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(101.9
+ ,96.4
+ ,110.4
+ ,100.5
+ ,98.8
+ ,93.7
+ ,106.2
+ ,101.9
+ ,96.4
+ ,110.4
+ ,100.5
+ ,106.7
+ ,81
+ ,106.2
+ ,101.9
+ ,96.4
+ ,110.4
+ ,86.7
+ ,94.7
+ ,81
+ ,106.2
+ ,101.9
+ ,96.4
+ ,95.3
+ ,101
+ ,94.7
+ ,81
+ ,106.2
+ ,101.9
+ ,99.3
+ ,109.4
+ ,101
+ ,94.7
+ ,81
+ ,106.2
+ ,101.8
+ ,102.3
+ ,109.4
+ ,101
+ ,94.7
+ ,81
+ ,96
+ ,90.7
+ ,102.3
+ ,109.4
+ ,101
+ ,94.7
+ ,91.7
+ ,96.2
+ ,90.7
+ ,102.3
+ ,109.4
+ ,101
+ ,95.3
+ ,96.1
+ ,96.2
+ ,90.7
+ ,102.3
+ ,109.4
+ ,96.6
+ ,106
+ ,96.1
+ ,96.2
+ ,90.7
+ ,102.3
+ ,107.2
+ ,103.1
+ ,106
+ ,96.1
+ ,96.2
+ ,90.7
+ ,108
+ ,102
+ ,103.1
+ ,106
+ ,96.1
+ ,96.2
+ ,98.4
+ ,104.7
+ ,102
+ ,103.1
+ ,106
+ ,96.1
+ ,103.1
+ ,86
+ ,104.7
+ ,102
+ ,103.1
+ ,106
+ ,81.1
+ ,92.1
+ ,86
+ ,104.7
+ ,102
+ ,103.1
+ ,96.6
+ ,106.9
+ ,92.1
+ ,86
+ ,104.7
+ ,102
+ ,103.7
+ ,112.6
+ ,106.9
+ ,92.1
+ ,86
+ ,104.7
+ ,106.6
+ ,101.7
+ ,112.6
+ ,106.9
+ ,92.1
+ ,86
+ ,97.6
+ ,92
+ ,101.7
+ ,112.6
+ ,106.9
+ ,92.1
+ ,87.6
+ ,97.4
+ ,92
+ ,101.7
+ ,112.6
+ ,106.9
+ ,99.4
+ ,97
+ ,97.4
+ ,92
+ ,101.7
+ ,112.6
+ ,98.5
+ ,105.4
+ ,97
+ ,97.4
+ ,92
+ ,101.7
+ ,105.2
+ ,102.7
+ ,105.4
+ ,97
+ ,97.4
+ ,92
+ ,104.6
+ ,98.1
+ ,102.7
+ ,105.4
+ ,97
+ ,97.4
+ ,97.5
+ ,104.5
+ ,98.1
+ ,102.7
+ ,105.4
+ ,97
+ ,108.9
+ ,87.4
+ ,104.5
+ ,98.1
+ ,102.7
+ ,105.4
+ ,86.8
+ ,89.9
+ ,87.4
+ ,104.5
+ ,98.1
+ ,102.7
+ ,88.9
+ ,109.8
+ ,89.9
+ ,87.4
+ ,104.5
+ ,98.1
+ ,110.3
+ ,111.7
+ ,109.8
+ ,89.9
+ ,87.4
+ ,104.5
+ ,114.8
+ ,98.6
+ ,111.7
+ ,109.8
+ ,89.9
+ ,87.4
+ ,94.6
+ ,96.9
+ ,98.6
+ ,111.7
+ ,109.8
+ ,89.9
+ ,92
+ ,95.1
+ ,96.9
+ ,98.6
+ ,111.7
+ ,109.8
+ ,93.8
+ ,97
+ ,95.1
+ ,96.9
+ ,98.6
+ ,111.7
+ ,93.8
+ ,112.7
+ ,97
+ ,95.1
+ ,96.9
+ ,98.6
+ ,107.6
+ ,102.9
+ ,112.7
+ ,97
+ ,95.1
+ ,96.9
+ ,101
+ ,97.4
+ ,102.9
+ ,112.7
+ ,97
+ ,95.1
+ ,95.4
+ ,111.4
+ ,97.4
+ ,102.9
+ ,112.7
+ ,97
+ ,96.5
+ ,87.4
+ ,111.4
+ ,97.4
+ ,102.9
+ ,112.7
+ ,89.2
+ ,96.8
+ ,87.4
+ ,111.4
+ ,97.4
+ ,102.9
+ ,87.1
+ ,114.1
+ ,96.8
+ ,87.4
+ ,111.4
+ ,97.4
+ ,110.5
+ ,110.3
+ ,114.1
+ ,96.8
+ ,87.4
+ ,111.4
+ ,110.8
+ ,103.9
+ ,110.3
+ ,114.1
+ ,96.8
+ ,87.4
+ ,104.2
+ ,101.6
+ ,103.9
+ ,110.3
+ ,114.1
+ ,96.8
+ ,88.9
+ ,94.6
+ ,101.6
+ ,103.9
+ ,110.3
+ ,114.1
+ ,89.8
+ ,95.9
+ ,94.6
+ ,101.6
+ ,103.9
+ ,110.3
+ ,90
+ ,104.7
+ ,95.9
+ ,94.6
+ ,101.6
+ ,103.9
+ ,93.9
+ ,102.8
+ ,104.7
+ ,95.9
+ ,94.6
+ ,101.6
+ ,91.3
+ ,98.1
+ ,102.8
+ ,104.7
+ ,95.9
+ ,94.6
+ ,87.8
+ ,113.9
+ ,98.1
+ ,102.8
+ ,104.7
+ ,95.9
+ ,99.7
+ ,80.9
+ ,113.9
+ ,98.1
+ ,102.8
+ ,104.7
+ ,73.5
+ ,95.7
+ ,80.9
+ ,113.9
+ ,98.1
+ ,102.8
+ ,79.2
+ ,113.2
+ ,95.7
+ ,80.9
+ ,113.9
+ ,98.1
+ ,96.9
+ ,105.9
+ ,113.2
+ ,95.7
+ ,80.9
+ ,113.9
+ ,95.2
+ ,108.8
+ ,105.9
+ ,113.2
+ ,95.7
+ ,80.9
+ ,95.6
