R version 2.9.0 (2009-04-17)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
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> x <- array(list(3.48,4143,3.6,4429,3.66,5219,3.45,4929,3.3,5761,3.14,5592,3.21,4163,3.12,4962,3.14,5208,3.4,4755,3.42,4491,3.29,5732,3.49,5731,3.52,5040,3.81,6102,4.03,4904,3.98,5369,4.1,5578,3.96,4619,3.83,4731,3.72,5011,3.82,5299,3.76,4146,3.98,4625,4.14,4736,4,4219,4.13,5116,4.28,4205,4.46,4121,4.63,5103,4.49,4300,4.41,4578,4.5,3809,4.39,5657,4.33,4248,4.45,3830,4.17,4736,4.13,4839,4.33,4411,4.47,4570,4.63,4104,4.9,4801,4.77,3953,4.51,3828,4.63,4440,4.36,4026,3.95,4109,3.74,4785,4.15,3224,4.14,3552,3.97,3940,3.81,3913,4.07,3681,3.84,4309,3.63,3830,3.55,4143,3.6,4087,3.63,3818,3.55,3380,3.69,3430,3.53,3458,3.43,3970,3.4,5260,3.41,5024,3.09,5634,3.35,6549,3.22,4676),dim=c(2,67),dimnames=list(c('leningen','nieuwbouw'),1:67))
> y <- array(NA,dim=c(2,67),dimnames=list(c('leningen','nieuwbouw'),1:67))
> 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
leningen nieuwbouw
1 3.48 4143
2 3.60 4429
3 3.66 5219
4 3.45 4929
5 3.30 5761
6 3.14 5592
7 3.21 4163
8 3.12 4962
9 3.14 5208
10 3.40 4755
11 3.42 4491
12 3.29 5732
13 3.49 5731
14 3.52 5040
15 3.81 6102
16 4.03 4904
17 3.98 5369
18 4.10 5578
19 3.96 4619
20 3.83 4731
21 3.72 5011
22 3.82 5299
23 3.76 4146
24 3.98 4625
25 4.14 4736
26 4.00 4219
27 4.13 5116
28 4.28 4205
29 4.46 4121
30 4.63 5103
31 4.49 4300
32 4.41 4578
33 4.50 3809
34 4.39 5657
35 4.33 4248
36 4.45 3830
37 4.17 4736
38 4.13 4839
39 4.33 4411
40 4.47 4570
41 4.63 4104
42 4.90 4801
43 4.77 3953
44 4.51 3828
45 4.63 4440
46 4.36 4026
47 3.95 4109
48 3.74 4785
49 4.15 3224
50 4.14 3552
51 3.97 3940
52 3.81 3913
53 4.07 3681
54 3.84 4309
55 3.63 3830
56 3.55 4143
57 3.60 4087
58 3.63 3818
59 3.55 3380
60 3.69 3430
61 3.53 3458
62 3.43 3970
63 3.40 5260
64 3.41 5024
65 3.09 5634
66 3.35 6549
67 3.22 4676
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) nieuwbouw
4.7859381 -0.0001974
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-0.75419 -0.38172 -0.02485 0.36134 1.06174
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 4.786e+00 3.573e-01 13.393 <2e-16 ***
nieuwbouw -1.974e-04 7.709e-05 -2.561 0.0128 *
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.4463 on 65 degrees of freedom
Multiple R-squared: 0.09163, Adjusted R-squared: 0.07766
F-statistic: 6.557 on 1 and 65 DF, p-value: 0.01278
> 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,] 0.042519063 0.0850381256 9.574809e-01
[2,] 0.037479509 0.0749590190 9.625205e-01
[3,] 0.047784060 0.0955681195 9.522159e-01
[4,] 0.043035577 0.0860711531 9.569644e-01
[5,] 0.029905738 0.0598114752 9.700943e-01
[6,] 0.014510566 0.0290211326 9.854894e-01
[7,] 0.006881734 0.0137634688 9.931183e-01
[8,] 0.003155106 0.0063102113 9.968449e-01
[9,] 0.002174029 0.0043480581 9.978260e-01
[10,] 0.001297001 0.0025940027 9.987030e-01
[11,] 0.003963800 0.0079275993 9.960362e-01
