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.
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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(21.3
+ ,2533
+ ,21.8
+ ,19.2
+ ,20
+ ,20.3
+ ,21.5
+ ,2058
+ ,21.3
+ ,21.8
+ ,19.2
+ ,20
+ ,19.5
+ ,2160
+ ,21.5
+ ,21.3
+ ,21.8
+ ,19.2
+ ,19.5
+ ,2260
+ ,19.5
+ ,21.5
+ ,21.3
+ ,21.8
+ ,19.7
+ ,2498
+ ,19.5
+ ,19.5
+ ,21.5
+ ,21.3
+ ,18.7
+ ,2695
+ ,19.7
+ ,19.5
+ ,19.5
+ ,21.5
+ ,19.7
+ ,2799
+ ,18.7
+ ,19.7
+ ,19.5
+ ,19.5
+ ,20
+ ,2946
+ ,19.7
+ ,18.7
+ ,19.7
+ ,19.5
+ ,19.7
+ ,2930
+ ,20
+ ,19.7
+ ,18.7
+ ,19.7
+ ,19.2
+ ,2318
+ ,19.7
+ ,20
+ ,19.7
+ ,18.7
+ ,19.7
+ ,2540
+ ,19.2
+ ,19.7
+ ,20
+ ,19.7
+ ,22
+ ,2570
+ ,19.7
+ ,19.2
+ ,19.7
+ ,20
+ ,21.8
+ ,2669
+ ,22
+ ,19.7
+ ,19.2
+ ,19.7
+ ,22.8
+ ,2450
+ ,21.8
+ ,22
+ ,19.7
+ ,19.2
+ ,21
+ ,2842
+ ,22.8
+ ,21.8
+ ,22
+ ,19.7
+ ,25
+ ,3440
+ ,21
+ ,22.8
+ ,21.8
+ ,22
+ ,23.3
+ ,2678
+ ,25
+ ,21
+ ,22.8
+ ,21.8
+ ,25
+ ,2981
+ ,23.3
+ ,25
+ ,21
+ ,22.8
+ ,26.8
+ ,2260
+ ,25
+ ,23.3
+ ,25
+ ,21
+ ,25.3
+ ,2844
+ ,26.8
+ ,25
+ ,23.3
+ ,25
+ ,26.5
+ ,2546
+ ,25.3
+ ,26.8
+ ,25
+ ,23.3
+ ,27.8
+ ,2456
+ ,26.5
+ ,25.3
+ ,26.8
+ ,25
+ ,22
+ ,2295
+ ,27.8
+ ,26.5
+ ,25.3
+ ,26.8
+ ,22.3
+ ,2379
+ ,22
+ ,27.8
+ ,26.5
+ ,25.3
+ ,28
+ ,2479
+ ,22.3
+ ,22
+ ,27.8
+ ,26.5
+ ,25
+ ,2057
+ ,28
+ ,22.3
+ ,22
+ ,27.8
+ ,27.3
+ ,2280
+ ,25
+ ,28
+ ,22.3
+ ,22
+ ,25.8
+ ,2351
+ ,27.3
+ ,25
+ ,28
+ ,22.3
+ ,27.3
+ ,2276
+ ,25.8
+ ,27.3
+ ,25
+ ,28
+ ,23.5
+ ,2548
+ ,27.3
+ ,25.8
+ ,27.3
+ ,25
+ ,24.5
+ ,2311
+ ,23.5
+ ,27.3
+ ,25.8
+ ,27.3
+ ,18
+ ,2201
+ ,24.5
+ ,23.5
+ ,27.3
+ ,25.8
+ ,21.3
+ ,2725
+ ,18
+ ,24.5
+ ,23.5
+ ,27.3
+ ,21.8
+ ,2408
+ ,21.3
+ ,18
+ ,24.5
+ ,23.5
+ ,20.5
+ ,2139
+ ,21.8
+ ,21.3
+ ,18
+ ,24.5
+ ,22.3
+ ,1898
+ ,20.5
+ ,21.8
+ ,21.3
+ ,18
+ ,18.7
+ ,2537
+ ,22.3
+ ,20.5
+ ,21.8
+ ,21.3
+ ,22.3
+ ,2068
+ ,18.7
+ ,22.3
+ ,20.5
+ ,21.8
+ ,17.7
+ ,2063
+ ,22.3
+ ,18.7
+ ,22.3
+ ,20.5
+ ,19.7
+ ,2520
+ ,17.7
+ ,22.3
+ ,18.7
+ ,22.3
+ ,20.5
+ ,2434
+ ,19.7
+ ,17.7
+ ,22.3
+ ,18.7
+ ,18.5
+ ,2190
+ ,20.5
+ ,19.7
+ ,17.7
+ ,22.3
+ ,10
+ ,2794
+ ,18.5
+ ,20.5
+ ,19.7
+ ,17.7
+ ,14.2
+ ,2070
+ ,10
+ ,18.5
+ ,20.5
+ ,19.7
+ ,15.5
+ ,2615
+ ,14.2
+ ,10
+ ,18.5
+ ,20.5
+ ,16.5
+ ,2265
+ ,15.5
+ ,14.2
+ ,10
+ ,18.5
+ ,20.5
+ ,2139
+ ,16.5
+ ,15.5
+ ,14.2
+ ,10
+ ,15.7
+ ,2428
+ ,20.5
+ ,16.5
+ ,15.5
+ ,14.2
+ ,11.7
+ ,2137
+ ,15.7
+ ,20.5
+ ,16.5
+ ,15.5
+ ,7.5
+ ,1823
+ ,11.7
+ ,15.7
+ ,20.5
+ ,16.5
+ ,3.5
+ ,2063
+ ,7.5
+ ,11.7
+ ,15.7
+ ,20.5
+ ,4.5
+ ,1806
+ ,3.5
+ ,7.5
+ ,11.7
+ ,15.7
+ ,2.2
+ ,1758
+ ,4.5
+ ,3.5
+ ,7.5
+ ,11.7
+ ,5
+ ,2243
+ ,2.2
