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(7.5
+ ,0
+ ,8.3
+ ,8.8
+ ,8.9
+ ,7.2
+ ,0
+ ,7.5
+ ,8.3
+ ,8.8
+ ,7.4
+ ,0
+ ,7.2
+ ,7.5
+ ,8.3
+ ,8.8
+ ,0
+ ,7.4
+ ,7.2
+ ,7.5
+ ,9.3
+ ,0
+ ,8.8
+ ,7.4
+ ,7.2
+ ,9.3
+ ,0
+ ,9.3
+ ,8.8
+ ,7.4
+ ,8.7
+ ,0
+ ,9.3
+ ,9.3
+ ,8.8
+ ,8.2
+ ,0
+ ,8.7
+ ,9.3
+ ,9.3
+ ,8.3
+ ,0
+ ,8.2
+ ,8.7
+ ,9.3
+ ,8.5
+ ,0
+ ,8.3
+ ,8.2
+ ,8.7
+ ,8.6
+ ,0
+ ,8.5
+ ,8.3
+ ,8.2
+ ,8.5
+ ,0
+ ,8.6
+ ,8.5
+ ,8.3
+ ,8.2
+ ,0
+ ,8.5
+ ,8.6
+ ,8.5
+ ,8.1
+ ,0
+ ,8.2
+ ,8.5
+ ,8.6
+ ,7.9
+ ,0
+ ,8.1
+ ,8.2
+ ,8.5
+ ,8.6
+ ,0
+ ,7.9
+ ,8.1
+ ,8.2
+ ,8.7
+ ,0
+ ,8.6
+ ,7.9
+ ,8.1
+ ,8.7
+ ,0
+ ,8.7
+ ,8.6
+ ,7.9
+ ,8.5
+ ,0
+ ,8.7
+ ,8.7
+ ,8.6
+ ,8.4
+ ,0
+ ,8.5
+ ,8.7
+ ,8.7
+ ,8.5
+ ,0
+ ,8.4
+ ,8.5
+ ,8.7
+ ,8.7
+ ,0
+ ,8.5
+ ,8.4
+ ,8.5
+ ,8.7
+ ,0
+ ,8.7
+ ,8.5
+ ,8.4
+ ,8.6
+ ,0
+ ,8.7
+ ,8.7
+ ,8.5
+ ,8.5
+ ,0
+ ,8.6
+ ,8.7
+ ,8.7
+ ,8.3
+ ,0
+ ,8.5
+ ,8.6
+ ,8.7
+ ,8
+ ,0
+ ,8.3
+ ,8.5
+ ,8.6
+ ,8.2
+ ,0
+ ,8
+ ,8.3
+ ,8.5
+ ,8.1
+ ,0
+ ,8.2
+ ,8
+ ,8.3
+ ,8.1
+ ,0
+ ,8.1
+ ,8.2
+ ,8
+ ,8
+ ,0
+ ,8.1
+ ,8.1
+ ,8.2
+ ,7.9
+ ,0
+ ,8
+ ,8.1
+ ,8.1
+ ,7.9
+ ,0
+ ,7.9
+ ,8
+ ,8.1
+ ,8
+ ,0
+ ,7.9
+ ,7.9
+ ,8
+ ,8
+ ,0
+ ,8
+ ,7.9
+ ,7.9
+ ,7.9
+ ,0
+ ,8
+ ,8
+ ,7.9
+ ,8
+ ,0
+ ,7.9
+ ,8
+ ,8
+ ,7.7
+ ,0
+ ,8
+ ,7.9
+ ,8
+ ,7.2
+ ,0
+ ,7.7
+ ,8
+ ,7.9
+ ,7.5
+ ,0
+ ,7.2
+ ,7.7
+ ,8
+ ,7.3
+ ,0
+ ,7.5
+ ,7.2
+ ,7.7
+ ,7
+ ,0
+ ,7.3
+ ,7.5
+ ,7.2
+ ,7
+ ,0
+ ,7
+ ,7.3
+ ,7.5
+ ,7
+ ,0
+ ,7
+ ,7
+ ,7.3
+ ,7.2
+ ,0
+ ,7
+ ,7
+ ,7
+ ,7.3
+ ,1
+ ,7.2
+ ,7
+ ,7
+ ,7.1
+ ,1
+ ,7.3
+ ,7.2
+ ,7
+ ,6.8
+ ,1
+ ,7.1
+ ,7.3
+ ,7.2
+ ,6.4
+ ,1
+ ,6.8
+ ,7.1
+ ,7.3
+ ,6.1
+ ,1
+ ,6.4
+ ,6.8
+ ,7.1
+ ,6.5
+ ,1
+ ,6.1
+ ,6.4
+ ,6.8
+ ,7.7
+ ,1
+ ,6.5
+ ,6.1
+ ,6.4
+ ,7.9
+ ,1
+ ,7.7
+ ,6.5
+ ,6.1
+ ,7.5
+ ,1
+ ,7.9
+ ,7.7
+ ,6.5
+ ,6.9
+ ,1
+ ,7.5
+ ,7.9
+ ,7.7
+ ,6.6
+ ,1
+ ,6.9
+ ,7.5
+ ,7.9
+ ,6.9
+ ,1
+ ,6.6
+ ,6.9
+ ,7.5)
+ ,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 7.5 0 8.3 8.8 8.9 1 0 0 0 0 0 0 0 0 0 0 1
2 7.2 0 7.5 8.3 8.8 0 1 0 0 0 0 0 0 0 0 0 2
3 7.4 0 7.2 7.5 8.3 0 0 1 0 0 0 0 0 0 0 0 3
4 8.8 0 7.4 7.2 7.5 0 0 0 1 0 0 0 0 0 0 0 4
5 9.3 0 8.8 7.4 7.2 0 0 0 0 1 0 0 0 0 0 0 5
6 9.3 0 9.3 8.8 7.4 0 0 0 0 0 1 0 0 0 0 0 6
7 8.7 0 9.3 9.3 8.8 0 0 0 0 0 0 1 0 0 0 0 7
8 8.2 0 8.7 9.3 9.3 0 0 0 0 0 0 0 1 0 0 0 8
9 8.3 0 8.2 8.7 9.3 0 0 0 0 0 0 0 0 1 0 0 9
10 8.5 0 8.3 8.2 8.7 0 0 0 0 0 0 0 0 0 1 0 10
