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(13807
+ ,0
+ ,19169
+ ,22782
+ ,20366
+ ,29743
+ ,0
+ ,13807
+ ,19169
+ ,22782
+ ,25591
+ ,0
+ ,29743
+ ,13807
+ ,19169
+ ,29096
+ ,0
+ ,25591
+ ,29743
+ ,13807
+ ,26482
+ ,0
+ ,29096
+ ,25591
+ ,29743
+ ,22405
+ ,0
+ ,26482
+ ,29096
+ ,25591
+ ,27044
+ ,0
+ ,22405
+ ,26482
+ ,29096
+ ,17970
+ ,0
+ ,27044
+ ,22405
+ ,26482
+ ,18730
+ ,0
+ ,17970
+ ,27044
+ ,22405
+ ,19684
+ ,0
+ ,18730
+ ,17970
+ ,27044
+ ,19785
+ ,0
+ ,19684
+ ,18730
+ ,17970
+ ,18479
+ ,0
+ ,19785
+ ,19684
+ ,18730
+ ,10698
+ ,0
+ ,18479
+ ,19785
+ ,19684
+ ,31956
+ ,0
+ ,10698
+ ,18479
+ ,19785
+ ,29506
+ ,0
+ ,31956
+ ,10698
+ ,18479
+ ,34506
+ ,0
+ ,29506
+ ,31956
+ ,10698
+ ,27165
+ ,0
+ ,34506
+ ,29506
+ ,31956
+ ,26736
+ ,0
+ ,27165
+ ,34506
+ ,29506
+ ,23691
+ ,0
+ ,26736
+ ,27165
+ ,34506
+ ,18157
+ ,0
+ ,23691
+ ,26736
+ ,27165
+ ,17328
+ ,0
+ ,18157
+ ,23691
+ ,26736
+ ,18205
+ ,0
+ ,17328
+ ,18157
+ ,23691
+ ,20995
+ ,0
+ ,18205
+ ,17328
+ ,18157
+ ,17382
+ ,0
+ ,20995
+ ,18205
+ ,17328
+ ,9367
+ ,0
+ ,17382
+ ,20995
+ ,18205
+ ,31124
+ ,0
+ ,9367
+ ,17382
+ ,20995
+ ,26551
+ ,0
+ ,31124
+ ,9367
+ ,17382
+ ,30651
+ ,0
+ ,26551
+ ,31124
+ ,9367
+ ,25859
+ ,0
+ ,30651
+ ,26551
+ ,31124
+ ,25100
+ ,0
+ ,25859
+ ,30651
+ ,26551
+ ,25778
+ ,0
+ ,25100
+ ,25859
+ ,30651
+ ,20418
+ ,0
+ ,25778
+ ,25100
+ ,25859
+ ,18688
+ ,0
+ ,20418
+ ,25778
+ ,25100
+ ,20424
+ ,0
+ ,18688
+ ,20418
+ ,25778
+ ,24776
+ ,0
+ ,20424
+ ,18688
+ ,20418
+ ,19814
+ ,0
+ ,24776
+ ,20424
+ ,18688
+ ,12738
+ ,0
+ ,19814
+ ,24776
+ ,20424
+ ,31566
+ ,0
+ ,12738
+ ,19814
+ ,24776
+ ,30111
+ ,0
+ ,31566
+ ,12738
+ ,19814
+ ,30019
+ ,0
+ ,30111
+ ,31566
+ ,12738
+ ,31934
+ ,1
+ ,30019
+ ,30111
+ ,31566
+ ,25826
+ ,1
+ ,31934
+ ,30019
+ ,30111
+ ,26835
+ ,1
+ ,25826
+ ,31934
+ ,30019
+ ,20205
+ ,1
+ ,26835
+ ,25826
+ ,31934
+ ,17789
+ ,1
+ ,20205
+ ,26835
+ ,25826
+ ,20520
+ ,1
+ ,17789
+ ,20205
+ ,26835
+ ,22518
+ ,1
+ ,20520
+ ,17789
+ ,20205
+ ,15572
+ ,1
+ ,22518
+ ,20520
+ ,17789
+ ,11509
+ ,1
+ ,15572
+ ,22518
+ ,20520
+ ,25447
+ ,1
+ ,11509
+ ,15572
+ ,22518
+ ,24090
+ ,1
+ ,25447
+ ,11509
+ ,15572
+ ,27786
+ ,1
+ ,24090
+ ,25447
+ ,11509
+ ,26195
+ ,1
+ ,27786
+ ,24090
+ ,25447
+ ,20516
+ ,1
+ ,26195
+ ,27786
+ ,24090
+ ,22759
+ ,1
+ ,20516
+ ,26195
+ ,27786
+ ,19028
+ ,1
+ ,22759
+ ,20516
+ ,26195
+ ,16971
+ ,1
+ ,19028
+ ,22759
+ ,20516)
+ ,dim=c(5
+ ,57)
+ ,dimnames=list(c('Y'
+ ,'X'
+ ,'Y1'
+ ,'Y2'
+ ,'Y3')
+ ,1:57))
> y <- array(NA,dim=c(5,57),dimnames=list(c('Y','X','Y1','Y2','Y3'),1:57))