+ ,4.5
+ ,3.5
+ ,7.5
+ ,2.3
+ ,1993
+ ,5
+ ,2.2
+ ,4.5
+ ,3.5
+ ,6.1
+ ,1932
+ ,2.3
+ ,5
+ ,2.2
+ ,4.5
+ ,3.3
+ ,2465
+ ,6.1
+ ,2.3
+ ,5
+ ,2.2)
+ ,dim=c(6
+ ,57)
+ ,dimnames=list(c('Y'
+ ,'X'
+ ,'Y1'
+ ,'Y2'
+ ,'Y3'
+ ,'Y4')
+ ,1:57))
> y <- array(NA,dim=c(6,57),dimnames=list(c('Y','X','Y1','Y2','Y3','Y4'),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 Y4 M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 21.3 2533 21.8 19.2 20.0 20.3 1 0 0 0 0 0 0 0 0 0 0 1
2 21.5 2058 21.3 21.8 19.2 20.0 0 1 0 0 0 0 0 0 0 0 0 2
3 19.5 2160 21.5 21.3 21.8 19.2 0 0 1 0 0 0 0 0 0 0 0 3
4 19.5 2260 19.5 21.5 21.3 21.8 0 0 0 1 0 0 0 0 0 0 0 4
5 19.7 2498 19.5 19.5 21.5 21.3 0 0 0 0 1 0 0 0 0 0 0 5
6 18.7 2695 19.7 19.5 19.5 21.5 0 0 0 0 0 1 0 0 0 0 0 6
7 19.7 2799 18.7 19.7 19.5 19.5 0 0 0 0 0 0 1 0 0 0 0 7
8 20.0 2946 19.7 18.7 19.7 19.5 0 0 0 0 0 0 0 1 0 0 0 8
9 19.7 2930 20.0 19.7 18.7 19.7 0 0 0 0 0 0 0 0 1 0 0 9
10 19.2 2318 19.7 20.0 19.7 18.7 0 0 0 0 0 0 0 0 0 1 0 10
11 19.7 2540 19.2 19.7 20.0 19.7 0 0 0 0 0 0 0 0 0 0 1 11
12 22.0 2570 19.7 19.2 19.7 20.0 0 0 0 0 0 0 0 0 0 0 0 12
13 21.8 2669 22.0 19.7 19.2 19.7 1 0 0 0 0 0 0 0 0 0 0 13
14 22.8 2450 21.8 22.0 19.7 19.2 0 1 0 0 0 0 0 0 0 0 0 14
15 21.0 2842 22.8 21.8 22.0 19.7 0 0 1 0 0 0 0 0 0 0 0 15
16 25.0 3440 21.0 22.8 21.8 22.0 0 0 0 1 0 0 0 0 0 0 0 16
17 23.3 2678 25.0 21.0 22.8 21.8 0 0 0 0 1 0 0 0 0 0 0 17
18 25.0 2981 23.3 25.0 21.0 22.8 0 0 0 0 0 1 0 0 0 0 0 18
19 26.8 2260 25.0 23.3 25.0 21.0 0 0 0 0 0 0 1 0 0 0 0 19
20 25.3 2844 26.8 25.0 23.3 25.0 0 0 0 0 0 0 0 1 0 0 0 20
21 26.5 2546 25.3 26.8 25.0 23.3 0 0 0 0 0 0 0 0 1 0 0 21
22 27.8 2456 26.5 25.3 26.8 25.0 0 0 0 0 0 0 0 0 0 1 0 22
23 22.0 2295 27.8 26.5 25.3 26.8 0 0 0 0 0 0 0 0 0 0 1 23
24 22.3 2379 22.0 27.8 26.5 25.3 0 0 0 0 0 0 0 0 0 0 0 24
25 28.0 2479 22.3 22.0 27.8 26.5 1 0 0 0 0 0 0 0 0 0 0 25
26 25.0 2057 28.0 22.3 22.0 27.8 0 1 0 0 0 0 0 0 0 0 0 26
27 27.3 2280 25.0 28.0 22.3 22.0 0 0 1 0 0 0 0 0 0 0 0 27
28 25.8 2351 27.3 25.0 28.0 22.3 0 0 0 1 0 0 0 0 0 0 0 28
29 27.3 2276 25.8 27.3 25.0 28.0 0 0 0 0 1 0 0 0 0 0 0 29
30 23.5 2548 27.3 25.8 27.3 25.0 0 0 0 0 0 1 0 0 0 0 0 30
31 24.5 2311 23.5 27.3 25.8 27.3 0 0 0 0 0 0 1 0 0 0 0 31
32 18.0 2201 24.5 23.5 27.3 25.8 0 0 0 0 0 0 0 1 0 0 0 32
33 21.3 2725 18.0 24.5 23.5 27.3 0 0 0 0 0 0 0 0 1 0 0 33
34 21.8 2408 21.3 18.0 24.5 23.5 0 0 0 0 0 0 0 0 0 1 0 34
35 20.5 2139 21.8 21.3 18.0 24.5 0 0 0 0 0 0 0 0 0 0 1 35
36 22.3 1898 20.5 21.8 21.3 18.0 0 0 0 0 0 0 0 0 0 0 0 36
37 18.7 2537 22.3 20.5 21.8 21.3 1 0 0 0 0 0 0 0 0 0 0 37
38 22.3 2068 18.7 22.3 20.5 21.8 0 1 0 0 0 0 0 0 0 0 0 38
