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 'contributors()' for more information and
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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(100.4
+ ,120.2
+ ,17
+ ,74
+ ,79.9
+ ,72.9
+ ,72.9
+ ,103
+ ,122.1
+ ,16
+ ,76
+ ,74
+ ,79.9
+ ,72.9
+ ,99
+ ,119.3
+ ,20
+ ,69.6
+ ,76
+ ,74
+ ,79.9
+ ,104.8
+ ,121.7
+ ,24
+ ,77.3
+ ,69.6
+ ,76
+ ,74
+ ,104.5
+ ,113.5
+ ,23
+ ,75.2
+ ,77.3
+ ,69.6
+ ,76
+ ,104.8
+ ,123.7
+ ,20
+ ,75.8
+ ,75.2
+ ,77.3
+ ,69.6
+ ,103.8
+ ,123.4
+ ,21
+ ,77.6
+ ,75.8
+ ,75.2
+ ,77.3
+ ,106.3
+ ,126.4
+ ,19
+ ,76.7
+ ,77.6
+ ,75.8
+ ,75.2
+ ,105.2
+ ,124.1
+ ,23
+ ,77
+ ,76.7
+ ,77.6
+ ,75.8
+ ,108.2
+ ,125.6
+ ,23
+ ,77.9
+ ,77
+ ,76.7
+ ,77.6
+ ,106.2
+ ,124.8
+ ,23
+ ,76.7
+ ,77.9
+ ,77
+ ,76.7
+ ,103.9
+ ,123
+ ,23
+ ,71.9
+ ,76.7
+ ,77.9
+ ,77
+ ,104.9
+ ,126.9
+ ,27
+ ,73.4
+ ,71.9
+ ,76.7
+ ,77.9
+ ,106.2
+ ,127.3
+ ,26
+ ,72.5
+ ,73.4
+ ,71.9
+ ,76.7
+ ,107.9
+ ,129
+ ,17
+ ,73.7
+ ,72.5
+ ,73.4
+ ,71.9
+ ,106.9
+ ,126.2
+ ,24
+ ,69.5
+ ,73.7
+ ,72.5
+ ,73.4
+ ,110.3
+ ,125.4
+ ,26
+ ,74.7
+ ,69.5
+ ,73.7
+ ,72.5
+ ,109.8
+ ,126.3
+ ,24
+ ,72.5
+ ,74.7
+ ,69.5
+ ,73.7
+ ,108.3
+ ,126.3
+ ,27
+ ,72.1
+ ,72.5
+ ,74.7
+ ,69.5
+ ,110.9
+ ,128.4
+ ,27
+ ,70.7
+ ,72.1
+ ,72.5
+ ,74.7
+ ,109.8
+ ,127.2
+ ,26
+ ,71.4
+ ,70.7
+ ,72.1
+ ,72.5
+ ,109.3
+ ,128.5
+ ,24
+ ,69.5
+ ,71.4
+ ,70.7
+ ,72.1
+ ,109
+ ,129
+ ,23
+ ,73.5
+ ,69.5
+ ,71.4
+ ,70.7
+ ,107.9
+ ,128.9
+ ,23
+ ,72.4
+ ,73.5
+ ,69.5
+ ,71.4
+ ,108.4
+ ,128.3
+ ,24
+ ,74.5
+ ,72.4
+ ,73.5
+ ,69.5
+ ,107.2
+ ,124.6
+ ,17
+ ,72.2
+ ,74.5
+ ,72.4
+ ,73.5
+ ,109.5
+ ,126.2
+ ,21
+ ,73
+ ,72.2
+ ,74.5
+ ,72.4
+ ,109.9
+ ,129.1
+ ,19
+ ,73.3
+ ,73
+ ,72.2
+ ,74.5
+ ,108
+ ,127.3
+ ,22
+ ,71.3
+ ,73.3
+ ,73
+ ,72.2
+ ,114.7
+ ,129.2
+ ,22
+ ,73.6
+ ,71.3
+ ,73.3
+ ,73
+ ,115.6
+ ,130.4
+ ,18
+ ,71.3
+ ,73.6
+ ,71.3
+ ,73.3
+ ,107.6
+ ,125.9
+ ,16
+ ,71.2
+ ,71.3
+ ,73.6
+ ,71.3
+ ,115.9
+ ,135.8
+ ,14
+ ,81.4
+ ,71.2
+ ,71.3
+ ,73.6
+ ,111.8
+ ,126.4
+ ,12
+ ,76.1
+ ,81.4
+ ,71.2
+ ,71.3
+ ,110
+ ,129.5
+ ,14
+ ,71.1
+ ,76.1
+ ,81.4
+ ,71.2
+ ,109.2
+ ,128.4
+ ,16
+ ,75.7
+ ,71.1
+ ,76.1
+ ,81.4
+ ,108
+ ,125.6
+ ,8
+ ,70
+ ,75.7
+ ,71.1
+ ,76.1
+ ,105.6
+ ,127.7
+ ,3
+ ,68.5
+ ,70
+ ,75.7
+ ,71.1
+ ,103
+ ,126.4
+ ,0
+ ,56.7
+ ,68.5
+ ,70
+ ,75.7
+ ,99.6
+ ,124.2
+ ,5
+ ,57.9
+ ,56.7
+ ,68.5
+ ,70
+ ,97.9
+ ,126.4
+ ,1
+ ,58.8
+ ,57.9
+ ,56.7
+ ,68.5