+ ,102.3
+ ,108.8
+ ,105.9
+ ,113.2
+ ,95.7
+ ,89.7)
+ ,dim=c(6
+ ,56)
+ ,dimnames=list(c('Y'
+ ,'Y(t-1)'
+ ,'Y(t-2)'
+ ,'Y(t-3)'
+ ,'Y(t-4)'
+ ,'X')
+ ,1:56))
> y <- array(NA,dim=c(6,56),dimnames=list(c('Y','Y(t-1)','Y(t-2)','Y(t-3)','Y(t-4)','X'),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 Y(t-1) Y(t-2) Y(t-3) Y(t-4) X M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11
1 101.9 96.4 110.4 100.5 98.8 93.7 1 0 0 0 0 0 0 0 0 0 0
2 106.2 101.9 96.4 110.4 100.5 106.7 0 1 0 0 0 0 0 0 0 0 0
3 81.0 106.2 101.9 96.4 110.4 86.7 0 0 1 0 0 0 0 0 0 0 0
4 94.7 81.0 106.2 101.9 96.4 95.3 0 0 0 1 0 0 0 0 0 0 0
5 101.0 94.7 81.0 106.2 101.9 99.3 0 0 0 0 1 0 0 0 0 0 0
6 109.4 101.0 94.7 81.0 106.2 101.8 0 0 0 0 0 1 0 0 0 0 0
7 102.3 109.4 101.0 94.7 81.0 96.0 0 0 0 0 0 0 1 0 0 0 0
8 90.7 102.3 109.4 101.0 94.7 91.7 0 0 0 0 0 0 0 1 0 0 0
9 96.2 90.7 102.3 109.4 101.0 95.3 0 0 0 0 0 0 0 0 1 0 0
10 96.1 96.2 90.7 102.3 109.4 96.6 0 0 0 0 0 0 0 0 0 1 0
11 106.0 96.1 96.2 90.7 102.3 107.2 0 0 0 0 0 0 0 0 0 0 1
12 103.1 106.0 96.1 96.2 90.7 108.0 0 0 0 0 0 0 0 0 0 0 0
13 102.0 103.1 106.0 96.1 96.2 98.4 1 0 0 0 0 0 0 0 0 0 0
14 104.7 102.0 103.1 106.0 96.1 103.1 0 1 0 0 0 0 0 0 0 0 0
15 86.0 104.7 102.0 103.1 106.0 81.1 0 0 1 0 0 0 0 0 0 0 0
16 92.1 86.0 104.7 102.0 103.1 96.6 0 0 0 1 0 0 0 0 0 0 0
17 106.9 92.1 86.0 104.7 102.0 103.7 0 0 0 0 1 0 0 0 0 0 0
18 112.6 106.9 92.1 86.0 104.7 106.6 0 0 0 0 0 1 0 0 0 0 0
19 101.7 112.6 106.9 92.1 86.0 97.6 0 0 0 0 0 0 1 0 0 0 0
20 92.0 101.7 112.6 106.9 92.1 87.6 0 0 0 0 0 0 0 1 0 0 0
21 97.4 92.0 101.7 112.6 106.9 99.4 0 0 0 0 0 0 0 0 1 0 0
22 97.0 97.4 92.0 101.7 112.6 98.5 0 0 0 0 0 0 0 0 0 1 0
23 105.4 97.0 97.4 92.0 101.7 105.2 0 0 0 0 0 0 0 0 0 0 1
24 102.7 105.4 97.0 97.4 92.0 104.6 0 0 0 0 0 0 0 0 0 0 0
25 98.1 102.7 105.4 97.0 97.4 97.5 1 0 0 0 0 0 0 0 0 0 0
26 104.5 98.1 102.7 105.4 97.0 108.9 0 1 0 0 0 0 0 0 0 0 0
27 87.4 104.5 98.1 102.7 105.4 86.8 0 0 1 0 0 0 0 0 0 0 0
28 89.9 87.4 104.5 98.1 102.7 88.9 0 0 0 1 0 0 0 0 0 0 0
29 109.8 89.9 87.4 104.5 98.1 110.3 0 0 0 0 1 0 0 0 0 0 0
30 111.7 109.8 89.9 87.4 104.5 114.8 0 0 0 0 0 1 0 0 0 0 0
31 98.6 111.7 109.8 89.9 87.4 94.6 0 0 0 0 0 0 1 0 0 0 0
32 96.9 98.6 111.7 109.8 89.9 92.0 0 0 0 0 0 0 0 1 0 0 0
33 95.1 96.9 98.6 111.7 109.8 93.8 0 0 0 0 0 0 0 0 1 0 0
34 97.0 95.1 96.9 98.6 111.7 93.8 0 0 0 0 0 0 0 0 0 1 0
35 112.7 97.0 95.1 96.9 98.6 107.6 0 0 0 0 0 0 0 0 0 0 1
36 102.9 112.7 97.0 95.1 96.9 101.0 0 0 0 0 0 0 0 0 0 0 0
37 97.4 102.9 112.7 97.0 95.1 95.4 1 0 0 0 0 0 0 0 0 0 0
38 111.4 97.4 102.9 112.7 97.0 96.5 0 1 0 0 0 0 0 0 0 0 0
39 87.4 111.4 97.4 102.9 112.7 89.2 0 0 1 0 0 0 0 0 0 0 0
40 96.8 87.4 111.4 97.4 102.9 87.1 0 0 0 1 0 0 0 0 0 0 0
41 114.1 96.8 87.4 111.4 97.4 110.5 0 0 0 0 1 0 0 0 0 0 0