11 8.6 0 8.5 8.3 8.2 0 0 0 0 0 0 0 0 0 0 1 11
12 8.5 0 8.6 8.5 8.3 0 0 0 0 0 0 0 0 0 0 0 12
13 8.2 0 8.5 8.6 8.5 1 0 0 0 0 0 0 0 0 0 0 13
14 8.1 0 8.2 8.5 8.6 0 1 0 0 0 0 0 0 0 0 0 14
15 7.9 0 8.1 8.2 8.5 0 0 1 0 0 0 0 0 0 0 0 15
16 8.6 0 7.9 8.1 8.2 0 0 0 1 0 0 0 0 0 0 0 16
17 8.7 0 8.6 7.9 8.1 0 0 0 0 1 0 0 0 0 0 0 17
18 8.7 0 8.7 8.6 7.9 0 0 0 0 0 1 0 0 0 0 0 18
19 8.5 0 8.7 8.7 8.6 0 0 0 0 0 0 1 0 0 0 0 19
20 8.4 0 8.5 8.7 8.7 0 0 0 0 0 0 0 1 0 0 0 20
21 8.5 0 8.4 8.5 8.7 0 0 0 0 0 0 0 0 1 0 0 21
22 8.7 0 8.5 8.4 8.5 0 0 0 0 0 0 0 0 0 1 0 22
23 8.7 0 8.7 8.5 8.4 0 0 0 0 0 0 0 0 0 0 1 23
24 8.6 0 8.7 8.7 8.5 0 0 0 0 0 0 0 0 0 0 0 24
25 8.5 0 8.6 8.7 8.7 1 0 0 0 0 0 0 0 0 0 0 25
26 8.3 0 8.5 8.6 8.7 0 1 0 0 0 0 0 0 0 0 0 26
27 8.0 0 8.3 8.5 8.6 0 0 1 0 0 0 0 0 0 0 0 27
28 8.2 0 8.0 8.3 8.5 0 0 0 1 0 0 0 0 0 0 0 28
29 8.1 0 8.2 8.0 8.3 0 0 0 0 1 0 0 0 0 0 0 29
30 8.1 0 8.1 8.2 8.0 0 0 0 0 0 1 0 0 0 0 0 30
31 8.0 0 8.1 8.1 8.2 0 0 0 0 0 0 1 0 0 0 0 31
32 7.9 0 8.0 8.1 8.1 0 0 0 0 0 0 0 1 0 0 0 32
33 7.9 0 7.9 8.0 8.1 0 0 0 0 0 0 0 0 1 0 0 33
34 8.0 0 7.9 7.9 8.0 0 0 0 0 0 0 0 0 0 1 0 34
35 8.0 0 8.0 7.9 7.9 0 0 0 0 0 0 0 0 0 0 1 35
36 7.9 0 8.0 8.0 7.9 0 0 0 0 0 0 0 0 0 0 0 36
37 8.0 0 7.9 8.0 8.0 1 0 0 0 0 0 0 0 0 0 0 37
38 7.7 0 8.0 7.9 8.0 0 1 0 0 0 0 0 0 0 0 0 38
39 7.2 0 7.7 8.0 7.9 0 0 1 0 0 0 0 0 0 0 0 39
40 7.5 0 7.2 7.7 8.0 0 0 0 1 0 0 0 0 0 0 0 40
41 7.3 0 7.5 7.2 7.7 0 0 0 0 1 0 0 0 0 0 0 41
42 7.0 0 7.3 7.5 7.2 0 0 0 0 0 1 0 0 0 0 0 42
43 7.0 0 7.0 7.3 7.5 0 0 0 0 0 0 1 0 0 0 0 43
44 7.0 0 7.0 7.0 7.3 0 0 0 0 0 0 0 1 0 0 0 44
45 7.2 0 7.0 7.0 7.0 0 0 0 0 0 0 0 0 1 0 0 45
46 7.3 1 7.2 7.0 7.0 0 0 0 0 0 0 0 0 0 1 0 46
47 7.1 1 7.3 7.2 7.0 0 0 0 0 0 0 0 0 0 0 1 47
48 6.8 1 7.1 7.3 7.2 0 0 0 0 0 0 0 0 0 0 0 48
49 6.4 1 6.8 7.1 7.3 1 0 0 0 0 0 0 0 0 0 0 49
50 6.1 1 6.4 6.8 7.1 0 1 0 0 0 0 0 0 0 0 0 50
51 6.5 1 6.1 6.4 6.8 0 0 1 0 0 0 0 0 0 0 0 51
52 7.7 1 6.5 6.1 6.4 0 0 0 1 0 0 0 0 0 0 0 52
53 7.9 1 7.7 6.5 6.1 0 0 0 0 1 0 0 0 0 0 0 53
54 7.5 1 7.9 7.7 6.5 0 0 0 0 0 1 0 0 0 0 0 54
55 6.9 1 7.5 7.9 7.7 0 0 0 0 0 0 1 0 0 0 0 55
56 6.6 1 6.9 7.5 7.9 0 0 0 0 0 0 0 1 0 0 0 56
57 6.9 1 6.6 6.9 7.5 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
1.565143 -0.023576 1.687194 -1.293433 0.427683 -0.107428
M2 M3 M4 M5 M6 M7
-0.102812 -0.065920 0.652842 -0.524351 0.190058 -0.063526
M8 M9 M10 M11 t
0.024689 0.179879 0.018655 -0.049332 -0.005905