+ ,97.6
+ ,123.7
+ ,1
+ ,59.3
+ ,58.8
+ ,57.9
+ ,56.7
+ ,96.2
+ ,121.8
+ ,3
+ ,61.3
+ ,59.3
+ ,58.8
+ ,57.9
+ ,97.9
+ ,124
+ ,6
+ ,62.9
+ ,61.3
+ ,59.3
+ ,58.8
+ ,94.5
+ ,122.7
+ ,7
+ ,61.4
+ ,62.9
+ ,61.3
+ ,59.3
+ ,95.4
+ ,122.9
+ ,8
+ ,64.5
+ ,61.4
+ ,62.9
+ ,61.3
+ ,94.4
+ ,121
+ ,14
+ ,63.8
+ ,64.5
+ ,61.4
+ ,62.9
+ ,96.3
+ ,122.8
+ ,14
+ ,61.6
+ ,63.8
+ ,64.5
+ ,61.4
+ ,95.1
+ ,122.9
+ ,13
+ ,64.7
+ ,61.6
+ ,63.8
+ ,64.5)
+ ,dim=c(7
+ ,49)
+ ,dimnames=list(c('totid'
+ ,'ndzcg'
+ ,'indc'
+ ,'Y'
+ ,'y1'
+ ,'y2'
+ ,'y3
')
+ ,1:49))
> y <- array(NA,dim=c(7,49),dimnames=list(c('totid','ndzcg','indc','Y','y1','y2','y3
'),1:49))
> 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 = '4'
> #'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 totid ndzcg indc y1 y2 y3\r M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 74.0 100.4 120.2 17 79.9 72.9 72.9 1 0 0 0 0 0 0 0 0 0 0 1
2 76.0 103.0 122.1 16 74.0 79.9 72.9 0 1 0 0 0 0 0 0 0 0 0 2
3 69.6 99.0 119.3 20 76.0 74.0 79.9 0 0 1 0 0 0 0 0 0 0 0 3
4 77.3 104.8 121.7 24 69.6 76.0 74.0 0 0 0 1 0 0 0 0 0 0 0 4
5 75.2 104.5 113.5 23 77.3 69.6 76.0 0 0 0 0 1 0 0 0 0 0 0 5
6 75.8 104.8 123.7 20 75.2 77.3 69.6 0 0 0 0 0 1 0 0 0 0 0 6
7 77.6 103.8 123.4 21 75.8 75.2 77.3 0 0 0 0 0 0 1 0 0 0 0 7
8 76.7 106.3 126.4 19 77.6 75.8 75.2 0 0 0 0 0 0 0 1 0 0 0 8
9 77.0 105.2 124.1 23 76.7 77.6 75.8 0 0 0 0 0 0 0 0 1 0 0 9
10 77.9 108.2 125.6 23 77.0 76.7 77.6 0 0 0 0 0 0 0 0 0 1 0 10
11 76.7 106.2 124.8 23 77.9 77.0 76.7 0 0 0 0 0 0 0 0 0 0 1 11
12 71.9 103.9 123.0 23 76.7 77.9 77.0 0 0 0 0 0 0 0 0 0 0 0 12
13 73.4 104.9 126.9 27 71.9 76.7 77.9 1 0 0 0 0 0 0 0 0 0 0 13
14 72.5 106.2 127.3 26 73.4 71.9 76.7 0 1 0 0 0 0 0 0 0 0 0 14
15 73.7 107.9 129.0 17 72.5 73.4 71.9 0 0 1 0 0 0 0 0 0 0 0 15
16 69.5 106.9 126.2 24 73.7 72.5 73.4 0 0 0 1 0 0 0 0 0 0 0 16
17 74.7 110.3 125.4 26 69.5 73.7 72.5 0 0 0 0 1 0 0 0 0 0 0 17
18 72.5 109.8 126.3 24 74.7 69.5 73.7 0 0 0 0 0 1 0 0 0 0 0 18
19 72.1 108.3 126.3 27 72.5 74.7 69.5 0 0 0 0 0 0 1 0 0 0 0 19
20 70.7 110.9 128.4 27 72.1 72.5 74.7 0 0 0 0 0 0 0 1 0 0 0 20
21 71.4 109.8 127.2 26 70.7 72.1 72.5 0 0 0 0 0 0 0 0 1 0 0 21
22 69.5 109.3 128.5 24 71.4 70.7 72.1 0 0 0 0 0 0 0 0 0 1 0 22
23 73.5 109.0 129.0 23 69.5 71.4 70.7 0 0 0 0 0 0 0 0 0 0 1 23
24 72.4 107.9 128.9 23 73.5 69.5 71.4 0 0 0 0 0 0 0 0 0 0 0 24
25 74.5 108.4 128.3 24 72.4 73.5 69.5 1 0 0 0 0 0 0 0 0 0 0 25
26 72.2 107.2 124.6 17 74.5 72.4 73.5 0 1 0 0 0 0 0 0 0 0 0 26