> 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 = 'Include Monthly 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 Y1 Y2 Y3 M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 13807 0 19169 22782 20366 1 0 0 0 0 0 0 0 0 0 0 1
2 29743 0 13807 19169 22782 0 1 0 0 0 0 0 0 0 0 0 2
3 25591 0 29743 13807 19169 0 0 1 0 0 0 0 0 0 0 0 3
4 29096 0 25591 29743 13807 0 0 0 1 0 0 0 0 0 0 0 4
5 26482 0 29096 25591 29743 0 0 0 0 1 0 0 0 0 0 0 5
6 22405 0 26482 29096 25591 0 0 0 0 0 1 0 0 0 0 0 6
7 27044 0 22405 26482 29096 0 0 0 0 0 0 1 0 0 0 0 7
8 17970 0 27044 22405 26482 0 0 0 0 0 0 0 1 0 0 0 8
9 18730 0 17970 27044 22405 0 0 0 0 0 0 0 0 1 0 0 9
10 19684 0 18730 17970 27044 0 0 0 0 0 0 0 0 0 1 0 10
11 19785 0 19684 18730 17970 0 0 0 0 0 0 0 0 0 0 1 11
12 18479 0 19785 19684 18730 0 0 0 0 0 0 0 0 0 0 0 12
13 10698 0 18479 19785 19684 1 0 0 0 0 0 0 0 0 0 0 13
14 31956 0 10698 18479 19785 0 1 0 0 0 0 0 0 0 0 0 14
15 29506 0 31956 10698 18479 0 0 1 0 0 0 0 0 0 0 0 15
16 34506 0 29506 31956 10698 0 0 0 1 0 0 0 0 0 0 0 16
17 27165 0 34506 29506 31956 0 0 0 0 1 0 0 0 0 0 0 17
18 26736 0 27165 34506 29506 0 0 0 0 0 1 0 0 0 0 0 18
19 23691 0 26736 27165 34506 0 0 0 0 0 0 1 0 0 0 0 19
20 18157 0 23691 26736 27165 0 0 0 0 0 0 0 1 0 0 0 20
21 17328 0 18157 23691 26736 0 0 0 0 0 0 0 0 1 0 0 21
22 18205 0 17328 18157 23691 0 0 0 0 0 0 0 0 0 1 0 22
23 20995 0 18205 17328 18157 0 0 0 0 0 0 0 0 0 0 1 23
24 17382 0 20995 18205 17328 0 0 0 0 0 0 0 0 0 0 0 24
25 9367 0 17382 20995 18205 1 0 0 0 0 0 0 0 0 0 0 25
26 31124 0 9367 17382 20995 0 1 0 0 0 0 0 0 0 0 0 26
27 26551 0 31124 9367 17382 0 0 1 0 0 0 0 0 0 0 0 27
28 30651 0 26551 31124 9367 0 0 0 1 0 0 0 0 0 0 0 28
29 25859 0 30651 26551 31124 0 0 0 0 1 0 0 0 0 0 0 29
30 25100 0 25859 30651 26551 0 0 0 0 0 1 0 0 0 0 0 30
31 25778 0 25100 25859 30651 0 0 0 0 0 0 1 0 0 0 0 31
32 20418 0 25778 25100 25859 0 0 0 0 0 0 0 1 0 0 0 32
33 18688 0 20418 25778 25100 0 0 0 0 0 0 0 0 1 0 0 33
34 20424 0 18688 20418 25778 0 0 0 0 0 0 0 0 0 1 0 34
35 24776 0 20424 18688 20418 0 0 0 0 0 0 0 0 0 0 1 35
36 19814 0 24776 20424 18688 0 0 0 0 0 0 0 0 0 0 0 36
37 12738 0 19814 24776 20424 1 0 0 0 0 0 0 0 0 0 0 37
38 31566 0 12738 19814 24776 0 1 0 0 0 0 0 0 0 0 0 38
39 30111 0 31566 12738 19814 0 0 1 0 0 0 0 0 0 0 0 39
40 30019 0 30111 31566 12738 0 0 0 1 0 0 0 0 0 0 0 40
41 31934 1 30019 30111 31566 0 0 0 0 1 0 0 0 0 0 0 41
42 25826 1 31934 30019 30111 0 0 0 0 0 1 0 0 0 0 0 42
43 26835 1 25826 31934 30019 0 0 0 0 0 0 1 0 0 0 0 43
44 20205 1 26835 25826 31934 0 0 0 0 0 0 0 1 0 0 0 44
