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.
Type 'license()' or 'licence()' for distribution details.
Natural language support but running in an English locale
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(8.30
+ ,3.00
+ ,3.10
+ ,4.28
+ ,2649.24
+ ,8.70
+ ,3.00
+ ,2.90
+ ,3.69
+ ,2579.39
+ ,8.90
+ ,7.00
+ ,2.40
+ ,3.54
+ ,2504.58
+ ,8.90
+ ,4.00
+ ,2.40
+ ,3.13
+ ,2462.32
+ ,8.10
+ ,-4.00
+ ,2.70
+ ,3.75
+ ,2467.38
+ ,8.00
+ ,-6.00
+ ,2.50
+ ,3.85
+ ,2446.66
+ ,8.30
+ ,8.00
+ ,2.10
+ ,3.66
+ ,2656.32
+ ,8.50
+ ,2.00
+ ,1.90
+ ,3.96
+ ,2626.15
+ ,8.70
+ ,-1.00
+ ,0.80
+ ,3.93
+ ,2482.60
+ ,8.60
+ ,-2.00
+ ,0.80
+ ,4.05
+ ,2539.91
+ ,8.30
+ ,0.00
+ ,0.30
+ ,4.19
+ ,2502.66
+ ,7.90
+ ,10.00
+ ,0.00
+ ,4.32
+ ,2466.92
+ ,7.90
+ ,3.00
+ ,-0.90
+ ,4.21
+ ,2513.17
+ ,8.10
+ ,6.00
+ ,-1.00
+ ,4.24
+ ,2443.27
+ ,8.30
+ ,7.00
+ ,-0.70
+ ,4.16
+ ,2293.41
+ ,8.10
+ ,-4.00
+ ,-1.70
+ ,4.19
+ ,2070.83
+ ,7.40
+ ,-5.00
+ ,-1.00
+ ,4.20
+ ,2029.60
+ ,7.30
+ ,-7.00
+ ,-0.20
+ ,4.46
+ ,2052.02
+ ,7.70
+ ,-10.00
+ ,0.70
+ ,4.63
+ ,1864.44
+ ,8.00
+ ,-21.00
+ ,0.60
+ ,4.33
+ ,1670.07
+ ,8.00
+ ,-22.00
+ ,1.90
+ ,4.40
+ ,1810.99
+ ,7.70
+ ,-16.00
+ ,2.10
+ ,4.58
+ ,1905.41
+ ,6.90
+ ,-25.00
+ ,2.70
+ ,4.52
+ ,1862.83
+ ,6.60
+ ,-22.00
+ ,3.20
+ ,4.04
+ ,2014.45
+ ,6.90
+ ,-22.00
+ ,4.80
+ ,4.16
+ ,2197.82
+ ,7.50
+ ,-19.00
+ ,5.50
+ ,4.73
+ ,2962.34
+ ,7.90
+ ,-21.00
+ ,5.40
+ ,4.81
+ ,3047.03
+ ,7.70
+ ,-31.00
+ ,5.90
+ ,4.75
+ ,3032.60
+ ,6.50
+ ,-28.00
+ ,5.80
+ ,4.90
+ ,3504.37
+ ,6.10
+ ,-23.00
+ ,5.10
+ ,5.12
+ ,3801.06
+ ,6.40
+ ,-17.00
+ ,4.10
+ ,4.95
+ ,3857.62
+ ,6.80
+ ,-12.00
+ ,4.40
+ ,4.76
+ ,3674.40
+ ,7.10
+ ,-14.00
+ ,3.60
+ ,4.69
+ ,3720.98
+ ,7.30
+ ,-18.00
+ ,3.50
+ ,4.58
+ ,3844.49
+ ,7.20
+ ,-16.00
+ ,3.10
+ ,4.55
+ ,4116.68
+ ,7.00
+ ,-22.00
+ ,2.90
+ ,4.71
+ ,4105.18
+ ,7.00
+ ,-9.00
+ ,2.20
+ ,4.67
+ ,4435.23
+ ,7.00
+ ,-10.00
+ ,1.40
+ ,4.57
+ ,4296.49
+ ,7.30
+ ,-10.00
+ ,1.20
+ ,4.68
+ ,4202.52
+ ,7.50
+ ,0.00
+ ,1.30
+ ,4.63
+ ,4562.84
+ ,7.20
+ ,3.00
+ ,1.30
+ ,4.60
+ ,4621.40
+ ,7.70
+ ,2.00
+ ,1.30
+ ,4.74
+ ,4696.96
+ ,8.00
+ ,4.00
+ ,1.80
+ ,4.56
+ ,4591.27
+ ,7.90
+ ,-3.00
+ ,1.80
+ ,4.38
+ ,4356.98
+ ,8.00
+ ,0.00
+ ,1.80
+ ,4.26
+ ,4502.64
+ ,8.00
+ ,-1.00
+ ,1.70
+ ,4.13
+ ,4443.91
+ ,7.90
+ ,-7.00
+ ,2.10
+ ,4.29
+ ,4290.89
+ ,7.90
+ ,2.00
+ ,2.00
+ ,4.11
+ ,4199.75
+ ,8.00
+ ,3.00
+ ,1.70
+ ,3.88
+ ,4138.52
+ ,8.10
+ ,-3.00
+ ,1.90
+ ,3.92
+ ,3970.10
+ ,8.10
+ ,-5.00
+ ,2.30
+ ,3.90
+ ,3862.27
+ ,8.20
+ ,0.00
+ ,2.40
+ ,4.06
+ ,3701.61
+ ,8.00
+ ,-3.00
+ ,2.50
+ ,4.22
+ ,3570.12
+ ,8.30
+ ,-7.00
+ ,2.80
+ ,4.36
+ ,3801.06
+ ,8.50
