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.
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(519,0,517,0,510,0,509,0,501,0,507,0,569,0,580,0,578,0,565,0,547,0,555,0,562,0,561,0,555,0,544,0,537,0,543,0,594,0,611,0,613,0,611,0,594,0,595,0,591,0,589,0,584,0,573,0,567,0,569,0,621,0,629,0,628,0,612,0,595,0,597,0,593,0,590,0,580,0,574,0,573,0,573,0,620,0,626,0,620,0,588,0,566,0,557,0,561,1,549,1,532,1,526,1,511,1,499,1,555,1,565,1,542,1,527,1,510,1,514,1,517,1,508,1,493,1,490,1,469,1,478,1),dim=c(2,66),dimnames=list(c('Aantal_werklozen','Dummyvariabele'),1:66))
> y <- array(NA,dim=c(2,66),dimnames=list(c('Aantal_werklozen','Dummyvariabele'),1:66))
> 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
Aantal_werklozen Dummyvariabele
1 519 0
2 517 0
3 510 0
4 509 0
5 501 0
6 507 0
7 569 0
8 580 0
9 578 0
10 565 0
11 547 0
12 555 0
13 562 0
14 561 0
15 555 0
16 544 0
17 537 0
18 543 0
19 594 0
20 611 0
21 613 0
22 611 0
23 594 0
24 595 0
25 591 0
26 589 0
27 584 0
28 573 0
29 567 0
30 569 0
31 621 0
32 629 0
33 628 0
34 612 0
35 595 0
36 597 0
37 593 0
38 590 0
39 580 0
40 574 0
41 573 0
42 573 0
43 620 0
44 626 0
45 620 0
46 588 0
47 566 0
48 557 0
49 561 1
50 549 1
51 532 1
52 526 1
53 511 1
54 499 1
55 555 1
56 565 1
57 542 1
58 527 1
59 510 1
60 514 1
61 517 1
62 508 1
63 493 1
64 490 1
65 469 1
66 478 1
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Dummyvariabele
574.83 -55.61
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-73.833 -19.333 -1.333 20.167 54.167
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 574.833 4.695 122.446 < 2e-16 ***
Dummyvariabele -55.611 8.989 -6.186 4.85e-08 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 32.52 on 64 degrees of freedom
Multiple R-squared: 0.3742, Adjusted R-squared: 0.3644
F-statistic: 38.27 on 1 and 64 DF, p-value: 4.853e-08
> 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,] 0.03457085 0.06914170 0.96542915
[2,] 0.01221812 0.02443624 0.98778188
[3,] 0.52813310 0.94373381 0.47186690
[4,] 0.81882392 0.36235216 0.18117608
[5,] 0.88961496 0.22077009 0.11038504
[6,] 0.88355206 0.23289587 0.11644794
[7,] 0.85284717 0.29430565 0.14715283
[8,] 0.82414656 0.35170688 0.17585344
[9,] 0.80176306 0.39647389 0.19823694
[10,] 0.77431370 0.45137261 0.22568630
[11,] 0.74061238 0.51877524 0.25938762
[12,] 0.72090207 0.55819587 0.27909793
[13,] 0.73400951 0.53198098 0.26599049
[14,] 0.74322473 0.51355053 0.25677527
[15,] 0.83308986 0.33382028 0.16691014
[16,] 0.93132823 0.13734354 0.06867177
[17,] 0.96941924 0.06116152 0.03058076
[18,] 0.98257855 0.03484290 0.01742145
[19,] 0.98136236 0.03727528 0.01863764
[20,] 0.97950320 0.04099360 0.02049680
[21,] 0.97509161 0.04981677 0.02490839
[22,] 0.96851862 0.06296275 0.03148138
[23,] 0.95858595 0.08282809 0.04141405
[24,] 0.94643272 0.10713457 0.05356728
[25,] 0.93569495 0.12861009 0.06430505
[26,] 0.92355960 0.15288080 0.07644040
[27,] 0.94602325 0.10795351 0.05397675
[28,] 0.97028382 0.05943236 0.02971618
[29,] 0.98308199 0.03383602 0.01691801
[30,] 0.98299188 0.03401625 0.01700812
[31,] 0.97604683 0.04790634 0.02395317
