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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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(8.6
+ ,0
+ ,8.5
+ ,8.3
+ ,8.2
+ ,8.7
+ ,8.5
+ ,0
+ ,8.6
+ ,8.5
+ ,8.3
+ ,8.2
+ ,8.2
+ ,0
+ ,8.5
+ ,8.6
+ ,8.5
+ ,8.3
+ ,8.1
+ ,0
+ ,8.2
+ ,8.5
+ ,8.6
+ ,8.5
+ ,7.9
+ ,0
+ ,8.1
+ ,8.2
+ ,8.5
+ ,8.6
+ ,8.6
+ ,0
+ ,7.9
+ ,8.1
+ ,8.2
+ ,8.5
+ ,8.7
+ ,0
+ ,8.6
+ ,7.9
+ ,8.1
+ ,8.2
+ ,8.7
+ ,0
+ ,8.7
+ ,8.6
+ ,7.9
+ ,8.1
+ ,8.5
+ ,0
+ ,8.7
+ ,8.7
+ ,8.6
+ ,7.9
+ ,8.4
+ ,0
+ ,8.5
+ ,8.7
+ ,8.7
+ ,8.6
+ ,8.5
+ ,0
+ ,8.4
+ ,8.5
+ ,8.7
+ ,8.7
+ ,8.7
+ ,0
+ ,8.5
+ ,8.4
+ ,8.5
+ ,8.7
+ ,8.7
+ ,0
+ ,8.7
+ ,8.5
+ ,8.4
+ ,8.5
+ ,8.6
+ ,0
+ ,8.7
+ ,8.7
+ ,8.5
+ ,8.4
+ ,8.5
+ ,0
+ ,8.6
+ ,8.7
+ ,8.7
+ ,8.5
+ ,8.3
+ ,0
+ ,8.5
+ ,8.6
+ ,8.7
+ ,8.7
+ ,8
+ ,0
+ ,8.3
+ ,8.5
+ ,8.6
+ ,8.7
+ ,8.2
+ ,0
+ ,8
+ ,8.3
+ ,8.5
+ ,8.6
+ ,8.1
+ ,0
+ ,8.2
+ ,8
+ ,8.3
+ ,8.5
+ ,8.1
+ ,0
+ ,8.1
+ ,8.2
+ ,8
+ ,8.3
+ ,8
+ ,0
+ ,8.1
+ ,8.1
+ ,8.2
+ ,8
+ ,7.9
+ ,0
+ ,8
+ ,8.1
+ ,8.1
+ ,8.2
+ ,7.9
+ ,0
+ ,7.9
+ ,8
+ ,8.1
+ ,8.1
+ ,8
+ ,0
+ ,7.9
+ ,7.9
+ ,8
+ ,8.1
+ ,8
+ ,0
+ ,8
+ ,7.9
+ ,7.9
+ ,8
+ ,7.9
+ ,0
+ ,8
+ ,8
+ ,7.9
+ ,7.9
+ ,8
+ ,0
+ ,7.9
+ ,8
+ ,8
+ ,7.9
+ ,7.7
+ ,0
+ ,8
+ ,7.9
+ ,8
+ ,8
+ ,7.2
+ ,0
+ ,7.7
+ ,8
+ ,7.9
+ ,8
+ ,7.5
+ ,0
+ ,7.2
+ ,7.7
+ ,8
+ ,7.9
+ ,7.3
+ ,0
+ ,7.5
+ ,7.2
+ ,7.7
+ ,8
+ ,7
+ ,0
+ ,7.3
+ ,7.5
+ ,7.2
+ ,7.7
+ ,7
+ ,0
+ ,7
+ ,7.3
+ ,7.5
+ ,7.2
+ ,7
+ ,0
+ ,7
+ ,7
+ ,7.3
+ ,7.5
+ ,7.2
+ ,0
+ ,7
+ ,7
+ ,7
+ ,7.3
+ ,7.3
+ ,0
+ ,7.2
+ ,7
+ ,7
+ ,7
+ ,7.1
+ ,0
+ ,7.3
+ ,7.2
+ ,7
+ ,7
+ ,6.8
+ ,0
+ ,7.1
+ ,7.3
+ ,7.2
+ ,7
+ ,6.4
+ ,0
+ ,6.8
+ ,7.1
+ ,7.3
+ ,7.2
+ ,6.1
+ ,0
+ ,6.4
+ ,6.8
+ ,7.1
+ ,7.3
+ ,6.5
+ ,0
+ ,6.1
+ ,6.4
+ ,6.8
+ ,7.1
+ ,7.7
+ ,0
+ ,6.5
+ ,6.1
+ ,6.4
+ ,6.8
+ ,7.9
+ ,0
+ ,7.7
+ ,6.5
+ ,6.1
+ ,6.4
+ ,7.5
+ ,1
+ ,7.9
+ ,7.7
+ ,6.5
+ ,6.1
+ ,6.9
+ ,1
+ ,7.5
+ ,7.9
+ ,7.7
+ ,6.5
+ ,6.6
+ ,1
+ ,6.9
+ ,7.5
+ ,7.9
+ ,7.7
+ ,6.9
+ ,1
+ ,6.6
+ ,6.9
+ ,7.5
+ ,7.9
+ ,7.7
+ ,1
+ ,6.9
+ ,6.6
+ ,6.9
+ ,7.5
+ ,8
+ ,1
+ ,7.7
+ ,6.9
+ ,6.6
+ ,6.9
+ ,8
+ ,1
+ ,8
+ ,7.7
+ ,6.9
+ ,6.6
+ ,7.7
+ ,1
+ ,8
+ ,8
+ ,7.7
+ ,6.9
+ ,7.3
+ ,1
+ ,7.7
+ ,8
+ ,8
+ ,7.7
+ ,7.4
+ ,1
+ ,7.3
+ ,7.7
+ ,8
+ ,8
+ ,8.1
+ ,1
+ ,7.4
+ ,7.3
+ ,7.7
+ ,8
+ ,8.3
+ ,1
+ ,8.1
+ ,7.4
+ ,7.3
+ ,7.7
+ ,8.2
+ ,1
+ ,8.3
+ ,8.1
+ ,7.4
+ ,7.3)
+ ,dim=c(6
+ ,56)
+ ,dimnames=list(c('Y'
+ ,'X'
+ ,'Y1'
+ ,'Y2'
+ ,'Y3'
+ ,'Y4')
+ ,1:56))
> y <- array(NA,dim=c(6,56),dimnames=list(c('Y','X','Y1','Y2','Y3','Y4'),1:56))
> 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 8.6 0 8.5 8.3 8.2 8.7 1 0 0 0 0 0 0 0 0 0 0 1