+ ,-7.00
+ ,2.60
+ ,4.28
+ ,3895.51
+ ,8.60
+ ,-7.00
+ ,2.20
+ ,4.27
+ ,3917.96
+ ,8.70
+ ,-4.00
+ ,2.80
+ ,4.04
+ ,3813.06
+ ,8.70
+ ,-3.00
+ ,2.80
+ ,3.71
+ ,3667.03
+ ,8.50
+ ,-6.00
+ ,2.80
+ ,3.71
+ ,3494.17
+ ,8.40
+ ,-10.00
+ ,2.30
+ ,3.51
+ ,3363.99)
+ ,dim=c(5
+ ,60)
+ ,dimnames=list(c('Werkloosheid'
+ ,'General'
+ ,'HICP'
+ ,'OLO'
+ ,'Bel20')
+ ,1:60))
> y <- array(NA,dim=c(5,60),dimnames=list(c('Werkloosheid','General','HICP','OLO','Bel20'),1:60))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par3 = 'No Linear Trend'
> par2 = 'Do not include Seasonal 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 General HICP OLO Bel20
1 8.3 3 3.1 4.28 2649.24
2 8.7 3 2.9 3.69 2579.39
3 8.9 7 2.4 3.54 2504.58
4 8.9 4 2.4 3.13 2462.32
5 8.1 -4 2.7 3.75 2467.38
6 8.0 -6 2.5 3.85 2446.66
7 8.3 8 2.1 3.66 2656.32
8 8.5 2 1.9 3.96 2626.15
9 8.7 -1 0.8 3.93 2482.60
10 8.6 -2 0.8 4.05 2539.91
11 8.3 0 0.3 4.19 2502.66
12 7.9 10 0.0 4.32 2466.92
13 7.9 3 -0.9 4.21 2513.17
14 8.1 6 -1.0 4.24 2443.27
15 8.3 7 -0.7 4.16 2293.41
16 8.1 -4 -1.7 4.19 2070.83
17 7.4 -5 -1.0 4.20 2029.60
18 7.3 -7 -0.2 4.46 2052.02
19 7.7 -10 0.7 4.63 1864.44
20 8.0 -21 0.6 4.33 1670.07
21 8.0 -22 1.9 4.40 1810.99
22 7.7 -16 2.1 4.58 1905.41
23 6.9 -25 2.7 4.52 1862.83
24 6.6 -22 3.2 4.04 2014.45
25 6.9 -22 4.8 4.16 2197.82
26 7.5 -19 5.5 4.73 2962.34
27 7.9 -21 5.4 4.81 3047.03
28 7.7 -31 5.9 4.75 3032.60
29 6.5 -28 5.8 4.90 3504.37
30 6.1 -23 5.1 5.12 3801.06
31 6.4 -17 4.1 4.95 3857.62
32 6.8 -12 4.4 4.76 3674.40
33 7.1 -14 3.6 4.69 3720.98
34 7.3 -18 3.5 4.58 3844.49
35 7.2 -16 3.1 4.55 4116.68
36 7.0 -22 2.9 4.71 4105.18
37 7.0 -9 2.2 4.67 4435.23
38 7.0 -10 1.4 4.57 4296.49
39 7.3 -10 1.2 4.68 4202.52
40 7.5 0 1.3 4.63 4562.84
41 7.2 3 1.3 4.60 4621.40
42 7.7 2 1.3 4.74 4696.96
43 8.0 4 1.8 4.56 4591.27
44 7.9 -3 1.8 4.38 4356.98
45 8.0 0 1.8 4.26 4502.64
46 8.0 -1 1.7 4.13 4443.91
47 7.9 -7 2.1 4.29 4290.89
48 7.9 2 2.0 4.11 4199.75
49 8.0 3 1.7 3.88 4138.52
50 8.1 -3 1.9 3.92 3970.10
51 8.1 -5 2.3 3.90 3862.27
52 8.2 0 2.4 4.06 3701.61
53 8.0 -3 2.5 4.22 3570.12
54 8.3 -7 2.8 4.36 3801.06
55 8.5 -7 2.6 4.28 3895.51
56 8.6 -7 2.2 4.27 3917.96
57 8.7 -4 2.8 4.04 3813.06
58 8.7 -3 2.8 3.71 3667.03
59 8.5 -6 2.8 3.71 3494.17
60 8.4 -10 2.3 3.51 3363.99
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) General HICP OLO Bel20
1.188e+01 2.437e-02 1.951e-02 -8.847e-01 -4.629e-05
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-1.136411 -0.288949 0.002539 0.235468 0.825350
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1.188e+01 7.000e-01 16.969 < 2e-16 ***
General 2.437e-02 9.285e-03 2.624 0.0112 *
