R version 2.8.0 (2008-10-20)
Copyright (C) 2008 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.
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Natural language support but running in an English locale
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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
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> x <- array(list(102.86
+ ,102.38
+ ,102.37
+ ,101.76
+ ,102.87
+ ,102.86
+ ,102.38
+ ,102.37
+ ,102.92
+ ,102.87
+ ,102.86
+ ,102.38
+ ,102.95
+ ,102.92
+ ,102.87
+ ,102.86
+ ,103.02
+ ,102.95
+ ,102.92
+ ,102.87
+ ,104.08
+ ,103.02
+ ,102.95
+ ,102.92
+ ,104.16
+ ,104.08
+ ,103.02
+ ,102.95
+ ,104.24
+ ,104.16
+ ,104.08
+ ,103.02
+ ,104.33
+ ,104.24
+ ,104.16
+ ,104.08
+ ,104.73
+ ,104.33
+ ,104.24
+ ,104.16
+ ,104.86
+ ,104.73
+ ,104.33
+ ,104.24
+ ,105.03
+ ,104.86
+ ,104.73
+ ,104.33
+ ,105.62
+ ,105.03
+ ,104.86
+ ,104.73
+ ,105.63
+ ,105.62
+ ,105.03
+ ,104.86
+ ,105.63
+ ,105.63
+ ,105.62
+ ,105.03
+ ,105.94
+ ,105.63
+ ,105.63
+ ,105.62
+ ,106.61
+ ,105.94
+ ,105.63
+ ,105.63
+ ,107.69
+ ,106.61
+ ,105.94
+ ,105.63
+ ,107.78
+ ,107.69
+ ,106.61
+ ,105.94
+ ,107.93
+ ,107.78
+ ,107.69
+ ,106.61
+ ,108.48
+ ,107.93
+ ,107.78
+ ,107.69
+ ,108.14
+ ,108.48
+ ,107.93
+ ,107.78
+ ,108.48
+ ,108.14
+ ,108.48
+ ,107.93
+ ,108.48
+ ,108.48
+ ,108.14
+ ,108.48
+ ,108.89
+ ,108.48
+ ,108.48
+ ,108.14
+ ,108.93
+ ,108.89
+ ,108.48
+ ,108.48
+ ,109.21
+ ,108.93
+ ,108.89
+ ,108.48
+ ,109.47
+ ,109.21
+ ,108.93
+ ,108.89
+ ,109.80
+ ,109.47
+ ,109.21
+ ,108.93
+ ,111.73
+ ,109.80
+ ,109.47
+ ,109.21
+ ,111.85
+ ,111.73
+ ,109.80
+ ,109.47
+ ,112.12
+ ,111.85
+ ,111.73
+ ,109.80
+ ,112.15
+ ,112.12
+ ,111.85
+ ,111.73
+ ,112.17
+ ,112.15
+ ,112.12
+ ,111.85
+ ,112.67
+ ,112.17
+ ,112.15
+ ,112.12
+ ,112.80
+ ,112.67
+ ,112.17
+ ,112.15
+ ,113.44
+ ,112.80
+ ,112.67
+ ,112.17
+ ,113.53
+ ,113.44
+ ,112.80
+ ,112.67
+ ,114.53
+ ,113.53
+ ,113.44
+ ,112.80
+ ,114.51
+ ,114.53
+ ,113.53
+ ,113.44
+ ,115.05
+ ,114.51
+ ,114.53
+ ,113.53
+ ,116.67
+ ,115.05
+ ,114.51
+ ,114.53
+ ,117.07
+ ,116.67
+ ,115.05
+ ,114.51
+ ,116.92
+ ,117.07
+ ,116.67
+ ,115.05
+ ,117.00
+ ,116.92
+ ,117.07
+ ,116.67
+ ,117.02
+ ,117.00
+ ,116.92
+ ,117.07
+ ,117.35
+ ,117.02
+ ,117.00
+ ,116.92
+ ,117.36
+ ,117.35
+ ,117.02
+ ,117.00
+ ,117.82
+ ,117.36
+ ,117.35
+ ,117.02
+ ,117.88
+ ,117.82
+ ,117.36
+ ,117.35
+ ,118.24
+ ,117.88
+ ,117.82
+ ,117.36
+ ,118.50
+ ,118.24
+ ,117.88
+ ,117.82
+ ,118.80
+ ,118.50
+ ,118.24
+ ,117.88
+ ,119.76
+ ,118.80
+ ,118.50
+ ,118.24
+ ,120.09
+ ,119.76
+ ,118.80
+ ,118.50)
+ ,dim=c(4
+ ,55)
+ ,dimnames=list(c('Y1'
+ ,'Y2'
+ ,'Y3'
+ ,'Y4')
+ ,1:55))
> y <- array(NA,dim=c(4,55),dimnames=list(c('Y1','Y2','Y3','Y4'),1:55))