45 17789 1 20205 26835 25826 0 0 0 0 0 0 0 0 1 0 0 45
46 20520 1 17789 20205 26835 0 0 0 0 0 0 0 0 0 1 0 46
47 22518 1 20520 17789 20205 0 0 0 0 0 0 0 0 0 0 1 47
48 15572 1 22518 20520 17789 0 0 0 0 0 0 0 0 0 0 0 48
49 11509 1 15572 22518 20520 1 0 0 0 0 0 0 0 0 0 0 49
50 25447 1 11509 15572 22518 0 1 0 0 0 0 0 0 0 0 0 50
51 24090 1 25447 11509 15572 0 0 1 0 0 0 0 0 0 0 0 51
52 27786 1 24090 25447 11509 0 0 0 1 0 0 0 0 0 0 0 52
53 26195 1 27786 24090 25447 0 0 0 0 1 0 0 0 0 0 0 53
54 20516 1 26195 27786 24090 0 0 0 0 0 1 0 0 0 0 0 54
55 22759 1 20516 26195 27786 0 0 0 0 0 0 1 0 0 0 0 55
56 19028 1 22759 20516 26195 0 0 0 0 0 0 0 1 0 0 0 56
57 16971 1 19028 22759 20516 0 0 0 0 0 0 0 0 1 0 0 57
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X Y1 Y2 Y3 M1
4.707e+03 -8.896e+02 1.535e-01 4.366e-01 5.087e-02 -6.720e+03
M2 M3 M4 M5 M6 M7
1.427e+04 1.167e+04 7.645e+03 4.715e+03 4.603e+02 3.169e+03
M8 M9 M10 M11 t
-1.445e+03 -2.091e+03 2.356e+03 5.209e+03 1.400e+01
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-3048.32 -928.23 53.19 843.24 3467.67
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 4.707e+03 3.579e+03 1.315 0.195926
X -8.896e+02 8.895e+02 -1.000 0.323284
Y1 1.535e-01 1.595e-01 0.963 0.341483
Y2 4.366e-01 1.436e-01 3.040 0.004160 **
Y3 5.087e-02 1.600e-01 0.318 0.752162
M1 -6.720e+03 1.491e+03 -4.507 5.62e-05 ***
M2 1.427e+04 2.354e+03 6.060 3.89e-07 ***
M3 1.167e+04 2.237e+03 5.216 5.94e-06 ***
M4 7.645e+03 2.524e+03 3.029 0.004280 **
M5 4.715e+03 2.035e+03 2.317 0.025735 *
M6 4.603e+02 1.984e+03 0.232 0.817678
M7 3.169e+03 2.205e+03 1.437 0.158401
M8 -1.445e+03 1.755e+03 -0.823 0.415339
M9 -2.091e+03 1.834e+03 -1.140 0.261068
M10 2.356e+03 2.052e+03 1.149 0.257576
M11 5.209e+03 1.360e+03 3.831 0.000441 ***
t 1.400e+01 2.408e+01 0.581 0.564240
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 1786 on 40 degrees of freedom
Multiple R-squared: 0.9341, Adjusted R-squared: 0.9077
F-statistic: 35.43 on 16 and 40 DF, p-value: < 2.2e-16
> 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,] 0.9091219 0.1817563 0.09087814
[2,] 0.8602758 0.2794485 0.13972424
[3,] 0.8712268 0.2575463 0.12877316
[4,] 0.8241657 0.3516686 0.17583432
[5,] 0.7584011 0.4831978 0.24159891
[6,] 0.7870890 0.4258219 0.21291097
[7,] 0.7725638 0.4548725 0.22743623
[8,] 0.6732450 0.6535100 0.32675499
[9,] 0.6245445 0.7509111 0.37545554
[10,] 0.8425172 0.3149655 0.15748276
[11,] 0.7802936 0.4394127 0.21970636
[12,] 0.6924074 0.6151851 0.30759257
[13,] 0.6390349 0.7219302 0.36096510
[14,] 0.5398169 0.9203661 0.46018306