42 110.3 114.1 96.8 87.4 111.4 110.8 0 0 0 0 0 1 0 0 0 0 0
43 103.9 110.3 114.1 96.8 87.4 104.2 0 0 0 0 0 0 1 0 0 0 0
44 101.6 103.9 110.3 114.1 96.8 88.9 0 0 0 0 0 0 0 1 0 0 0
45 94.6 101.6 103.9 110.3 114.1 89.8 0 0 0 0 0 0 0 0 1 0 0
46 95.9 94.6 101.6 103.9 110.3 90.0 0 0 0 0 0 0 0 0 0 1 0
47 104.7 95.9 94.6 101.6 103.9 93.9 0 0 0 0 0 0 0 0 0 0 1
48 102.8 104.7 95.9 94.6 101.6 91.3 0 0 0 0 0 0 0 0 0 0 0
49 98.1 102.8 104.7 95.9 94.6 87.8 1 0 0 0 0 0 0 0 0 0 0
50 113.9 98.1 102.8 104.7 95.9 99.7 0 1 0 0 0 0 0 0 0 0 0
51 80.9 113.9 98.1 102.8 104.7 73.5 0 0 1 0 0 0 0 0 0 0 0
52 95.7 80.9 113.9 98.1 102.8 79.2 0 0 0 1 0 0 0 0 0 0 0
53 113.2 95.7 80.9 113.9 98.1 96.9 0 0 0 0 1 0 0 0 0 0 0
54 105.9 113.2 95.7 80.9 113.9 95.2 0 0 0 0 0 1 0 0 0 0 0
55 108.8 105.9 113.2 95.7 80.9 95.6 0 0 0 0 0 0 1 0 0 0 0
56 102.3 108.8 105.9 113.2 95.7 89.7 0 0 0 0 0 0 0 1 0 0 0
t
1 1
2 2
3 3
4 4
5 5
6 6
7 7
8 8
9 9
10 10
11 11
12 12
13 13
14 14
15 15
16 16
17 17
18 18
19 19
20 20
21 21
22 22
23 23
24 24
25 25
26 26
27 27
28 28
29 29
30 30
31 31
32 32
33 33
34 34
35 35
36 36
37 37
38 38
39 39
40 40
41 41
42 42
43 43
44 44
45 45
46 46
47 47
48 48
49 49
50 50
51 51
52 52
53 53
54 54
55 55
56 56
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) `Y(t-1)` `Y(t-2)` `Y(t-3)` `Y(t-4)` X
95.41289 -0.37352 -0.07516 0.35885 -0.07881 0.24021
M1 M2 M3 M4 M5 M6
-2.86774 -1.32952 -14.21143 -14.37463 -4.43379 11.53044
M7 M8 M9 M10 M11 t
2.77911 -9.08766 -13.60441 -9.75894 0.54283 0.11883
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-4.73664 -1.69797 0.02436 1.35731 4.28109
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 95.41289 29.57155 3.227 0.002580 **
`Y(t-1)` -0.37352 0.15293 -2.443 0.019347 *
`Y(t-2)` -0.07516 0.14320 -0.525 0.602730
`Y(t-3)` 0.35885 0.13368 2.684 0.010706 *
`Y(t-4)` -0.07881 0.14080 -0.560 0.578927
X 0.24021 0.08373 2.869 0.006688 **
M1 -2.86774 2.43224 -1.179 0.245706
M2 -1.32952 2.72907 -0.487 0.628936
M3 -14.21143 2.99754 -4.741 2.97e-05 ***
M4 -14.37463 3.89792 -3.688 0.000705 ***
M5 -4.43379 3.96881 -1.117 0.270940
M6 11.53044 2.95942 3.896 0.000384 ***
M7 2.77911 3.33762 0.833 0.410237
M8 -9.08766 3.56879 -2.546 0.015058 *
M9 -13.60441 4.06424 -3.347 0.001849 **
M10 -9.75894 3.86144 -2.527 0.015776 *
M11 0.54283 2.91376 0.186 0.853202
t 0.11883 0.03212 3.700 0.000680 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 2.539 on 38 degrees of freedom
Multiple R-squared: 0.9317, Adjusted R-squared: 0.9011
F-statistic: 30.47 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,] 0.134811767 0.26962353 0.8651882
[2,] 0.053011374 0.10602275 0.9469886
[3,] 0.025996028 0.05199206 0.9740040
[4,] 0.008691643 0.01738329 0.9913084
[5,] 0.039274356 0.07854871 0.9607256
[6,] 0.142077264 0.28415453 0.8579227
[7,] 0.147039788 0.29407958 0.8529602
