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 = '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 t
1 562000 4814 1
2 561000 3908 2
3 555000 5250 3
4 544000 3937 4
5 537000 4004 5
6 543000 5560 6
7 594000 3922 7
8 611000 3759 8
9 613000 4138 9
10 611000 4634 10
11 594000 3996 11
12 595000 4308 12
13 591000 4143 13
14 589000 4429 14
15 584000 5219 15
16 573000 4929 16
17 567000 5755 17
18 569000 5592 18
19 621000 4163 19
20 629000 4962 20
21 628000 5208 21
22 612000 4755 22
23 595000 4491 23
24 597000 5732 24
25 593000 5731 25
26 590000 5040 26
27 580000 6102 27
28 574000 4904 28
29 573000 5369 29
30 573000 5578 30
31 620000 4619 31
32 626000 4731 32
33 620000 5011 33
34 588000 5299 34
35 566000 4146 35
36 557000 4625 36
37 561000 4736 37
38 549000 4219 38
39 532000 5116 39
40 526000 4205 40
41 511000 4121 41
42 499000 5103 42
43 555000 4300 43
44 565000 4578 44
45 542000 3809 45
46 527000 5526 46
47 510000 4247 47
48 514000 3830 48
49 517000 4394 49
50 508000 4826 50
51 493000 4409 51
52 490000 4569 52
53 469000 4106 53
54 478000 4794 54
55 528000 3914 55
56 534000 3793 56
57 518000 4405 57
58 506000 4022 58
59 502000 4100 59
60 516000 4788 60
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) bouw t
566709.674 8.701 -1553.215
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-62769 -19153 4477 18144 67828
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 566709.674 34135.292 16.602 < 2e-16 ***
bouw 8.701 6.904 1.260 0.213
t -1553.215 237.173 -6.549 1.79e-08 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 31470 on 57 degrees of freedom
Multiple R-squared: 0.4568, Adjusted R-squared: 0.4377
F-statistic: 23.97 on 2 and 57 DF, p-value: 2.797e-08
> 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,] 0.005944997 0.01188999 0.99405500
[2,] 0.457778806 0.91555761 0.54222119
[3,] 0.537328090 0.92534382 0.46267191
[4,] 0.478681673 0.95736335 0.52131833
[5,] 0.374373442 0.74874688 0.62562656
[6,] 0.329155368 0.65831074 0.67084463
[7,] 0.272352073 0.54470415 0.72764793
[8,] 0.253344644 0.50668929 0.74665536
[9,] 0.231745554 0.46349111 0.76825445
[10,] 0.196092996 0.39218599 0.80390700
[11,] 0.239012927 0.47802585 0.76098707
[12,] 0.245001825 0.49000365 0.75499818
[13,] 0.263675052 0.52735010 0.73632495
[14,] 0.203726416 0.40745283 0.79627358
[15,] 0.217785097 0.43557019 0.78221490
[16,] 0.214597568 0.42919514 0.78540243
[17,] 0.163631255 0.32726251 0.83636875
[18,] 0.184396541 0.36879308 0.81560346
[19,] 0.136055438 0.27211088 0.86394456
[20,] 0.101630973 0.20326195 0.89836903
[21,] 0.100934617 0.20186923 0.89906538
[22,] 0.079434077 0.15886815 0.92056592
[23,] 0.130675945 0.26135189 0.86932406
[24,] 0.141341488 0.28268298 0.85865851
[25,] 0.132986339 0.26597268 0.86701366
[26,] 0.131113410 0.26222682 0.86888659
[27,] 0.190416831 0.38083366 0.80958317
[28,] 0.335794291 0.67158858 0.66420571
[29,] 0.436006644 0.87201329 0.56399336
[30,] 0.611893721 0.77621256 0.38810628
[31,] 0.697039381 0.60592124 0.30296062
[32,] 0.751233481 0.49753304 0.24876652
[33,] 0.786882206 0.42623559 0.21311779
[34,] 0.817189727 0.36562055 0.18281027
[35,] 0.835841210 0.32831758 0.16415879
[36,] 0.879424389 0.24115122 0.12057561
[37,] 0.923707024 0.15258595 0.07629298
[38,] 0.908023773 0.18395245 0.09197623
[39,] 0.952654900 0.09469020 0.04734510
[40,] 0.952380392 0.09523922 0.04761961
[41,] 0.968956136 0.06208773 0.03104386
[42,] 0.953782890 0.09243422 0.04621711
[43,] 0.925673643 0.14865271 0.07432636
[44,] 0.917255162 0.16548968 0.08274484
[45,] 0.931284386 0.13743123 0.06871561
[46,] 0.891909434 0.21618113 0.10809057
[47,] 0.835805940 0.32838812 0.16419406
[48,] 0.887074120 0.22585176 0.11292588
[49,] 0.967278796 0.06544241 0.03272120