> 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
Y1 Y2 Y3 Y4 M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 102.86 102.38 102.37 101.76 1 0 0 0 0 0 0 0 0 0 0 1
2 102.87 102.86 102.38 102.37 0 1 0 0 0 0 0 0 0 0 0 2
3 102.92 102.87 102.86 102.38 0 0 1 0 0 0 0 0 0 0 0 3
4 102.95 102.92 102.87 102.86 0 0 0 1 0 0 0 0 0 0 0 4
5 103.02 102.95 102.92 102.87 0 0 0 0 1 0 0 0 0 0 0 5
6 104.08 103.02 102.95 102.92 0 0 0 0 0 1 0 0 0 0 0 6
7 104.16 104.08 103.02 102.95 0 0 0 0 0 0 1 0 0 0 0 7
8 104.24 104.16 104.08 103.02 0 0 0 0 0 0 0 1 0 0 0 8
9 104.33 104.24 104.16 104.08 0 0 0 0 0 0 0 0 1 0 0 9
10 104.73 104.33 104.24 104.16 0 0 0 0 0 0 0 0 0 1 0 10
11 104.86 104.73 104.33 104.24 0 0 0 0 0 0 0 0 0 0 1 11
12 105.03 104.86 104.73 104.33 0 0 0 0 0 0 0 0 0 0 0 12
13 105.62 105.03 104.86 104.73 1 0 0 0 0 0 0 0 0 0 0 13
14 105.63 105.62 105.03 104.86 0 1 0 0 0 0 0 0 0 0 0 14
15 105.63 105.63 105.62 105.03 0 0 1 0 0 0 0 0 0 0 0 15
16 105.94 105.63 105.63 105.62 0 0 0 1 0 0 0 0 0 0 0 16
17 106.61 105.94 105.63 105.63 0 0 0 0 1 0 0 0 0 0 0 17
18 107.69 106.61 105.94 105.63 0 0 0 0 0 1 0 0 0 0 0 18
19 107.78 107.69 106.61 105.94 0 0 0 0 0 0 1 0 0 0 0 19
20 107.93 107.78 107.69 106.61 0 0 0 0 0 0 0 1 0 0 0 20
21 108.48 107.93 107.78 107.69 0 0 0 0 0 0 0 0 1 0 0 21
22 108.14 108.48 107.93 107.78 0 0 0 0 0 0 0 0 0 1 0 22
23 108.48 108.14 108.48 107.93 0 0 0 0 0 0 0 0 0 0 1 23
24 108.48 108.48 108.14 108.48 0 0 0 0 0 0 0 0 0 0 0 24
25 108.89 108.48 108.48 108.14 1 0 0 0 0 0 0 0 0 0 0 25
26 108.93 108.89 108.48 108.48 0 1 0 0 0 0 0 0 0 0 0 26
27 109.21 108.93 108.89 108.48 0 0 1 0 0 0 0 0 0 0 0 27
28 109.47 109.21 108.93 108.89 0 0 0 1 0 0 0 0 0 0 0 28
29 109.80 109.47 109.21 108.93 0 0 0 0 1 0 0 0 0 0 0 29
30 111.73 109.80 109.47 109.21 0 0 0 0 0 1 0 0 0 0 0 30
31 111.85 111.73 109.80 109.47 0 0 0 0 0 0 1 0 0 0 0 31
32 112.12 111.85 111.73 109.80 0 0 0 0 0 0 0 1 0 0 0 32
33 112.15 112.12 111.85 111.73 0 0 0 0 0 0 0 0 1 0 0 33
34 112.17 112.15 112.12 111.85 0 0 0 0 0 0 0 0 0 1 0 34
35 112.67 112.17 112.15 112.12 0 0 0 0 0 0 0 0 0 0 1 35
36 112.80 112.67 112.17 112.15 0 0 0 0 0 0 0 0 0 0 0 36
37 113.44 112.80 112.67 112.17 1 0 0 0 0 0 0 0 0 0 0 37
38 113.53 113.44 112.80 112.67 0 1 0 0 0 0 0 0 0 0 0 38
39 114.53 113.53 113.44 112.80 0 0 1 0 0 0 0 0 0 0 0 39
40 114.51 114.53 113.53 113.44 0 0 0 1 0 0 0 0 0 0 0 40
41 115.05 114.51 114.53 113.53 0 0 0 0 1 0 0 0 0 0 0 41
42 116.67 115.05 114.51 114.53 0 0 0 0 0 1 0 0 0 0 0 42
43 117.07 116.67 115.05 114.51 0 0 0 0 0 0 1 0 0 0 0 43
44 116.92 117.07 116.67 115.05 0 0 0 0 0 0 0 1 0 0 0 44
45 117.00 116.92 117.07 116.67 0 0 0 0 0 0 0 0 1 0 0 45
46 117.02 117.00 116.92 117.07 0 0 0 0 0 0 0 0 0 1 0 46
47 117.35 117.02 117.00 116.92 0 0 0 0 0 0 0 0 0 0 1 47
48 117.36 117.35 117.02 117.00 0 0 0 0 0 0 0 0 0 0 0 48