2 8.5 0 8.6 8.5 8.3 8.2 0 1 0 0 0 0 0 0 0 0 0 2
3 8.2 0 8.5 8.6 8.5 8.3 0 0 1 0 0 0 0 0 0 0 0 3
4 8.1 0 8.2 8.5 8.6 8.5 0 0 0 1 0 0 0 0 0 0 0 4
5 7.9 0 8.1 8.2 8.5 8.6 0 0 0 0 1 0 0 0 0 0 0 5
6 8.6 0 7.9 8.1 8.2 8.5 0 0 0 0 0 1 0 0 0 0 0 6
7 8.7 0 8.6 7.9 8.1 8.2 0 0 0 0 0 0 1 0 0 0 0 7
8 8.7 0 8.7 8.6 7.9 8.1 0 0 0 0 0 0 0 1 0 0 0 8
9 8.5 0 8.7 8.7 8.6 7.9 0 0 0 0 0 0 0 0 1 0 0 9
10 8.4 0 8.5 8.7 8.7 8.6 0 0 0 0 0 0 0 0 0 1 0 10
11 8.5 0 8.4 8.5 8.7 8.7 0 0 0 0 0 0 0 0 0 0 1 11
12 8.7 0 8.5 8.4 8.5 8.7 0 0 0 0 0 0 0 0 0 0 0 12
13 8.7 0 8.7 8.5 8.4 8.5 1 0 0 0 0 0 0 0 0 0 0 13
14 8.6 0 8.7 8.7 8.5 8.4 0 1 0 0 0 0 0 0 0 0 0 14
15 8.5 0 8.6 8.7 8.7 8.5 0 0 1 0 0 0 0 0 0 0 0 15
16 8.3 0 8.5 8.6 8.7 8.7 0 0 0 1 0 0 0 0 0 0 0 16
17 8.0 0 8.3 8.5 8.6 8.7 0 0 0 0 1 0 0 0 0 0 0 17
18 8.2 0 8.0 8.3 8.5 8.6 0 0 0 0 0 1 0 0 0 0 0 18
19 8.1 0 8.2 8.0 8.3 8.5 0 0 0 0 0 0 1 0 0 0 0 19
20 8.1 0 8.1 8.2 8.0 8.3 0 0 0 0 0 0 0 1 0 0 0 20
21 8.0 0 8.1 8.1 8.2 8.0 0 0 0 0 0 0 0 0 1 0 0 21
22 7.9 0 8.0 8.1 8.1 8.2 0 0 0 0 0 0 0 0 0 1 0 22
23 7.9 0 7.9 8.0 8.1 8.1 0 0 0 0 0 0 0 0 0 0 1 23
24 8.0 0 7.9 7.9 8.0 8.1 0 0 0 0 0 0 0 0 0 0 0 24
25 8.0 0 8.0 7.9 7.9 8.0 1 0 0 0 0 0 0 0 0 0 0 25
26 7.9 0 8.0 8.0 7.9 7.9 0 1 0 0 0 0 0 0 0 0 0 26
27 8.0 0 7.9 8.0 8.0 7.9 0 0 1 0 0 0 0 0 0 0 0 27
28 7.7 0 8.0 7.9 8.0 8.0 0 0 0 1 0 0 0 0 0 0 0 28
29 7.2 0 7.7 8.0 7.9 8.0 0 0 0 0 1 0 0 0 0 0 0 29
30 7.5 0 7.2 7.7 8.0 7.9 0 0 0 0 0 1 0 0 0 0 0 30
31 7.3 0 7.5 7.2 7.7 8.0 0 0 0 0 0 0 1 0 0 0 0 31
32 7.0 0 7.3 7.5 7.2 7.7 0 0 0 0 0 0 0 1 0 0 0 32
33 7.0 0 7.0 7.3 7.5 7.2 0 0 0 0 0 0 0 0 1 0 0 33
34 7.0 0 7.0 7.0 7.3 7.5 0 0 0 0 0 0 0 0 0 1 0 34
35 7.2 0 7.0 7.0 7.0 7.3 0 0 0 0 0 0 0 0 0 0 1 35
36 7.3 0 7.2 7.0 7.0 7.0 0 0 0 0 0 0 0 0 0 0 0 36
37 7.1 0 7.3 7.2 7.0 7.0 1 0 0 0 0 0 0 0 0 0 0 37
38 6.8 0 7.1 7.3 7.2 7.0 0 1 0 0 0 0 0 0 0 0 0 38
39 6.4 0 6.8 7.1 7.3 7.2 0 0 1 0 0 0 0 0 0 0 0 39
40 6.1 0 6.4 6.8 7.1 7.3 0 0 0 1 0 0 0 0 0 0 0 40
41 6.5 0 6.1 6.4 6.8 7.1 0 0 0 0 1 0 0 0 0 0 0 41
42 7.7 0 6.5 6.1 6.4 6.8 0 0 0 0 0 1 0 0 0 0 0 42
43 7.9 0 7.7 6.5 6.1 6.4 0 0 0 0 0 0 1 0 0 0 0 43
44 7.5 1 7.9 7.7 6.5 6.1 0 0 0 0 0 0 0 1 0 0 0 44
45 6.9 1 7.5 7.9 7.7 6.5 0 0 0 0 0 0 0 0 1 0 0 45
46 6.6 1 6.9 7.5 7.9 7.7 0 0 0 0 0 0 0 0 0 1 0 46
47 6.9 1 6.6 6.9 7.5 7.9 0 0 0 0 0 0 0 0 0 0 1 47
48 7.7 1 6.9 6.6 6.9 7.5 0 0 0 0 0 0 0 0 0 0 0 48
49 8.0 1 7.7 6.9 6.6 6.9 1 0 0 0 0 0 0 0 0 0 0 49
50 8.0 1 8.0 7.7 6.9 6.6 0 1 0 0 0 0 0 0 0 0 0 50
51 7.7 1 8.0 8.0 7.7 6.9 0 0 1 0 0 0 0 0 0 0 0 51
52 7.3 1 7.7 8.0 8.0 7.7 0 0 0 1 0 0 0 0 0 0 0 52
