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(7.60
+ ,101.60
+ ,7.50
+ ,7.70
+ ,8.10
+ ,8.00
+ ,7.80
+ ,94.60
+ ,7.60
+ ,7.50
+ ,7.70
+ ,8.10
+ ,7.80
+ ,95.90
+ ,7.80
+ ,7.60
+ ,7.50
+ ,7.70
+ ,7.80
+ ,104.70
+ ,7.80
+ ,7.80
+ ,7.60
+ ,7.50
+ ,7.50
+ ,102.80
+ ,7.80
+ ,7.80
+ ,7.80
+ ,7.60
+ ,7.50
+ ,98.10
+ ,7.50
+ ,7.80
+ ,7.80
+ ,7.80
+ ,7.10
+ ,113.90
+ ,7.50
+ ,7.50
+ ,7.80
+ ,7.80
+ ,7.50
+ ,80.90
+ ,7.10
+ ,7.50
+ ,7.50
+ ,7.80
+ ,7.50
+ ,95.70
+ ,7.50
+ ,7.10
+ ,7.50
+ ,7.50
+ ,7.60
+ ,113.20
+ ,7.50
+ ,7.50
+ ,7.10
+ ,7.50
+ ,7.70
+ ,105.90
+ ,7.60
+ ,7.50
+ ,7.50
+ ,7.10
+ ,7.70
+ ,108.80
+ ,7.70
+ ,7.60
+ ,7.50
+ ,7.50
+ ,7.90
+ ,102.30
+ ,7.70
+ ,7.70
+ ,7.60
+ ,7.50
+ ,8.10
+ ,99.00
+ ,7.90
+ ,7.70
+ ,7.70
+ ,7.60
+ ,8.20
+ ,100.70
+ ,8.10
+ ,7.90
+ ,7.70
+ ,7.70
+ ,8.20
+ ,115.50
+ ,8.20
+ ,8.10
+ ,7.90
+ ,7.70
+ ,8.20
+ ,100.70
+ ,8.20
+ ,8.20
+ ,8.10
+ ,7.90
+ ,7.90
+ ,109.90
+ ,8.20
+ ,8.20
+ ,8.20
+ ,8.10
+ ,7.30
+ ,114.60
+ ,7.90
+ ,8.20
+ ,8.20
+ ,8.20
+ ,6.90
+ ,85.40
+ ,7.30
+ ,7.90
+ ,8.20
+ ,8.20
+ ,6.60
+ ,100.50
+ ,6.90
+ ,7.30
+ ,7.90
+ ,8.20
+ ,6.70
+ ,114.80
+ ,6.60
+ ,6.90
+ ,7.30
+ ,7.90
+ ,6.90
+ ,116.50
+ ,6.70
+ ,6.60
+ ,6.90
+ ,7.30
+ ,7.00
+ ,112.90
+ ,6.90
+ ,6.70
+ ,6.60
+ ,6.90
+ ,7.10
+ ,102.00
+ ,7.00
+ ,6.90
+ ,6.70
+ ,6.60
+ ,7.20
+ ,106.00
+ ,7.10
+ ,7.00
+ ,6.90
+ ,6.70
+ ,7.10
+ ,105.30
+ ,7.20
+ ,7.10
+ ,7.00
+ ,6.90
+ ,6.90
+ ,118.80
+ ,7.10
+ ,7.20
+ ,7.10
+ ,7.00
+ ,7.00
+ ,106.10
+ ,6.90
+ ,7.10
+ ,7.20
+ ,7.10
+ ,6.80
+ ,109.30
+ ,7.00
+ ,6.90
+ ,7.10
+ ,7.20
+ ,6.40
+ ,117.20
+ ,6.80
+ ,7.00
+ ,6.90
+ ,7.10
+ ,6.70
+ ,92.50
+ ,6.40
+ ,6.80
+ ,7.00
+ ,6.90
+ ,6.60
+ ,104.20
+ ,6.70
+ ,6.40
+ ,6.80
+ ,7.00
+ ,6.40
+ ,112.50
+ ,6.60
+ ,6.70
+ ,6.40
+ ,6.80
+ ,6.30
+ ,122.40
+ ,6.40
+ ,6.60
+ ,6.70
+ ,6.40
+ ,6.20
+ ,113.30
+ ,6.30
+ ,6.40
+ ,6.60
+ ,6.70
+ ,6.50
+ ,100.00
+ ,6.20
+ ,6.30
+ ,6.40
+ ,6.60
+ ,6.80
+ ,110.70
+ ,6.50
+ ,6.20
+ ,6.30
+ ,6.40
+ ,6.80
+ ,112.80
+ ,6.80
+ ,6.50
+ ,6.20
+ ,6.30
+ ,6.40
+ ,109.80
+ ,6.80
+ ,6.80
+ ,6.50
+ ,6.20
+ ,6.10
+ ,117.30
+ ,6.40
+ ,6.80
+ ,6.80
+ ,6.50
+ ,5.80
+ ,109.10
+ ,6.10
+ ,6.40
+ ,6.80
+ ,6.80
+ ,6.10
+ ,115.90
+ ,5.80
+ ,6.10
+ ,6.40
+ ,6.80
+ ,7.20
+ ,96.00
+ ,6.10
+ ,5.80
+ ,6.10
+ ,6.40
+ ,7.30
+ ,99.80
+ ,7.20
+ ,6.10
+ ,5.80
+ ,6.10
+ ,6.90
+ ,116.80
+ ,7.30
+ ,7.20
+ ,6.10
+ ,5.80
+ ,6.10
+ ,115.70
+ ,6.90
+ ,7.30
+ ,7.20
+ ,6.10
+ ,5.80
+ ,99.40
+ ,6.10
+ ,6.90
+ ,7.30
+ ,7.20
+ ,6.20
+ ,94.30
+ ,5.80
+ ,6.10
+ ,6.90
+ ,7.30
+ ,7.10
+ ,91.00
+ ,6.20
+ ,5.80
+ ,6.10
+ ,6.90
+ ,7.70
+ ,93.20
+ ,7.10
+ ,6.20
