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(524,0,552,0,532,0,511,0,492,0,492,0,493,0,481,0,462,0,457,0,442,0,439,0,488,0,521,0,501,0,485,0,464,0,460,0,467,0,460,0,448,0,443,0,436,0,431,0,484,0,510,0,513,0,503,0,471,0,471,0,476,0,475,0,470,0,461,0,455,0,456,0,517,0,525,0,523,0,519,0,509,0,512,0,519,0,517,0,510,0,509,0,501,0,507,0,569,1,580,1,578,1,565,1,547,1,555,1,562,1,561,1,555,1,544,1,537,1,543,1,594,1,611,1,613,1,611,1,594,1,595,1,591,1,589,1,584,1,573,1,567,1,569,1,621,1,629,1,628,1,612,1,595,1,597,1,593,1,590,1,580,1,574,1,573,1,573,1,620,1,626,1,620,1,588,1,566,1,557,1,561,1,549,1,532,1,526,1,511,1,499,1),dim=c(2,96),dimnames=list(c('Aantal_werklozen_(*1000)','dummyvariabele'),1:96))
> y <- array(NA,dim=c(2,96),dimnames=list(c('Aantal_werklozen_(*1000)','dummyvariabele'),1:96))
> 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_(*1000) dummyvariabele
1 524 0
2 552 0
3 532 0
4 511 0
5 492 0
6 492 0
7 493 0
8 481 0
9 462 0
10 457 0
11 442 0
12 439 0
13 488 0
14 521 0
15 501 0
16 485 0
17 464 0
18 460 0
19 467 0
20 460 0
21 448 0
22 443 0
23 436 0
24 431 0
25 484 0
26 510 0
27 513 0
28 503 0
29 471 0
30 471 0
31 476 0
32 475 0
33 470 0
34 461 0
35 455 0
36 456 0
37 517 0
38 525 0
39 523 0
40 519 0
41 509 0
42 512 0
43 519 0
44 517 0
45 510 0
46 509 0
47 501 0
48 507 0
49 569 1
50 580 1
51 578 1
52 565 1
53 547 1
54 555 1
55 562 1
56 561 1
57 555 1
58 544 1
59 537 1
60 543 1
61 594 1
62 611 1
63 613 1
64 611 1
65 594 1
66 595 1
67 591 1
68 589 1
69 584 1
70 573 1
71 567 1
72 569 1
73 621 1
74 629 1
75 628 1
76 612 1
77 595 1
78 597 1
79 593 1
80 590 1
81 580 1
82 574 1
83 573 1
84 573 1
85 620 1
86 626 1
87 620 1
88 588 1
89 566 1
90 557 1
91 561 1
92 549 1
93 532 1
94 526 1
95 511 1
96 499 1
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) dummyvariabele
487.37 89.85
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-78.2292 -22.2292 0.6979 22.6250 64.6250
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 487.375 4.356 111.89 <2e-16 ***
dummyvariabele 89.854 6.160 14.59 <2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 30.18 on 94 degrees of freedom
Multiple R-squared: 0.6936, Adjusted R-squared: 0.6903
F-statistic: 212.8 on 1 and 94 DF, p-value: < 2.2e-16
> if (n > n25) {
+ kp3 <- k + 3
+ nmkm3 <- n - k - 3
+ gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
+ numgqtests <- 0
+ numsignificant1 <- 0
+ numsignificant5 <- 0
+ numsignificant10 <- 0
+ for (mypoint in kp3:nmkm3) {
+ j <- 0
+ numgqtests <- numgqtests + 1
+ for (myalt in c('greater', 'two.sided', 'less')) {
+ j <- j + 1
+ gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
+ }
+ if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
+ }
+ gqarr
+ }
[,1] [,2] [,3]
[1,] 0.49293887 0.98587775 0.5070611
[2,] 0.47060268 0.94120536 0.5293973
[3,] 0.40877587 0.81755173 0.5912241
[4,] 0.41955475 0.83910949 0.5804453