[15,] 0.4526440 0.9052879 0.54735604
[16,] 0.4264832 0.8529664 0.57351681
[17,] 0.2918475 0.5836950 0.70815249
[18,] 0.2330853 0.4661707 0.76691467
> postscript(file="/var/www/html/rcomp/tmp/1dd0p1260972727.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2n94s1260972727.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3belu1260972727.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4kma61260972727.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5vdyc1260972727.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 = 57
Frequency = 1
1 2 3 4 5 6
1881.22502 -906.32803 -2394.55815 -928.23485 -162.14795 -916.29314
7 8 9 10 11 12
2588.73002 -684.83291 282.44117 383.97067 -2398.49765 1020.06735
13 14 15 16 17 18
53.18501 2069.63662 2405.00345 2904.69804 -2299.47170 580.89548
19 20 21 22 23 24
-2170.59473 -2076.55057 -72.81919 -958.89517 -526.91435 286.24662
25 26 27 28 29 30
-1730.42868 1691.31172 46.56797 -233.73165 -1849.29245 810.61460
31 32 33 34 35 36
765.78154 476.63877 -55.86490 -209.94293 2036.64333 931.81550
37 38 39 40 41 42
-664.34418 193.69602 1775.33323 -1944.75895 3467.67324 1420.30298
43 44 45 46 47 48
-187.06200 196.97183 -698.96914 784.86742 888.76866 -2238.12947
49 50 51 52 53 54
460.36284 -3048.31633 -1832.34650 202.02740 843.23887 -1895.51991
55 56 57
-996.85483 2087.77288 545.21206
> postscript(file="/var/www/html/rcomp/tmp/6m62x1260972727.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 = 57
Frequency = 1
lag(myerror, k = 1) myerror
0 1881.22502 NA
1 -906.32803 1881.22502
2 -2394.55815 -906.32803
3 -928.23485 -2394.55815
4 -162.14795 -928.23485
5 -916.29314 -162.14795
6 2588.73002 -916.29314
7 -684.83291 2588.73002
8 282.44117 -684.83291
9 383.97067 282.44117
10 -2398.49765 383.97067
11 1020.06735 -2398.49765
12 53.18501 1020.06735
13 2069.63662 53.18501
14 2405.00345 2069.63662
15 2904.69804 2405.00345
16 -2299.47170 2904.69804
17 580.89548 -2299.47170
18 -2170.59473 580.89548
19 -2076.55057 -2170.59473
20 -72.81919 -2076.55057
21 -958.89517 -72.81919
22 -526.91435 -958.89517
23 286.24662 -526.91435
24 -1730.42868 286.24662
25 1691.31172 -1730.42868
26 46.56797 1691.31172
27 -233.73165 46.56797
28 -1849.29245 -233.73165
29 810.61460 -1849.29245
30 765.78154 810.61460
31 476.63877 765.78154
32 -55.86490 476.63877
33 -209.94293 -55.86490
34 2036.64333 -209.94293
35 931.81550 2036.64333
36 -664.34418 931.81550
37 193.69602 -664.34418
38 1775.33323 193.69602
39 -1944.75895 1775.33323
40 3467.67324 -1944.75895
41 1420.30298 3467.67324
42 -187.06200 1420.30298