39 17.7 2063 22.3 18.7 22.3 20.5 0 0 1 0 0 0 0 0 0 0 0 39
40 19.7 2520 17.7 22.3 18.7 22.3 0 0 0 1 0 0 0 0 0 0 0 40
41 20.5 2434 19.7 17.7 22.3 18.7 0 0 0 0 1 0 0 0 0 0 0 41
42 18.5 2190 20.5 19.7 17.7 22.3 0 0 0 0 0 1 0 0 0 0 0 42
43 10.0 2794 18.5 20.5 19.7 17.7 0 0 0 0 0 0 1 0 0 0 0 43
44 14.2 2070 10.0 18.5 20.5 19.7 0 0 0 0 0 0 0 1 0 0 0 44
45 15.5 2615 14.2 10.0 18.5 20.5 0 0 0 0 0 0 0 0 1 0 0 45
46 16.5 2265 15.5 14.2 10.0 18.5 0 0 0 0 0 0 0 0 0 1 0 46
47 20.5 2139 16.5 15.5 14.2 10.0 0 0 0 0 0 0 0 0 0 0 1 47
48 15.7 2428 20.5 16.5 15.5 14.2 0 0 0 0 0 0 0 0 0 0 0 48
49 11.7 2137 15.7 20.5 16.5 15.5 1 0 0 0 0 0 0 0 0 0 0 49
50 7.5 1823 11.7 15.7 20.5 16.5 0 1 0 0 0 0 0 0 0 0 0 50
51 3.5 2063 7.5 11.7 15.7 20.5 0 0 1 0 0 0 0 0 0 0 0 51
52 4.5 1806 3.5 7.5 11.7 15.7 0 0 0 1 0 0 0 0 0 0 0 52
53 2.2 1758 4.5 3.5 7.5 11.7 0 0 0 0 1 0 0 0 0 0 0 53
54 5.0 2243 2.2 4.5 3.5 7.5 0 0 0 0 0 1 0 0 0 0 0 54
55 2.3 1993 5.0 2.2 4.5 3.5 0 0 0 0 0 0 1 0 0 0 0 55
56 6.1 1932 2.3 5.0 2.2 4.5 0 0 0 0 0 0 0 1 0 0 0 56
57 3.3 2465 6.1 2.3 5.0 2.2 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 Y4
1.8542278 0.0006048 0.5744850 0.3918863 -0.0635822 -0.0054746
M1 M2 M3 M4 M5 M6
-0.3017605 -0.4171006 -1.9987818 0.3516046 0.3162734 -0.6063672
M7 M8 M9 M10 M11 t
-1.5354831 -0.3885013 0.5600185 1.3251348 -0.1559111 -0.0496907
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-7.18410 -1.51021 -0.01465 1.41658 6.67058
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1.8542278 5.0740531 0.365 0.71676
X 0.0006048 0.0017560 0.344 0.73237
Y1 0.5744850 0.1640869 3.501 0.00118 **
Y2 0.3918863 0.1897302 2.065 0.04557 *
Y3 -0.0635822 0.1929700 -0.329 0.74355
Y4 -0.0054746 0.1673520 -0.033 0.97407
M1 -0.3017605 2.0620446 -0.146 0.88441
M2 -0.4171006 2.1002739 -0.199 0.84361
M3 -1.9987818 2.0431679 -0.978 0.33397
M4 0.3516046 2.1102332 0.167 0.86853
M5 0.3162734 2.1127328 0.150 0.88177
M6 -0.6063672 2.1276731 -0.285 0.77716
M7 -1.5354831 2.0482913 -0.750 0.45797
M8 -0.3885013 2.0799452 -0.187 0.85280
M9 0.5600185 2.2119551 0.253 0.80146
M10 1.3251348 2.2139383 0.599 0.55294
M11 -0.1559111 2.1724501 -0.072 0.94315
t -0.0496907 0.0346648 -1.433 0.15970
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 3.009 on 39 degrees of freedom
Multiple R-squared: 0.8706, Adjusted R-squared: 0.8142
F-statistic: 15.43 on 17 and 39 DF, p-value: 2.585e-12
> 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,] 0.010573638 0.021147275 0.9894264
[2,] 0.003011653 0.006023307 0.9969883
[3,] 0.011626517 0.023253034 0.9883735
[4,] 0.035969433 0.071938866 0.9640306
[5,] 0.064553861 0.129107723 0.9354461