[5,] 0.55889146 0.88221709 0.4411085
[6,] 0.65982900 0.68034200 0.3401710
[7,] 0.80347836 0.39304327 0.1965216
[8,] 0.88359449 0.23281103 0.1164055
[9,] 0.83351765 0.33296470 0.1664823
[10,] 0.82754779 0.34490441 0.1724522
[11,] 0.77460623 0.45078753 0.2253938
[12,] 0.71074475 0.57851050 0.2892552
[13,] 0.68838920 0.62322161 0.3116108
[14,] 0.67677935 0.64644131 0.3232207
[15,] 0.63703851 0.72592298 0.3629615
[16,] 0.61884092 0.76231817 0.3811591
[17,] 0.65246415 0.69507170 0.3475359
[18,] 0.70529657 0.58940687 0.2947034
[19,] 0.78447430 0.43105140 0.2155257
[20,] 0.86794017 0.26411966 0.1320598
[21,] 0.83141758 0.33716484 0.1685824
[22,] 0.81989264 0.36021471 0.1801074
[23,] 0.81281801 0.37436397 0.1871820
[24,] 0.78247119 0.43505762 0.2175288
[25,] 0.74723490 0.50553020 0.2527651
[26,] 0.71091417 0.57817165 0.2890858
[27,] 0.66591448 0.66817104 0.3340855
[28,] 0.62192681 0.75614637 0.3780732
[29,] 0.58950867 0.82098266 0.4104913
[30,] 0.59014611 0.81970778 0.4098539
[31,] 0.62663764 0.74672472 0.3733624
[32,] 0.67274140 0.65451721 0.3272586
[33,] 0.67419398 0.65161205 0.3258060
[34,] 0.69751166 0.60497668 0.3024883
[35,] 0.70719621 0.58560757 0.2928038
[36,] 0.70050681 0.59898638 0.2994932
[37,] 0.66903436 0.66193129 0.3309656
[38,] 0.64029405 0.71941190 0.3597060
[39,] 0.62578299 0.74843401 0.3742170
[40,] 0.60404161 0.79191679 0.3959584
[41,] 0.56531960 0.86936079 0.4346804
[42,] 0.52351611 0.95296778 0.4764839
[43,] 0.47130396 0.94260791 0.5286960
[44,] 0.42513394 0.85026789 0.5748661
[45,] 0.36984406 0.73968813 0.6301559
[46,] 0.31716059 0.63432118 0.6828394
[47,] 0.26636818 0.53273636 0.7336318
[48,] 0.22544033 0.45088066 0.7745597
[49,] 0.21621718 0.43243436 0.7837828
[50,] 0.18959318 0.37918637 0.8104068
[51,] 0.15751404 0.31502808 0.8424860
[52,] 0.13012643 0.26025287 0.8698736
[53,] 0.11154266 0.22308531 0.8884573
[54,] 0.10956479 0.21912959 0.8904352
[55,] 0.12254517 0.24509034 0.8774548
[56,] 0.12510580 0.25021160 0.8748942
[57,] 0.11459594 0.22919188 0.8854041
[58,] 0.13262912 0.26525825 0.8673709
[59,] 0.15210511 0.30421021 0.8478949
[60,] 0.16298438 0.32596875 0.8370156
[61,] 0.13830147 0.27660294 0.8616985
[62,] 0.11662242 0.23324483 0.8833776
[63,] 0.09351272 0.18702544 0.9064873
[64,] 0.07254122 0.14508244 0.9274588
[65,] 0.05358300 0.10716600 0.9464170
[66,] 0.03836275 0.07672550 0.9616372
[67,] 0.02771464 0.05542928 0.9722854
[68,] 0.01932906 0.03865812 0.9806709
[69,] 0.02623593 0.05247186 0.9737641
[70,] 0.04653677 0.09307355 0.9534632
[71,] 0.07937114 0.15874228 0.9206289
[72,] 0.08831088 0.17662177 0.9116891
[73,] 0.07323260 0.14646520 0.9267674
[74,] 0.06287137 0.12574275 0.9371286
[75,] 0.05107321 0.10214642 0.9489268
[76,] 0.03976812 0.07953624 0.9602319
[77,] 0.02729983 0.05459966 0.9727002
[78,] 0.01749404 0.03498809 0.9825060
[79,] 0.01072330 0.02144661 0.9892767
[80,] 0.00628918 0.01257836 0.9937108