> postscript(file="/var/www/html/rcomp/tmp/112bc1258816737.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2t6a71258816737.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3gjjs1258816737.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4uuxs1258816737.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5l3th1258816737.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
-45044.2642 -36607.7193 -52731.5784 -50753.6258 -56783.3945 -62769.3205
7 8 9 10 11 12
4036.5375 24008.0556 24263.4977 19500.8939 9605.5045 9443.9302
13 14 15 16 17 18
8432.8509 5497.5090 -4823.2616 -11746.6850 -23380.7005 -18409.1823
19 20 21 22 23 24
47578.1150 50179.0332 48591.7412 38086.6211 24936.9652 17691.9321
25 26 27 28 29 30
15253.8482 19819.6249 2132.1151 8109.4243 4616.5591 4351.2132
31 32 33 34 35 36
61248.9243 67827.5994 60944.4650 27991.7206 17577.4737 5962.7910
37 38 39 40 41 42
10550.1674 4601.9271 -18649.8769 -15169.8257 -27885.7061 -46877.1162
43 44 45 46 47 48
17663.2003 26797.4684 12041.9424 -16344.8844 -20662.7742 -11481.1392
49 50 51 52 53 54
-11835.4279 -23041.1519 -32859.5169 -35698.5017 -51116.6093 -46549.8526
55 56 57 58 59 60
12660.4599 21266.5257 1494.5771 -5619.6303 -8745.1127 821.6439
> postscript(file="/var/www/html/rcomp/tmp/6s6br1258816737.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 -45044.2642 NA
1 -36607.7193 -45044.2642
2 -52731.5784 -36607.7193
3 -50753.6258 -52731.5784
4 -56783.3945 -50753.6258
5 -62769.3205 -56783.3945
6 4036.5375 -62769.3205
7 24008.0556 4036.5375
8 24263.4977 24008.0556
9 19500.8939 24263.4977
10 9605.5045 19500.8939
11 9443.9302 9605.5045
12 8432.8509 9443.9302
13 5497.5090 8432.8509
14 -4823.2616 5497.5090
15 -11746.6850 -4823.2616
16 -23380.7005 -11746.6850
17 -18409.1823 -23380.7005
18 47578.1150 -18409.1823
19 50179.0332 47578.1150
20 48591.7412 50179.0332
21 38086.6211 48591.7412
22 24936.9652 38086.6211
23 17691.9321 24936.9652
24 15253.8482 17691.9321
25 19819.6249 15253.8482
26 2132.1151 19819.6249
27 8109.4243 2132.1151
28 4616.5591 8109.4243
29 4351.2132 4616.5591
30 61248.9243 4351.2132
31 67827.5994 61248.9243
32 60944.4650 67827.5994
33 27991.7206 60944.4650
34 17577.4737 27991.7206
35 5962.7910 17577.4737
36 10550.1674 5962.7910
37 4601.9271 10550.1674
38 -18649.8769 4601.9271
39 -15169.8257 -18649.8769
40 -27885.7061 -15169.8257
41 -46877.1162 -27885.7061
42 17663.2003 -46877.1162
43 26797.4684 17663.2003
44 12041.9424 26797.4684
45 -16344.8844 12041.9424
46 -20662.7742 -16344.8844
47 -11481.1392 -20662.7742
48 -11835.4279 -11481.1392
49 -23041.1519 -11835.4279
50 -32859.5169 -23041.1519
51 -35698.5017 -32859.5169
52 -51116.6093 -35698.5017
53 -46549.8526 -51116.6093
54 12660.4599 -46549.8526
55 21266.5257 12660.4599
56 1494.5771 21266.5257
57 -5619.6303 1494.5771
58 -8745.1127 -5619.6303
59 821.6439 -8745.1127
60 NA 821.6439
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -36607.7193 -45044.264
[2,] -52731.5784 -36607.719
[3,] -50753.6258 -52731.578
[4,] -56783.3945 -50753.626
[5,] -62769.3205 -56783.394
[6,] 4036.5375 -62769.321
[7,] 24008.0556 4036.537
[8,] 24263.4977 24008.056
[9,] 19500.8939 24263.498
[10,] 9605.5045 19500.894
[11,] 9443.9302 9605.505
[12,] 8432.8509 9443.930
[13,] 5497.5090 8432.851
[14,] -4823.2616 5497.509
[15,] -11746.6850 -4823.262
[16,] -23380.7005 -11746.685
[17,] -18409.1823 -23380.700
[18,] 47578.1150 -18409.182
[19,] 50179.0332 47578.115
[20,] 48591.7412 50179.033
[21,] 38086.6211 48591.741
[22,] 24936.9652 38086.621
[23,] 17691.9321 24936.965
[24,] 15253.8482 17691.932
[25,] 19819.6249 15253.848
[26,] 2132.1151 19819.625
[27,] 8109.4243 2132.115
[28,] 4616.5591 8109.424
[29,] 4351.2132 4616.559
[30,] 61248.9243 4351.213
[31,] 67827.5994 61248.924
