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.
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Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> x <- array(list(108.00,0,99.00,0,108.00,0,104.00,0,111.00,0,110.00,0,106.00,0,101.00,0,102.00,0,99.00,0,100.00,0,98.00,0,92.00,1,87.00,1,79.00,1,87.00,1,87.00,1,88.00,1,83.00,1,85.00,1,92.00,1,84.00,1,92.00,1,98.00,1,103.00,0,104.00,0,109.00,0,107.00,0,106.00,0,113.00,0,107.00,0,114.00,0,108.00,0,104.00,0,105.00,0,109.00,0,109.00,0,112.00,0,118.00,0,111.00,0,99.00,1,92.00,1,92.00,1,98.00,1,87.00,1,97.00,1,102.00,0,105.00,0,111.00,0,110.00,0,109.00,0,111.00,0,113.00,0,114.00,0,120.00,0,114.00,0,120.00,0,122.00,0,123.00,0,115.00,0,123.00,0,124.00,0,124.00,0,132.00,0,126.00,0,126.00,0,122.00,0,120.00,0,114.00,0,116.00,0,100.00,0,97.00,0),dim=c(2,72),dimnames=list(c('Consumentenvertrouwen','Dummy'),1:72))
> y <- array(NA,dim=c(2,72),dimnames=list(c('Consumentenvertrouwen','Dummy'),1:72))
> 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
Consumentenvertrouwen Dummy
1 108 0
2 99 0
3 108 0
4 104 0
5 111 0
6 110 0
7 106 0
8 101 0
9 102 0
10 99 0
11 100 0
12 98 0
13 92 1
14 87 1
15 79 1
16 87 1
17 87 1
18 88 1
19 83 1
20 85 1
21 92 1
22 84 1
23 92 1
24 98 1
25 103 0
26 104 0
27 109 0
28 107 0
29 106 0
30 113 0
31 107 0
32 114 0
33 108 0
34 104 0
35 105 0
36 109 0
37 109 0
38 112 0
39 118 0
40 111 0
41 99 1
42 92 1
43 92 1
44 98 1
45 87 1
46 97 1
47 102 0
48 105 0
49 111 0
50 110 0
51 109 0
52 111 0
53 113 0
54 114 0
55 120 0
56 114 0
57 120 0
58 122 0
59 123 0
60 115 0
61 123 0
62 124 0
63 124 0
64 132 0
65 126 0
66 126 0
67 122 0
68 120 0
69 114 0
70 116 0
71 100 0
72 97 0
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Dummy
111.07 -21.13
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-14.074 -5.292 -1.074 4.176 20.926
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 111.074 1.061 104.72 < 2e-16 ***
Dummy -21.130 2.121 -9.96 4.71e-15 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 7.794 on 70 degrees of freedom
Multiple R-squared: 0.5863, Adjusted R-squared: 0.5804
F-statistic: 99.21 on 1 and 70 DF, p-value: 4.711e-15
> 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,] 0.290886754 0.581773509 0.7091132
[2,] 0.188607897 0.377215794 0.8113921
[3,] 0.097754335 0.195508669 0.9022457
[4,] 0.086155173 0.172310346 0.9138448
[5,] 0.059800130 0.119600260 0.9401999
[6,] 0.068044079 0.136088157 0.9319559
[7,] 0.059445588 0.118891177 0.9405544
[8,] 0.071889624 0.143779248 0.9281104
[9,] 0.041745484 0.083490968 0.9582545
[10,] 0.028739284 0.057478568 0.9712607
[11,] 0.054573245 0.109146491 0.9454268
[12,] 0.033727142 0.067454284 0.9662729
[13,] 0.020183906 0.040367811 0.9798161
[14,] 0.011927623 0.023855247 0.9880724
[15,] 0.009125870 0.018251740 0.9908741
[16,] 0.005670560 0.011341121 0.9943294
[17,] 0.005274700 0.010549400 0.9947253
[18,] 0.003913547 0.007827094 0.9960865
[19,] 0.003448517 0.006897034 0.9965515
[20,] 0.009808135 0.019616269 0.9901919
[21,] 0.007410427 0.014820854 0.9925896
[22,] 0.005401056 0.010802112 0.9945989
[23,] 0.004592113 0.009184225 0.9954079
[24,] 0.003307425 0.006614850 0.9966926
[25,] 0.002346064 0.004692128 0.9976539
[26,] 0.003327074 0.006654149 0.9966729
[27,] 0.002367566 0.004735131 0.9976324
[28,] 0.003401422 0.006802844 0.9965986
[29,] 0.002420703 0.004841406 0.9975793
[30,] 0.002157817 0.004315633 0.9978422
[31,] 0.001824845 0.003649690 0.9981752