27 73.0 109.5 126.2 21 72.2 74.5 72.4 0 0 1 0 0 0 0 0 0 0 0 27
28 73.3 109.9 129.1 19 73.0 72.2 74.5 0 0 0 1 0 0 0 0 0 0 0 28
29 71.3 108.0 127.3 22 73.3 73.0 72.2 0 0 0 0 1 0 0 0 0 0 0 29
30 73.6 114.7 129.2 22 71.3 73.3 73.0 0 0 0 0 0 1 0 0 0 0 0 30
31 71.3 115.6 130.4 18 73.6 71.3 73.3 0 0 0 0 0 0 1 0 0 0 0 31
32 71.2 107.6 125.9 16 71.3 73.6 71.3 0 0 0 0 0 0 0 1 0 0 0 32
33 81.4 115.9 135.8 14 71.2 71.3 73.6 0 0 0 0 0 0 0 0 1 0 0 33
34 76.1 111.8 126.4 12 81.4 71.2 71.3 0 0 0 0 0 0 0 0 0 1 0 34
35 71.1 110.0 129.5 14 76.1 81.4 71.2 0 0 0 0 0 0 0 0 0 0 1 35
36 75.7 109.2 128.4 16 71.1 76.1 81.4 0 0 0 0 0 0 0 0 0 0 0 36
37 70.0 108.0 125.6 8 75.7 71.1 76.1 1 0 0 0 0 0 0 0 0 0 0 37
38 68.5 105.6 127.7 3 70.0 75.7 71.1 0 1 0 0 0 0 0 0 0 0 0 38
39 56.7 103.0 126.4 0 68.5 70.0 75.7 0 0 1 0 0 0 0 0 0 0 0 39
40 57.9 99.6 124.2 5 56.7 68.5 70.0 0 0 0 1 0 0 0 0 0 0 0 40
41 58.8 97.9 126.4 1 57.9 56.7 68.5 0 0 0 0 1 0 0 0 0 0 0 41
42 59.3 97.6 123.7 1 58.8 57.9 56.7 0 0 0 0 0 1 0 0 0 0 0 42
43 61.3 96.2 121.8 3 59.3 58.8 57.9 0 0 0 0 0 0 1 0 0 0 0 43
44 62.9 97.9 124.0 6 61.3 59.3 58.8 0 0 0 0 0 0 0 1 0 0 0 44
45 61.4 94.5 122.7 7 62.9 61.3 59.3 0 0 0 0 0 0 0 0 1 0 0 45
46 64.5 95.4 122.9 8 61.4 62.9 61.3 0 0 0 0 0 0 0 0 0 1 0 46
47 63.8 94.4 121.0 14 64.5 61.4 62.9 0 0 0 0 0 0 0 0 0 0 1 47
48 61.6 96.3 122.8 14 63.8 64.5 61.4 0 0 0 0 0 0 0 0 0 0 0 48
49 64.7 95.1 122.9 13 61.6 63.8 64.5 1 0 0 0 0 0 0 0 0 0 0 49
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) totid ndzcg indc y1 y2
20.25132 0.42534 -0.04554 0.04368 0.18834 0.16357
`y3\r` M1 M2 M3 M4 M5
-0.13097 0.29651 -0.83584 -3.76745 -2.08061 -1.12031
M6 M7 M8 M9 M10 M11
-1.97032 -1.21767 -1.11621 1.25634 0.26910 -0.08551
t
-0.16644
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-5.7830 -1.1662 0.1615 1.2789 6.2280
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 20.25132 23.26808 0.870 0.3910
totid 0.42534 0.24450 1.740 0.0922 .
ndzcg -0.04554 0.26858 -0.170 0.8665
indc 0.04368 0.10458 0.418 0.6792
y1 0.18834 0.18955 0.994 0.3283
y2 0.16357 0.16883 0.969 0.3404
`y3\r` -0.13097 0.16344 -0.801 0.4292
M1 0.29651 2.12716 0.139 0.8901
M2 -0.83584 2.41593 -0.346 0.7318
M3 -3.76745 2.40512 -1.566 0.1277
M4 -2.08061 2.52678 -0.823 0.4168
M5 -1.12031 2.68075 -0.418 0.6790
M6 -1.97032 2.71805 -0.725 0.4741
M7 -1.21767 2.51746 -0.484 0.6321
M8 -1.11621 2.40973 -0.463 0.6466
M9 1.25634 2.38567 0.527 0.6023