[6,] 0.031582907 0.063165813 0.9684171
[7,] 0.061010910 0.122021819 0.9389891
[8,] 0.054006583 0.108013167 0.9459934
[9,] 0.027056780 0.054113560 0.9729432
[10,] 0.028747107 0.057494213 0.9712529
[11,] 0.037370218 0.074740436 0.9626298
[12,] 0.152253198 0.304506395 0.8477468
[13,] 0.086878841 0.173757682 0.9131212
[14,] 0.062856831 0.125713661 0.9371432
[15,] 0.128070572 0.256141144 0.8719294
[16,] 0.068592549 0.137185098 0.9314075
> postscript(file="/var/www/html/rcomp/tmp/1tkij1258727926.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2b1xy1258727926.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/33sf51258727926.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4w80y1258727926.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5sf931258727926.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
-0.40001251 -0.53185917 -0.72019936 -2.02834219 -1.09351730 -1.48130349
7 8 9 10 11 12
0.91975970 -0.13632329 -1.95219421 -2.68457886 -0.35875608 1.70814702
13 14 15 16 17 18
0.24902826 0.78912836 0.03627691 2.01595672 -0.66820093 1.12097381
19 20 21 22 23 24
4.26991717 -0.46706376 0.26946066 0.93067158 -4.54382781 -1.51020608
25 26 27 28 29 30
6.67058380 0.33706098 3.61058167 -0.01465239 1.41657920 -1.71968524
31 32 33 34 35 36
1.91489714 -4.61401888 0.57908863 1.24963189 -0.34521026 2.21945624
37 38 39 40 41 42
-1.89034024 3.44118524 -0.07444315 0.36125400 2.16118529 -0.23503605
43 44 45 46 47 48
-7.18410244 2.08521086 2.95216289 0.50427539 5.24779415 -2.41739718
49 50 51 52 53 54
-4.62925931 -4.03551540 -2.85221606 -0.33421614 -1.81604627 2.31505097
55 56 57
0.07952844 3.13219507 -1.84851797
> postscript(file="/var/www/html/rcomp/tmp/6gbfn1258727926.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 -0.40001251 NA
1 -0.53185917 -0.40001251
2 -0.72019936 -0.53185917
3 -2.02834219 -0.72019936
4 -1.09351730 -2.02834219
5 -1.48130349 -1.09351730
6 0.91975970 -1.48130349
7 -0.13632329 0.91975970
8 -1.95219421 -0.13632329
9 -2.68457886 -1.95219421
10 -0.35875608 -2.68457886
11 1.70814702 -0.35875608
12 0.24902826 1.70814702
13 0.78912836 0.24902826
14 0.03627691 0.78912836
15 2.01595672 0.03627691
16 -0.66820093 2.01595672
17 1.12097381 -0.66820093
18 4.26991717 1.12097381
19 -0.46706376 4.26991717
20 0.26946066 -0.46706376
21 0.93067158 0.26946066
22 -4.54382781 0.93067158
23 -1.51020608 -4.54382781
24 6.67058380 -1.51020608
25 0.33706098 6.67058380
26 3.61058167 0.33706098
27 -0.01465239 3.61058167
28 1.41657920 -0.01465239
29 -1.71968524 1.41657920
30 1.91489714 -1.71968524
31 -4.61401888 1.91489714
32 0.57908863 -4.61401888
33 1.24963189 0.57908863