53 7.4 1 7.3 7.7 8.0 8.0 0 0 0 0 1 0 0 0 0 0 0 53
54 8.1 1 7.4 7.3 7.7 8.0 0 0 0 0 0 1 0 0 0 0 0 54
55 8.3 1 8.1 7.4 7.3 7.7 0 0 0 0 0 0 1 0 0 0 0 55
56 8.2 1 8.3 8.1 7.4 7.3 0 0 0 0 0 0 0 1 0 0 0 56
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X Y1 Y2 Y3 Y4
0.926377 0.208622 1.513004 -0.848951 -0.133140 0.372616
M1 M2 M3 M4 M5 M6
-0.240677 -0.085391 -0.079821 -0.233164 -0.135517 0.438080
M7 M8 M9 M10 M11 t
-0.500033 -0.147424 0.014903 -0.136869 -0.007119 -0.004938
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-0.23531 -0.08382 -0.00655 0.08945 0.37533
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.926377 0.647107 1.432 0.160442
X 0.208622 0.095114 2.193 0.034469 *
Y1 1.513004 0.145007 10.434 1.03e-12 ***
Y2 -0.848951 0.274528 -3.092 0.003710 **
Y3 -0.133140 0.274445 -0.485 0.630372
Y4 0.372616 0.147810 2.521 0.016022 *
M1 -0.240677 0.111247 -2.163 0.036862 *
M2 -0.085391 0.120872 -0.706 0.484216
M3 -0.079821 0.121187 -0.659 0.514083
M4 -0.233164 0.115391 -2.021 0.050406 .
M5 -0.135517 0.115866 -1.170 0.249445
M6 0.438080 0.109585 3.998 0.000284 ***
M7 -0.500033 0.124218 -4.025 0.000262 ***
M8 -0.147424 0.159982 -0.922 0.362600
M9 0.014903 0.146837 0.101 0.919692
M10 -0.136869 0.120038 -1.140 0.261333
M11 -0.007119 0.115911 -0.061 0.951345
t -0.004938 0.003658 -1.350 0.185060
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.1588 on 38 degrees of freedom
Multiple R-squared: 0.9601, Adjusted R-squared: 0.9422
F-statistic: 53.76 on 17 and 38 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,] 0.65750861 0.6849828 0.3424914
[2,] 0.49502596 0.9900519 0.5049740
[3,] 0.33659312 0.6731862 0.6634069
[4,] 0.21189659 0.4237932 0.7881034
[5,] 0.17075907 0.3415181 0.8292409
[6,] 0.09815574 0.1963115 0.9018443
[7,] 0.34858794 0.6971759 0.6514121
[8,] 0.35730491 0.7146098 0.6426951
[9,] 0.46078386 0.9215677 0.5392161
[10,] 0.40192412 0.8038482 0.5980759
[11,] 0.39899573 0.7979915 0.6010043
[12,] 0.34945321 0.6989064 0.6505468
[13,] 0.48468281 0.9693656 0.5153172
[14,] 0.46119556 0.9223911 0.5388044
[15,] 0.68663315 0.6267337 0.3133669
> postscript(file="/var/www/html/rcomp/tmp/1jcdk1261669863.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2m96c1261669863.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3jey51261669863.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/49bfo1261669863.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5yd4o1261669863.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 = 56
Frequency = 1
1 2 3 4 5 6