49 117.82 117.36 117.35 117.02 1 0 0 0 0 0 0 0 0 0 0 49
50 117.88 117.82 117.36 117.35 0 1 0 0 0 0 0 0 0 0 0 50
51 118.24 117.88 117.82 117.36 0 0 1 0 0 0 0 0 0 0 0 51
52 118.50 118.24 117.88 117.82 0 0 0 1 0 0 0 0 0 0 0 52
53 118.80 118.50 118.24 117.88 0 0 0 0 1 0 0 0 0 0 0 53
54 119.76 118.80 118.50 118.24 0 0 0 0 0 1 0 0 0 0 0 54
55 120.09 119.76 118.80 118.50 0 0 0 0 0 0 1 0 0 0 0 55
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Y2 Y3 Y4 M1 M2
14.24778 0.75735 0.16233 -0.06052 0.40608 0.02095
M3 M4 M5 M6 M7 M8
0.19819 0.08555 0.23892 1.22373 0.31955 0.01813
M9 M10 M11 t
0.14839 -0.02145 0.21041 0.04906
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-0.41448 -0.09479 -0.02204 0.07512 0.60044
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 14.24778 6.17467 2.307 0.0264 *
Y2 0.75735 0.15831 4.784 2.47e-05 ***
Y3 0.16233 0.20230 0.802 0.4272
Y4 -0.06052 0.15490 -0.391 0.6982
M1 0.40608 0.16653 2.438 0.0194 *
M2 0.02095 0.15700 0.133 0.8945
M3 0.19819 0.17456 1.135 0.2632
M4 0.08555 0.15342 0.558 0.5803
M5 0.23892 0.16251 1.470 0.1495
M6 1.22373 0.15579 7.855 1.48e-09 ***
M7 0.31955 0.22858 1.398 0.1700
M8 0.01813 0.27090 0.067 0.9470
M9 0.14839 0.16884 0.879 0.3849
M10 -0.02145 0.16416 -0.131 0.8967
M11 0.21041 0.16874 1.247 0.2198
t 0.04906 0.02031 2.415 0.0205 *
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 0.2284 on 39 degrees of freedom
Multiple R-squared: 0.9987, Adjusted R-squared: 0.9982
F-statistic: 1999 on 15 and 39 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,] 0.4754059 0.95081178 0.52459411
[2,] 0.3068296 0.61365925 0.69317038
[3,] 0.3046061 0.60921227 0.69539386
[4,] 0.7020003 0.59599938 0.29799969
[5,] 0.6330234 0.73395319 0.36697660
[6,] 0.5177163 0.96456743 0.48228372
[7,] 0.4934903 0.98698059 0.50650971
[8,] 0.4063018 0.81260355 0.59369823
[9,] 0.5727274 0.85454524 0.42727262
[10,] 0.6459133 0.70817336 0.35408668
[11,] 0.9043951 0.19120985 0.09560493
[12,] 0.9683468 0.06330638 0.03165319
[13,] 0.9606356 0.07872889 0.03936444
[14,] 0.9424105 0.11517910 0.05758955
[15,] 0.8934441 0.21311182 0.10655591
[16,] 0.8037779 0.39244421 0.19622211
[17,] 0.7323086 0.53538270 0.26769135
[18,] 0.5675184 0.86496320 0.43248160
> postscript(file="/var/www/html/freestat/rcomp/tmp/18l0k1291122980.ps",horizontal=F,onefile=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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/28l0k1291122980.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/freestat/rcomp/tmp/31uh51291122980.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/41uh51291122980.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/51uh51291122980.ps",horizontal=F,onefile=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 = 55