[32,] 0.96738745 0.06522511 0.03261255
[33,] 0.95431036 0.09137927 0.04568964
[34,] 0.93580489 0.12839021 0.06419511
[35,] 0.91057265 0.17885469 0.08942735
[36,] 0.88237751 0.23524499 0.11762249
[37,] 0.85154964 0.29690071 0.14845036
[38,] 0.81977064 0.36045873 0.18022936
[39,] 0.82529667 0.34940666 0.17470333
[40,] 0.86332308 0.27335385 0.13667692
[41,] 0.90055826 0.19888349 0.09944174
[42,] 0.87788452 0.24423096 0.12211548
[43,] 0.83258642 0.33482715 0.16741358
[44,] 0.77762690 0.44474620 0.22237310
[45,] 0.81038745 0.37922509 0.18961255
[46,] 0.80935885 0.38128230 0.19064115
[47,] 0.76523830 0.46952339 0.23476170
[48,] 0.70301460 0.59397080 0.29698540
[49,] 0.62489717 0.75020565 0.37510283
[50,] 0.55949933 0.88100133 0.44050067
[51,] 0.62054097 0.75891806 0.37945903
[52,] 0.83643312 0.32713376 0.16356688
[53,] 0.89924668 0.20150664 0.10075332
[54,] 0.90800289 0.18399422 0.09199711
[55,] 0.85662150 0.28675701 0.14337850
[56,] 0.81415196 0.37169607 0.18584804
[57,] 0.83101543 0.33796915 0.16898457
> postscript(file="/var/www/html/rcomp/tmp/1ppbr1227471267.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2k3eo1227471267.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3s58v1227471267.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4r3gf1227471267.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5m87y1227471267.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 = 66
Frequency = 1
1 2 3 4 5 6
-55.8333333 -57.8333333 -64.8333333 -65.8333333 -73.8333333 -67.8333333
7 8 9 10 11 12
-5.8333333 5.1666667 3.1666667 -9.8333333 -27.8333333 -19.8333333
13 14 15 16 17 18
-12.8333333 -13.8333333 -19.8333333 -30.8333333 -37.8333333 -31.8333333
19 20 21 22 23 24
19.1666667 36.1666667 38.1666667 36.1666667 19.1666667 20.1666667
25 26 27 28 29 30
16.1666667 14.1666667 9.1666667 -1.8333333 -7.8333333 -5.8333333
31 32 33 34 35 36
46.1666667 54.1666667 53.1666667 37.1666667 20.1666667 22.1666667
37 38 39 40 41 42
18.1666667 15.1666667 5.1666667 -0.8333333 -1.8333333 -1.8333333
43 44 45 46 47 48
45.1666667 51.1666667 45.1666667 13.1666667 -8.8333333 -17.8333333
49 50 51 52 53 54
41.7777778 29.7777778 12.7777778 6.7777778 -8.2222222 -20.2222222
55 56 57 58 59 60
35.7777778 45.7777778 22.7777778 7.7777778 -9.2222222 -5.2222222
61 62 63 64 65 66
-2.2222222 -11.2222222 -26.2222222 -29.2222222 -50.2222222 -41.2222222
> postscript(file="/var/www/html/rcomp/tmp/6sghh1227471267.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 = 66
Frequency = 1
lag(myerror, k = 1) myerror
0 -55.8333333 NA
1 -57.8333333 -55.8333333
2 -64.8333333 -57.8333333
3 -65.8333333 -64.8333333
4 -73.8333333 -65.8333333
5 -67.8333333 -73.8333333
6 -5.8333333 -67.8333333
7 5.1666667 -5.8333333
8 3.1666667 5.1666667
9 -9.8333333 3.1666667
10 -27.8333333 -9.8333333
11 -19.8333333 -27.8333333
12 -12.8333333 -19.8333333
13 -13.8333333 -12.8333333
14 -19.8333333 -13.8333333
15 -30.8333333 -19.8333333
16 -37.8333333 -30.8333333
17 -31.8333333 -37.8333333
18 19.1666667 -31.8333333
19 36.1666667 19.1666667
20 38.1666667 36.1666667
21 36.1666667 38.1666667
