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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> x <- array(list(8.1,10.9,7.7,10.0,7.5,9.2,7.6,9.2,7.8,9.5,7.8,9.6,7.8,9.5,7.5,9.1,7.5,8.9,7.1,9.0,7.5,10.1,7.5,10.3,7.6,10.2,7.7,9.6,7.7,9.2,7.9,9.3,8.1,9.4,8.2,9.4,8.2,9.2,8.2,9.0,7.9,9.0,7.3,9.0,6.9,9.8,6.6,10.0,6.7,9.8,6.9,9.3,7.0,9.0,7.1,9.0,7.2,9.1,7.1,9.1,6.9,9.1,7.0,9.2,6.8,8.8,6.4,8.3,6.7,8.4,6.6,8.1,6.4,7.7,6.3,7.9,6.2,7.9,6.5,8.0,6.8,7.9,6.8,7.6,6.4,7.1,6.1,6.8,5.8,6.5,6.1,6.9,7.2,8.2,7.3,8.7,6.9,8.3,6.1,7.9,5.8,7.5,6.2,7.8,7.1,8.3,7.7,8.4,7.9,8.2,7.7,7.7,7.4,7.2,7.5,7.3,8.0,8.1,8.1,8.5),dim=c(2,60),dimnames=list(c('Y','X'),1:60))
> y <- array(NA,dim=c(2,60),dimnames=list(c('Y','X'),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 = '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
Y X M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11
1 8.1 10.9 1 0 0 0 0 0 0 0 0 0 0
2 7.7 10.0 0 1 0 0 0 0 0 0 0 0 0
3 7.5 9.2 0 0 1 0 0 0 0 0 0 0 0
4 7.6 9.2 0 0 0 1 0 0 0 0 0 0 0
5 7.8 9.5 0 0 0 0 1 0 0 0 0 0 0
6 7.8 9.6 0 0 0 0 0 1 0 0 0 0 0
7 7.8 9.5 0 0 0 0 0 0 1 0 0 0 0
8 7.5 9.1 0 0 0 0 0 0 0 1 0 0 0
9 7.5 8.9 0 0 0 0 0 0 0 0 1 0 0
10 7.1 9.0 0 0 0 0 0 0 0 0 0 1 0
11 7.5 10.1 0 0 0 0 0 0 0 0 0 0 1
12 7.5 10.3 0 0 0 0 0 0 0 0 0 0 0
13 7.6 10.2 1 0 0 0 0 0 0 0 0 0 0
14 7.7 9.6 0 1 0 0 0 0 0 0 0 0 0
15 7.7 9.2 0 0 1 0 0 0 0 0 0 0 0
16 7.9 9.3 0 0 0 1 0 0 0 0 0 0 0
17 8.1 9.4 0 0 0 0 1 0 0 0 0 0 0
18 8.2 9.4 0 0 0 0 0 1 0 0 0 0 0
19 8.2 9.2 0 0 0 0 0 0 1 0 0 0 0
20 8.2 9.0 0 0 0 0 0 0 0 1 0 0 0
21 7.9 9.0 0 0 0 0 0 0 0 0 1 0 0
22 7.3 9.0 0 0 0 0 0 0 0 0 0 1 0
23 6.9 9.8 0 0 0 0 0 0 0 0 0 0 1
24 6.6 10.0 0 0 0 0 0 0 0 0 0 0 0
25 6.7 9.8 1 0 0 0 0 0 0 0 0 0 0
26 6.9 9.3 0 1 0 0 0 0 0 0 0 0 0
27 7.0 9.0 0 0 1 0 0 0 0 0 0 0 0
28 7.1 9.0 0 0 0 1 0 0 0 0 0 0 0
29 7.2 9.1 0 0 0 0 1 0 0 0 0 0 0
30 7.1 9.1 0 0 0 0 0 1 0 0 0 0 0
31 6.9 9.1 0 0 0 0 0 0 1 0 0 0 0
32 7.0 9.2 0 0 0 0 0 0 0 1 0 0 0
33 6.8 8.8 0 0 0 0 0 0 0 0 1 0 0
34 6.4 8.3 0 0 0 0 0 0 0 0 0 1 0
35 6.7 8.4 0 0 0 0 0 0 0 0 0 0 1
36 6.6 8.1 0 0 0 0 0 0 0 0 0 0 0
37 6.4 7.7 1 0 0 0 0 0 0 0 0 0 0
38 6.3 7.9 0 1 0 0 0 0 0 0 0 0 0
39 6.2 7.9 0 0 1 0 0 0 0 0 0 0 0
40 6.5 8.0 0 0 0 1 0 0 0 0 0 0 0
41 6.8 7.9 0 0 0 0 1 0 0 0 0 0 0
42 6.8 7.6 0 0 0 0 0 1 0 0 0 0 0
43 6.4 7.1 0 0 0 0 0 0 1 0 0 0 0
44 6.1 6.8 0 0 0 0 0 0 0 1 0 0 0
45 5.8 6.5 0 0 0 0 0 0 0 0 1 0 0
46 6.1 6.9 0 0 0 0 0 0 0 0 0 1 0
47 7.2 8.2 0 0 0 0 0 0 0 0 0 0 1
48 7.3 8.7 0 0 0 0 0 0 0 0 0 0 0
49 6.9 8.3 1 0 0 0 0 0 0 0 0 0 0
50 6.1 7.9 0 1 0 0 0 0 0 0 0 0 0
51 5.8 7.5 0 0 1 0 0 0 0 0 0 0 0
52 6.2 7.8 0 0 0 1 0 0 0 0 0 0 0
53 7.1 8.3 0 0 0 0 1 0 0 0 0 0 0
54 7.7 8.4 0 0 0 0 0 1 0 0 0 0 0
55 7.9 8.2 0 0 0 0 0 0 1 0 0 0 0
56 7.7 7.7 0 0 0 0 0 0 0 1 0 0 0
57 7.4 7.2 0 0 0 0 0 0 0 0 1 0 0
58 7.5 7.3 0 0 0 0 0 0 0 0 0 1 0
59 8.0 8.1 0 0 0 0 0 0 0 0 0 0 1
60 8.1 8.5 0 0 0 0 0 0 0 0 0 0 0
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X M1 M2 M3 M4
3.13252 0.44819 -0.19653 -0.19933 -0.12901 0.04617
M5 M6 M7 M8 M9 M10
0.30549 0.43446 0.44409 0.42062 0.32612 0.11715
M11
0.12964
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-1.01441 -0.33126 -0.06378 0.36947 1.15788
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 3.13252 0.77893 4.022 0.000208 ***