43 196.97183 -187.06200
44 -698.96914 196.97183
45 784.86742 -698.96914
46 888.76866 784.86742
47 -2238.12947 888.76866
48 460.36284 -2238.12947
49 -3048.31633 460.36284
50 -1832.34650 -3048.31633
51 202.02740 -1832.34650
52 843.23887 202.02740
53 -1895.51991 843.23887
54 -996.85483 -1895.51991
55 2087.77288 -996.85483
56 545.21206 2087.77288
57 NA 545.21206
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -906.32803 1881.22502
[2,] -2394.55815 -906.32803
[3,] -928.23485 -2394.55815
[4,] -162.14795 -928.23485
[5,] -916.29314 -162.14795
[6,] 2588.73002 -916.29314
[7,] -684.83291 2588.73002
[8,] 282.44117 -684.83291
[9,] 383.97067 282.44117
[10,] -2398.49765 383.97067
[11,] 1020.06735 -2398.49765
[12,] 53.18501 1020.06735
[13,] 2069.63662 53.18501
[14,] 2405.00345 2069.63662
[15,] 2904.69804 2405.00345
[16,] -2299.47170 2904.69804
[17,] 580.89548 -2299.47170
[18,] -2170.59473 580.89548
[19,] -2076.55057 -2170.59473
[20,] -72.81919 -2076.55057
[21,] -958.89517 -72.81919
[22,] -526.91435 -958.89517
[23,] 286.24662 -526.91435
[24,] -1730.42868 286.24662
[25,] 1691.31172 -1730.42868
[26,] 46.56797 1691.31172
[27,] -233.73165 46.56797
[28,] -1849.29245 -233.73165
[29,] 810.61460 -1849.29245
[30,] 765.78154 810.61460
[31,] 476.63877 765.78154
[32,] -55.86490 476.63877
[33,] -209.94293 -55.86490
[34,] 2036.64333 -209.94293
[35,] 931.81550 2036.64333
[36,] -664.34418 931.81550
[37,] 193.69602 -664.34418
[38,] 1775.33323 193.69602
[39,] -1944.75895 1775.33323
[40,] 3467.67324 -1944.75895
[41,] 1420.30298 3467.67324
[42,] -187.06200 1420.30298
[43,] 196.97183 -187.06200
[44,] -698.96914 196.97183
[45,] 784.86742 -698.96914
[46,] 888.76866 784.86742
[47,] -2238.12947 888.76866
[48,] 460.36284 -2238.12947
[49,] -3048.31633 460.36284
[50,] -1832.34650 -3048.31633
[51,] 202.02740 -1832.34650
[52,] 843.23887 202.02740
[53,] -1895.51991 843.23887
[54,] -996.85483 -1895.51991
[55,] 2087.77288 -996.85483
[56,] 545.21206 2087.77288
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -906.32803 1881.22502
2 -2394.55815 -906.32803
3 -928.23485 -2394.55815
4 -162.14795 -928.23485
5 -916.29314 -162.14795
6 2588.73002 -916.29314
7 -684.83291 2588.73002
8 282.44117 -684.83291
9 383.97067 282.44117
10 -2398.49765 383.97067
11 1020.06735 -2398.49765
12 53.18501 1020.06735
13 2069.63662 53.18501
14 2405.00345 2069.63662
15 2904.69804 2405.00345
16 -2299.47170 2904.69804
17 580.89548 -2299.47170
18 -2170.59473 580.89548
19 -2076.55057 -2170.59473
20 -72.81919 -2076.55057
21 -958.89517 -72.81919
22 -526.91435 -958.89517
23 286.24662 -526.91435