+ ,5.80
+ ,6.10
+ ,7.90
+ ,103.10
+ ,7.70
+ ,7.10
+ ,6.20
+ ,5.80
+ ,7.70
+ ,94.10
+ ,7.90
+ ,7.70
+ ,7.10
+ ,6.20
+ ,7.40
+ ,91.80
+ ,7.70
+ ,7.90
+ ,7.70
+ ,7.10
+ ,7.50
+ ,102.70
+ ,7.40
+ ,7.70
+ ,7.90
+ ,7.70
+ ,8.00
+ ,82.60
+ ,7.50
+ ,7.40
+ ,7.70
+ ,7.90)
+ ,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 7.6 101.6 7.5 7.7 8.1 8.0 1 0 0 0 0 0 0 0 0 0 0 1
2 7.8 94.6 7.6 7.5 7.7 8.1 0 1 0 0 0 0 0 0 0 0 0 2
3 7.8 95.9 7.8 7.6 7.5 7.7 0 0 1 0 0 0 0 0 0 0 0 3
4 7.8 104.7 7.8 7.8 7.6 7.5 0 0 0 1 0 0 0 0 0 0 0 4
5 7.5 102.8 7.8 7.8 7.8 7.6 0 0 0 0 1 0 0 0 0 0 0 5
6 7.5 98.1 7.5 7.8 7.8 7.8 0 0 0 0 0 1 0 0 0 0 0 6
7 7.1 113.9 7.5 7.5 7.8 7.8 0 0 0 0 0 0 1 0 0 0 0 7
8 7.5 80.9 7.1 7.5 7.5 7.8 0 0 0 0 0 0 0 1 0 0 0 8
9 7.5 95.7 7.5 7.1 7.5 7.5 0 0 0 0 0 0 0 0 1 0 0 9
10 7.6 113.2 7.5 7.5 7.1 7.5 0 0 0 0 0 0 0 0 0 1 0 10
11 7.7 105.9 7.6 7.5 7.5 7.1 0 0 0 0 0 0 0 0 0 0 1 11
12 7.7 108.8 7.7 7.6 7.5 7.5 0 0 0 0 0 0 0 0 0 0 0 12
13 7.9 102.3 7.7 7.7 7.6 7.5 1 0 0 0 0 0 0 0 0 0 0 13
14 8.1 99.0 7.9 7.7 7.7 7.6 0 1 0 0 0 0 0 0 0 0 0 14
15 8.2 100.7 8.1 7.9 7.7 7.7 0 0 1 0 0 0 0 0 0 0 0 15
16 8.2 115.5 8.2 8.1 7.9 7.7 0 0 0 1 0 0 0 0 0 0 0 16
17 8.2 100.7 8.2 8.2 8.1 7.9 0 0 0 0 1 0 0 0 0 0 0 17
18 7.9 109.9 8.2 8.2 8.2 8.1 0 0 0 0 0 1 0 0 0 0 0 18
19 7.3 114.6 7.9 8.2 8.2 8.2 0 0 0 0 0 0 1 0 0 0 0 19
20 6.9 85.4 7.3 7.9 8.2 8.2 0 0 0 0 0 0 0 1 0 0 0 20
21 6.6 100.5 6.9 7.3 7.9 8.2 0 0 0 0 0 0 0 0 1 0 0 21
22 6.7 114.8 6.6 6.9 7.3 7.9 0 0 0 0 0 0 0 0 0 1 0 22
23 6.9 116.5 6.7 6.6 6.9 7.3 0 0 0 0 0 0 0 0 0 0 1 23
24 7.0 112.9 6.9 6.7 6.6 6.9 0 0 0 0 0 0 0 0 0 0 0 24
25 7.1 102.0 7.0 6.9 6.7 6.6 1 0 0 0 0 0 0 0 0 0 0 25
26 7.2 106.0 7.1 7.0 6.9 6.7 0 1 0 0 0 0 0 0 0 0 0 26
27 7.1 105.3 7.2 7.1 7.0 6.9 0 0 1 0 0 0 0 0 0 0 0 27
28 6.9 118.8 7.1 7.2 7.1 7.0 0 0 0 1 0 0 0 0 0 0 0 28
29 7.0 106.1 6.9 7.1 7.2 7.1 0 0 0 0 1 0 0 0 0 0 0 29
30 6.8 109.3 7.0 6.9 7.1 7.2 0 0 0 0 0 1 0 0 0 0 0 30
31 6.4 117.2 6.8 7.0 6.9 7.1 0 0 0 0 0 0 1 0 0 0 0 31
32 6.7 92.5 6.4 6.8 7.0 6.9 0 0 0 0 0 0 0 1 0 0 0 32
33 6.6 104.2 6.7 6.4 6.8 7.0 0 0 0 0 0 0 0 0 1 0 0 33
34 6.4 112.5 6.6 6.7 6.4 6.8 0 0 0 0 0 0 0 0 0 1 0 34
35 6.3 122.4 6.4 6.6 6.7 6.4 0 0 0 0 0 0 0 0 0 0 1 35
36 6.2 113.3 6.3 6.4 6.6 6.7 0 0 0 0 0 0 0 0 0 0 0 36
37 6.5 100.0 6.2 6.3 6.4 6.6 1 0 0 0 0 0 0 0 0 0 0 37
38 6.8 110.7 6.5 6.2 6.3 6.4 0 1 0 0 0 0 0 0 0 0 0 38
39 6.8 112.8 6.8 6.5 6.2 6.3 0 0 1 0 0 0 0 0 0 0 0 39
40 6.4 109.8 6.8 6.8 6.5 6.2 0 0 0 1 0 0 0 0 0 0 0 40
41 6.1 117.3 6.4 6.8 6.8 6.5 0 0 0 0 1 0 0 0 0 0 0 41
42 5.8 109.1 6.1 6.4 6.8 6.8 0 0 0 0 0 1 0 0 0 0 0 42