HICP 1.951e-02 4.710e-02 0.414 0.6803
OLO -8.847e-01 1.850e-01 -4.782 1.34e-05 ***
Bel20 -4.629e-05 7.350e-05 -0.630 0.5314
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 0.4188 on 55 degrees of freedom
Multiple R-squared: 0.6268, Adjusted R-squared: 0.5997
F-statistic: 23.1 on 4 and 55 DF, p-value: 3.076e-11
> 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,] 0.27146432 0.5429286435 0.7285356782
[2,] 0.17958704 0.3591740738 0.8204129631
[3,] 0.10627046 0.2125409293 0.8937295354
[4,] 0.10607397 0.2121479316 0.8939260342
[5,] 0.14894829 0.2978965873 0.8510517064
[6,] 0.14889103 0.2977820628 0.8511089686
[7,] 0.09013284 0.1802656840 0.9098671580
[8,] 0.06419042 0.1283808365 0.9358095817
[9,] 0.03759055 0.0751811026 0.9624094487
[10,] 0.05231609 0.1046321869 0.9476839065
[11,] 0.03709842 0.0741968441 0.9629015779
[12,] 0.04504723 0.0900944514 0.9549527743
[13,] 0.05548376 0.1109675115 0.9445162442
[14,] 0.05620447 0.1124089363 0.9437955318
[15,] 0.05073041 0.1014608118 0.9492695941
[16,] 0.12987370 0.2597473972 0.8701263014
[17,] 0.50752521 0.9849495798 0.4924747899
[18,] 0.75229295 0.4954141093 0.2477070547
[19,] 0.70427603 0.5914479314 0.2957239657
[20,] 0.75615826 0.4876834717 0.2438417359
[21,] 0.85732462 0.2853507510 0.1426753755
[22,] 0.90774427 0.1845114684 0.0922557342
[23,] 0.93715612 0.1256877653 0.0628438826
[24,] 0.94526516 0.1094696728 0.0547348364
[25,] 0.96958258 0.0608348350 0.0304174175
[26,] 0.97619230 0.0476154065 0.0238077033
[27,] 0.97329055 0.0534188965 0.0267094483
[28,] 0.97326141 0.0534771828 0.0267385914
[29,] 0.97746674 0.0450665181 0.0225332591
[30,] 0.99840312 0.0031937569 0.0015968784
[31,] 0.99951902 0.0009619675 0.0004809838
[32,] 0.99902491 0.0019501759 0.0009750879
[33,] 0.99785962 0.0042807586 0.0021403793
[34,] 0.99876366 0.0024726745 0.0012363373
[35,] 0.99765648 0.0046870401 0.0023435201
[36,] 0.99624380 0.0075123942 0.0037561971
[37,] 0.99224531 0.0155093787 0.0077546894
[38,] 0.98418414 0.0316317263 0.0158158631
[39,] 0.96894079 0.0621184244 0.0310592122
[40,] 0.97861460 0.0427708068 0.0213854034
[41,] 0.96857241 0.0628551721 0.0314275860
[42,] 0.93351147 0.1329770662 0.0664885331
[43,] 0.88078806 0.2384238899 0.1192119449
[44,] 0.99734912 0.0053017653 0.0026508826
[45,] 0.99579371 0.0084125823 0.0042062912
> postscript(file="/var/www/html/freestat/rcomp/tmp/1pell1291298082.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/2pell1291298082.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/30ok61291298082.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/40ok61291298082.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/50ok61291298082.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 = 60