[81,] 0.01523962 0.03047923 0.9847604
[82,] 0.07028316 0.14056631 0.9297168
[83,] 0.31927358 0.63854716 0.6807264
[84,] 0.48977446 0.97954892 0.5102255
[85,] 0.51002168 0.97995665 0.4899783
[86,] 0.48593689 0.97187378 0.5140631
[87,] 0.58597757 0.82804486 0.4140224
> postscript(file="/var/www/html/rcomp/tmp/13vjy1229456281.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/21w071229456281.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3yj041229456281.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4erpz1229456281.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5d34v1229456281.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 = 96
Frequency = 1
1 2 3 4 5 6
36.6250000 64.6250000 44.6250000 23.6250000 4.6250000 4.6250000
7 8 9 10 11 12
5.6250000 -6.3750000 -25.3750000 -30.3750000 -45.3750000 -48.3750000
13 14 15 16 17 18
0.6250000 33.6250000 13.6250000 -2.3750000 -23.3750000 -27.3750000
19 20 21 22 23 24
-20.3750000 -27.3750000 -39.3750000 -44.3750000 -51.3750000 -56.3750000
25 26 27 28 29 30
-3.3750000 22.6250000 25.6250000 15.6250000 -16.3750000 -16.3750000
31 32 33 34 35 36
-11.3750000 -12.3750000 -17.3750000 -26.3750000 -32.3750000 -31.3750000
37 38 39 40 41 42
29.6250000 37.6250000 35.6250000 31.6250000 21.6250000 24.6250000
43 44 45 46 47 48
31.6250000 29.6250000 22.6250000 21.6250000 13.6250000 19.6250000
49 50 51 52 53 54
-8.2291667 2.7708333 0.7708333 -12.2291667 -30.2291667 -22.2291667
55 56 57 58 59 60
-15.2291667 -16.2291667 -22.2291667 -33.2291667 -40.2291667 -34.2291667
61 62 63 64 65 66
16.7708333 33.7708333 35.7708333 33.7708333 16.7708333 17.7708333
67 68 69 70 71 72
13.7708333 11.7708333 6.7708333 -4.2291667 -10.2291667 -8.2291667
73 74 75 76 77 78
43.7708333 51.7708333 50.7708333 34.7708333 17.7708333 19.7708333
79 80 81 82 83 84
15.7708333 12.7708333 2.7708333 -3.2291667 -4.2291667 -4.2291667
85 86 87 88 89 90
42.7708333 48.7708333 42.7708333 10.7708333 -11.2291667 -20.2291667
91 92 93 94 95 96
-16.2291667 -28.2291667 -45.2291667 -51.2291667 -66.2291667 -78.2291667
> postscript(file="/var/www/html/rcomp/tmp/6ia861229456281.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 = 96
Frequency = 1
lag(myerror, k = 1) myerror
0 36.6250000 NA
1 64.6250000 36.6250000
2 44.6250000 64.6250000
3 23.6250000 44.6250000
4 4.6250000 23.6250000
5 4.6250000 4.6250000
6 5.6250000 4.6250000
7 -6.3750000 5.6250000
8 -25.3750000 -6.3750000
9 -30.3750000 -25.3750000
10 -45.3750000 -30.3750000
11 -48.3750000 -45.3750000
12 0.6250000 -48.3750000
13 33.6250000 0.6250000
14 13.6250000 33.6250000
15 -2.3750000 13.6250000
16 -23.3750000 -2.3750000
17 -27.3750000 -23.3750000
18 -20.3750000 -27.3750000
19 -27.3750000 -20.3750000
20 -39.3750000 -27.3750000
21 -44.3750000 -39.3750000
22 -51.3750000 -44.3750000
23 -56.3750000 -51.3750000
24 -3.3750000 -56.3750000
25 22.6250000 -3.3750000
26 25.6250000 22.6250000