[12,] 0.021914889 0.0438297775 9.780851e-01
[13,] 0.038092951 0.0761859016 9.619070e-01
[14,] 0.068411376 0.1368227529 9.315886e-01
[15,] 0.079303835 0.1586076706 9.206962e-01
[16,] 0.066532137 0.1330642741 9.334679e-01
[17,] 0.048318370 0.0966367398 9.516816e-01
[18,] 0.036817856 0.0736357123 9.631821e-01
[19,] 0.027662898 0.0553257968 9.723371e-01
[20,] 0.026291619 0.0525832372 9.737084e-01
[21,] 0.033293696 0.0665873920 9.667063e-01
[22,] 0.027747185 0.0554943697 9.722528e-01
[23,] 0.031050979 0.0621019577 9.689490e-01
[24,] 0.038003582 0.0760071646 9.619964e-01
[25,] 0.057951349 0.1159026976 9.420487e-01
[26,] 0.159507182 0.3190143644 8.404928e-01
[27,] 0.195539263 0.3910785252 8.044607e-01
[28,] 0.217420825 0.4348416507 7.825792e-01
[29,] 0.218924877 0.4378497547 7.810751e-01
[30,] 0.305532200 0.6110643993 6.944678e-01
[31,] 0.284878674 0.5697573485 7.151213e-01
[32,] 0.270860733 0.5417214651 7.291393e-01
[33,] 0.239591893 0.4791837851 7.604081e-01
[34,] 0.208507157 0.4170143145 7.914928e-01
[35,] 0.198328803 0.3966576053 8.016712e-01
[36,] 0.235712564 0.4714251277 7.642874e-01
[37,] 0.302805082 0.6056101647 6.971949e-01
[38,] 0.701741871 0.5965162584 2.982581e-01
[39,] 0.865950651 0.2680986976 1.340493e-01
[40,] 0.912633522 0.1747329550 8.736648e-02
[41,] 0.991473981 0.0170520389 8.526019e-03
[42,] 0.998037171 0.0039256580 1.962829e-03
[43,] 0.997689757 0.0046204864 2.310243e-03
[44,] 0.996799233 0.0064015340 3.200767e-03
[45,] 0.996896551 0.0062068987 3.103449e-03
[46,] 0.998263237 0.0034735250 1.736763e-03
[47,] 0.998746564 0.0025068718 1.253436e-03
[48,] 0.998226114 0.0035477719 1.773886e-03
[49,] 0.999717368 0.0005652649 2.826325e-04
[50,] 0.999941837 0.0001163255 5.816274e-05
[51,] 0.999861193 0.0002776144 1.388072e-04
[52,] 0.999611067 0.0007778661 3.889331e-04
[53,] 0.999109625 0.0017807491 8.903745e-04
[54,] 0.998094999 0.0038100019 1.905001e-03
[55,] 0.994341778 0.0113164433 5.658222e-03
[56,] 0.991830513 0.0163389732 8.169487e-03
[57,] 0.978975637 0.0420487265 2.102436e-02
[58,] 0.943475339 0.1130493216 5.652466e-02
> postscript(file="/var/www/html/rcomp/tmp/1ida01293204952.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2ida01293204952.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/html/rcomp/tmp/3ida01293204952.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4bm9l1293204952.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5bm9l1293204952.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 = 67
Frequency = 1
1 2 3 4 5
-0.4881409511 -0.3116866969 -0.0957466238 -0.3629904481 -0.3487598902
6 7 8 9 10
-0.5421192223 -0.7541931012 -0.6864764957 -0.6179179413 -0.4473367427
11 12 13 14 15
-0.4794483620 -0.3644842726 -0.1646816651 -0.2710798809 0.2285509515
16 17 18 19 20
0.2120747395 0.2538622508 0.4151172828 0.0858178777 -0.0220741626
21 22 23 24 25
-0.0768042633 0.0800447760 -0.2075487737 0.1070022327 0.2889127999
26 27 28 29 30