[8,] 0.300637984 0.60127597 0.6993620
[9,] 0.245606993 0.49121399 0.7543930
[10,] 0.236046779 0.47209356 0.7639532
[11,] 0.162639601 0.32527920 0.8373604
[12,] 0.286608429 0.57321686 0.7133916
[13,] 0.695066113 0.60986777 0.3049339
[14,] 0.753568751 0.49286250 0.2464312
[15,] 0.645597182 0.70880564 0.3544028
> postscript(file="/var/www/html/rcomp/tmp/1nrvb1260718563.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/227721260718563.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/34cio1260718563.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4em3p1260718563.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5m0bd1260718563.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
2.755413923 -0.140899428 0.050096241 -0.437994725 -3.044869076 1.436373282
7 8 9 10 11 12
1.070831371 -0.950020784 0.698807354 0.714630880 1.626919210 -0.238815942
13 14 15 16 17 18
3.846341264 -0.429056291 1.665421613 -2.529248695 0.322988646 2.153236554
19 20 21 22 23 24
1.626271427 -2.396904755 -0.754917387 0.745664283 -0.006101384 -1.732742095
25 26 27 28 29 30
-1.686373990 -4.648850145 -0.001366505 -2.429734391 -0.740541535 -1.742799113
31 32 33 34 35 36
-1.397500221 -2.419464711 -0.986955503 0.999337426 3.115822150 1.844261315
37 38 39 40 41 42
-2.865841224 0.937711654 1.024368648 4.262194601 2.131462846 -0.939411450
43 44 45 46 47 48
-2.505362949 2.474369858 1.043065535 -2.459632589 -4.736639976 0.127296723
49 50 51 52 53 54
-2.049539973 4.281094210 -2.738519996 1.134783210 1.330959118 -0.907399274
55 56
1.205760371 3.292020392
> postscript(file="/var/www/html/rcomp/tmp/6vx031260718563.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 2.755413923 NA
1 -0.140899428 2.755413923
2 0.050096241 -0.140899428
3 -0.437994725 0.050096241
4 -3.044869076 -0.437994725
5 1.436373282 -3.044869076
6 1.070831371 1.436373282
7 -0.950020784 1.070831371
8 0.698807354 -0.950020784
9 0.714630880 0.698807354
10 1.626919210 0.714630880
11 -0.238815942 1.626919210
12 3.846341264 -0.238815942
13 -0.429056291 3.846341264
14 1.665421613 -0.429056291
15 -2.529248695 1.665421613
16 0.322988646 -2.529248695
17 2.153236554 0.322988646
18 1.626271427 2.153236554
19 -2.396904755 1.626271427
20 -0.754917387 -2.396904755
21 0.745664283 -0.754917387
22 -0.006101384 0.745664283
23 -1.732742095 -0.006101384
24 -1.686373990 -1.732742095
25 -4.648850145 -1.686373990
26 -0.001366505 -4.648850145
27 -2.429734391 -0.001366505
28 -0.740541535 -2.429734391
29 -1.742799113 -0.740541535
30 -1.397500221 -1.742799113
31 -2.419464711 -1.397500221
32 -0.986955503 -2.419464711
33 0.999337426 -0.986955503
34 3.115822150 0.999337426
35 1.844261315 3.115822150
36 -2.865841224 1.844261315
37 0.937711654 -2.865841224
38 1.024368648 0.937711654