22 19.1666667 36.1666667
23 20.1666667 19.1666667
24 16.1666667 20.1666667
25 14.1666667 16.1666667
26 9.1666667 14.1666667
27 -1.8333333 9.1666667
28 -7.8333333 -1.8333333
29 -5.8333333 -7.8333333
30 46.1666667 -5.8333333
31 54.1666667 46.1666667
32 53.1666667 54.1666667
33 37.1666667 53.1666667
34 20.1666667 37.1666667
35 22.1666667 20.1666667
36 18.1666667 22.1666667
37 15.1666667 18.1666667
38 5.1666667 15.1666667
39 -0.8333333 5.1666667
40 -1.8333333 -0.8333333
41 -1.8333333 -1.8333333
42 45.1666667 -1.8333333
43 51.1666667 45.1666667
44 45.1666667 51.1666667
45 13.1666667 45.1666667
46 -8.8333333 13.1666667
47 -17.8333333 -8.8333333
48 41.7777778 -17.8333333
49 29.7777778 41.7777778
50 12.7777778 29.7777778
51 6.7777778 12.7777778
52 -8.2222222 6.7777778
53 -20.2222222 -8.2222222
54 35.7777778 -20.2222222
55 45.7777778 35.7777778
56 22.7777778 45.7777778
57 7.7777778 22.7777778
58 -9.2222222 7.7777778
59 -5.2222222 -9.2222222
60 -2.2222222 -5.2222222
61 -11.2222222 -2.2222222
62 -26.2222222 -11.2222222
63 -29.2222222 -26.2222222
64 -50.2222222 -29.2222222
65 -41.2222222 -50.2222222
66 NA -41.2222222
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -57.8333333 -55.8333333
[2,] -64.8333333 -57.8333333
[3,] -65.8333333 -64.8333333
[4,] -73.8333333 -65.8333333
[5,] -67.8333333 -73.8333333
[6,] -5.8333333 -67.8333333
[7,] 5.1666667 -5.8333333
[8,] 3.1666667 5.1666667
[9,] -9.8333333 3.1666667
[10,] -27.8333333 -9.8333333
[11,] -19.8333333 -27.8333333
[12,] -12.8333333 -19.8333333
[13,] -13.8333333 -12.8333333
[14,] -19.8333333 -13.8333333
[15,] -30.8333333 -19.8333333
[16,] -37.8333333 -30.8333333
[17,] -31.8333333 -37.8333333
[18,] 19.1666667 -31.8333333
[19,] 36.1666667 19.1666667
[20,] 38.1666667 36.1666667
[21,] 36.1666667 38.1666667
[22,] 19.1666667 36.1666667
[23,] 20.1666667 19.1666667
[24,] 16.1666667 20.1666667
[25,] 14.1666667 16.1666667
[26,] 9.1666667 14.1666667
[27,] -1.8333333 9.1666667
[28,] -7.8333333 -1.8333333
[29,] -5.8333333 -7.8333333
[30,] 46.1666667 -5.8333333
[31,] 54.1666667 46.1666667
[32,] 53.1666667 54.1666667
[33,] 37.1666667 53.1666667
[34,] 20.1666667 37.1666667
[35,] 22.1666667 20.1666667
[36,] 18.1666667 22.1666667
[37,] 15.1666667 18.1666667
[38,] 5.1666667 15.1666667
[39,] -0.8333333 5.1666667
[40,] -1.8333333 -0.8333333
[41,] -1.8333333 -1.8333333
[42,] 45.1666667 -1.8333333
[43,] 51.1666667 45.1666667
[44,] 45.1666667 51.1666667
[45,] 13.1666667 45.1666667
[46,] -8.8333333 13.1666667
[47,] -17.8333333 -8.8333333
[48,] 41.7777778 -17.8333333
[49,] 29.7777778 41.7777778
[50,] 12.7777778 29.7777778
[51,] 6.7777778 12.7777778
[52,] -8.2222222 6.7777778
[53,] -20.2222222 -8.2222222
[54,] 35.7777778 -20.2222222
[55,] 45.7777778 35.7777778
[56,] 22.7777778 45.7777778
[57,] 7.7777778 22.7777778
[58,] -9.2222222 7.7777778
[59,] -5.2222222 -9.2222222
[60,] -2.2222222 -5.2222222
[61,] -11.2222222 -2.2222222
[62,] -26.2222222 -11.2222222
[63,] -29.2222222 -26.2222222
[64,] -50.2222222 -29.2222222
[65,] -41.2222222 -50.2222222
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -57.8333333 -55.8333333