0.0468608787 0.3539219489 0.3240973837 0.4875164139 0.8513558465
31 32 33 34 35
0.5528496710 0.5277247853 0.4659299547 0.7207112901 0.3825852611
36 37 38 39 40
0.4200751971 0.3189127999 0.2992442271 0.4147602382 0.5861456453
41 42 43 44 45
0.6541607415 1.0617433122 0.7643544743 0.4796804121 0.7204846206
46 47 48 49 50
0.3687641266 -0.0248522961 -0.1014149677 0.0004553436 0.0552000828
51 52 53 54 55
-0.0382116281 -0.2035412256 0.0106637150 -0.0953737966 -0.3999248029
56 57 58 59 60
-0.4181409511 -0.3791949310 -0.4022935128 -0.5687514267 -0.4188818019
61 62 63 64 65
-0.5733548119 -0.5722898532 -0.3476535314 -0.3842381608 -0.5838287374
66 67
-0.1432146022 -0.6429307500
> postscript(file="/var/www/html/rcomp/tmp/6bm9l1293204952.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 = 67
Frequency = 1
lag(myerror, k = 1) myerror
0 -0.4881409511 NA
1 -0.3116866969 -0.4881409511
2 -0.0957466238 -0.3116866969
3 -0.3629904481 -0.0957466238
4 -0.3487598902 -0.3629904481
5 -0.5421192223 -0.3487598902
6 -0.7541931012 -0.5421192223
7 -0.6864764957 -0.7541931012
8 -0.6179179413 -0.6864764957
9 -0.4473367427 -0.6179179413
10 -0.4794483620 -0.4473367427
11 -0.3644842726 -0.4794483620
12 -0.1646816651 -0.3644842726
13 -0.2710798809 -0.1646816651
14 0.2285509515 -0.2710798809
15 0.2120747395 0.2285509515
16 0.2538622508 0.2120747395
17 0.4151172828 0.2538622508
18 0.0858178777 0.4151172828
19 -0.0220741626 0.0858178777
20 -0.0768042633 -0.0220741626
21 0.0800447760 -0.0768042633
22 -0.2075487737 0.0800447760
23 0.1070022327 -0.2075487737
24 0.2889127999 0.1070022327
25 0.0468608787 0.2889127999
26 0.3539219489 0.0468608787
27 0.3240973837 0.3539219489
28 0.4875164139 0.3240973837
29 0.8513558465 0.4875164139
30 0.5528496710 0.8513558465
31 0.5277247853 0.5528496710
32 0.4659299547 0.5277247853
33 0.7207112901 0.4659299547
34 0.3825852611 0.7207112901
35 0.4200751971 0.3825852611
36 0.3189127999 0.4200751971
37 0.2992442271 0.3189127999
38 0.4147602382 0.2992442271
39 0.5861456453 0.4147602382
40 0.6541607415 0.5861456453
41 1.0617433122 0.6541607415
42 0.7643544743 1.0617433122
43 0.4796804121 0.7643544743
44 0.7204846206 0.4796804121
45 0.3687641266 0.7204846206
46 -0.0248522961 0.3687641266
47 -0.1014149677 -0.0248522961
48 0.0004553436 -0.1014149677
49 0.0552000828 0.0004553436
50 -0.0382116281 0.0552000828
51 -0.2035412256 -0.0382116281
52 0.0106637150 -0.2035412256
53 -0.0953737966 0.0106637150
54 -0.3999248029 -0.0953737966
55 -0.4181409511 -0.3999248029
56 -0.3791949310 -0.4181409511
57 -0.4022935128 -0.3791949310
58 -0.5687514267 -0.4022935128
59 -0.4188818019 -0.5687514267
60 -0.5733548119 -0.4188818019
61 -0.5722898532 -0.5733548119
62 -0.3476535314 -0.5722898532
63 -0.3842381608 -0.3476535314
64 -0.5838287374 -0.3842381608
65 -0.1432146022 -0.5838287374
66 -0.6429307500 -0.1432146022
67 NA -0.6429307500
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -0.3116866969 -0.4881409511
[2,] -0.0957466238 -0.3116866969