39 4.262194601 1.024368648
40 2.131462846 4.262194601
41 -0.939411450 2.131462846
42 -2.505362949 -0.939411450
43 2.474369858 -2.505362949
44 1.043065535 2.474369858
45 -2.459632589 1.043065535
46 -4.736639976 -2.459632589
47 0.127296723 -4.736639976
48 -2.049539973 0.127296723
49 4.281094210 -2.049539973
50 -2.738519996 4.281094210
51 1.134783210 -2.738519996
52 1.330959118 1.134783210
53 -0.907399274 1.330959118
54 1.205760371 -0.907399274
55 3.292020392 1.205760371
56 NA 3.292020392
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -0.140899428 2.755413923
[2,] 0.050096241 -0.140899428
[3,] -0.437994725 0.050096241
[4,] -3.044869076 -0.437994725
[5,] 1.436373282 -3.044869076
[6,] 1.070831371 1.436373282
[7,] -0.950020784 1.070831371
[8,] 0.698807354 -0.950020784
[9,] 0.714630880 0.698807354
[10,] 1.626919210 0.714630880
[11,] -0.238815942 1.626919210
[12,] 3.846341264 -0.238815942
[13,] -0.429056291 3.846341264
[14,] 1.665421613 -0.429056291
[15,] -2.529248695 1.665421613
[16,] 0.322988646 -2.529248695
[17,] 2.153236554 0.322988646
[18,] 1.626271427 2.153236554
[19,] -2.396904755 1.626271427
[20,] -0.754917387 -2.396904755
[21,] 0.745664283 -0.754917387
[22,] -0.006101384 0.745664283
[23,] -1.732742095 -0.006101384
[24,] -1.686373990 -1.732742095
[25,] -4.648850145 -1.686373990
[26,] -0.001366505 -4.648850145
[27,] -2.429734391 -0.001366505
[28,] -0.740541535 -2.429734391
[29,] -1.742799113 -0.740541535
[30,] -1.397500221 -1.742799113
[31,] -2.419464711 -1.397500221
[32,] -0.986955503 -2.419464711
[33,] 0.999337426 -0.986955503
[34,] 3.115822150 0.999337426
[35,] 1.844261315 3.115822150
[36,] -2.865841224 1.844261315
[37,] 0.937711654 -2.865841224
[38,] 1.024368648 0.937711654
[39,] 4.262194601 1.024368648
[40,] 2.131462846 4.262194601
[41,] -0.939411450 2.131462846
[42,] -2.505362949 -0.939411450
[43,] 2.474369858 -2.505362949
[44,] 1.043065535 2.474369858
[45,] -2.459632589 1.043065535
[46,] -4.736639976 -2.459632589
[47,] 0.127296723 -4.736639976
[48,] -2.049539973 0.127296723
[49,] 4.281094210 -2.049539973
[50,] -2.738519996 4.281094210
[51,] 1.134783210 -2.738519996
[52,] 1.330959118 1.134783210
[53,] -0.907399274 1.330959118
[54,] 1.205760371 -0.907399274
[55,] 3.292020392 1.205760371
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -0.140899428 2.755413923
2 0.050096241 -0.140899428
3 -0.437994725 0.050096241
4 -3.044869076 -0.437994725
5 1.436373282 -3.044869076
6 1.070831371 1.436373282
7 -0.950020784 1.070831371
8 0.698807354 -0.950020784
9 0.714630880 0.698807354
10 1.626919210 0.714630880
11 -0.238815942 1.626919210
12 3.846341264 -0.238815942
13 -0.429056291 3.846341264
14 1.665421613 -0.429056291
15 -2.529248695 1.665421613
16 0.322988646 -2.529248695
17 2.153236554 0.322988646
18 1.626271427 2.153236554
