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(86.0
+ ,88.4
+ ,90.7
+ ,95.3
+ ,100.0
+ ,94.7
+ ,86.0
+ ,86.0
+ ,88.4
+ ,90.7
+ ,95.3
+ ,110.6
+ ,95.3
+ ,86.0
+ ,86.0
+ ,88.4
+ ,90.7
+ ,71.3
+ ,95.3
+ ,95.3
+ ,86.0
+ ,86.0
+ ,88.4
+ ,104.1
+ ,88.4
+ ,95.3
+ ,95.3
+ ,86.0
+ ,86.0
+ ,112.3
+ ,86.0
+ ,88.4
+ ,95.3
+ ,95.3
+ ,86.0
+ ,110.2
+ ,81.4
+ ,86.0
+ ,88.4
+ ,95.3
+ ,95.3
+ ,112.9
+ ,83.7
+ ,81.4
+ ,86.0
+ ,88.4
+ ,95.3
+ ,95.1
+ ,95.3
+ ,83.7
+ ,81.4
+ ,86.0
+ ,88.4
+ ,103.1
+ ,88.4
+ ,95.3
+ ,83.7
+ ,81.4
+ ,86.0
+ ,101.9
+ ,86.0
+ ,88.4
+ ,95.3
+ ,83.7
+ ,81.4
+ ,100.4
+ ,83.7
+ ,86.0
+ ,88.4
+ ,95.3
+ ,83.7
+ ,106.9
+ ,76.7
+ ,83.7
+ ,86.0
+ ,88.4
+ ,95.3
+ ,100.7
+ ,79.1
+ ,76.7
+ ,83.7
+ ,86.0
+ ,88.4
+ ,114.3
+ ,86.0
+ ,79.1
+ ,76.7
+ ,83.7
+ ,86.0
+ ,73.3
+ ,86.0
+ ,86.0
+ ,79.1
+ ,76.7
+ ,83.7
+ ,105.9
+ ,79.1
+ ,86.0
+ ,86.0
+ ,79.1
+ ,76.7
+ ,113.9
+ ,76.7
+ ,79.1
+ ,86.0
+ ,86.0
+ ,79.1
+ ,112.1
+ ,69.8
+ ,76.7
+ ,79.1
+ ,86.0
+ ,86.0
+ ,117.5
+ ,69.8
+ ,69.8
+ ,76.7
+ ,79.1
+ ,86.0
+ ,97.5
+ ,76.7
+ ,69.8
+ ,69.8
+ ,76.7
+ ,79.1
+ ,112.3
+ ,69.8
+ ,76.7
+ ,69.8
+ ,69.8
+ ,76.7
+ ,106.9
+ ,67.4
+ ,69.8
+ ,76.7
+ ,69.8
+ ,69.8
+ ,120.9
+ ,65.1
+ ,67.4
+ ,69.8
+ ,76.7
+ ,69.8
+ ,92.7
+ ,58.1
+ ,65.1
+ ,67.4
+ ,69.8
+ ,76.7
+ ,110.9
+ ,60.5
+ ,58.1
+ ,65.1
+ ,67.4
+ ,69.8
+ ,116.5
+ ,65.1
+ ,60.5
+ ,58.1
+ ,65.1
+ ,67.4
+ ,77.1
+ ,62.8
+ ,65.1
+ ,60.5
+ ,58.1
+ ,65.1
+ ,113.1
+ ,55.8
+ ,62.8
+ ,65.1
+ ,60.5
+ ,58.1
+ ,115.9
+ ,51.2
+ ,55.8
+ ,62.8
+ ,65.1
+ ,60.5
+ ,123.5
+ ,48.8
+ ,51.2
+ ,55.8
+ ,62.8
+ ,65.1
+ ,123.6
+ ,48.8
+ ,48.8
+ ,51.2
+ ,55.8
+ ,62.8
+ ,101.5
+ ,53.5
+ ,48.8
+ ,48.8
+ ,51.2
+ ,55.8
+ ,121.0
+ ,48.8
+ ,53.5
+ ,48.8
+ ,48.8
+ ,51.2
+ ,112.2
+ ,46.5
+ ,48.8
+ ,53.5
+ ,48.8
+ ,48.8
+ ,126.0
+ ,44.2
+ ,46.5
+ ,48.8
+ ,53.5
+ ,48.8
+ ,101.8
+ ,39.5
+ ,44.2
+ ,46.5
+ ,48.8
+ ,53.5
+ ,117.9
+ ,41.9
+ ,39.5
+ ,44.2
+ ,46.5
+ ,48.8
+ ,122.2
+ ,48.8
+ ,41.9
+ ,39.5
+ ,44.2
+ ,46.5
+ ,82.7
+ ,46.5
+ ,48.8
+ ,41.9
+ ,39.5
+ ,44.2
+ ,120.5
+ ,41.9
+ ,46.5
+ ,48.8
+ ,41.9
+ ,39.5
+ ,120.3
+ ,39.5
+ ,41.9
+ ,46.5
+ ,48.8
+ ,41.9
+ ,134.2
+ ,37.2
+ ,39.5
+ ,41.9
+ ,46.5
+ ,48.8
+ ,128.2
+ ,37.2
+ ,37.2
+ ,39.5
+ ,41.9
+ ,46.5
+ ,100.5
+ ,41.9
+ ,37.2
+ ,37.2
+ ,39.5
+ ,41.9
+ ,126.0
+ ,39.5
+ ,41.9
+ ,37.2
+ ,37.2
+ ,39.5
+ ,122.9
+ ,39.5
+ ,39.5
+ ,41.9
+ ,37.2
+ ,37.2
+ ,106.1
+ ,34.9
+ ,39.5
+ ,39.5
+ ,41.9
+ ,37.2
+ ,130.4
+ ,34.9
+ ,34.9
+ ,39.5
+ ,39.5
+ ,41.9
+ ,121.3
+ ,34.9
+ ,34.9
+ ,34.9
+ ,39.5
+ ,39.5
+ ,126.1
+ ,41.9
+ ,34.9
+ ,34.9
+ ,34.9
+ ,39.5
+ ,88.7
+ ,41.9
+ ,41.9
+ ,34.9
+ ,34.9
+ ,34.9
+ ,118.7
+ ,39.5
+ ,41.9
+ ,41.9
+ ,34.9
+ ,34.9
+ ,129.3
+ ,39.5
+ ,39.5
+ ,41.9
+ ,41.9