Frequency = 1
1 2 3 4 5
0.1603286140 0.1781570588 -0.0830318739 0.0001001020 -0.1625712080
6 7 8 9 10
-0.1913063042 -0.0685267156 0.0354055959 -0.0633363965 0.3811245490
11 12 13 14 15
-0.0825073028 0.0909008039 0.1001127606 -0.0203885228 -0.3397510131
16 17 18 19 20
0.0679052906 0.3012932839 -0.2103287746 -0.1731497456 0.0262731748
21 22 23 24 25
0.3341039172 -0.3205728931 -0.0842037518 -0.0918754257 -0.2127871384
26 27 28 29 30
-0.1266608877 -0.1698122473 -0.0399763319 -0.1523581215 0.4685794509
31 32 33 34 35
-0.0558200822 0.0823249931 -0.1741557107 -0.0926761054 0.1227222710
36 37 38 39 40
0.0339665872 0.0404131833 -0.0090706254 0.6004418353 -0.0892097617
41 42 43 44 45
0.1066132585 0.3475334219 0.2868770482 -0.1440037638 -0.0966118100
46 47 48 49 50
0.0321244496 0.0439887837 -0.0329919653 -0.0880674196 -0.0220370229
51 52 53 54 55
-0.0078467010 0.0611807010 -0.0929772129 -0.4144777941 0.0106194952
> postscript(file="/var/www/html/freestat/rcomp/tmp/6tlgp1291122980.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> dum <- cbind(lag(myerror,k=1),myerror)
> dum
Time Series:
Start = 0
End = 55
Frequency = 1
lag(myerror, k = 1) myerror
0 0.1603286140 NA
1 0.1781570588 0.1603286140
2 -0.0830318739 0.1781570588
3 0.0001001020 -0.0830318739
4 -0.1625712080 0.0001001020
5 -0.1913063042 -0.1625712080
6 -0.0685267156 -0.1913063042
7 0.0354055959 -0.0685267156
8 -0.0633363965 0.0354055959
9 0.3811245490 -0.0633363965
10 -0.0825073028 0.3811245490
11 0.0909008039 -0.0825073028
12 0.1001127606 0.0909008039
13 -0.0203885228 0.1001127606
14 -0.3397510131 -0.0203885228
15 0.0679052906 -0.3397510131
16 0.3012932839 0.0679052906
17 -0.2103287746 0.3012932839
18 -0.1731497456 -0.2103287746
19 0.0262731748 -0.1731497456
20 0.3341039172 0.0262731748
21 -0.3205728931 0.3341039172
22 -0.0842037518 -0.3205728931
23 -0.0918754257 -0.0842037518
24 -0.2127871384 -0.0918754257
25 -0.1266608877 -0.2127871384
26 -0.1698122473 -0.1266608877
27 -0.0399763319 -0.1698122473
28 -0.1523581215 -0.0399763319
29 0.4685794509 -0.1523581215
30 -0.0558200822 0.4685794509
31 0.0823249931 -0.0558200822
32 -0.1741557107 0.0823249931
33 -0.0926761054 -0.1741557107
34 0.1227222710 -0.0926761054
35 0.0339665872 0.1227222710
36 0.0404131833 0.0339665872
37 -0.0090706254 0.0404131833
38 0.6004418353 -0.0090706254
39 -0.0892097617 0.6004418353
40 0.1066132585 -0.0892097617
41 0.3475334219 0.1066132585
42 0.2868770482 0.3475334219
43 -0.1440037638 0.2868770482
44 -0.0966118100 -0.1440037638
45 0.0321244496 -0.0966118100
46 0.0439887837 0.0321244496
47 -0.0329919653 0.0439887837
48 -0.0880674196 -0.0329919653
49 -0.0220370229 -0.0880674196
50 -0.0078467010 -0.0220370229
51 0.0611807010 -0.0078467010
52 -0.0929772129 0.0611807010
53 -0.4144777941 -0.0929772129