2 -64.8333333 -57.8333333
3 -65.8333333 -64.8333333
4 -73.8333333 -65.8333333
5 -67.8333333 -73.8333333
6 -5.8333333 -67.8333333
7 5.1666667 -5.8333333
8 3.1666667 5.1666667
9 -9.8333333 3.1666667
10 -27.8333333 -9.8333333
11 -19.8333333 -27.8333333
12 -12.8333333 -19.8333333
13 -13.8333333 -12.8333333
14 -19.8333333 -13.8333333
15 -30.8333333 -19.8333333
16 -37.8333333 -30.8333333
17 -31.8333333 -37.8333333
18 19.1666667 -31.8333333
19 36.1666667 19.1666667
20 38.1666667 36.1666667
21 36.1666667 38.1666667
22 19.1666667 36.1666667
23 20.1666667 19.1666667
24 16.1666667 20.1666667
25 14.1666667 16.1666667
26 9.1666667 14.1666667
27 -1.8333333 9.1666667
28 -7.8333333 -1.8333333
29 -5.8333333 -7.8333333
30 46.1666667 -5.8333333
31 54.1666667 46.1666667
32 53.1666667 54.1666667
33 37.1666667 53.1666667
34 20.1666667 37.1666667
35 22.1666667 20.1666667
36 18.1666667 22.1666667
37 15.1666667 18.1666667
38 5.1666667 15.1666667
39 -0.8333333 5.1666667
40 -1.8333333 -0.8333333
41 -1.8333333 -1.8333333
42 45.1666667 -1.8333333
43 51.1666667 45.1666667
44 45.1666667 51.1666667
45 13.1666667 45.1666667
46 -8.8333333 13.1666667
47 -17.8333333 -8.8333333
48 41.7777778 -17.8333333
49 29.7777778 41.7777778
50 12.7777778 29.7777778
51 6.7777778 12.7777778
52 -8.2222222 6.7777778
53 -20.2222222 -8.2222222
54 35.7777778 -20.2222222
55 45.7777778 35.7777778
56 22.7777778 45.7777778
57 7.7777778 22.7777778
58 -9.2222222 7.7777778
59 -5.2222222 -9.2222222
60 -2.2222222 -5.2222222
61 -11.2222222 -2.2222222
62 -26.2222222 -11.2222222
63 -29.2222222 -26.2222222
64 -50.2222222 -29.2222222
65 -41.2222222 -50.2222222
> 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/73lys1227471267.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8lgjq1227471267.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9z0k31227471267.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10lmkq1227471267.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11a44i1227471267.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/12plke1227471267.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/13gsaf1227471267.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/143cu41227471267.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/15k64t1227471267.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/16v65z1227471268.tab")
+ }
>
> system("convert tmp/1ppbr1227471267.ps tmp/1ppbr1227471267.png")
> system("convert tmp/2k3eo1227471267.ps tmp/2k3eo1227471267.png")
> system("convert tmp/3s58v1227471267.ps tmp/3s58v1227471267.png")
> system("convert tmp/4r3gf1227471267.ps tmp/4r3gf1227471267.png")
> system("convert tmp/5m87y1227471267.ps tmp/5m87y1227471267.png")
> system("convert tmp/6sghh1227471267.ps tmp/6sghh1227471267.png")
> system("convert tmp/73lys1227471267.ps tmp/73lys1227471267.png")
> system("convert tmp/8lgjq1227471267.ps tmp/8lgjq1227471267.png")
> system("convert tmp/9z0k31227471267.ps tmp/9z0k31227471267.png")
> system("convert tmp/10lmkq1227471267.ps tmp/10lmkq1227471267.png")
>
>
> proc.time()
user system elapsed
2.507 1.569 2.917