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-0.379694 -0.082749 0.003610 0.084796 0.403354
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1.565143 0.697048 2.245 0.03034 *
X -0.023576 0.092540 -0.255 0.80021
Y1 1.687194 0.143836 11.730 1.60e-14 ***
Y2 -1.293433 0.225728 -5.730 1.13e-06 ***
Y3 0.427683 0.148415 2.882 0.00633 **
M1 -0.107428 0.117560 -0.914 0.36629
M2 -0.102812 0.121311 -0.848 0.40175
M3 -0.065920 0.124228 -0.531 0.59860
M4 0.652842 0.124990 5.223 5.80e-06 ***
M5 -0.524351 0.159282 -3.292 0.00209 **
M6 0.190058 0.139563 1.362 0.18088
M7 -0.063526 0.116041 -0.547 0.58712
M8 0.024689 0.119373 0.207 0.83720
M9 0.179879 0.123432 1.457 0.15284
M10 0.018655 0.131590 0.142 0.88798
M11 -0.049332 0.123996 -0.398 0.69286
t -0.005905 0.002615 -2.258 0.02946 *
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.1719 on 40 degrees of freedom
Multiple R-squared: 0.9613, Adjusted R-squared: 0.9459
F-statistic: 62.15 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,] 0.34291972 0.68583943 0.6570803
[2,] 0.27012987 0.54025974 0.7298701
[3,] 0.28629304 0.57258608 0.7137070
[4,] 0.17298763 0.34597526 0.8270124
[5,] 0.11621457 0.23242913 0.8837854
[6,] 0.16087762 0.32175524 0.8391224
[7,] 0.16786724 0.33573449 0.8321328
[8,] 0.11217592 0.22435185 0.8878241
[9,] 0.29431504 0.58863008 0.7056850
[10,] 0.24840462 0.49680923 0.7515954
[11,] 0.22058318 0.44116635 0.7794168
[12,] 0.19167440 0.38334879 0.8083256
[13,] 0.19938612 0.39877224 0.8006139
[14,] 0.15366170 0.30732339 0.8463383
[15,] 0.10599399 0.21198799 0.8940060
[16,] 0.06573203 0.13146407 0.9342680
[17,] 0.03561538 0.07123076 0.9643846
[18,] 0.45226245 0.90452489 0.5477376
> postscript(file="/var/www/html/rcomp/tmp/1usrh1260369383.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/245ba1260369383.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/36eyd1260369383.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/49zaf1260369383.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/58p701260369383.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
-0.379694191 0.067402636 -0.078330748 0.225490685 -0.066491289 0.106676725
7 8 9 10 11 12
-0.185874724 0.030290689 0.048543375 -0.143153085 0.036484331 -0.059743280
13 14 15 16 17 18
-0.033884507 0.201451744 -0.206077426 0.117466440 0.003610467 0.117326513
19 20 21 22 23 24