+ ,34.9
+ ,136.2
+ ,41.9
+ ,39.5
+ ,39.5
+ ,41.9
+ ,41.9
+ ,123.0
+ ,46.5
+ ,41.9
+ ,39.5
+ ,39.5
+ ,41.9
+ ,103.5)
+ ,dim=c(6
+ ,56)
+ ,dimnames=list(c('Werkloosheid(Y(t))'
+ ,'Y(t-1)'
+ ,'Y(t-2)'
+ ,'Y(t-3)'
+ ,'Y(t-4)'
+ ,'Productie')
+ ,1:56))
> y <- array(NA,dim=c(6,56),dimnames=list(c('Werkloosheid(Y(t))','Y(t-1)','Y(t-2)','Y(t-3)','Y(t-4)','Productie'),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
Werkloosheid(Y(t)) Y(t-1) Y(t-2) Y(t-3) Y(t-4) Productie M1 M2 M3 M4 M5 M6
1 86.0 88.4 90.7 95.3 100.0 94.7 1 0 0 0 0 0
2 86.0 86.0 88.4 90.7 95.3 110.6 0 1 0 0 0 0
3 95.3 86.0 86.0 88.4 90.7 71.3 0 0 1 0 0 0
4 95.3 95.3 86.0 86.0 88.4 104.1 0 0 0 1 0 0
5 88.4 95.3 95.3 86.0 86.0 112.3 0 0 0 0 1 0
6 86.0 88.4 95.3 95.3 86.0 110.2 0 0 0 0 0 1
7 81.4 86.0 88.4 95.3 95.3 112.9 0 0 0 0 0 0
8 83.7 81.4 86.0 88.4 95.3 95.1 0 0 0 0 0 0
9 95.3 83.7 81.4 86.0 88.4 103.1 0 0 0 0 0 0
10 88.4 95.3 83.7 81.4 86.0 101.9 0 0 0 0 0 0
11 86.0 88.4 95.3 83.7 81.4 100.4 0 0 0 0 0 0
12 83.7 86.0 88.4 95.3 83.7 106.9 0 0 0 0 0 0
13 76.7 83.7 86.0 88.4 95.3 100.7 1 0 0 0 0 0
14 79.1 76.7 83.7 86.0 88.4 114.3 0 1 0 0 0 0
15 86.0 79.1 76.7 83.7 86.0 73.3 0 0 1 0 0 0
16 86.0 86.0 79.1 76.7 83.7 105.9 0 0 0 1 0 0
17 79.1 86.0 86.0 79.1 76.7 113.9 0 0 0 0 1 0
18 76.7 79.1 86.0 86.0 79.1 112.1 0 0 0 0 0 1
19 69.8 76.7 79.1 86.0 86.0 117.5 0 0 0 0 0 0
20 69.8 69.8 76.7 79.1 86.0 97.5 0 0 0 0 0 0
21 76.7 69.8 69.8 76.7 79.1 112.3 0 0 0 0 0 0
22 69.8 76.7 69.8 69.8 76.7 106.9 0 0 0 0 0 0
23 67.4 69.8 76.7 69.8 69.8 120.9 0 0 0 0 0 0
24 65.1 67.4 69.8 76.7 69.8 92.7 0 0 0 0 0 0
25 58.1 65.1 67.4 69.8 76.7 110.9 1 0 0 0 0 0
26 60.5 58.1 65.1 67.4 69.8 116.5 0 1 0 0 0 0
27 65.1 60.5 58.1 65.1 67.4 77.1 0 0 1 0 0 0
28 62.8 65.1 60.5 58.1 65.1 113.1 0 0 0 1 0 0
29 55.8 62.8 65.1 60.5 58.1 115.9 0 0 0 0 1 0
30 51.2 55.8 62.8 65.1 60.5 123.5 0 0 0 0 0 1
31 48.8 51.2 55.8 62.8 65.1 123.6 0 0 0 0 0 0
32 48.8 48.8 51.2 55.8 62.8 101.5 0 0 0 0 0 0
33 53.5 48.8 48.8 51.2 55.8 121.0 0 0 0 0 0 0
34 48.8 53.5 48.8 48.8 51.2 112.2 0 0 0 0 0 0
35 46.5 48.8 53.5 48.8 48.8 126.0 0 0 0 0 0 0
36 44.2 46.5 48.8 53.5 48.8 101.8 0 0 0 0 0 0
37 39.5 44.2 46.5 48.8 53.5 117.9 1 0 0 0 0 0
38 41.9 39.5 44.2 46.5 48.8 122.2 0 1 0 0 0 0
39 48.8 41.9 39.5 44.2 46.5 82.7 0 0 1 0 0 0
40 46.5 48.8 41.9 39.5 44.2 120.5 0 0 0 1 0 0
41 41.9 46.5 48.8 41.9 39.5 120.3 0 0 0 0 1 0
42 39.5 41.9 46.5 48.8 41.9 134.2 0 0 0 0 0 1
43 37.2 39.5 41.9 46.5 48.8 128.2 0 0 0 0 0 0
44 37.2 37.2 39.5 41.9 46.5 100.5 0 0 0 0 0 0
45 41.9 37.2 37.2 39.5 41.9 126.0 0 0 0 0 0 0
46 39.5 41.9 37.2 37.2 39.5 122.9 0 0 0 0 0 0
47 39.5 39.5 41.9 37.2 37.2 106.1 0 0 0 0 0 0
48 34.9 39.5 39.5 41.9 37.2 130.4 0 0 0 0 0 0