34 -0.34521026 1.24963189
35 2.21945624 -0.34521026
36 -1.89034024 2.21945624
37 3.44118524 -1.89034024
38 -0.07444315 3.44118524
39 0.36125400 -0.07444315
40 2.16118529 0.36125400
41 -0.23503605 2.16118529
42 -7.18410244 -0.23503605
43 2.08521086 -7.18410244
44 2.95216289 2.08521086
45 0.50427539 2.95216289
46 5.24779415 0.50427539
47 -2.41739718 5.24779415
48 -4.62925931 -2.41739718
49 -4.03551540 -4.62925931
50 -2.85221606 -4.03551540
51 -0.33421614 -2.85221606
52 -1.81604627 -0.33421614
53 2.31505097 -1.81604627
54 0.07952844 2.31505097
55 3.13219507 0.07952844
56 -1.84851797 3.13219507
57 NA -1.84851797
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -0.53185917 -0.40001251
[2,] -0.72019936 -0.53185917
[3,] -2.02834219 -0.72019936
[4,] -1.09351730 -2.02834219
[5,] -1.48130349 -1.09351730
[6,] 0.91975970 -1.48130349
[7,] -0.13632329 0.91975970
[8,] -1.95219421 -0.13632329
[9,] -2.68457886 -1.95219421
[10,] -0.35875608 -2.68457886
[11,] 1.70814702 -0.35875608
[12,] 0.24902826 1.70814702
[13,] 0.78912836 0.24902826
[14,] 0.03627691 0.78912836
[15,] 2.01595672 0.03627691
[16,] -0.66820093 2.01595672
[17,] 1.12097381 -0.66820093
[18,] 4.26991717 1.12097381
[19,] -0.46706376 4.26991717
[20,] 0.26946066 -0.46706376
[21,] 0.93067158 0.26946066
[22,] -4.54382781 0.93067158
[23,] -1.51020608 -4.54382781
[24,] 6.67058380 -1.51020608
[25,] 0.33706098 6.67058380
[26,] 3.61058167 0.33706098
[27,] -0.01465239 3.61058167
[28,] 1.41657920 -0.01465239
[29,] -1.71968524 1.41657920
[30,] 1.91489714 -1.71968524
[31,] -4.61401888 1.91489714
[32,] 0.57908863 -4.61401888
[33,] 1.24963189 0.57908863
[34,] -0.34521026 1.24963189
[35,] 2.21945624 -0.34521026
[36,] -1.89034024 2.21945624
[37,] 3.44118524 -1.89034024
[38,] -0.07444315 3.44118524
[39,] 0.36125400 -0.07444315
[40,] 2.16118529 0.36125400
[41,] -0.23503605 2.16118529
[42,] -7.18410244 -0.23503605
[43,] 2.08521086 -7.18410244
[44,] 2.95216289 2.08521086
[45,] 0.50427539 2.95216289
[46,] 5.24779415 0.50427539
[47,] -2.41739718 5.24779415
[48,] -4.62925931 -2.41739718
[49,] -4.03551540 -4.62925931
[50,] -2.85221606 -4.03551540
[51,] -0.33421614 -2.85221606
[52,] -1.81604627 -0.33421614
[53,] 2.31505097 -1.81604627
[54,] 0.07952844 2.31505097
[55,] 3.13219507 0.07952844
[56,] -1.84851797 3.13219507
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -0.53185917 -0.40001251
2 -0.72019936 -0.53185917
3 -2.02834219 -0.72019936
4 -1.09351730 -2.02834219
5 -1.48130349 -1.09351730
6 0.91975970 -1.48130349
7 -0.13632329 0.91975970
8 -1.95219421 -0.13632329
9 -2.68457886 -1.95219421
10 -0.35875608 -2.68457886
11 1.70814702 -0.35875608