27 15.6250000 25.6250000
28 -16.3750000 15.6250000
29 -16.3750000 -16.3750000
30 -11.3750000 -16.3750000
31 -12.3750000 -11.3750000
32 -17.3750000 -12.3750000
33 -26.3750000 -17.3750000
34 -32.3750000 -26.3750000
35 -31.3750000 -32.3750000
36 29.6250000 -31.3750000
37 37.6250000 29.6250000
38 35.6250000 37.6250000
39 31.6250000 35.6250000
40 21.6250000 31.6250000
41 24.6250000 21.6250000
42 31.6250000 24.6250000
43 29.6250000 31.6250000
44 22.6250000 29.6250000
45 21.6250000 22.6250000
46 13.6250000 21.6250000
47 19.6250000 13.6250000
48 -8.2291667 19.6250000
49 2.7708333 -8.2291667
50 0.7708333 2.7708333
51 -12.2291667 0.7708333
52 -30.2291667 -12.2291667
53 -22.2291667 -30.2291667
54 -15.2291667 -22.2291667
55 -16.2291667 -15.2291667
56 -22.2291667 -16.2291667
57 -33.2291667 -22.2291667
58 -40.2291667 -33.2291667
59 -34.2291667 -40.2291667
60 16.7708333 -34.2291667
61 33.7708333 16.7708333
62 35.7708333 33.7708333
63 33.7708333 35.7708333
64 16.7708333 33.7708333
65 17.7708333 16.7708333
66 13.7708333 17.7708333
67 11.7708333 13.7708333
68 6.7708333 11.7708333
69 -4.2291667 6.7708333
70 -10.2291667 -4.2291667
71 -8.2291667 -10.2291667
72 43.7708333 -8.2291667
73 51.7708333 43.7708333
74 50.7708333 51.7708333
75 34.7708333 50.7708333
76 17.7708333 34.7708333
77 19.7708333 17.7708333
78 15.7708333 19.7708333
79 12.7708333 15.7708333
80 2.7708333 12.7708333
81 -3.2291667 2.7708333
82 -4.2291667 -3.2291667
83 -4.2291667 -4.2291667
84 42.7708333 -4.2291667
85 48.7708333 42.7708333
86 42.7708333 48.7708333
87 10.7708333 42.7708333
88 -11.2291667 10.7708333
89 -20.2291667 -11.2291667
90 -16.2291667 -20.2291667
91 -28.2291667 -16.2291667
92 -45.2291667 -28.2291667
93 -51.2291667 -45.2291667
94 -66.2291667 -51.2291667
95 -78.2291667 -66.2291667
96 NA -78.2291667
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 64.6250000 36.6250000
[2,] 44.6250000 64.6250000
[3,] 23.6250000 44.6250000
[4,] 4.6250000 23.6250000
[5,] 4.6250000 4.6250000
[6,] 5.6250000 4.6250000
[7,] -6.3750000 5.6250000
[8,] -25.3750000 -6.3750000
[9,] -30.3750000 -25.3750000
[10,] -45.3750000 -30.3750000
[11,] -48.3750000 -45.3750000
[12,] 0.6250000 -48.3750000
[13,] 33.6250000 0.6250000
[14,] 13.6250000 33.6250000
[15,] -2.3750000 13.6250000
[16,] -23.3750000 -2.3750000
[17,] -27.3750000 -23.3750000
[18,] -20.3750000 -27.3750000
[19,] -27.3750000 -20.3750000
[20,] -39.3750000 -27.3750000
[21,] -44.3750000 -39.3750000
[22,] -51.3750000 -44.3750000
[23,] -56.3750000 -51.3750000
[24,] -3.3750000 -56.3750000
[25,] 22.6250000 -3.3750000
[26,] 25.6250000 22.6250000
[27,] 15.6250000 25.6250000
[28,] -16.3750000 15.6250000
[29,] -16.3750000 -16.3750000
[30,] -11.3750000 -16.3750000
[31,] -12.3750000 -11.3750000
[32,] -17.3750000 -12.3750000
[33,] -26.3750000 -17.3750000
[34,] -32.3750000 -26.3750000
[35,] -31.3750000 -32.3750000
[36,] 29.6250000 -31.3750000