[3,] -0.3629904481 -0.0957466238
[4,] -0.3487598902 -0.3629904481
[5,] -0.5421192223 -0.3487598902
[6,] -0.7541931012 -0.5421192223
[7,] -0.6864764957 -0.7541931012
[8,] -0.6179179413 -0.6864764957
[9,] -0.4473367427 -0.6179179413
[10,] -0.4794483620 -0.4473367427
[11,] -0.3644842726 -0.4794483620
[12,] -0.1646816651 -0.3644842726
[13,] -0.2710798809 -0.1646816651
[14,] 0.2285509515 -0.2710798809
[15,] 0.2120747395 0.2285509515
[16,] 0.2538622508 0.2120747395
[17,] 0.4151172828 0.2538622508
[18,] 0.0858178777 0.4151172828
[19,] -0.0220741626 0.0858178777
[20,] -0.0768042633 -0.0220741626
[21,] 0.0800447760 -0.0768042633
[22,] -0.2075487737 0.0800447760
[23,] 0.1070022327 -0.2075487737
[24,] 0.2889127999 0.1070022327
[25,] 0.0468608787 0.2889127999
[26,] 0.3539219489 0.0468608787
[27,] 0.3240973837 0.3539219489
[28,] 0.4875164139 0.3240973837
[29,] 0.8513558465 0.4875164139
[30,] 0.5528496710 0.8513558465
[31,] 0.5277247853 0.5528496710
[32,] 0.4659299547 0.5277247853
[33,] 0.7207112901 0.4659299547
[34,] 0.3825852611 0.7207112901
[35,] 0.4200751971 0.3825852611
[36,] 0.3189127999 0.4200751971
[37,] 0.2992442271 0.3189127999
[38,] 0.4147602382 0.2992442271
[39,] 0.5861456453 0.4147602382
[40,] 0.6541607415 0.5861456453
[41,] 1.0617433122 0.6541607415
[42,] 0.7643544743 1.0617433122
[43,] 0.4796804121 0.7643544743
[44,] 0.7204846206 0.4796804121
[45,] 0.3687641266 0.7204846206
[46,] -0.0248522961 0.3687641266
[47,] -0.1014149677 -0.0248522961
[48,] 0.0004553436 -0.1014149677
[49,] 0.0552000828 0.0004553436
[50,] -0.0382116281 0.0552000828
[51,] -0.2035412256 -0.0382116281
[52,] 0.0106637150 -0.2035412256
[53,] -0.0953737966 0.0106637150
[54,] -0.3999248029 -0.0953737966
[55,] -0.4181409511 -0.3999248029
[56,] -0.3791949310 -0.4181409511
[57,] -0.4022935128 -0.3791949310
[58,] -0.5687514267 -0.4022935128
[59,] -0.4188818019 -0.5687514267
[60,] -0.5733548119 -0.4188818019
[61,] -0.5722898532 -0.5733548119
[62,] -0.3476535314 -0.5722898532
[63,] -0.3842381608 -0.3476535314
[64,] -0.5838287374 -0.3842381608
[65,] -0.1432146022 -0.5838287374
[66,] -0.6429307500 -0.1432146022
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -0.3116866969 -0.4881409511
2 -0.0957466238 -0.3116866969
3 -0.3629904481 -0.0957466238
4 -0.3487598902 -0.3629904481
5 -0.5421192223 -0.3487598902
6 -0.7541931012 -0.5421192223
7 -0.6864764957 -0.7541931012
8 -0.6179179413 -0.6864764957
9 -0.4473367427 -0.6179179413
10 -0.4794483620 -0.4473367427
11 -0.3644842726 -0.4794483620
12 -0.1646816651 -0.3644842726
13 -0.2710798809 -0.1646816651
14 0.2285509515 -0.2710798809
15 0.2120747395 0.2285509515
16 0.2538622508 0.2120747395
17 0.4151172828 0.2538622508
18 0.0858178777 0.4151172828
19 -0.0220741626 0.0858178777
20 -0.0768042633 -0.0220741626
21 0.0800447760 -0.0768042633
22 -0.2075487737 0.0800447760
23 0.1070022327 -0.2075487737
24 0.2889127999 0.1070022327
25 0.0468608787 0.2889127999
26 0.3539219489 0.0468608787