43 6.1 115.9 5.8 6.1 6.4 6.8 0 0 0 0 0 0 1 0 0 0 0 43
44 7.2 96.0 6.1 5.8 6.1 6.4 0 0 0 0 0 0 0 1 0 0 0 44
45 7.3 99.8 7.2 6.1 5.8 6.1 0 0 0 0 0 0 0 0 1 0 0 45
46 6.9 116.8 7.3 7.2 6.1 5.8 0 0 0 0 0 0 0 0 0 1 0 46
47 6.1 115.7 6.9 7.3 7.2 6.1 0 0 0 0 0 0 0 0 0 0 1 47
48 5.8 99.4 6.1 6.9 7.3 7.2 0 0 0 0 0 0 0 0 0 0 0 48
49 6.2 94.3 5.8 6.1 6.9 7.3 1 0 0 0 0 0 0 0 0 0 0 49
50 7.1 91.0 6.2 5.8 6.1 6.9 0 1 0 0 0 0 0 0 0 0 0 50
51 7.7 93.2 7.1 6.2 5.8 6.1 0 0 1 0 0 0 0 0 0 0 0 51
52 7.9 103.1 7.7 7.1 6.2 5.8 0 0 0 1 0 0 0 0 0 0 0 52
53 7.7 94.1 7.9 7.7 7.1 6.2 0 0 0 0 1 0 0 0 0 0 0 53
54 7.4 91.8 7.7 7.9 7.7 7.1 0 0 0 0 0 1 0 0 0 0 0 54
55 7.5 102.7 7.4 7.7 7.9 7.7 0 0 0 0 0 0 1 0 0 0 0 55
56 8.0 82.6 7.5 7.4 7.7 7.9 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
1.7960288 -0.0114002 1.5114373 -0.7999828 -0.1498902 0.3485778
M1 M2 M3 M4 M5 M6
0.1637557 0.0840941 -0.0646154 0.1135697 0.0937133 -0.0861896
M7 M8 M9 M10 M11 t
-0.0149737 0.2082909 -0.4454825 0.0385108 0.1365046 0.0005918
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-0.4854468 -0.1094851 -0.0006492 0.0889070 0.3676240
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1.7960288 1.0954505 1.640 0.10936
X -0.0114002 0.0052479 -2.172 0.03614 *
Y1 1.5114373 0.1404882 10.758 4.31e-13 ***
Y2 -0.7999828 0.2772416 -2.886 0.00641 **
Y3 -0.1498902 0.2827658 -0.530 0.59914
Y4 0.3485778 0.1646581 2.117 0.04087 *
M1 0.1637557 0.1422865 1.151 0.25697
M2 0.0840941 0.1449362 0.580 0.56519
M3 -0.0646154 0.1439438 -0.449 0.65606
M4 0.1135697 0.1413038 0.804 0.42655
M5 0.0937133 0.1399889 0.669 0.50727
M6 -0.0861896 0.1364872 -0.631 0.53150
M7 -0.0149737 0.1413930 -0.106 0.91622
M8 0.2082909 0.1658600 1.256 0.21685
M9 -0.4454825 0.1664043 -2.677 0.01090 *
M10 0.0385108 0.1695437 0.227 0.82153
M11 0.1365046 0.1548017 0.882 0.38343
t 0.0005918 0.0028241 0.210 0.83514
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.1957 on 38 degrees of freedom
Multiple R-squared: 0.938, Adjusted R-squared: 0.9102
F-statistic: 33.81 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,] 0.8749237 0.2501526 0.1250763
[2,] 0.7804596 0.4390808 0.2195404
[3,] 0.6859608 0.6280784 0.3140392
[4,] 0.5896358 0.8207283 0.4103642
[5,] 0.5479785 0.9040429 0.4520215
[6,] 0.4588271 0.9176541 0.5411729
[7,] 0.3338756 0.6677512 0.6661244
[8,] 0.2544729 0.5089457 0.7455271
[9,] 0.3131131 0.6262261 0.6868869
[10,] 0.2259172 0.4518345 0.7740828
[11,] 0.3322961 0.6645921 0.6677039
[12,] 0.3317363 0.6634727 0.6682637
[13,] 0.3885776 0.7771552 0.6114224
[14,] 0.3349216 0.6698431 0.6650784
[15,] 0.6249030 0.7501941 0.3750970