-0.045008826 -0.077246063 -0.152315684 0.213761364 -0.232908449 0.113457727
7 8 9 10 11 12
0.026086329 0.132014135 0.027240716 0.139034476 0.058471131 -0.006534125
13 14 15 16 17 18
0.082584036 0.052600963 0.092636262 0.042798535 -0.145519187 -0.206119675
19 20 21 22 23 24
0.090278610 0.098279309 -0.105592808 0.014580304 -0.006564855 -0.006955713
25 26 27 28 29 30
0.111306192 -0.016885980 0.247096854 -0.168080074 -0.235307260 0.048425965
31 32 33 34 35 36
-0.164103412 -0.209273739 0.143697323 -0.092690753 0.017078287 -0.075919568
37 38 39 40 41 42
-0.011815039 -0.048039971 -0.225769647 -0.080862883 0.375329604 0.205312442
43 44 45 46 47 48
-0.018556852 -0.093669175 -0.065345231 -0.060924027 -0.068984563 0.089409406
49 50 51 52 53 54
-0.137066364 0.089571051 0.038352216 -0.007616941 0.238405291 -0.161076459
55 56
0.066295326 0.072649471
> postscript(file="/var/www/html/rcomp/tmp/66pca1261669863.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 = 56
Frequency = 1
lag(myerror, k = 1) myerror
0 -0.045008826 NA
1 -0.077246063 -0.045008826
2 -0.152315684 -0.077246063
3 0.213761364 -0.152315684
4 -0.232908449 0.213761364
5 0.113457727 -0.232908449
6 0.026086329 0.113457727
7 0.132014135 0.026086329
8 0.027240716 0.132014135
9 0.139034476 0.027240716
10 0.058471131 0.139034476
11 -0.006534125 0.058471131
12 0.082584036 -0.006534125
13 0.052600963 0.082584036
14 0.092636262 0.052600963
15 0.042798535 0.092636262
16 -0.145519187 0.042798535
17 -0.206119675 -0.145519187
18 0.090278610 -0.206119675
19 0.098279309 0.090278610
20 -0.105592808 0.098279309
21 0.014580304 -0.105592808
22 -0.006564855 0.014580304
23 -0.006955713 -0.006564855
24 0.111306192 -0.006955713
25 -0.016885980 0.111306192
26 0.247096854 -0.016885980
27 -0.168080074 0.247096854
28 -0.235307260 -0.168080074
29 0.048425965 -0.235307260
30 -0.164103412 0.048425965
31 -0.209273739 -0.164103412
32 0.143697323 -0.209273739
33 -0.092690753 0.143697323
34 0.017078287 -0.092690753
35 -0.075919568 0.017078287
36 -0.011815039 -0.075919568
37 -0.048039971 -0.011815039
38 -0.225769647 -0.048039971
39 -0.080862883 -0.225769647
40 0.375329604 -0.080862883
41 0.205312442 0.375329604
42 -0.018556852 0.205312442
43 -0.093669175 -0.018556852
44 -0.065345231 -0.093669175
45 -0.060924027 -0.065345231
46 -0.068984563 -0.060924027
47 0.089409406 -0.068984563
48 -0.137066364 0.089409406
49 0.089571051 -0.137066364
50 0.038352216 0.089571051
51 -0.007616941 0.038352216
52 0.238405291 -0.007616941
53 -0.161076459 0.238405291
54 0.066295326 -0.161076459
55 0.072649471 0.066295326
