 0.52774291 0.26387145
[36,] 0.766080048 0.46783990 0.23391995
[37,] 0.805542454 0.38891509 0.19445755
[38,] 0.853730220 0.29253956 0.14626978
[39,] 0.890534400 0.21893120 0.10946560
[40,] 0.968309175 0.06338165 0.03169082
[41,] 0.977123587 0.04575283 0.02287641
[42,] 0.986985838 0.02602832 0.01301416
[43,] 0.982004163 0.03599167 0.01799584
[44,] 0.971899832 0.05620034 0.02810017
[45,] 0.961652366 0.07669527 0.03834763
[46,] 0.951538351 0.09692330 0.04846165
[47,] 0.930093760 0.13981248 0.06990624
[48,] 0.896831333 0.20633733 0.10316867
[49,] 0.974674386 0.05065123 0.02532561
[50,] 0.981960317 0.03607937 0.01803968
[51,] 0.949377848 0.10124430 0.05062215
> postscript(file="/var/www/html/rcomp/tmp/1vdji1258815078.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/22q141258815078.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3d64f1258815078.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/42u911258815078.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5ekcp1258815078.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
-348.8669 12546.5205 -14035.8304 -4898.2546 -12925.8384 -30790.3227
7 8 9 10 11 12
45331.8015 64831.7443 61018.9939 51411.8061 44196.8582 40411.6916
13 14 15 16 17 18
38942.3086 32555.9059 15439.6189 8887.3698 -9781.0518 -5281.1090
19 20 21 22 23 24
68635.5671 64381.2464 59608.3267 50556.0204 37605.0074 20571.7009
25 26 27 28 29 30
16587.0379 24184.9548 -2103.0158 10270.7966 2139.0581 -1066.3900
31 32 33 34 35 36
60641.8622 64924.1101 54629.7299 18212.6531 13896.2973 -2450.1602
37 38 39 40 41 42
-152.5753 -4223.3089 -34980.6627 -27008.5899 -40720.2759 -67781.2807
43 44 45 46 47 48
534.3882 6270.6822 -4935.1093 -46268.8623 -43652.7470 -33257.1879
49 50 51 52 53 54
-38907.2966 -54532.9117 -63137.3526 -68591.2842 -82490.2198 -84042.1254
55 56 57 58 59 60
-20545.5019 -12689.7162 -38076.0044 -44201.9057 -49398.1973 -45950.1030
> postscript(file="/var/www/html/rcomp/tmp/637861258815078.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 -348.8669 NA
1 12546.5205 -348.8669
2 -14035.8304 12546.5205
3 -4898.2546 -14035.8304
4 -12925.8384 -4898.2546
5 -30790.3227 -12925.8384
6 45331.8015 -30790.3227
7 64831.7443 45331.8015
8 61018.9939 64831.7443
9 51411.8061 61018.9939
10 44196.8582 51411.8061
11 40411.6916 44196.8582
12 38942.3086 40411.6916
13 32555.9059 38942.3086
14 15439.6189 32555.9059
15 8887.3698 15439.6189
16 -9781.0518 8887.3698
17 -5281.1090 -9781.0518
18 68635.5671 -5281.1090
19 64381.2464 68635.5671
20 59608.3267 64381.2464
21 50556.0204 59608.3267
22 37605.0074 50556.0204
23 20571.7009 37605.0074
24 16587.0379 20571.7009
25 24184.9548 16587.0379
26 -2103.0158 24184.9548
27 10270.7966 -2103.0158
28 2139.0581 10270.7966
29 -1066.3900 2139.0581
30 60641.8622 -1066.3900
31 64924.1101 60641.8622
32 54629.7299 64924.1101
33 18212.6531 54629.7299
34 13896.2973 18212.6531
35 -2450.1602 13896.2973
36 -152.5753 -2450.1602
37 -4223.3089 -152.5753
38 -34980.6627 -4223.3089
39 -27008.5899 -34980.6627
40 -40720.2759 -27008.5899
41 -67781.2807 -40720.2759
42 534.3882 -67781.2807
43 6270.6822 534.3882
44 -4935.1093 6270.6822
45 -46268.8623 -4935.1093
46 -43652.7470 -46268.8623
47 -33257.1879 -43652.7470
48 -38907.2966 -33257.1879
49 -54532.9117 -38907.2966
50 -63137.3526 -54532.9117
51 -68591.2842 -63137.3526
52 -82490.2198 -68591.2842
53 -84042.1254 -82490.2198
54 -20545.5019 -84042.1254
55 -12689.7162 -20545.5019
56 -38076.0044 -12689.7162
57 -44201.9057 -38076.0044
58 -49398.1973 -44201.9057
59 -45950.1030 -49398.1973
60 NA -45950.1030
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 12546.5205 -348.8669
[2,] -14035.8304 12546.5205
[3,] -4898.2546 -14035.8304
[4,] -12925.8384 -4898.2546
[5,] -30790.3227 -12925.8384
[6,] 45331.8015 -30790.3227
[7,] 64831.7443 45331.8015
[8,] 61018.9939 64831.7443
[9,] 51411.8061 61018.9939
[10,] 44196.8582 51411.8061
[11,] 40411.6916 44196.8582
[12,] 38942.3086 40411.6916
[13,] 32555.9059 38942.3086
[14,] 15439.6189 32555.9059
[15,] 8887.3698 15439.6189
[16,] -9781.0518 8887.3698
[17,] -5281.1090 -9781.0518
[18,] 68635.5671 -5281.1090
[19,] 64381.2464 68635.5671
[20,] 59608.3267 64381.2464