0.006780360 0.119141548 -0.020110255 0.134493019 0.043057062 0.115548851
25 26 27 28 29 30
0.212064347 0.052730143 -0.027393075 -0.250009772 0.193156317 0.040363120
31 32 33 34 35 36
-0.015027870 0.014150605 -0.095757921 0.084796409 0.032736574 0.018653430
37 38 39 40 41 42
0.357937268 -0.238835733 -0.091552999 -0.091610861 -0.133082381 -0.202276216
43 44 45 46 47 48
0.176379371 -0.208423039 -0.029402658 -0.076136343 -0.112277968 -0.074459001
49 50 51 52 53 54
-0.156422917 -0.082748790 0.403354247 -0.001336491 0.002806887 -0.062090142
55 56 57
0.017742862 0.044840197 0.096727458
> postscript(file="/var/www/html/rcomp/tmp/6199v1260369383.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 -0.379694191 NA
1 0.067402636 -0.379694191
2 -0.078330748 0.067402636
3 0.225490685 -0.078330748
4 -0.066491289 0.225490685
5 0.106676725 -0.066491289
6 -0.185874724 0.106676725
7 0.030290689 -0.185874724
8 0.048543375 0.030290689
9 -0.143153085 0.048543375
10 0.036484331 -0.143153085
11 -0.059743280 0.036484331
12 -0.033884507 -0.059743280
13 0.201451744 -0.033884507
14 -0.206077426 0.201451744
15 0.117466440 -0.206077426
16 0.003610467 0.117466440
17 0.117326513 0.003610467
18 0.006780360 0.117326513
19 0.119141548 0.006780360
20 -0.020110255 0.119141548
21 0.134493019 -0.020110255
22 0.043057062 0.134493019
23 0.115548851 0.043057062
24 0.212064347 0.115548851
25 0.052730143 0.212064347
26 -0.027393075 0.052730143
27 -0.250009772 -0.027393075
28 0.193156317 -0.250009772
29 0.040363120 0.193156317
30 -0.015027870 0.040363120
31 0.014150605 -0.015027870
32 -0.095757921 0.014150605
33 0.084796409 -0.095757921
34 0.032736574 0.084796409
35 0.018653430 0.032736574
36 0.357937268 0.018653430
37 -0.238835733 0.357937268
38 -0.091552999 -0.238835733
39 -0.091610861 -0.091552999
40 -0.133082381 -0.091610861
41 -0.202276216 -0.133082381
42 0.176379371 -0.202276216
43 -0.208423039 0.176379371
44 -0.029402658 -0.208423039
45 -0.076136343 -0.029402658
46 -0.112277968 -0.076136343
47 -0.074459001 -0.112277968
48 -0.156422917 -0.074459001
49 -0.082748790 -0.156422917
50 0.403354247 -0.082748790
51 -0.001336491 0.403354247
52 0.002806887 -0.001336491
53 -0.062090142 0.002806887
54 0.017742862 -0.062090142
55 0.044840197 0.017742862
56 0.096727458 0.044840197
57 NA 0.096727458
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 0.067402636 -0.379694191