M10 0.26910 2.36299 0.114 0.9101
M11 -0.08551 2.25996 -0.038 0.9701
t -0.16644 0.07748 -2.148 0.0399 *
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 3.108 on 30 degrees of freedom
Multiple R-squared: 0.8277, Adjusted R-squared: 0.7243
F-statistic: 8.004 on 18 and 30 DF, p-value: 4.226e-07
> 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,] 0.07163750 0.14327499 0.9283625
[2,] 0.04892777 0.09785553 0.9510722
[3,] 0.04091235 0.08182471 0.9590876
[4,] 0.27685878 0.55371757 0.7231412
[5,] 0.41717679 0.83435359 0.5828232
[6,] 0.30660265 0.61320530 0.6933974
> postscript(file="/var/www/html/rcomp/tmp/1ycms1258661103.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2wbni1258661103.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/38xem1258661103.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4c5di1258661103.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/501921258661103.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 = 49
Frequency = 1
1 2 3 4 5 6
-1.77902536 0.51035512 0.11266870 3.86543387 0.62790281 1.01021204
7 8 9 10 11 12
3.83094350 1.44436888 -0.31966265 0.85276065 0.65160867 -3.05306124
13 14 15 16 17 18
-0.88736542 -0.63417074 2.70687135 -2.90382430 0.40925027 -0.56852201
19 20 21 22 23 24
-2.03401001 -3.26305960 -4.27127879 -4.61358999 0.16151897 -0.74514943
25 26 27 28 29 30
0.24517130 0.19989337 2.96345376 2.29292126 -0.39439470 0.59119432
31 32 33 34 35 36
-2.51520748 0.52996455 6.22804576 1.27888651 -3.06387829 4.96436648
37 38 39 40 41 42
-0.87605299 -0.07607776 -5.78299381 -3.25453083 -0.64275838 -1.03288435
43 44 45 46 47 48
0.71827399 1.28872617 -1.63710432 2.48194283 2.25075065 -1.16615581
49
3.29727246
> postscript(file="/var/www/html/rcomp/tmp/6ecu61258661103.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 = 49
Frequency = 1
lag(myerror, k = 1) myerror
0 -1.77902536 NA
1 0.51035512 -1.77902536
2 0.11266870 0.51035512
3 3.86543387 0.11266870
4 0.62790281 3.86543387
5 1.01021204 0.62790281
6 3.83094350 1.01021204
7 1.44436888 3.83094350
8 -0.31966265 1.44436888
9 0.85276065 -0.31966265
10 0.65160867 0.85276065
11 -3.05306124 0.65160867
12 -0.88736542 -3.05306124
13 -0.63417074 -0.88736542
14 2.70687135 -0.63417074
15 -2.90382430 2.70687135
16 0.40925027 -2.90382430
17 -0.56852201 0.40925027
18 -2.03401001 -0.56852201
19 -3.26305960 -2.03401001
20 -4.27127879 -3.26305960
21 -4.61358999 -4.27127879
22 0.16151897 -4.61358999