Frequency = 1
1 2 3 4 5 6
0.19813640 0.07680870 0.05292971 -0.23867463 -0.30083462 -0.26068764
7 8 9 10 11 12
-0.45238914 0.16172850 0.42309780 0.45628458 0.23944888 -0.28498682
13 14 15 16 17 18
-0.19205239 -0.03989011 0.05217525 0.15593985 -0.52641365 -0.36222179
19 20 21 22 23 24
0.23503624 0.53058326 0.59803990 0.31157148 -0.33590482 -1.13641142
25 26 27 28 29 30
-0.75297091 0.29996913 0.82534989 0.80549280 -0.31110130 -0.61089222
31 32 33 34 35 36
-0.58535950 -0.48961999 -0.18505700 0.02275040 -0.13211754 -0.04099917
37 38 39 40 41 42
-0.36419847 -0.41912152 -0.02224811 -0.09540679 -0.49233328 0.15939311
43 44 45 46 47 48
0.23676208 0.13721862 0.06469758 -0.02672117 0.14613970 -0.23466686
49 50 51 52 53 54
-0.35950331 -0.08962198 -0.07138250 0.03896228 0.04557780 0.57173902
55 56 57 58 59 60
0.70923422 0.80923026 0.61608273 0.29299364 0.15808680 -0.01767193
> postscript(file="/var/www/html/freestat/rcomp/tmp/6bf291291298082.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 = 60
Frequency = 1
lag(myerror, k = 1) myerror
0 0.19813640 NA
1 0.07680870 0.19813640
2 0.05292971 0.07680870
3 -0.23867463 0.05292971
4 -0.30083462 -0.23867463
5 -0.26068764 -0.30083462
6 -0.45238914 -0.26068764
7 0.16172850 -0.45238914
8 0.42309780 0.16172850
9 0.45628458 0.42309780
10 0.23944888 0.45628458
11 -0.28498682 0.23944888
12 -0.19205239 -0.28498682
13 -0.03989011 -0.19205239
14 0.05217525 -0.03989011
15 0.15593985 0.05217525
16 -0.52641365 0.15593985
17 -0.36222179 -0.52641365
18 0.23503624 -0.36222179
19 0.53058326 0.23503624
20 0.59803990 0.53058326
21 0.31157148 0.59803990
22 -0.33590482 0.31157148
23 -1.13641142 -0.33590482
24 -0.75297091 -1.13641142
25 0.29996913 -0.75297091
26 0.82534989 0.29996913
27 0.80549280 0.82534989
28 -0.31110130 0.80549280
29 -0.61089222 -0.31110130
30 -0.58535950 -0.61089222
31 -0.48961999 -0.58535950
32 -0.18505700 -0.48961999
33 0.02275040 -0.18505700
34 -0.13211754 0.02275040
35 -0.04099917 -0.13211754
36 -0.36419847 -0.04099917
37 -0.41912152 -0.36419847
38 -0.02224811 -0.41912152
39 -0.09540679 -0.02224811
40 -0.49233328 -0.09540679
41 0.15939311 -0.49233328
42 0.23676208 0.15939311
43 0.13721862 0.23676208
44 0.06469758 0.13721862
45 -0.02672117 0.06469758
46 0.14613970 -0.02672117
47 -0.23466686 0.14613970
48 -0.35950331 -0.23466686
49 -0.08962198 -0.35950331
50 -0.07138250 -0.08962198
51 0.03896228 -0.07138250
52 0.04557780 0.03896228
53 0.57173902 0.04557780
54 0.70923422 0.57173902
55 0.80923026 0.70923422
56 0.61608273 0.80923026