X 0.44819 0.08113 5.524 1.4e-06 ***
M1 -0.19653 0.34502 -0.570 0.571655
M2 -0.19933 0.34469 -0.578 0.565836
M3 -0.12901 0.34736 -0.371 0.712000
M4 0.04617 0.34639 0.133 0.894543
M5 0.30549 0.34513 0.885 0.380576
M6 0.43446 0.34524 1.258 0.214452
M7 0.44409 0.34676 1.281 0.206583
M8 0.42062 0.34985 1.202 0.235277
M9 0.32612 0.35456 0.920 0.362390
M10 0.11715 0.35418 0.331 0.742288
M11 0.12964 0.34476 0.376 0.708592
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.5445 on 47 degrees of freedom
Multiple R-squared: 0.4577, Adjusted R-squared: 0.3193
F-statistic: 3.306 on 12 and 47 DF, p-value: 0.001595
> 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,] 0.026035625 0.052071251 0.9739644
[2,] 0.017705256 0.035410511 0.9822947
[3,] 0.019583245 0.039166490 0.9804168
[4,] 0.018589166 0.037178333 0.9814108
[5,] 0.035705645 0.071411289 0.9642944
[6,] 0.026933244 0.053866489 0.9730668
[7,] 0.013573199 0.027146399 0.9864268
[8,] 0.013340115 0.026680231 0.9866599
[9,] 0.030030108 0.060060216 0.9699699
[10,] 0.031330591 0.062661182 0.9686694
[11,] 0.019415600 0.038831200 0.9805844
[12,] 0.015083501 0.030167002 0.9849165
[13,] 0.010663647 0.021327294 0.9893364
[14,] 0.006448594 0.012897188 0.9935514
[15,] 0.004653637 0.009307274 0.9953464
[16,] 0.008692230 0.017384460 0.9913078
[17,] 0.027962390 0.055924780 0.9720376
[18,] 0.051754243 0.103508486 0.9482458
[19,] 0.211861924 0.423723849 0.7881381
[20,] 0.618881822 0.762236357 0.3811182
[21,] 0.649555474 0.700889052 0.3504445
[22,] 0.583746011 0.832507979 0.4162540
[23,] 0.487899793 0.975799587 0.5121002
[24,] 0.412647576 0.825295152 0.5873524
[25,] 0.313542094 0.627084189 0.6864579
[26,] 0.227899765 0.455799529 0.7721002
[27,] 0.160248328 0.320496656 0.8397517
[28,] 0.107322359 0.214644718 0.8926776
[29,] 0.054073555 0.108147110 0.9459264
> postscript(file="/var/www/html/rcomp/tmp/1m3g81259181506.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2jfcm1259181506.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3dkn31259181506.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4mu741259181506.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5vyrk1259181506.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 = 60
Frequency = 1
1 2 3 4 5 6
0.27875333 0.28492009 0.37315930 0.29797816 0.10419552 -0.06958711
7 8 9 10 11 12
-0.03440597 -0.13165956 0.05248535 -0.18336974 -0.28886255 -0.24886255
13 14 15 16 17 18
0.09248535 0.46419552 0.57315930 0.55315930 0.44901438 0.42005061
19 20 21 22 23 24
0.50005061 0.61315930 0.40766649 0.01663026 -0.75440597 -1.01440597
25 26 27 28 29 30
-0.62823921 -0.20134790 -0.03720298 -0.11238412 -0.31652904 -0.54549281
31 32 33 34 35 36
-0.75513053 -0.67647842 -0.60269579 -0.56963772 -0.32694193 -0.16284763
37 38 39 40 41 42
0.01295685 -0.17388386 -0.34419552 -0.26419552 -0.17870272 -0.17320991
43 44 45 46 47 48
-0.35875333 -0.50082579 -0.57186201 -0.24217368 0.26269579 0.26823921
49 50 51 52 53 54
0.24404369 -0.37388386 -0.56492009 -0.47455781 -0.05797816 0.36823921
55 56 57 58 59 60
0.64823921 0.69580448 0.71440597 0.97855088 1.10751465 1.15787693
> postscript(file="/var/www/html/rcomp/tmp/6b3p61259181506.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 = 60