27 0.3240973837 0.3539219489
28 0.4875164139 0.3240973837
29 0.8513558465 0.4875164139
30 0.5528496710 0.8513558465
31 0.5277247853 0.5528496710
32 0.4659299547 0.5277247853
33 0.7207112901 0.4659299547
34 0.3825852611 0.7207112901
35 0.4200751971 0.3825852611
36 0.3189127999 0.4200751971
37 0.2992442271 0.3189127999
38 0.4147602382 0.2992442271
39 0.5861456453 0.4147602382
40 0.6541607415 0.5861456453
41 1.0617433122 0.6541607415
42 0.7643544743 1.0617433122
43 0.4796804121 0.7643544743
44 0.7204846206 0.4796804121
45 0.3687641266 0.7204846206
46 -0.0248522961 0.3687641266
47 -0.1014149677 -0.0248522961
48 0.0004553436 -0.1014149677
49 0.0552000828 0.0004553436
50 -0.0382116281 0.0552000828
51 -0.2035412256 -0.0382116281
52 0.0106637150 -0.2035412256
53 -0.0953737966 0.0106637150
54 -0.3999248029 -0.0953737966
55 -0.4181409511 -0.3999248029
56 -0.3791949310 -0.4181409511
57 -0.4022935128 -0.3791949310
58 -0.5687514267 -0.4022935128
59 -0.4188818019 -0.5687514267
60 -0.5733548119 -0.4188818019
61 -0.5722898532 -0.5733548119
62 -0.3476535314 -0.5722898532
63 -0.3842381608 -0.3476535314
64 -0.5838287374 -0.3842381608
65 -0.1432146022 -0.5838287374
66 -0.6429307500 -0.1432146022
> 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/7md8o1293204952.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8e4q91293204952.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9e4q91293204952.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10e4q91293204952.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11ten01293204952.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/12wf461293204952.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/13sp2x1293204952.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/14v7ik1293204952.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/15z7h81293204952.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/16k8fe1293204952.tab")
+ }
>
> try(system("convert tmp/1ida01293204952.ps tmp/1ida01293204952.png",intern=TRUE))
character(0)
> try(system("convert tmp/2ida01293204952.ps tmp/2ida01293204952.png",intern=TRUE))
character(0)
> try(system("convert tmp/3ida01293204952.ps tmp/3ida01293204952.png",intern=TRUE))
character(0)
> try(system("convert tmp/4bm9l1293204952.ps tmp/4bm9l1293204952.png",intern=TRUE))
character(0)
> try(system("convert tmp/5bm9l1293204952.ps tmp/5bm9l1293204952.png",intern=TRUE))
character(0)
> try(system("convert tmp/6bm9l1293204952.ps tmp/6bm9l1293204952.png",intern=TRUE))
character(0)
> try(system("convert tmp/7md8o1293204952.ps tmp/7md8o1293204952.png",intern=TRUE))
character(0)
> try(system("convert tmp/8e4q91293204952.ps tmp/8e4q91293204952.png",intern=TRUE))
character(0)
> try(system("convert tmp/9e4q91293204952.ps tmp/9e4q91293204952.png",intern=TRUE))
character(0)
> try(system("convert tmp/10e4q91293204952.ps tmp/10e4q91293204952.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
2.572 1.622 10.879