57 0.29299364 0.61608273
58 0.15808680 0.29299364
59 -0.01767193 0.15808680
60 NA -0.01767193
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 0.07680870 0.19813640
[2,] 0.05292971 0.07680870
[3,] -0.23867463 0.05292971
[4,] -0.30083462 -0.23867463
[5,] -0.26068764 -0.30083462
[6,] -0.45238914 -0.26068764
[7,] 0.16172850 -0.45238914
[8,] 0.42309780 0.16172850
[9,] 0.45628458 0.42309780
[10,] 0.23944888 0.45628458
[11,] -0.28498682 0.23944888
[12,] -0.19205239 -0.28498682
[13,] -0.03989011 -0.19205239
[14,] 0.05217525 -0.03989011
[15,] 0.15593985 0.05217525
[16,] -0.52641365 0.15593985
[17,] -0.36222179 -0.52641365
[18,] 0.23503624 -0.36222179
[19,] 0.53058326 0.23503624
[20,] 0.59803990 0.53058326
[21,] 0.31157148 0.59803990
[22,] -0.33590482 0.31157148
[23,] -1.13641142 -0.33590482
[24,] -0.75297091 -1.13641142
[25,] 0.29996913 -0.75297091
[26,] 0.82534989 0.29996913
[27,] 0.80549280 0.82534989
[28,] -0.31110130 0.80549280
[29,] -0.61089222 -0.31110130
[30,] -0.58535950 -0.61089222
[31,] -0.48961999 -0.58535950
[32,] -0.18505700 -0.48961999
[33,] 0.02275040 -0.18505700
[34,] -0.13211754 0.02275040
[35,] -0.04099917 -0.13211754
[36,] -0.36419847 -0.04099917
[37,] -0.41912152 -0.36419847
[38,] -0.02224811 -0.41912152
[39,] -0.09540679 -0.02224811
[40,] -0.49233328 -0.09540679
[41,] 0.15939311 -0.49233328
[42,] 0.23676208 0.15939311
[43,] 0.13721862 0.23676208
[44,] 0.06469758 0.13721862
[45,] -0.02672117 0.06469758
[46,] 0.14613970 -0.02672117
[47,] -0.23466686 0.14613970
[48,] -0.35950331 -0.23466686
[49,] -0.08962198 -0.35950331
[50,] -0.07138250 -0.08962198
[51,] 0.03896228 -0.07138250
[52,] 0.04557780 0.03896228
[53,] 0.57173902 0.04557780
[54,] 0.70923422 0.57173902
[55,] 0.80923026 0.70923422
[56,] 0.61608273 0.80923026
[57,] 0.29299364 0.61608273
[58,] 0.15808680 0.29299364
[59,] -0.01767193 0.15808680
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 0.07680870 0.19813640
2 0.05292971 0.07680870
3 -0.23867463 0.05292971
4 -0.30083462 -0.23867463
5 -0.26068764 -0.30083462
6 -0.45238914 -0.26068764
7 0.16172850 -0.45238914
8 0.42309780 0.16172850
9 0.45628458 0.42309780
10 0.23944888 0.45628458
11 -0.28498682 0.23944888
12 -0.19205239 -0.28498682
13 -0.03989011 -0.19205239
14 0.05217525 -0.03989011
15 0.15593985 0.05217525
16 -0.52641365 0.15593985
17 -0.36222179 -0.52641365
18 0.23503624 -0.36222179
19 0.53058326 0.23503624
20 0.59803990 0.53058326
21 0.31157148 0.59803990
22 -0.33590482 0.31157148
23 -1.13641142 -0.33590482
24 -0.75297091 -1.13641142
25 0.29996913 -0.75297091
26 0.82534989 0.29996913
27 0.80549280 0.82534989
28 -0.31110130 0.80549280