Frequency = 1
lag(myerror, k = 1) myerror
0 0.27875333 NA
1 0.28492009 0.27875333
2 0.37315930 0.28492009
3 0.29797816 0.37315930
4 0.10419552 0.29797816
5 -0.06958711 0.10419552
6 -0.03440597 -0.06958711
7 -0.13165956 -0.03440597
8 0.05248535 -0.13165956
9 -0.18336974 0.05248535
10 -0.28886255 -0.18336974
11 -0.24886255 -0.28886255
12 0.09248535 -0.24886255
13 0.46419552 0.09248535
14 0.57315930 0.46419552
15 0.55315930 0.57315930
16 0.44901438 0.55315930
17 0.42005061 0.44901438
18 0.50005061 0.42005061
19 0.61315930 0.50005061
20 0.40766649 0.61315930
21 0.01663026 0.40766649
22 -0.75440597 0.01663026
23 -1.01440597 -0.75440597
24 -0.62823921 -1.01440597
25 -0.20134790 -0.62823921
26 -0.03720298 -0.20134790
27 -0.11238412 -0.03720298
28 -0.31652904 -0.11238412
29 -0.54549281 -0.31652904
30 -0.75513053 -0.54549281
31 -0.67647842 -0.75513053
32 -0.60269579 -0.67647842
33 -0.56963772 -0.60269579
34 -0.32694193 -0.56963772
35 -0.16284763 -0.32694193
36 0.01295685 -0.16284763
37 -0.17388386 0.01295685
38 -0.34419552 -0.17388386
39 -0.26419552 -0.34419552
40 -0.17870272 -0.26419552
41 -0.17320991 -0.17870272
42 -0.35875333 -0.17320991
43 -0.50082579 -0.35875333
44 -0.57186201 -0.50082579
45 -0.24217368 -0.57186201
46 0.26269579 -0.24217368
47 0.26823921 0.26269579
48 0.24404369 0.26823921
49 -0.37388386 0.24404369
50 -0.56492009 -0.37388386
51 -0.47455781 -0.56492009
52 -0.05797816 -0.47455781
53 0.36823921 -0.05797816
54 0.64823921 0.36823921
55 0.69580448 0.64823921
56 0.71440597 0.69580448
57 0.97855088 0.71440597
58 1.10751465 0.97855088
59 1.15787693 1.10751465
60 NA 1.15787693
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 0.28492009 0.27875333
[2,] 0.37315930 0.28492009
[3,] 0.29797816 0.37315930
[4,] 0.10419552 0.29797816
[5,] -0.06958711 0.10419552
[6,] -0.03440597 -0.06958711
[7,] -0.13165956 -0.03440597
[8,] 0.05248535 -0.13165956
[9,] -0.18336974 0.05248535
[10,] -0.28886255 -0.18336974
[11,] -0.24886255 -0.28886255
[12,] 0.09248535 -0.24886255
[13,] 0.46419552 0.09248535
[14,] 0.57315930 0.46419552
[15,] 0.55315930 0.57315930
[16,] 0.44901438 0.55315930
[17,] 0.42005061 0.44901438
[18,] 0.50005061 0.42005061
[19,] 0.61315930 0.50005061
[20,] 0.40766649 0.61315930
[21,] 0.01663026 0.40766649
[22,] -0.75440597 0.01663026
[23,] -1.01440597 -0.75440597
[24,] -0.62823921 -1.01440597
[25,] -0.20134790 -0.62823921
[26,] -0.03720298 -0.20134790
[27,] -0.11238412 -0.03720298
[28,] -0.31652904 -0.11238412
[29,] -0.54549281 -0.31652904
[30,] -0.75513053 -0.54549281
[31,] -0.67647842 -0.75513053
[32,] -0.60269579 -0.67647842
[33,] -0.56963772 -0.60269579
[34,] -0.32694193 -0.56963772
[35,] -0.16284763 -0.32694193
[36,] 0.01295685 -0.16284763
[37,] -0.17388386 0.01295685
[38,] -0.34419552 -0.17388386
[39,] -0.26419552 -0.34419552
[40,] -0.17870272 -0.26419552
[41,] -0.17320991 -0.17870272
[42,] -0.35875333 -0.17320991
[43,] -0.50082579 -0.35875333
[44,] -0.57186201 -0.50082579
[45,] -0.24217368 -0.57186201
[46,] 0.26269579 -0.24217368
[47,] 0.26823921 0.26269579
[48,] 0.24404369 0.26823921
[49,] -0.37388386 0.24404369
[50,] -0.56492009 -0.37388386
[51,] -0.47455781 -0.56492009
[52,] -0.05797816 -0.47455781
[53,] 0.36823921 -0.05797816