12 0.24902826 1.70814702
13 0.78912836 0.24902826
14 0.03627691 0.78912836
15 2.01595672 0.03627691
16 -0.66820093 2.01595672
17 1.12097381 -0.66820093
18 4.26991717 1.12097381
19 -0.46706376 4.26991717
20 0.26946066 -0.46706376
21 0.93067158 0.26946066
22 -4.54382781 0.93067158
23 -1.51020608 -4.54382781
24 6.67058380 -1.51020608
25 0.33706098 6.67058380
26 3.61058167 0.33706098
27 -0.01465239 3.61058167
28 1.41657920 -0.01465239
29 -1.71968524 1.41657920
30 1.91489714 -1.71968524
31 -4.61401888 1.91489714
32 0.57908863 -4.61401888
33 1.24963189 0.57908863
34 -0.34521026 1.24963189
35 2.21945624 -0.34521026
36 -1.89034024 2.21945624
37 3.44118524 -1.89034024
38 -0.07444315 3.44118524
39 0.36125400 -0.07444315
40 2.16118529 0.36125400
41 -0.23503605 2.16118529
42 -7.18410244 -0.23503605
43 2.08521086 -7.18410244
44 2.95216289 2.08521086
45 0.50427539 2.95216289
46 5.24779415 0.50427539
47 -2.41739718 5.24779415
48 -4.62925931 -2.41739718
49 -4.03551540 -4.62925931
50 -2.85221606 -4.03551540
51 -0.33421614 -2.85221606
52 -1.81604627 -0.33421614
53 2.31505097 -1.81604627
54 0.07952844 2.31505097
55 3.13219507 0.07952844
56 -1.84851797 3.13219507
> 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/76ila1258727926.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8s7hn1258727926.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9vg9a1258727926.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10hmo41258727926.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11yxqn1258727926.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/12p87c1258727926.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/130aw81258727926.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/1411fs1258727926.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/1532sm1258727926.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/16omzz1258727926.tab")
+ }
>
> system("convert tmp/1tkij1258727926.ps tmp/1tkij1258727926.png")
> system("convert tmp/2b1xy1258727926.ps tmp/2b1xy1258727926.png")
> system("convert tmp/33sf51258727926.ps tmp/33sf51258727926.png")
> system("convert tmp/4w80y1258727926.ps tmp/4w80y1258727926.png")
> system("convert tmp/5sf931258727926.ps tmp/5sf931258727926.png")
> system("convert tmp/6gbfn1258727926.ps tmp/6gbfn1258727926.png")
> system("convert tmp/76ila1258727926.ps tmp/76ila1258727926.png")
> system("convert tmp/8s7hn1258727926.ps tmp/8s7hn1258727926.png")
> system("convert tmp/9vg9a1258727926.ps tmp/9vg9a1258727926.png")
> system("convert tmp/10hmo41258727926.ps tmp/10hmo41258727926.png")
>
>
> proc.time()
user system elapsed
2.416 1.606 3.632