29 -0.61089222 -0.31110130
30 -0.58535950 -0.61089222
31 -0.48961999 -0.58535950
32 -0.18505700 -0.48961999
33 0.02275040 -0.18505700
34 -0.13211754 0.02275040
35 -0.04099917 -0.13211754
36 -0.36419847 -0.04099917
37 -0.41912152 -0.36419847
38 -0.02224811 -0.41912152
39 -0.09540679 -0.02224811
40 -0.49233328 -0.09540679
41 0.15939311 -0.49233328
42 0.23676208 0.15939311
43 0.13721862 0.23676208
44 0.06469758 0.13721862
45 -0.02672117 0.06469758
46 0.14613970 -0.02672117
47 -0.23466686 0.14613970
48 -0.35950331 -0.23466686
49 -0.08962198 -0.35950331
50 -0.07138250 -0.08962198
51 0.03896228 -0.07138250
52 0.04557780 0.03896228
53 0.57173902 0.04557780
54 0.70923422 0.57173902
55 0.80923026 0.70923422
56 0.61608273 0.80923026
57 0.29299364 0.61608273
58 0.15808680 0.29299364
59 -0.01767193 0.15808680
> 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/7loju1291298082.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/8loju1291298082.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/9loju1291298082.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/freestat/rcomp/tmp/10wx0x1291298082.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/freestat/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11zgzl1291298082.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/12lgxr1291298082.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/13hqv01291298082.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/14kqb51291298082.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/156rat1291298082.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/162jq21291298082.tab")
+ }
>
> try(system("convert tmp/1pell1291298082.ps tmp/1pell1291298082.png",intern=TRUE))
character(0)
> try(system("convert tmp/2pell1291298082.ps tmp/2pell1291298082.png",intern=TRUE))
character(0)
> try(system("convert tmp/30ok61291298082.ps tmp/30ok61291298082.png",intern=TRUE))
character(0)
> try(system("convert tmp/40ok61291298082.ps tmp/40ok61291298082.png",intern=TRUE))
character(0)
> try(system("convert tmp/50ok61291298082.ps tmp/50ok61291298082.png",intern=TRUE))
character(0)
> try(system("convert tmp/6bf291291298082.ps tmp/6bf291291298082.png",intern=TRUE))
character(0)
> try(system("convert tmp/7loju1291298082.ps tmp/7loju1291298082.png",intern=TRUE))
character(0)
> try(system("convert tmp/8loju1291298082.ps tmp/8loju1291298082.png",intern=TRUE))
character(0)
> try(system("convert tmp/9loju1291298082.ps tmp/9loju1291298082.png",intern=TRUE))
character(0)
> try(system("convert tmp/10wx0x1291298082.ps tmp/10wx0x1291298082.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
3.946 2.504 4.791