[37,] 37.6250000 29.6250000
[38,] 35.6250000 37.6250000
[39,] 31.6250000 35.6250000
[40,] 21.6250000 31.6250000
[41,] 24.6250000 21.6250000
[42,] 31.6250000 24.6250000
[43,] 29.6250000 31.6250000
[44,] 22.6250000 29.6250000
[45,] 21.6250000 22.6250000
[46,] 13.6250000 21.6250000
[47,] 19.6250000 13.6250000
[48,] -8.2291667 19.6250000
[49,] 2.7708333 -8.2291667
[50,] 0.7708333 2.7708333
[51,] -12.2291667 0.7708333
[52,] -30.2291667 -12.2291667
[53,] -22.2291667 -30.2291667
[54,] -15.2291667 -22.2291667
[55,] -16.2291667 -15.2291667
[56,] -22.2291667 -16.2291667
[57,] -33.2291667 -22.2291667
[58,] -40.2291667 -33.2291667
[59,] -34.2291667 -40.2291667
[60,] 16.7708333 -34.2291667
[61,] 33.7708333 16.7708333
[62,] 35.7708333 33.7708333
[63,] 33.7708333 35.7708333
[64,] 16.7708333 33.7708333
[65,] 17.7708333 16.7708333
[66,] 13.7708333 17.7708333
[67,] 11.7708333 13.7708333
[68,] 6.7708333 11.7708333
[69,] -4.2291667 6.7708333
[70,] -10.2291667 -4.2291667
[71,] -8.2291667 -10.2291667
[72,] 43.7708333 -8.2291667
[73,] 51.7708333 43.7708333
[74,] 50.7708333 51.7708333
[75,] 34.7708333 50.7708333
[76,] 17.7708333 34.7708333
[77,] 19.7708333 17.7708333
[78,] 15.7708333 19.7708333
[79,] 12.7708333 15.7708333
[80,] 2.7708333 12.7708333
[81,] -3.2291667 2.7708333
[82,] -4.2291667 -3.2291667
[83,] -4.2291667 -4.2291667
[84,] 42.7708333 -4.2291667
[85,] 48.7708333 42.7708333
[86,] 42.7708333 48.7708333
[87,] 10.7708333 42.7708333
[88,] -11.2291667 10.7708333
[89,] -20.2291667 -11.2291667
[90,] -16.2291667 -20.2291667
[91,] -28.2291667 -16.2291667
[92,] -45.2291667 -28.2291667
[93,] -51.2291667 -45.2291667
[94,] -66.2291667 -51.2291667
[95,] -78.2291667 -66.2291667
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 64.6250000 36.6250000
2 44.6250000 64.6250000
3 23.6250000 44.6250000
4 4.6250000 23.6250000
5 4.6250000 4.6250000
6 5.6250000 4.6250000
7 -6.3750000 5.6250000
8 -25.3750000 -6.3750000
9 -30.3750000 -25.3750000
10 -45.3750000 -30.3750000
11 -48.3750000 -45.3750000
12 0.6250000 -48.3750000
13 33.6250000 0.6250000
14 13.6250000 33.6250000
15 -2.3750000 13.6250000
16 -23.3750000 -2.3750000
17 -27.3750000 -23.3750000
18 -20.3750000 -27.3750000
19 -27.3750000 -20.3750000
20 -39.3750000 -27.3750000
21 -44.3750000 -39.3750000
22 -51.3750000 -44.3750000
23 -56.3750000 -51.3750000
24 -3.3750000 -56.3750000
25 22.6250000 -3.3750000
26 25.6250000 22.6250000
27 15.6250000 25.6250000
28 -16.3750000 15.6250000
29 -16.3750000 -16.3750000
30 -11.3750000 -16.3750000
31 -12.3750000 -11.3750000
32 -17.3750000 -12.3750000
33 -26.3750000 -17.3750000
34 -32.3750000 -26.3750000
35 -31.3750000 -32.3750000
36 29.6250000 -31.3750000
37 37.6250000 29.6250000
38 35.6250000 37.6250000
39 31.6250000 35.6250000
40 21.6250000 31.6250000
41 24.6250000 21.6250000
42 31.6250000 24.6250000
43 29.6250000 31.6250000
44 22.6250000 29.6250000
45 21.6250000 22.6250000