[2,] -0.078330748 0.067402636
[3,] 0.225490685 -0.078330748
[4,] -0.066491289 0.225490685
[5,] 0.106676725 -0.066491289
[6,] -0.185874724 0.106676725
[7,] 0.030290689 -0.185874724
[8,] 0.048543375 0.030290689
[9,] -0.143153085 0.048543375
[10,] 0.036484331 -0.143153085
[11,] -0.059743280 0.036484331
[12,] -0.033884507 -0.059743280
[13,] 0.201451744 -0.033884507
[14,] -0.206077426 0.201451744
[15,] 0.117466440 -0.206077426
[16,] 0.003610467 0.117466440
[17,] 0.117326513 0.003610467
[18,] 0.006780360 0.117326513
[19,] 0.119141548 0.006780360
[20,] -0.020110255 0.119141548
[21,] 0.134493019 -0.020110255
[22,] 0.043057062 0.134493019
[23,] 0.115548851 0.043057062
[24,] 0.212064347 0.115548851
[25,] 0.052730143 0.212064347
[26,] -0.027393075 0.052730143
[27,] -0.250009772 -0.027393075
[28,] 0.193156317 -0.250009772
[29,] 0.040363120 0.193156317
[30,] -0.015027870 0.040363120
[31,] 0.014150605 -0.015027870
[32,] -0.095757921 0.014150605
[33,] 0.084796409 -0.095757921
[34,] 0.032736574 0.084796409
[35,] 0.018653430 0.032736574
[36,] 0.357937268 0.018653430
[37,] -0.238835733 0.357937268
[38,] -0.091552999 -0.238835733
[39,] -0.091610861 -0.091552999
[40,] -0.133082381 -0.091610861
[41,] -0.202276216 -0.133082381
[42,] 0.176379371 -0.202276216
[43,] -0.208423039 0.176379371
[44,] -0.029402658 -0.208423039
[45,] -0.076136343 -0.029402658
[46,] -0.112277968 -0.076136343
[47,] -0.074459001 -0.112277968
[48,] -0.156422917 -0.074459001
[49,] -0.082748790 -0.156422917
[50,] 0.403354247 -0.082748790
[51,] -0.001336491 0.403354247
[52,] 0.002806887 -0.001336491
[53,] -0.062090142 0.002806887
[54,] 0.017742862 -0.062090142
[55,] 0.044840197 0.017742862
[56,] 0.096727458 0.044840197
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 0.067402636 -0.379694191
2 -0.078330748 0.067402636
3 0.225490685 -0.078330748
4 -0.066491289 0.225490685
5 0.106676725 -0.066491289
6 -0.185874724 0.106676725
7 0.030290689 -0.185874724
8 0.048543375 0.030290689
9 -0.143153085 0.048543375
10 0.036484331 -0.143153085
11 -0.059743280 0.036484331
12 -0.033884507 -0.059743280
13 0.201451744 -0.033884507
14 -0.206077426 0.201451744
15 0.117466440 -0.206077426
16 0.003610467 0.117466440
17 0.117326513 0.003610467
18 0.006780360 0.117326513
19 0.119141548 0.006780360
20 -0.020110255 0.119141548
21 0.134493019 -0.020110255
22 0.043057062 0.134493019
23 0.115548851 0.043057062