49 34.9 34.9 39.5 39.5 41.9 121.3 1 0 0 0 0 0
50 34.9 34.9 34.9 39.5 39.5 126.1 0 1 0 0 0 0
51 41.9 34.9 34.9 34.9 39.5 88.7 0 0 1 0 0 0
52 41.9 41.9 34.9 34.9 34.9 118.7 0 0 0 1 0 0
53 39.5 41.9 41.9 34.9 34.9 129.3 0 0 0 0 1 0
54 39.5 39.5 41.9 41.9 34.9 136.2 0 0 0 0 0 1
55 41.9 39.5 39.5 41.9 41.9 123.0 0 0 0 0 0 0
56 46.5 41.9 39.5 39.5 41.9 103.5 0 0 0 0 0 0
M7 M8 M9 M10 M11 t
1 0 0 0 0 0 1
2 0 0 0 0 0 2
3 0 0 0 0 0 3
4 0 0 0 0 0 4
5 0 0 0 0 0 5
6 0 0 0 0 0 6
7 1 0 0 0 0 7
8 0 1 0 0 0 8
9 0 0 1 0 0 9
10 0 0 0 1 0 10
11 0 0 0 0 1 11
12 0 0 0 0 0 12
13 0 0 0 0 0 13
14 0 0 0 0 0 14
15 0 0 0 0 0 15
16 0 0 0 0 0 16
17 0 0 0 0 0 17
18 0 0 0 0 0 18
19 1 0 0 0 0 19
20 0 1 0 0 0 20
21 0 0 1 0 0 21
22 0 0 0 1 0 22
23 0 0 0 0 1 23
24 0 0 0 0 0 24
25 0 0 0 0 0 25
26 0 0 0 0 0 26
27 0 0 0 0 0 27
28 0 0 0 0 0 28
29 0 0 0 0 0 29
30 0 0 0 0 0 30
31 1 0 0 0 0 31
32 0 1 0 0 0 32
33 0 0 1 0 0 33
34 0 0 0 1 0 34
35 0 0 0 0 1 35
36 0 0 0 0 0 36
37 0 0 0 0 0 37
38 0 0 0 0 0 38
39 0 0 0 0 0 39
40 0 0 0 0 0 40
41 0 0 0 0 0 41
42 0 0 0 0 0 42
43 1 0 0 0 0 43
44 0 1 0 0 0 44
45 0 0 1 0 0 45
46 0 0 0 1 0 46
47 0 0 0 0 1 47
48 0 0 0 0 0 48
49 0 0 0 0 0 49
50 0 0 0 0 0 50
51 0 0 0 0 0 51
52 0 0 0 0 0 52
53 0 0 0 0 0 53
54 0 0 0 0 0 54
55 1 0 0 0 0 55
56 0 1 0 0 0 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)` Productie
2.85104 0.97613 0.23637 0.13459 -0.34198 -0.08643
M1 M2 M3 M4 M5 M6
2.57043 8.04528 10.68526 5.13454 -2.36139 0.84038
M7 M8 M9 M10 M11 t
3.94041 7.08999 13.92405 0.82638 1.18104 0.06482
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-3.7986 -1.1514 -0.1193 0.8659 4.5657
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 2.85104 10.30659 0.277 0.783569
`Y(t-1)` 0.97613 0.15188 6.427 1.48e-07 ***
`Y(t-2)` 0.23637 0.21716 1.088 0.283264
`Y(t-3)` 0.13459 0.21623 0.622 0.537359
`Y(t-4)` -0.34198 0.17316 -1.975 0.055580 .
Productie -0.08643 0.05589 -1.546 0.130315
M1 2.57043 2.40670 1.068 0.292246
M2 8.04528 2.08431 3.860 0.000427 ***
M3 10.68526 2.78216 3.841 0.000452 ***
M4 5.13454 2.87356 1.787 0.081945 .
M5 -2.36139 2.51338 -0.940 0.353395
M6 0.84038 1.79216 0.469 0.641807
M7 3.94041 2.04567 1.926 0.061582 .
M8 7.08999 2.59709 2.730 0.009546 **
M9 13.92405 2.23946 6.218 2.86e-07 ***
M10 0.82638 2.85157 0.290 0.773547
M11 1.18104 2.56328 0.461 0.647601
t 0.06482 0.09596 0.676 0.503428
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 2.034 on 38 degrees of freedom
Multiple R-squared: 0.9928, Adjusted R-squared: 0.9895
F-statistic: 307.1 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,] 0.5114034 0.9771933 0.4885966
[2,] 0.3446576 0.6893152 0.6553424
[3,] 0.8419105 0.3161791 0.1580895