[21,] 50556.0204 59608.3267
[22,] 37605.0074 50556.0204
[23,] 20571.7009 37605.0074
[24,] 16587.0379 20571.7009
[25,] 24184.9548 16587.0379
[26,] -2103.0158 24184.9548
[27,] 10270.7966 -2103.0158
[28,] 2139.0581 10270.7966
[29,] -1066.3900 2139.0581
[30,] 60641.8622 -1066.3900
[31,] 64924.1101 60641.8622
[32,] 54629.7299 64924.1101
[33,] 18212.6531 54629.7299
[34,] 13896.2973 18212.6531
[35,] -2450.1602 13896.2973
[36,] -152.5753 -2450.1602
[37,] -4223.3089 -152.5753
[38,] -34980.6627 -4223.3089
[39,] -27008.5899 -34980.6627
[40,] -40720.2759 -27008.5899
[41,] -67781.2807 -40720.2759
[42,] 534.3882 -67781.2807
[43,] 6270.6822 534.3882
[44,] -4935.1093 6270.6822
[45,] -46268.8623 -4935.1093
[46,] -43652.7470 -46268.8623
[47,] -33257.1879 -43652.7470
[48,] -38907.2966 -33257.1879
[49,] -54532.9117 -38907.2966
[50,] -63137.3526 -54532.9117
[51,] -68591.2842 -63137.3526
[52,] -82490.2198 -68591.2842
[53,] -84042.1254 -82490.2198
[54,] -20545.5019 -84042.1254
[55,] -12689.7162 -20545.5019
[56,] -38076.0044 -12689.7162
[57,] -44201.9057 -38076.0044
[58,] -49398.1973 -44201.9057
[59,] -45950.1030 -49398.1973
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 12546.5205 -348.8669
2 -14035.8304 12546.5205
3 -4898.2546 -14035.8304
4 -12925.8384 -4898.2546
5 -30790.3227 -12925.8384
6 45331.8015 -30790.3227
7 64831.7443 45331.8015
8 61018.9939 64831.7443
9 51411.8061 61018.9939
10 44196.8582 51411.8061
11 40411.6916 44196.8582
12 38942.3086 40411.6916
13 32555.9059 38942.3086
14 15439.6189 32555.9059
15 8887.3698 15439.6189
16 -9781.0518 8887.3698
17 -5281.1090 -9781.0518
18 68635.5671 -5281.1090
19 64381.2464 68635.5671
20 59608.3267 64381.2464
21 50556.0204 59608.3267
22 37605.0074 50556.0204
23 20571.7009 37605.0074
24 16587.0379 20571.7009
25 24184.9548 16587.0379
26 -2103.0158 24184.9548
27 10270.7966 -2103.0158
28 2139.0581 10270.7966
29 -1066.3900 2139.0581
30 60641.8622 -1066.3900
31 64924.1101 60641.8622
32 54629.7299 64924.1101
33 18212.6531 54629.7299
34 13896.2973 18212.6531
35 -2450.1602 13896.2973
36 -152.5753 -2450.1602
37 -4223.3089 -152.5753
38 -34980.6627 -4223.3089
39 -27008.5899 -34980.6627
40 -40720.2759 -27008.5899
41 -67781.2807 -40720.2759
42 534.3882 -67781.2807
43 6270.6822 534.3882
44 -4935.1093 6270.6822
45 -46268.8623 -4935.1093
46 -43652.7470 -46268.8623
47 -33257.1879 -43652.7470
48 -38907.2966 -33257.1879
49 -54532.9117 -38907.2966
50 -63137.3526 -54532.9117
51 -68591.2842 -63137.3526
52 -82490.2198 -68591.2842
53 -84042.1254 -82490.2198
54 -20545.5019 -84042.1254
55 -12689.7162 -20545.5019
56 -38076.0044 -12689.7162
57 -44201.9057 -38076.0044
58 -49398.1973 -44201.9057
59 -45950.1030 -49398.1973
> 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/77bsx1258815078.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8wn4p1258815078.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9u3g51258815078.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/1006d51258815078.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11h3et1258815078.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/125e0n1258815079.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/131ax61258815079.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/14c6571258815079.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/15ikzo1258815079.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/167ghe1258815079.tab")
+ }
>
> system("convert tmp/1vdji1258815078.ps tmp/1vdji1258815078.png")
> system("convert tmp/22q141258815078.ps tmp/22q141258815078.png")
> system("convert tmp/3d64f1258815078.ps tmp/3d64f1258815078.png")
> system("convert tmp/42u911258815078.ps tmp/42u911258815078.png")
> system("convert tmp/5ekcp1258815078.ps tmp/5ekcp1258815078.png")
> system("convert tmp/637861258815078.ps tmp/637861258815078.png")
> system("convert tmp/77bsx1258815078.ps tmp/77bsx1258815078.png")
> system("convert tmp/8wn4p1258815078.ps tmp/8wn4p1258815078.png")
> system("convert tmp/9u3g51258815078.ps tmp/9u3g51258815078.png")
> system("convert tmp/1006d51258815078.ps tmp/1006d51258815078.png")
>
>
> proc.time()
user system elapsed
2.496 1.559 2.903