24 0.212064347 0.115548851
25 0.052730143 0.212064347
26 -0.027393075 0.052730143
27 -0.250009772 -0.027393075
28 0.193156317 -0.250009772
29 0.040363120 0.193156317
30 -0.015027870 0.040363120
31 0.014150605 -0.015027870
32 -0.095757921 0.014150605
33 0.084796409 -0.095757921
34 0.032736574 0.084796409
35 0.018653430 0.032736574
36 0.357937268 0.018653430
37 -0.238835733 0.357937268
38 -0.091552999 -0.238835733
39 -0.091610861 -0.091552999
40 -0.133082381 -0.091610861
41 -0.202276216 -0.133082381
42 0.176379371 -0.202276216
43 -0.208423039 0.176379371
44 -0.029402658 -0.208423039
45 -0.076136343 -0.029402658
46 -0.112277968 -0.076136343
47 -0.074459001 -0.112277968
48 -0.156422917 -0.074459001
49 -0.082748790 -0.156422917
50 0.403354247 -0.082748790
51 -0.001336491 0.403354247
52 0.002806887 -0.001336491
53 -0.062090142 0.002806887
54 0.017742862 -0.062090142
55 0.044840197 0.017742862
56 0.096727458 0.044840197
> 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/77izi1260369383.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8vrxl1260369383.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9q9u81260369383.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10ivhz1260369383.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11b8751260369383.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/122pda1260369383.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/13enpu1260369383.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/14moux1260369383.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/150tfs1260369383.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/16wrqt1260369383.tab")
+ }
>
> system("convert tmp/1usrh1260369383.ps tmp/1usrh1260369383.png")
> system("convert tmp/245ba1260369383.ps tmp/245ba1260369383.png")
> system("convert tmp/36eyd1260369383.ps tmp/36eyd1260369383.png")
> system("convert tmp/49zaf1260369383.ps tmp/49zaf1260369383.png")
> system("convert tmp/58p701260369383.ps tmp/58p701260369383.png")
> system("convert tmp/6199v1260369383.ps tmp/6199v1260369383.png")
> system("convert tmp/77izi1260369383.ps tmp/77izi1260369383.png")
> system("convert tmp/8vrxl1260369383.ps tmp/8vrxl1260369383.png")
> system("convert tmp/9q9u81260369383.ps tmp/9q9u81260369383.png")
> system("convert tmp/10ivhz1260369383.ps tmp/10ivhz1260369383.png")
>
>
> proc.time()
user system elapsed
2.414 1.610 4.964