23 -0.74514943 0.16151897
24 0.24517130 -0.74514943
25 0.19989337 0.24517130
26 2.96345376 0.19989337
27 2.29292126 2.96345376
28 -0.39439470 2.29292126
29 0.59119432 -0.39439470
30 -2.51520748 0.59119432
31 0.52996455 -2.51520748
32 6.22804576 0.52996455
33 1.27888651 6.22804576
34 -3.06387829 1.27888651
35 4.96436648 -3.06387829
36 -0.87605299 4.96436648
37 -0.07607776 -0.87605299
38 -5.78299381 -0.07607776
39 -3.25453083 -5.78299381
40 -0.64275838 -3.25453083
41 -1.03288435 -0.64275838
42 0.71827399 -1.03288435
43 1.28872617 0.71827399
44 -1.63710432 1.28872617
45 2.48194283 -1.63710432
46 2.25075065 2.48194283
47 -1.16615581 2.25075065
48 3.29727246 -1.16615581
49 NA 3.29727246
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 0.51035512 -1.77902536
[2,] 0.11266870 0.51035512
[3,] 3.86543387 0.11266870
[4,] 0.62790281 3.86543387
[5,] 1.01021204 0.62790281
[6,] 3.83094350 1.01021204
[7,] 1.44436888 3.83094350
[8,] -0.31966265 1.44436888
[9,] 0.85276065 -0.31966265
[10,] 0.65160867 0.85276065
[11,] -3.05306124 0.65160867
[12,] -0.88736542 -3.05306124
[13,] -0.63417074 -0.88736542
[14,] 2.70687135 -0.63417074
[15,] -2.90382430 2.70687135
[16,] 0.40925027 -2.90382430
[17,] -0.56852201 0.40925027
[18,] -2.03401001 -0.56852201
[19,] -3.26305960 -2.03401001
[20,] -4.27127879 -3.26305960
[21,] -4.61358999 -4.27127879
[22,] 0.16151897 -4.61358999
[23,] -0.74514943 0.16151897
[24,] 0.24517130 -0.74514943
[25,] 0.19989337 0.24517130
[26,] 2.96345376 0.19989337
[27,] 2.29292126 2.96345376
[28,] -0.39439470 2.29292126
[29,] 0.59119432 -0.39439470
[30,] -2.51520748 0.59119432
[31,] 0.52996455 -2.51520748
[32,] 6.22804576 0.52996455
[33,] 1.27888651 6.22804576
[34,] -3.06387829 1.27888651
[35,] 4.96436648 -3.06387829
[36,] -0.87605299 4.96436648
[37,] -0.07607776 -0.87605299
[38,] -5.78299381 -0.07607776
[39,] -3.25453083 -5.78299381
[40,] -0.64275838 -3.25453083
[41,] -1.03288435 -0.64275838
[42,] 0.71827399 -1.03288435
[43,] 1.28872617 0.71827399
[44,] -1.63710432 1.28872617
[45,] 2.48194283 -1.63710432
[46,] 2.25075065 2.48194283
[47,] -1.16615581 2.25075065
[48,] 3.29727246 -1.16615581
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 0.51035512 -1.77902536
2 0.11266870 0.51035512
3 3.86543387 0.11266870
4 0.62790281 3.86543387
5 1.01021204 0.62790281
6 3.83094350 1.01021204
7 1.44436888 3.83094350
8 -0.31966265 1.44436888
9 0.85276065 -0.31966265
10 0.65160867 0.85276065