[4,] 0.7492497 0.5015007 0.2507503
[5,] 0.7078822 0.5842355 0.2921178
[6,] 0.6452810 0.7094380 0.3547190
[7,] 0.5790096 0.8419807 0.4209904
[8,] 0.4957606 0.9915213 0.5042394
[9,] 0.4320840 0.8641679 0.5679160
[10,] 0.4922701 0.9845402 0.5077299
[11,] 0.5825693 0.8348615 0.4174307
[12,] 0.4477621 0.8955242 0.5522379
[13,] 0.4017423 0.8034845 0.5982577
[14,] 0.4101919 0.8203838 0.5898081
[15,] 0.3035973 0.6071946 0.6964027
> postscript(file="/var/www/html/rcomp/tmp/1pbec1261307442.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2iu6r1261307442.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/33xv91261307442.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4h3so1261307442.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5jbu61261307442.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
2.34109291 0.07379422 2.57618167 1.35535253 -0.42378791 -0.78830498
7 8 9 10 11 12
-1.16580167 2.36756532 4.56567254 -1.47352560 -2.31186704 0.26501594
13 14 15 16 17 18
-2.19808862 1.17756651 0.62995296 1.78639652 -1.33886567 -0.53368783
19 20 21 22 23 24
-3.79857582 -0.51025325 0.36428979 -0.59689280 0.53831596 -0.03775771
25 26 27 28 29 30
-1.99934340 0.68489959 -2.02443153 -0.62904389 -1.51498848 -1.14658230
31 32 33 34 35 36
1.32460636 -0.21422279 -1.93521390 -0.20078326 0.92855695 0.37667698
37 38 39 40 41 42
-0.53849403 0.52718888 -0.40022884 -1.40393212 0.09374744 0.55436925
43 44 45 46 47 48
0.67014212 -2.29331735 -2.99474843 2.27120167 0.84499413 -0.60393522
49 50 51 52 53 54
2.39483315 -2.46344920 -0.78147425 -1.10877305 3.18389462 1.91420586
55 56
2.96962901 0.65022807
> postscript(file="/var/www/html/rcomp/tmp/6jxa81261307442.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 2.34109291 NA
1 0.07379422 2.34109291
2 2.57618167 0.07379422
3 1.35535253 2.57618167
4 -0.42378791 1.35535253
5 -0.78830498 -0.42378791
6 -1.16580167 -0.78830498
7 2.36756532 -1.16580167
8 4.56567254 2.36756532
9 -1.47352560 4.56567254
10 -2.31186704 -1.47352560
11 0.26501594 -2.31186704
12 -2.19808862 0.26501594
13 1.17756651 -2.19808862
14 0.62995296 1.17756651
15 1.78639652 0.62995296
16 -1.33886567 1.78639652
17 -0.53368783 -1.33886567
18 -3.79857582 -0.53368783
19 -0.51025325 -3.79857582
20 0.36428979 -0.51025325
21 -0.59689280 0.36428979
22 0.53831596 -0.59689280
23 -0.03775771 0.53831596
24 -1.99934340 -0.03775771
25 0.68489959 -1.99934340
26 -2.02443153 0.68489959
27 -0.62904389 -2.02443153
28 -1.51498848 -0.62904389
29 -1.14658230 -1.51498848
30 1.32460636 -1.14658230
31 -0.21422279 1.32460636
32 -1.93521390 -0.21422279
33 -0.20078326 -1.93521390
34 0.92855695 -0.20078326
35 0.37667698 0.92855695
36 -0.53849403 0.37667698