46 13.6250000 21.6250000
47 19.6250000 13.6250000
48 -8.2291667 19.6250000
49 2.7708333 -8.2291667
50 0.7708333 2.7708333
51 -12.2291667 0.7708333
52 -30.2291667 -12.2291667
53 -22.2291667 -30.2291667
54 -15.2291667 -22.2291667
55 -16.2291667 -15.2291667
56 -22.2291667 -16.2291667
57 -33.2291667 -22.2291667
58 -40.2291667 -33.2291667
59 -34.2291667 -40.2291667
60 16.7708333 -34.2291667
61 33.7708333 16.7708333
62 35.7708333 33.7708333
63 33.7708333 35.7708333
64 16.7708333 33.7708333
65 17.7708333 16.7708333
66 13.7708333 17.7708333
67 11.7708333 13.7708333
68 6.7708333 11.7708333
69 -4.2291667 6.7708333
70 -10.2291667 -4.2291667
71 -8.2291667 -10.2291667
72 43.7708333 -8.2291667
73 51.7708333 43.7708333
74 50.7708333 51.7708333
75 34.7708333 50.7708333
76 17.7708333 34.7708333
77 19.7708333 17.7708333
78 15.7708333 19.7708333
79 12.7708333 15.7708333
80 2.7708333 12.7708333
81 -3.2291667 2.7708333
82 -4.2291667 -3.2291667
83 -4.2291667 -4.2291667
84 42.7708333 -4.2291667
85 48.7708333 42.7708333
86 42.7708333 48.7708333
87 10.7708333 42.7708333
88 -11.2291667 10.7708333
89 -20.2291667 -11.2291667
90 -16.2291667 -20.2291667
91 -28.2291667 -16.2291667
92 -45.2291667 -28.2291667
93 -51.2291667 -45.2291667
94 -66.2291667 -51.2291667
95 -78.2291667 -66.2291667
> 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/7t6x01229456281.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8xnhq1229456282.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9zr1s1229456282.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
hat values (leverages) are all = 0.02083333
and there are no factor predictors; no plot no. 5
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10jddn1229456282.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11iisl1229456282.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/12rns71229456282.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/13tvhs1229456282.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/1489v71229456282.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/15ibaq1229456282.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/16j4ts1229456282.tab")
+ }
>
> system("convert tmp/13vjy1229456281.ps tmp/13vjy1229456281.png")
> system("convert tmp/21w071229456281.ps tmp/21w071229456281.png")
> system("convert tmp/3yj041229456281.ps tmp/3yj041229456281.png")
> system("convert tmp/4erpz1229456281.ps tmp/4erpz1229456281.png")
> system("convert tmp/5d34v1229456281.ps tmp/5d34v1229456281.png")
> system("convert tmp/6ia861229456281.ps tmp/6ia861229456281.png")
> system("convert tmp/7t6x01229456281.ps tmp/7t6x01229456281.png")
> system("convert tmp/8xnhq1229456282.ps tmp/8xnhq1229456282.png")
> system("convert tmp/9zr1s1229456282.ps tmp/9zr1s1229456282.png")
> system("convert tmp/10jddn1229456282.ps tmp/10jddn1229456282.png")
>
>
> proc.time()
user system elapsed
2.881 1.610 3.314