> postscript(file="/var/www/html/rcomp/tmp/10ns21258562981.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/20uyi1258562981.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3eumz1258562981.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/49zki1258562981.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5bbkk1258562981.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
0.047457598 -0.159227981 -0.109126152 0.057119693 -0.250155750 0.259290173
7 8 9 10 11 12
-0.272389556 0.087156106 0.089065676 0.164020762 0.130457288 0.088854079
13 14 15 16 17 18
0.145392720 0.064685721 0.155035038 0.183811686 0.074614428 0.004080665
19 20 21 22 23 24
-0.195572798 -0.485446774 0.119495760 0.046010536 -0.075142749 -0.008095672
25 26 27 28 29 30
-0.068289934 0.080355408 -0.005379014 -0.018980212 0.157922575 -0.187272813
31 32 33 34 35 36
-0.181853631 0.141988591 -0.009707817 -0.198773368 0.122190143 -0.074053830
37 38 39 40 41 42
-0.013998509 0.008350294 -0.013159229 -0.306316964 0.043417668 -0.141887935
43 44 45 46 47 48
0.317305848 0.367624010 -0.198853619 -0.011257931 -0.177504682 -0.006704578
49 50 51 52 53 54
-0.110561875 0.005836558 -0.027370642 0.084365796 -0.025798921 0.065789910
55 56
0.332510137 -0.111321933
> postscript(file="/var/www/html/rcomp/tmp/6b8tf1258562981.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 0.047457598 NA
1 -0.159227981 0.047457598
2 -0.109126152 -0.159227981
3 0.057119693 -0.109126152
4 -0.250155750 0.057119693
5 0.259290173 -0.250155750
6 -0.272389556 0.259290173
7 0.087156106 -0.272389556
8 0.089065676 0.087156106
9 0.164020762 0.089065676
10 0.130457288 0.164020762
11 0.088854079 0.130457288
12 0.145392720 0.088854079
13 0.064685721 0.145392720
14 0.155035038 0.064685721
15 0.183811686 0.155035038
16 0.074614428 0.183811686
17 0.004080665 0.074614428
18 -0.195572798 0.004080665
19 -0.485446774 -0.195572798
20 0.119495760 -0.485446774
21 0.046010536 0.119495760
22 -0.075142749 0.046010536
23 -0.008095672 -0.075142749
24 -0.068289934 -0.008095672
25 0.080355408 -0.068289934
26 -0.005379014 0.080355408
27 -0.018980212 -0.005379014
28 0.157922575 -0.018980212
29 -0.187272813 0.157922575
30 -0.181853631 -0.187272813
31 0.141988591 -0.181853631
32 -0.009707817 0.141988591
33 -0.198773368 -0.009707817
34 0.122190143 -0.198773368
35 -0.074053830 0.122190143
36 -0.013998509 -0.074053830
37 0.008350294 -0.013998509
38 -0.013159229 0.008350294
39 -0.306316964 -0.013159229
40 0.043417668 -0.306316964
41 -0.141887935 0.043417668
42 0.317305848 -0.141887935
43 0.367624010 0.317305848