37 0.52718888 -0.53849403
38 -0.40022884 0.52718888
39 -1.40393212 -0.40022884
40 0.09374744 -1.40393212
41 0.55436925 0.09374744
42 0.67014212 0.55436925
43 -2.29331735 0.67014212
44 -2.99474843 -2.29331735
45 2.27120167 -2.99474843
46 0.84499413 2.27120167
47 -0.60393522 0.84499413
48 2.39483315 -0.60393522
49 -2.46344920 2.39483315
50 -0.78147425 -2.46344920
51 -1.10877305 -0.78147425
52 3.18389462 -1.10877305
53 1.91420586 3.18389462
54 2.96962901 1.91420586
55 0.65022807 2.96962901
56 NA 0.65022807
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 0.07379422 2.34109291
[2,] 2.57618167 0.07379422
[3,] 1.35535253 2.57618167
[4,] -0.42378791 1.35535253
[5,] -0.78830498 -0.42378791
[6,] -1.16580167 -0.78830498
[7,] 2.36756532 -1.16580167
[8,] 4.56567254 2.36756532
[9,] -1.47352560 4.56567254
[10,] -2.31186704 -1.47352560
[11,] 0.26501594 -2.31186704
[12,] -2.19808862 0.26501594
[13,] 1.17756651 -2.19808862
[14,] 0.62995296 1.17756651
[15,] 1.78639652 0.62995296
[16,] -1.33886567 1.78639652
[17,] -0.53368783 -1.33886567
[18,] -3.79857582 -0.53368783
[19,] -0.51025325 -3.79857582
[20,] 0.36428979 -0.51025325
[21,] -0.59689280 0.36428979
[22,] 0.53831596 -0.59689280
[23,] -0.03775771 0.53831596
[24,] -1.99934340 -0.03775771
[25,] 0.68489959 -1.99934340
[26,] -2.02443153 0.68489959
[27,] -0.62904389 -2.02443153
[28,] -1.51498848 -0.62904389
[29,] -1.14658230 -1.51498848
[30,] 1.32460636 -1.14658230
[31,] -0.21422279 1.32460636
[32,] -1.93521390 -0.21422279
[33,] -0.20078326 -1.93521390
[34,] 0.92855695 -0.20078326
[35,] 0.37667698 0.92855695
[36,] -0.53849403 0.37667698
[37,] 0.52718888 -0.53849403
[38,] -0.40022884 0.52718888
[39,] -1.40393212 -0.40022884
[40,] 0.09374744 -1.40393212
[41,] 0.55436925 0.09374744
[42,] 0.67014212 0.55436925
[43,] -2.29331735 0.67014212
[44,] -2.99474843 -2.29331735
[45,] 2.27120167 -2.99474843
[46,] 0.84499413 2.27120167
[47,] -0.60393522 0.84499413
[48,] 2.39483315 -0.60393522
[49,] -2.46344920 2.39483315
[50,] -0.78147425 -2.46344920
[51,] -1.10877305 -0.78147425
[52,] 3.18389462 -1.10877305
[53,] 1.91420586 3.18389462
[54,] 2.96962901 1.91420586
[55,] 0.65022807 2.96962901
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 0.07379422 2.34109291
2 2.57618167 0.07379422
3 1.35535253 2.57618167
4 -0.42378791 1.35535253
5 -0.78830498 -0.42378791
6 -1.16580167 -0.78830498
7 2.36756532 -1.16580167
8 4.56567254 2.36756532
9 -1.47352560 4.56567254
10 -2.31186704 -1.47352560
11 0.26501594 -2.31186704
12 -2.19808862 0.26501594
13 1.17756651 -2.19808862
14 0.62995296 1.17756651
15 1.78639652 0.62995296
16 -1.33886567 1.78639652
17 -0.53368783 -1.33886567
18 -3.79857582 -0.53368783
19 -0.51025325 -3.79857582