11 -3.05306124 0.65160867
12 -0.88736542 -3.05306124
13 -0.63417074 -0.88736542
14 2.70687135 -0.63417074
15 -2.90382430 2.70687135
16 0.40925027 -2.90382430
17 -0.56852201 0.40925027
18 -2.03401001 -0.56852201
19 -3.26305960 -2.03401001
20 -4.27127879 -3.26305960
21 -4.61358999 -4.27127879
22 0.16151897 -4.61358999
23 -0.74514943 0.16151897
24 0.24517130 -0.74514943
25 0.19989337 0.24517130
26 2.96345376 0.19989337
27 2.29292126 2.96345376
28 -0.39439470 2.29292126
29 0.59119432 -0.39439470
30 -2.51520748 0.59119432
31 0.52996455 -2.51520748
32 6.22804576 0.52996455
33 1.27888651 6.22804576
34 -3.06387829 1.27888651
35 4.96436648 -3.06387829
36 -0.87605299 4.96436648
37 -0.07607776 -0.87605299
38 -5.78299381 -0.07607776
39 -3.25453083 -5.78299381
40 -0.64275838 -3.25453083
41 -1.03288435 -0.64275838
42 0.71827399 -1.03288435
43 1.28872617 0.71827399
44 -1.63710432 1.28872617
45 2.48194283 -1.63710432
46 2.25075065 2.48194283
47 -1.16615581 2.25075065
48 3.29727246 -1.16615581
> 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/7uky91258661103.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8p1yo1258661103.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9mibd1258661103.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/107ohf1258661103.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11optn1258661103.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/12ev8d1258661103.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/133ckh1258661103.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/14o8b81258661103.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/155iup1258661103.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/16t8321258661103.tab")
+ }
>
> system("convert tmp/1ycms1258661103.ps tmp/1ycms1258661103.png")
> system("convert tmp/2wbni1258661103.ps tmp/2wbni1258661103.png")
> system("convert tmp/38xem1258661103.ps tmp/38xem1258661103.png")
> system("convert tmp/4c5di1258661103.ps tmp/4c5di1258661103.png")
> system("convert tmp/501921258661103.ps tmp/501921258661103.png")
> system("convert tmp/6ecu61258661103.ps tmp/6ecu61258661103.png")
> system("convert tmp/7uky91258661103.ps tmp/7uky91258661103.png")
> system("convert tmp/8p1yo1258661103.ps tmp/8p1yo1258661103.png")
> system("convert tmp/9mibd1258661103.ps tmp/9mibd1258661103.png")
> system("convert tmp/107ohf1258661103.ps tmp/107ohf1258661103.png")
>
>
> proc.time()
user system elapsed
2.292 1.608 2.915