[32,] 60944.4650 67827.599
[33,] 27991.7206 60944.465
[34,] 17577.4737 27991.721
[35,] 5962.7910 17577.474
[36,] 10550.1674 5962.791
[37,] 4601.9271 10550.167
[38,] -18649.8769 4601.927
[39,] -15169.8257 -18649.877
[40,] -27885.7061 -15169.826
[41,] -46877.1162 -27885.706
[42,] 17663.2003 -46877.116
[43,] 26797.4684 17663.200
[44,] 12041.9424 26797.468
[45,] -16344.8844 12041.942
[46,] -20662.7742 -16344.884
[47,] -11481.1392 -20662.774
[48,] -11835.4279 -11481.139
[49,] -23041.1519 -11835.428
[50,] -32859.5169 -23041.152
[51,] -35698.5017 -32859.517
[52,] -51116.6093 -35698.502
[53,] -46549.8526 -51116.609
[54,] 12660.4599 -46549.853
[55,] 21266.5257 12660.460
[56,] 1494.5771 21266.526
[57,] -5619.6303 1494.577
[58,] -8745.1127 -5619.630
[59,] 821.6439 -8745.113
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -36607.7193 -45044.264
2 -52731.5784 -36607.719
3 -50753.6258 -52731.578
4 -56783.3945 -50753.626
5 -62769.3205 -56783.394
6 4036.5375 -62769.321
7 24008.0556 4036.537
8 24263.4977 24008.056
9 19500.8939 24263.498
10 9605.5045 19500.894
11 9443.9302 9605.505
12 8432.8509 9443.930
13 5497.5090 8432.851
14 -4823.2616 5497.509
15 -11746.6850 -4823.262
16 -23380.7005 -11746.685
17 -18409.1823 -23380.700
18 47578.1150 -18409.182
19 50179.0332 47578.115
20 48591.7412 50179.033
21 38086.6211 48591.741
22 24936.9652 38086.621
23 17691.9321 24936.965
24 15253.8482 17691.932
25 19819.6249 15253.848
26 2132.1151 19819.625
27 8109.4243 2132.115
28 4616.5591 8109.424
29 4351.2132 4616.559
30 61248.9243 4351.213
31 67827.5994 61248.924
32 60944.4650 67827.599
33 27991.7206 60944.465
34 17577.4737 27991.721
35 5962.7910 17577.474
36 10550.1674 5962.791
37 4601.9271 10550.167
38 -18649.8769 4601.927
39 -15169.8257 -18649.877
40 -27885.7061 -15169.826
41 -46877.1162 -27885.706
42 17663.2003 -46877.116
43 26797.4684 17663.200
44 12041.9424 26797.468
45 -16344.8844 12041.942
46 -20662.7742 -16344.884
47 -11481.1392 -20662.774
48 -11835.4279 -11481.139
49 -23041.1519 -11835.428
50 -32859.5169 -23041.152
51 -35698.5017 -32859.517
52 -51116.6093 -35698.502
53 -46549.8526 -51116.609
54 12660.4599 -46549.853
55 21266.5257 12660.460
56 1494.5771 21266.526
57 -5619.6303 1494.577
58 -8745.1127 -5619.630
59 821.6439 -8745.113
> 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/7rgba1258816737.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8wb0r1258816737.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9wart1258816737.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10es8b1258816737.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11m2dw1258816737.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/12a63t1258816737.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/13wi2u1258816737.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/14ctdo1258816737.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/1553ur1258816737.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/16295o1258816737.tab")
+ }
>
> system("convert tmp/112bc1258816737.ps tmp/112bc1258816737.png")
> system("convert tmp/2t6a71258816737.ps tmp/2t6a71258816737.png")
> system("convert tmp/3gjjs1258816737.ps tmp/3gjjs1258816737.png")
> system("convert tmp/4uuxs1258816737.ps tmp/4uuxs1258816737.png")
> system("convert tmp/5l3th1258816737.ps tmp/5l3th1258816737.png")
> system("convert tmp/6s6br1258816737.ps tmp/6s6br1258816737.png")
> system("convert tmp/7rgba1258816737.ps tmp/7rgba1258816737.png")
> system("convert tmp/8wb0r1258816737.ps tmp/8wb0r1258816737.png")
> system("convert tmp/9wart1258816737.ps tmp/9wart1258816737.png")
> system("convert tmp/10es8b1258816737.ps tmp/10es8b1258816737.png")
>
>
> proc.time()
user system elapsed
2.433 1.593 2.993