[32,] 0.001401084 0.002802168 0.9985989
[33,] 0.001075508 0.002151016 0.9989245
[34,] 0.000999519 0.001999038 0.9990005
[35,] 0.002546590 0.005093180 0.9974534
[36,] 0.001968471 0.003936943 0.9980315
[37,] 0.003584624 0.007169248 0.9964154
[38,] 0.002301601 0.004603202 0.9976984
[39,] 0.001438654 0.002877307 0.9985613
[40,] 0.001695324 0.003390648 0.9983047
[41,] 0.001289764 0.002579528 0.9987102
[42,] 0.001102143 0.002204285 0.9988979
[43,] 0.002065348 0.004130697 0.9979347
[44,] 0.002555625 0.005111249 0.9974444
[45,] 0.002095980 0.004191960 0.9979040
[46,] 0.001782922 0.003565844 0.9982171
[47,] 0.001679214 0.003358428 0.9983208
[48,] 0.001475409 0.002950817 0.9985246
[49,] 0.001277669 0.002555339 0.9987223
[50,] 0.001110889 0.002221778 0.9988891
[51,] 0.001648492 0.003296984 0.9983515
[52,] 0.001305314 0.002610629 0.9986947
[53,] 0.001533626 0.003067251 0.9984664
[54,] 0.002126146 0.004252292 0.9978739
[55,] 0.002968357 0.005936714 0.9970316
[56,] 0.001901486 0.003802973 0.9980985
[57,] 0.002173036 0.004346072 0.9978270
[58,] 0.002630243 0.005260486 0.9973698
[59,] 0.002932095 0.005864190 0.9970679
[60,] 0.018798949 0.037597898 0.9812011
[61,] 0.030515675 0.061031350 0.9694843
[62,] 0.060390189 0.120780377 0.9396098
[63,] 0.077767762 0.155535525 0.9222322
> postscript(file="/var/www/html/rcomp/tmp/1pus31228940767.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/27tka1228940767.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3tq7s1228940767.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4137u1228940767.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5mp1r1228940767.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 = 72
Frequency = 1
1 2 3 4 5 6
-3.07407407 -12.07407407 -3.07407407 -7.07407407 -0.07407407 -1.07407407
7 8 9 10 11 12
-5.07407407 -10.07407407 -9.07407407 -12.07407407 -11.07407407 -13.07407407
13 14 15 16 17 18
2.05555556 -2.94444444 -10.94444444 -2.94444444 -2.94444444 -1.94444444
19 20 21 22 23 24
-6.94444444 -4.94444444 2.05555556 -5.94444444 2.05555556 8.05555556
25 26 27 28 29 30
-8.07407407 -7.07407407 -2.07407407 -4.07407407 -5.07407407 1.92592593
31 32 33 34 35 36
-4.07407407 2.92592593 -3.07407407 -7.07407407 -6.07407407 -2.07407407
37 38 39 40 41 42
-2.07407407 0.92592593 6.92592593 -0.07407407 9.05555556 2.05555556
43 44 45 46 47 48
2.05555556 8.05555556 -2.94444444 7.05555556 -9.07407407 -6.07407407
49 50 51 52 53 54
-0.07407407 -1.07407407 -2.07407407 -0.07407407 1.92592593 2.92592593
55 56 57 58 59 60
8.92592593 2.92592593 8.92592593 10.92592593 11.92592593 3.92592593
61 62 63 64 65 66
11.92592593 12.92592593 12.92592593 20.92592593 14.92592593 14.92592593
67 68 69 70 71 72
10.92592593 8.92592593 2.92592593 4.92592593 -11.07407407 -14.07407407
> postscript(file="/var/www/html/rcomp/tmp/60g0a1228940767.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 = 72
Frequency = 1
lag(myerror, k = 1) myerror
0 -3.07407407 NA
1 -12.07407407 -3.07407407
2 -3.07407407 -12.07407407
3 -7.07407407 -3.07407407
4 -0.07407407 -7.07407407
5 -1.07407407 -0.07407407
6 -5.07407407 -1.07407407
7 -10.07407407 -5.07407407
8 -9.07407407 -10.07407407
9 -12.07407407 -9.07407407
10 -11.07407407 -12.07407407
11 -13.07407407 -11.07407407
12 2.05555556 -13.07407407
13 -2.94444444 2.05555556
14 -10.94444444 -2.94444444
15 -2.94444444 -10.94444444
16 -2.94444444 -2.94444444
17 -1.94444444 -2.94444444
18 -6.94444444 -1.94444444
19 -4.94444444 -6.94444444
20 2.05555556 -4.94444444