19 -2.396904755 1.626271427
20 -0.754917387 -2.396904755
21 0.745664283 -0.754917387
22 -0.006101384 0.745664283
23 -1.732742095 -0.006101384
24 -1.686373990 -1.732742095
25 -4.648850145 -1.686373990
26 -0.001366505 -4.648850145
27 -2.429734391 -0.001366505
28 -0.740541535 -2.429734391
29 -1.742799113 -0.740541535
30 -1.397500221 -1.742799113
31 -2.419464711 -1.397500221
32 -0.986955503 -2.419464711
33 0.999337426 -0.986955503
34 3.115822150 0.999337426
35 1.844261315 3.115822150
36 -2.865841224 1.844261315
37 0.937711654 -2.865841224
38 1.024368648 0.937711654
39 4.262194601 1.024368648
40 2.131462846 4.262194601
41 -0.939411450 2.131462846
42 -2.505362949 -0.939411450
43 2.474369858 -2.505362949
44 1.043065535 2.474369858
45 -2.459632589 1.043065535
46 -4.736639976 -2.459632589
47 0.127296723 -4.736639976
48 -2.049539973 0.127296723
49 4.281094210 -2.049539973
50 -2.738519996 4.281094210
51 1.134783210 -2.738519996
52 1.330959118 1.134783210
53 -0.907399274 1.330959118
54 1.205760371 -0.907399274
55 3.292020392 1.205760371
> 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/701eg1260718563.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8kblw1260718563.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9stco1260718563.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10nqxq1260718564.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11dmrg1260718564.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/125q0l1260718564.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/13p1k61260718564.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/143ptm1260718564.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/15osfq1260718564.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/165m1w1260718564.tab")
+ }
> try(system("convert tmp/1nrvb1260718563.ps tmp/1nrvb1260718563.png",intern=TRUE))
character(0)
> try(system("convert tmp/227721260718563.ps tmp/227721260718563.png",intern=TRUE))
character(0)
> try(system("convert tmp/34cio1260718563.ps tmp/34cio1260718563.png",intern=TRUE))
character(0)
> try(system("convert tmp/4em3p1260718563.ps tmp/4em3p1260718563.png",intern=TRUE))
character(0)
> try(system("convert tmp/5m0bd1260718563.ps tmp/5m0bd1260718563.png",intern=TRUE))
character(0)
> try(system("convert tmp/6vx031260718563.ps tmp/6vx031260718563.png",intern=TRUE))
character(0)
> try(system("convert tmp/701eg1260718563.ps tmp/701eg1260718563.png",intern=TRUE))
character(0)
> try(system("convert tmp/8kblw1260718563.ps tmp/8kblw1260718563.png",intern=TRUE))
character(0)
> try(system("convert tmp/9stco1260718563.ps tmp/9stco1260718563.png",intern=TRUE))
character(0)
> try(system("convert tmp/10nqxq1260718564.ps tmp/10nqxq1260718564.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
2.319 1.554 2.730