44 -0.198853619 0.367624010
45 -0.011257931 -0.198853619
46 -0.177504682 -0.011257931
47 -0.006704578 -0.177504682
48 -0.110561875 -0.006704578
49 0.005836558 -0.110561875
50 -0.027370642 0.005836558
51 0.084365796 -0.027370642
52 -0.025798921 0.084365796
53 0.065789910 -0.025798921
54 0.332510137 0.065789910
55 -0.111321933 0.332510137
56 NA -0.111321933
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -0.159227981 0.047457598
[2,] -0.109126152 -0.159227981
[3,] 0.057119693 -0.109126152
[4,] -0.250155750 0.057119693
[5,] 0.259290173 -0.250155750
[6,] -0.272389556 0.259290173
[7,] 0.087156106 -0.272389556
[8,] 0.089065676 0.087156106
[9,] 0.164020762 0.089065676
[10,] 0.130457288 0.164020762
[11,] 0.088854079 0.130457288
[12,] 0.145392720 0.088854079
[13,] 0.064685721 0.145392720
[14,] 0.155035038 0.064685721
[15,] 0.183811686 0.155035038
[16,] 0.074614428 0.183811686
[17,] 0.004080665 0.074614428
[18,] -0.195572798 0.004080665
[19,] -0.485446774 -0.195572798
[20,] 0.119495760 -0.485446774
[21,] 0.046010536 0.119495760
[22,] -0.075142749 0.046010536
[23,] -0.008095672 -0.075142749
[24,] -0.068289934 -0.008095672
[25,] 0.080355408 -0.068289934
[26,] -0.005379014 0.080355408
[27,] -0.018980212 -0.005379014
[28,] 0.157922575 -0.018980212
[29,] -0.187272813 0.157922575
[30,] -0.181853631 -0.187272813
[31,] 0.141988591 -0.181853631
[32,] -0.009707817 0.141988591
[33,] -0.198773368 -0.009707817
[34,] 0.122190143 -0.198773368
[35,] -0.074053830 0.122190143
[36,] -0.013998509 -0.074053830
[37,] 0.008350294 -0.013998509
[38,] -0.013159229 0.008350294
[39,] -0.306316964 -0.013159229
[40,] 0.043417668 -0.306316964
[41,] -0.141887935 0.043417668
[42,] 0.317305848 -0.141887935
[43,] 0.367624010 0.317305848
[44,] -0.198853619 0.367624010
[45,] -0.011257931 -0.198853619
[46,] -0.177504682 -0.011257931
[47,] -0.006704578 -0.177504682
[48,] -0.110561875 -0.006704578
[49,] 0.005836558 -0.110561875
[50,] -0.027370642 0.005836558
[51,] 0.084365796 -0.027370642
[52,] -0.025798921 0.084365796
[53,] 0.065789910 -0.025798921
[54,] 0.332510137 0.065789910
[55,] -0.111321933 0.332510137
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -0.159227981 0.047457598
2 -0.109126152 -0.159227981
3 0.057119693 -0.109126152
4 -0.250155750 0.057119693
5 0.259290173 -0.250155750
6 -0.272389556 0.259290173
7 0.087156106 -0.272389556
8 0.089065676 0.087156106
9 0.164020762 0.089065676
10 0.130457288 0.164020762
11 0.088854079 0.130457288
12 0.145392720 0.088854079
13 0.064685721 0.145392720
14 0.155035038 0.064685721
15 0.183811686 0.155035038