21 -5.94444444 2.05555556
22 2.05555556 -5.94444444
23 8.05555556 2.05555556
24 -8.07407407 8.05555556
25 -7.07407407 -8.07407407
26 -2.07407407 -7.07407407
27 -4.07407407 -2.07407407
28 -5.07407407 -4.07407407
29 1.92592593 -5.07407407
30 -4.07407407 1.92592593
31 2.92592593 -4.07407407
32 -3.07407407 2.92592593
33 -7.07407407 -3.07407407
34 -6.07407407 -7.07407407
35 -2.07407407 -6.07407407
36 -2.07407407 -2.07407407
37 0.92592593 -2.07407407
38 6.92592593 0.92592593
39 -0.07407407 6.92592593
40 9.05555556 -0.07407407
41 2.05555556 9.05555556
42 2.05555556 2.05555556
43 8.05555556 2.05555556
44 -2.94444444 8.05555556
45 7.05555556 -2.94444444
46 -9.07407407 7.05555556
47 -6.07407407 -9.07407407
48 -0.07407407 -6.07407407
49 -1.07407407 -0.07407407
50 -2.07407407 -1.07407407
51 -0.07407407 -2.07407407
52 1.92592593 -0.07407407
53 2.92592593 1.92592593
54 8.92592593 2.92592593
55 2.92592593 8.92592593
56 8.92592593 2.92592593
57 10.92592593 8.92592593
58 11.92592593 10.92592593
59 3.92592593 11.92592593
60 11.92592593 3.92592593
61 12.92592593 11.92592593
62 12.92592593 12.92592593
63 20.92592593 12.92592593
64 14.92592593 20.92592593
65 14.92592593 14.92592593
66 10.92592593 14.92592593
67 8.92592593 10.92592593
68 2.92592593 8.92592593
69 4.92592593 2.92592593
70 -11.07407407 4.92592593
71 -14.07407407 -11.07407407
72 NA -14.07407407
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -12.07407407 -3.07407407
[2,] -3.07407407 -12.07407407
[3,] -7.07407407 -3.07407407
[4,] -0.07407407 -7.07407407
[5,] -1.07407407 -0.07407407
[6,] -5.07407407 -1.07407407
[7,] -10.07407407 -5.07407407
[8,] -9.07407407 -10.07407407
[9,] -12.07407407 -9.07407407
[10,] -11.07407407 -12.07407407
[11,] -13.07407407 -11.07407407
[12,] 2.05555556 -13.07407407
[13,] -2.94444444 2.05555556
[14,] -10.94444444 -2.94444444
[15,] -2.94444444 -10.94444444
[16,] -2.94444444 -2.94444444
[17,] -1.94444444 -2.94444444
[18,] -6.94444444 -1.94444444
[19,] -4.94444444 -6.94444444
[20,] 2.05555556 -4.94444444
[21,] -5.94444444 2.05555556
[22,] 2.05555556 -5.94444444
[23,] 8.05555556 2.05555556
[24,] -8.07407407 8.05555556
[25,] -7.07407407 -8.07407407
[26,] -2.07407407 -7.07407407
[27,] -4.07407407 -2.07407407
[28,] -5.07407407 -4.07407407
[29,] 1.92592593 -5.07407407
[30,] -4.07407407 1.92592593
[31,] 2.92592593 -4.07407407
[32,] -3.07407407 2.92592593
[33,] -7.07407407 -3.07407407
[34,] -6.07407407 -7.07407407
[35,] -2.07407407 -6.07407407
[36,] -2.07407407 -2.07407407
[37,] 0.92592593 -2.07407407
[38,] 6.92592593 0.92592593
[39,] -0.07407407 6.92592593
[40,] 9.05555556 -0.07407407
[41,] 2.05555556 9.05555556
[42,] 2.05555556 2.05555556
[43,] 8.05555556 2.05555556
[44,] -2.94444444 8.05555556
[45,] 7.05555556 -2.94444444
[46,] -9.07407407 7.05555556
[47,] -6.07407407 -9.07407407
[48,] -0.07407407 -6.07407407
[49,] -1.07407407 -0.07407407
[50,] -2.07407407 -1.07407407
[51,] -0.07407407 -2.07407407
[52,] 1.92592593 -0.07407407
[53,] 2.92592593 1.92592593
[54,] 8.92592593 2.92592593
[55,] 2.92592593 8.92592593
[56,] 8.92592593 2.92592593
[57,] 10.92592593 8.92592593
[58,] 11.92592593 10.92592593
[59,] 3.92592593 11.92592593
[60,] 11.92592593 3.92592593
[61,] 12.92592593 11.92592593
[62,] 12.92592593 12.92592593
[63,] 20.92592593 12.92592593
[64,] 14.92592593 20.92592593
[65,] 14.92592593 14.92592593
[66,] 10.92592593 14.92592593
[67,] 8.92592593 10.92592593
[68,] 2.92592593 8.92592593
[69,] 4.92592593 2.92592593