54 0.0106194952 -0.4144777941
55 NA 0.0106194952
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 0.1781570588 0.1603286140
[2,] -0.0830318739 0.1781570588
[3,] 0.0001001020 -0.0830318739
[4,] -0.1625712080 0.0001001020
[5,] -0.1913063042 -0.1625712080
[6,] -0.0685267156 -0.1913063042
[7,] 0.0354055959 -0.0685267156
[8,] -0.0633363965 0.0354055959
[9,] 0.3811245490 -0.0633363965
[10,] -0.0825073028 0.3811245490
[11,] 0.0909008039 -0.0825073028
[12,] 0.1001127606 0.0909008039
[13,] -0.0203885228 0.1001127606
[14,] -0.3397510131 -0.0203885228
[15,] 0.0679052906 -0.3397510131
[16,] 0.3012932839 0.0679052906
[17,] -0.2103287746 0.3012932839
[18,] -0.1731497456 -0.2103287746
[19,] 0.0262731748 -0.1731497456
[20,] 0.3341039172 0.0262731748
[21,] -0.3205728931 0.3341039172
[22,] -0.0842037518 -0.3205728931
[23,] -0.0918754257 -0.0842037518
[24,] -0.2127871384 -0.0918754257
[25,] -0.1266608877 -0.2127871384
[26,] -0.1698122473 -0.1266608877
[27,] -0.0399763319 -0.1698122473
[28,] -0.1523581215 -0.0399763319
[29,] 0.4685794509 -0.1523581215
[30,] -0.0558200822 0.4685794509
[31,] 0.0823249931 -0.0558200822
[32,] -0.1741557107 0.0823249931
[33,] -0.0926761054 -0.1741557107
[34,] 0.1227222710 -0.0926761054
[35,] 0.0339665872 0.1227222710
[36,] 0.0404131833 0.0339665872
[37,] -0.0090706254 0.0404131833
[38,] 0.6004418353 -0.0090706254
[39,] -0.0892097617 0.6004418353
[40,] 0.1066132585 -0.0892097617
[41,] 0.3475334219 0.1066132585
[42,] 0.2868770482 0.3475334219
[43,] -0.1440037638 0.2868770482
[44,] -0.0966118100 -0.1440037638
[45,] 0.0321244496 -0.0966118100
[46,] 0.0439887837 0.0321244496
[47,] -0.0329919653 0.0439887837
[48,] -0.0880674196 -0.0329919653
[49,] -0.0220370229 -0.0880674196
[50,] -0.0078467010 -0.0220370229
[51,] 0.0611807010 -0.0078467010
[52,] -0.0929772129 0.0611807010
[53,] -0.4144777941 -0.0929772129
[54,] 0.0106194952 -0.4144777941
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 0.1781570588 0.1603286140
2 -0.0830318739 0.1781570588
3 0.0001001020 -0.0830318739
4 -0.1625712080 0.0001001020
5 -0.1913063042 -0.1625712080
6 -0.0685267156 -0.1913063042
7 0.0354055959 -0.0685267156
8 -0.0633363965 0.0354055959
9 0.3811245490 -0.0633363965
10 -0.0825073028 0.3811245490
11 0.0909008039 -0.0825073028
12 0.1001127606 0.0909008039
13 -0.0203885228 0.1001127606
14 -0.3397510131 -0.0203885228
15 0.0679052906 -0.3397510131
16 0.3012932839 0.0679052906
17 -0.2103287746 0.3012932839
18 -0.1731497456 -0.2103287746
19 0.0262731748 -0.1731497456
20 0.3341039172 0.0262731748
21 -0.3205728931 0.3341039172
22 -0.0842037518 -0.3205728931
23 -0.0918754257 -0.0842037518
24 -0.2127871384 -0.0918754257
25 -0.1266608877 -0.2127871384
26 -0.1698122473 -0.1266608877
27 -0.0399763319 -0.1698122473