56 NA 0.072649471
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -0.077246063 -0.045008826
[2,] -0.152315684 -0.077246063
[3,] 0.213761364 -0.152315684
[4,] -0.232908449 0.213761364
[5,] 0.113457727 -0.232908449
[6,] 0.026086329 0.113457727
[7,] 0.132014135 0.026086329
[8,] 0.027240716 0.132014135
[9,] 0.139034476 0.027240716
[10,] 0.058471131 0.139034476
[11,] -0.006534125 0.058471131
[12,] 0.082584036 -0.006534125
[13,] 0.052600963 0.082584036
[14,] 0.092636262 0.052600963
[15,] 0.042798535 0.092636262
[16,] -0.145519187 0.042798535
[17,] -0.206119675 -0.145519187
[18,] 0.090278610 -0.206119675
[19,] 0.098279309 0.090278610
[20,] -0.105592808 0.098279309
[21,] 0.014580304 -0.105592808
[22,] -0.006564855 0.014580304
[23,] -0.006955713 -0.006564855
[24,] 0.111306192 -0.006955713
[25,] -0.016885980 0.111306192
[26,] 0.247096854 -0.016885980
[27,] -0.168080074 0.247096854
[28,] -0.235307260 -0.168080074
[29,] 0.048425965 -0.235307260
[30,] -0.164103412 0.048425965
[31,] -0.209273739 -0.164103412
[32,] 0.143697323 -0.209273739
[33,] -0.092690753 0.143697323
[34,] 0.017078287 -0.092690753
[35,] -0.075919568 0.017078287
[36,] -0.011815039 -0.075919568
[37,] -0.048039971 -0.011815039
[38,] -0.225769647 -0.048039971
[39,] -0.080862883 -0.225769647
[40,] 0.375329604 -0.080862883
[41,] 0.205312442 0.375329604
[42,] -0.018556852 0.205312442
[43,] -0.093669175 -0.018556852
[44,] -0.065345231 -0.093669175
[45,] -0.060924027 -0.065345231
[46,] -0.068984563 -0.060924027
[47,] 0.089409406 -0.068984563
[48,] -0.137066364 0.089409406
[49,] 0.089571051 -0.137066364
[50,] 0.038352216 0.089571051
[51,] -0.007616941 0.038352216
[52,] 0.238405291 -0.007616941
[53,] -0.161076459 0.238405291
[54,] 0.066295326 -0.161076459
[55,] 0.072649471 0.066295326
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -0.077246063 -0.045008826
2 -0.152315684 -0.077246063
3 0.213761364 -0.152315684
4 -0.232908449 0.213761364
5 0.113457727 -0.232908449
6 0.026086329 0.113457727
7 0.132014135 0.026086329
8 0.027240716 0.132014135
9 0.139034476 0.027240716
10 0.058471131 0.139034476
11 -0.006534125 0.058471131
12 0.082584036 -0.006534125
13 0.052600963 0.082584036
14 0.092636262 0.052600963
15 0.042798535 0.092636262
16 -0.145519187 0.042798535
17 -0.206119675 -0.145519187
18 0.090278610 -0.206119675
19 0.098279309 0.090278610
20 -0.105592808 0.098279309
21 0.014580304 -0.105592808
22 -0.006564855 0.014580304
23 -0.006955713 -0.006564855
24 0.111306192 -0.006955713
25 -0.016885980 0.111306192
26 0.247096854 -0.016885980