24 -1730.42868 286.24662
25 1691.31172 -1730.42868
26 46.56797 1691.31172
27 -233.73165 46.56797
28 -1849.29245 -233.73165
29 810.61460 -1849.29245
30 765.78154 810.61460
31 476.63877 765.78154
32 -55.86490 476.63877
33 -209.94293 -55.86490
34 2036.64333 -209.94293
35 931.81550 2036.64333
36 -664.34418 931.81550
37 193.69602 -664.34418
38 1775.33323 193.69602
39 -1944.75895 1775.33323
40 3467.67324 -1944.75895
41 1420.30298 3467.67324
42 -187.06200 1420.30298
43 196.97183 -187.06200
44 -698.96914 196.97183
45 784.86742 -698.96914
46 888.76866 784.86742
47 -2238.12947 888.76866
48 460.36284 -2238.12947
49 -3048.31633 460.36284
50 -1832.34650 -3048.31633
51 202.02740 -1832.34650
52 843.23887 202.02740
53 -1895.51991 843.23887
54 -996.85483 -1895.51991
55 2087.77288 -996.85483
56 545.21206 2087.77288
> 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/7h1hk1260972727.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8sqr31260972727.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9gzah1260972727.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10jb8x1260972727.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11pl9w1260972727.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/12u3ow1260972727.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/13nibq1260972727.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/14il3z1260972727.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/15r5161260972727.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/164dne1260972727.tab")
+ }
>
> try(system("convert tmp/1dd0p1260972727.ps tmp/1dd0p1260972727.png",intern=TRUE))
character(0)
> try(system("convert tmp/2n94s1260972727.ps tmp/2n94s1260972727.png",intern=TRUE))
character(0)
> try(system("convert tmp/3belu1260972727.ps tmp/3belu1260972727.png",intern=TRUE))
character(0)
> try(system("convert tmp/4kma61260972727.ps tmp/4kma61260972727.png",intern=TRUE))
character(0)
> try(system("convert tmp/5vdyc1260972727.ps tmp/5vdyc1260972727.png",intern=TRUE))
character(0)
> try(system("convert tmp/6m62x1260972727.ps tmp/6m62x1260972727.png",intern=TRUE))
character(0)
> try(system("convert tmp/7h1hk1260972727.ps tmp/7h1hk1260972727.png",intern=TRUE))
character(0)
> try(system("convert tmp/8sqr31260972727.ps tmp/8sqr31260972727.png",intern=TRUE))
character(0)
> try(system("convert tmp/9gzah1260972727.ps tmp/9gzah1260972727.png",intern=TRUE))
character(0)
> try(system("convert tmp/10jb8x1260972727.ps tmp/10jb8x1260972727.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
2.348 1.613 8.787