16 0.074614428 0.183811686
17 0.004080665 0.074614428
18 -0.195572798 0.004080665
19 -0.485446774 -0.195572798
20 0.119495760 -0.485446774
21 0.046010536 0.119495760
22 -0.075142749 0.046010536
23 -0.008095672 -0.075142749
24 -0.068289934 -0.008095672
25 0.080355408 -0.068289934
26 -0.005379014 0.080355408
27 -0.018980212 -0.005379014
28 0.157922575 -0.018980212
29 -0.187272813 0.157922575
30 -0.181853631 -0.187272813
31 0.141988591 -0.181853631
32 -0.009707817 0.141988591
33 -0.198773368 -0.009707817
34 0.122190143 -0.198773368
35 -0.074053830 0.122190143
36 -0.013998509 -0.074053830
37 0.008350294 -0.013998509
38 -0.013159229 0.008350294
39 -0.306316964 -0.013159229
40 0.043417668 -0.306316964
41 -0.141887935 0.043417668
42 0.317305848 -0.141887935
43 0.367624010 0.317305848
44 -0.198853619 0.367624010
45 -0.011257931 -0.198853619
46 -0.177504682 -0.011257931
47 -0.006704578 -0.177504682
48 -0.110561875 -0.006704578
49 0.005836558 -0.110561875
50 -0.027370642 0.005836558
51 0.084365796 -0.027370642
52 -0.025798921 0.084365796
53 0.065789910 -0.025798921
54 0.332510137 0.065789910
55 -0.111321933 0.332510137
> 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/79ovk1258562981.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8za0m1258562981.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9h2101258562981.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10mpy31258562981.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/118awe1258562981.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/12s7ki1258562981.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/13dvs01258562981.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/144f891258562981.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/15fuyz1258562981.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/16zusn1258562981.tab")
+ }
>
> system("convert tmp/10ns21258562981.ps tmp/10ns21258562981.png")
> system("convert tmp/20uyi1258562981.ps tmp/20uyi1258562981.png")
> system("convert tmp/3eumz1258562981.ps tmp/3eumz1258562981.png")
> system("convert tmp/49zki1258562981.ps tmp/49zki1258562981.png")
> system("convert tmp/5bbkk1258562981.ps tmp/5bbkk1258562981.png")
> system("convert tmp/6b8tf1258562981.ps tmp/6b8tf1258562981.png")
> system("convert tmp/79ovk1258562981.ps tmp/79ovk1258562981.png")
> system("convert tmp/8za0m1258562981.ps tmp/8za0m1258562981.png")
> system("convert tmp/9h2101258562981.ps tmp/9h2101258562981.png")
> system("convert tmp/10mpy31258562981.ps tmp/10mpy31258562981.png")
>
>
> proc.time()
user system elapsed
2.356 1.549 3.137