20 0.36428979 -0.51025325
21 -0.59689280 0.36428979
22 0.53831596 -0.59689280
23 -0.03775771 0.53831596
24 -1.99934340 -0.03775771
25 0.68489959 -1.99934340
26 -2.02443153 0.68489959
27 -0.62904389 -2.02443153
28 -1.51498848 -0.62904389
29 -1.14658230 -1.51498848
30 1.32460636 -1.14658230
31 -0.21422279 1.32460636
32 -1.93521390 -0.21422279
33 -0.20078326 -1.93521390
34 0.92855695 -0.20078326
35 0.37667698 0.92855695
36 -0.53849403 0.37667698
37 0.52718888 -0.53849403
38 -0.40022884 0.52718888
39 -1.40393212 -0.40022884
40 0.09374744 -1.40393212
41 0.55436925 0.09374744
42 0.67014212 0.55436925
43 -2.29331735 0.67014212
44 -2.99474843 -2.29331735
45 2.27120167 -2.99474843
46 0.84499413 2.27120167
47 -0.60393522 0.84499413
48 2.39483315 -0.60393522
49 -2.46344920 2.39483315
50 -0.78147425 -2.46344920
51 -1.10877305 -0.78147425
52 3.18389462 -1.10877305
53 1.91420586 3.18389462
54 2.96962901 1.91420586
55 0.65022807 2.96962901
> 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/7dd761261307442.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8idq81261307442.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/92o9i1261307442.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10n41y1261307442.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11362w1261307442.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/1297b81261307442.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/13ky9r1261307442.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/14u7n51261307442.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/15ppqf1261307442.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/16bx7v1261307442.tab")
+ }
>
> try(system("convert tmp/1pbec1261307442.ps tmp/1pbec1261307442.png",intern=TRUE))
character(0)
> try(system("convert tmp/2iu6r1261307442.ps tmp/2iu6r1261307442.png",intern=TRUE))
character(0)
> try(system("convert tmp/33xv91261307442.ps tmp/33xv91261307442.png",intern=TRUE))
character(0)
> try(system("convert tmp/4h3so1261307442.ps tmp/4h3so1261307442.png",intern=TRUE))
character(0)
> try(system("convert tmp/5jbu61261307442.ps tmp/5jbu61261307442.png",intern=TRUE))
character(0)
> try(system("convert tmp/6jxa81261307442.ps tmp/6jxa81261307442.png",intern=TRUE))
character(0)
> try(system("convert tmp/7dd761261307442.ps tmp/7dd761261307442.png",intern=TRUE))
character(0)
> try(system("convert tmp/8idq81261307442.ps tmp/8idq81261307442.png",intern=TRUE))
character(0)
> try(system("convert tmp/92o9i1261307442.ps tmp/92o9i1261307442.png",intern=TRUE))
character(0)
> try(system("convert tmp/10n41y1261307442.ps tmp/10n41y1261307442.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
2.305 1.532 3.728