[70,] -11.07407407 4.92592593
[71,] -14.07407407 -11.07407407
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -12.07407407 -3.07407407
2 -3.07407407 -12.07407407
3 -7.07407407 -3.07407407
4 -0.07407407 -7.07407407
5 -1.07407407 -0.07407407
6 -5.07407407 -1.07407407
7 -10.07407407 -5.07407407
8 -9.07407407 -10.07407407
9 -12.07407407 -9.07407407
10 -11.07407407 -12.07407407
11 -13.07407407 -11.07407407
12 2.05555556 -13.07407407
13 -2.94444444 2.05555556
14 -10.94444444 -2.94444444
15 -2.94444444 -10.94444444
16 -2.94444444 -2.94444444
17 -1.94444444 -2.94444444
18 -6.94444444 -1.94444444
19 -4.94444444 -6.94444444
20 2.05555556 -4.94444444
21 -5.94444444 2.05555556
22 2.05555556 -5.94444444
23 8.05555556 2.05555556
24 -8.07407407 8.05555556
25 -7.07407407 -8.07407407
26 -2.07407407 -7.07407407
27 -4.07407407 -2.07407407
28 -5.07407407 -4.07407407
29 1.92592593 -5.07407407
30 -4.07407407 1.92592593
31 2.92592593 -4.07407407
32 -3.07407407 2.92592593
33 -7.07407407 -3.07407407
34 -6.07407407 -7.07407407
35 -2.07407407 -6.07407407
36 -2.07407407 -2.07407407
37 0.92592593 -2.07407407
38 6.92592593 0.92592593
39 -0.07407407 6.92592593
40 9.05555556 -0.07407407
41 2.05555556 9.05555556
42 2.05555556 2.05555556
43 8.05555556 2.05555556
44 -2.94444444 8.05555556
45 7.05555556 -2.94444444
46 -9.07407407 7.05555556
47 -6.07407407 -9.07407407
48 -0.07407407 -6.07407407
49 -1.07407407 -0.07407407
50 -2.07407407 -1.07407407
51 -0.07407407 -2.07407407
52 1.92592593 -0.07407407
53 2.92592593 1.92592593
54 8.92592593 2.92592593
55 2.92592593 8.92592593
56 8.92592593 2.92592593
57 10.92592593 8.92592593
58 11.92592593 10.92592593
59 3.92592593 11.92592593
60 11.92592593 3.92592593
61 12.92592593 11.92592593
62 12.92592593 12.92592593
63 20.92592593 12.92592593
64 14.92592593 20.92592593
65 14.92592593 14.92592593
66 10.92592593 14.92592593
67 8.92592593 10.92592593
68 2.92592593 8.92592593
69 4.92592593 2.92592593
70 -11.07407407 4.92592593
71 -14.07407407 -11.07407407
> 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/7jkre1228940767.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8b6hr1228940767.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9wtbg1228940767.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10r5921228940767.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/118nsz1228940767.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/121g7k1228940767.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/13wzwy1228940767.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/14i74n1228940767.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/15jo7n1228940768.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/16bgk61228940768.tab")
+ }
>
> system("convert tmp/1pus31228940767.ps tmp/1pus31228940767.png")
> system("convert tmp/27tka1228940767.ps tmp/27tka1228940767.png")
> system("convert tmp/3tq7s1228940767.ps tmp/3tq7s1228940767.png")
> system("convert tmp/4137u1228940767.ps tmp/4137u1228940767.png")
> system("convert tmp/5mp1r1228940767.ps tmp/5mp1r1228940767.png")
> system("convert tmp/60g0a1228940767.ps tmp/60g0a1228940767.png")
> system("convert tmp/7jkre1228940767.ps tmp/7jkre1228940767.png")
> system("convert tmp/8b6hr1228940767.ps tmp/8b6hr1228940767.png")
> system("convert tmp/9wtbg1228940767.ps tmp/9wtbg1228940767.png")
> system("convert tmp/10r5921228940767.ps tmp/10r5921228940767.png")
>
>
> proc.time()
user system elapsed
2.707 1.691 3.723