27 -0.168080074 0.247096854
28 -0.235307260 -0.168080074
29 0.048425965 -0.235307260
30 -0.164103412 0.048425965
31 -0.209273739 -0.164103412
32 0.143697323 -0.209273739
33 -0.092690753 0.143697323
34 0.017078287 -0.092690753
35 -0.075919568 0.017078287
36 -0.011815039 -0.075919568
37 -0.048039971 -0.011815039
38 -0.225769647 -0.048039971
39 -0.080862883 -0.225769647
40 0.375329604 -0.080862883
41 0.205312442 0.375329604
42 -0.018556852 0.205312442
43 -0.093669175 -0.018556852
44 -0.065345231 -0.093669175
45 -0.060924027 -0.065345231
46 -0.068984563 -0.060924027
47 0.089409406 -0.068984563
48 -0.137066364 0.089409406
49 0.089571051 -0.137066364
50 0.038352216 0.089571051
51 -0.007616941 0.038352216
52 0.238405291 -0.007616941
53 -0.161076459 0.238405291
54 0.066295326 -0.161076459
55 0.072649471 0.066295326
> 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/7i4ju1261669863.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8snp81261669863.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9e9b01261669863.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/1080ue1261669863.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/114tdl1261669863.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/12pyln1261669863.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/13ojtc1261669863.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/14lrlx1261669863.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/15ct141261669863.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/1682h81261669863.tab")
+ }
>
> try(system("convert tmp/1jcdk1261669863.ps tmp/1jcdk1261669863.png",intern=TRUE))
character(0)
> try(system("convert tmp/2m96c1261669863.ps tmp/2m96c1261669863.png",intern=TRUE))
character(0)
> try(system("convert tmp/3jey51261669863.ps tmp/3jey51261669863.png",intern=TRUE))
character(0)
> try(system("convert tmp/49bfo1261669863.ps tmp/49bfo1261669863.png",intern=TRUE))
character(0)
> try(system("convert tmp/5yd4o1261669863.ps tmp/5yd4o1261669863.png",intern=TRUE))
character(0)
> try(system("convert tmp/66pca1261669863.ps tmp/66pca1261669863.png",intern=TRUE))
character(0)
> try(system("convert tmp/7i4ju1261669863.ps tmp/7i4ju1261669863.png",intern=TRUE))
character(0)
> try(system("convert tmp/8snp81261669863.ps tmp/8snp81261669863.png",intern=TRUE))
character(0)
> try(system("convert tmp/9e9b01261669863.ps tmp/9e9b01261669863.png",intern=TRUE))
character(0)
> try(system("convert tmp/1080ue1261669863.ps tmp/1080ue1261669863.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
2.317 1.661 3.818