28 -0.1523581215 -0.0399763319
29 0.4685794509 -0.1523581215
30 -0.0558200822 0.4685794509
31 0.0823249931 -0.0558200822
32 -0.1741557107 0.0823249931
33 -0.0926761054 -0.1741557107
34 0.1227222710 -0.0926761054
35 0.0339665872 0.1227222710
36 0.0404131833 0.0339665872
37 -0.0090706254 0.0404131833
38 0.6004418353 -0.0090706254
39 -0.0892097617 0.6004418353
40 0.1066132585 -0.0892097617
41 0.3475334219 0.1066132585
42 0.2868770482 0.3475334219
43 -0.1440037638 0.2868770482
44 -0.0966118100 -0.1440037638
45 0.0321244496 -0.0966118100
46 0.0439887837 0.0321244496
47 -0.0329919653 0.0439887837
48 -0.0880674196 -0.0329919653
49 -0.0220370229 -0.0880674196
50 -0.0078467010 -0.0220370229
51 0.0611807010 -0.0078467010
52 -0.0929772129 0.0611807010
53 -0.4144777941 -0.0929772129
54 0.0106194952 -0.4144777941
> 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/freestat/rcomp/tmp/74cxt1291122980.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/84cxt1291122980.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/94cxt1291122980.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/freestat/rcomp/tmp/10x4xv1291122980.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/freestat/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/freestat/rcomp/tmp/1104v11291122980.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/freestat/rcomp/tmp/1235b71291122980.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/freestat/rcomp/tmp/13ixay1291122980.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/freestat/rcomp/tmp/14lf841291122980.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/freestat/rcomp/tmp/15og7a1291122980.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/freestat/rcomp/tmp/16274j1291122980.tab")
+ }
>
> try(system("convert tmp/18l0k1291122980.ps tmp/18l0k1291122980.png",intern=TRUE))
character(0)
> try(system("convert tmp/28l0k1291122980.ps tmp/28l0k1291122980.png",intern=TRUE))
character(0)
> try(system("convert tmp/31uh51291122980.ps tmp/31uh51291122980.png",intern=TRUE))
character(0)
> try(system("convert tmp/41uh51291122980.ps tmp/41uh51291122980.png",intern=TRUE))
character(0)
> try(system("convert tmp/51uh51291122980.ps tmp/51uh51291122980.png",intern=TRUE))
character(0)
> try(system("convert tmp/6tlgp1291122980.ps tmp/6tlgp1291122980.png",intern=TRUE))
character(0)
> try(system("convert tmp/74cxt1291122980.ps tmp/74cxt1291122980.png",intern=TRUE))
character(0)
> try(system("convert tmp/84cxt1291122980.ps tmp/84cxt1291122980.png",intern=TRUE))
character(0)
> try(system("convert tmp/94cxt1291122980.ps tmp/94cxt1291122980.png",intern=TRUE))
character(0)
> try(system("convert tmp/10x4xv1291122980.ps tmp/10x4xv1291122980.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
3.703 2.465 4.205