[54,] 0.64823921 0.36823921
[55,] 0.69580448 0.64823921
[56,] 0.71440597 0.69580448
[57,] 0.97855088 0.71440597
[58,] 1.10751465 0.97855088
[59,] 1.15787693 1.10751465
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 0.28492009 0.27875333
2 0.37315930 0.28492009
3 0.29797816 0.37315930
4 0.10419552 0.29797816
5 -0.06958711 0.10419552
6 -0.03440597 -0.06958711
7 -0.13165956 -0.03440597
8 0.05248535 -0.13165956
9 -0.18336974 0.05248535
10 -0.28886255 -0.18336974
11 -0.24886255 -0.28886255
12 0.09248535 -0.24886255
13 0.46419552 0.09248535
14 0.57315930 0.46419552
15 0.55315930 0.57315930
16 0.44901438 0.55315930
17 0.42005061 0.44901438
18 0.50005061 0.42005061
19 0.61315930 0.50005061
20 0.40766649 0.61315930
21 0.01663026 0.40766649
22 -0.75440597 0.01663026
23 -1.01440597 -0.75440597
24 -0.62823921 -1.01440597
25 -0.20134790 -0.62823921
26 -0.03720298 -0.20134790
27 -0.11238412 -0.03720298
28 -0.31652904 -0.11238412
29 -0.54549281 -0.31652904
30 -0.75513053 -0.54549281
31 -0.67647842 -0.75513053
32 -0.60269579 -0.67647842
33 -0.56963772 -0.60269579
34 -0.32694193 -0.56963772
35 -0.16284763 -0.32694193
36 0.01295685 -0.16284763
37 -0.17388386 0.01295685
38 -0.34419552 -0.17388386
39 -0.26419552 -0.34419552
40 -0.17870272 -0.26419552
41 -0.17320991 -0.17870272
42 -0.35875333 -0.17320991
43 -0.50082579 -0.35875333
44 -0.57186201 -0.50082579
45 -0.24217368 -0.57186201
46 0.26269579 -0.24217368
47 0.26823921 0.26269579
48 0.24404369 0.26823921
49 -0.37388386 0.24404369
50 -0.56492009 -0.37388386
51 -0.47455781 -0.56492009
52 -0.05797816 -0.47455781
53 0.36823921 -0.05797816
54 0.64823921 0.36823921
55 0.69580448 0.64823921
56 0.71440597 0.69580448
57 0.97855088 0.71440597
58 1.10751465 0.97855088
59 1.15787693 1.10751465
> 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/7mcic1259181506.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/891zz1259181506.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/97dfn1259181506.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10ttwq1259181506.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/118j8c1259181506.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/12yobq1259181506.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/134lk21259181506.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/14s4vv1259181506.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/1593eh1259181506.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/16njm21259181507.tab")
+ }
>
> system("convert tmp/1m3g81259181506.ps tmp/1m3g81259181506.png")
> system("convert tmp/2jfcm1259181506.ps tmp/2jfcm1259181506.png")
> system("convert tmp/3dkn31259181506.ps tmp/3dkn31259181506.png")
> system("convert tmp/4mu741259181506.ps tmp/4mu741259181506.png")
> system("convert tmp/5vyrk1259181506.ps tmp/5vyrk1259181506.png")
> system("convert tmp/6b3p61259181506.ps tmp/6b3p61259181506.png")
> system("convert tmp/7mcic1259181506.ps tmp/7mcic1259181506.png")
> system("convert tmp/891zz1259181506.ps tmp/891zz1259181506.png")
> system("convert tmp/97dfn1259181506.ps tmp/97dfn1259181506.png")
> system("convert tmp/10ttwq1259181506.ps tmp/10ttwq1259181506.png")
>
>
> proc.time()
user system elapsed
2.398 1.547 3.087