R version 2.7.0 (2008-04-22)
Copyright (C) 2008 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
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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(11554.5
+ ,180144
+ ,13182.1
+ ,173666
+ ,14800.1
+ ,165688
+ ,12150.7
+ ,161570
+ ,14478.2
+ ,156145
+ ,13253.9
+ ,153730
+ ,12036.8
+ ,182698
+ ,12653.2
+ ,200765
+ ,14035.4
+ ,176512
+ ,14571.4
+ ,166618
+ ,15400.9
+ ,158644
+ ,14283.2
+ ,159585
+ ,14485.3
+ ,163095
+ ,14196.3
+ ,159044
+ ,15559.1
+ ,155511
+ ,13767.4
+ ,153745
+ ,14634
+ ,150569
+ ,14381.1
+ ,150605
+ ,12509.9
+ ,179612
+ ,12122.3
+ ,194690
+ ,13122.3
+ ,189917
+ ,13908.7
+ ,184128
+ ,13456.5
+ ,175335
+ ,12441.6
+ ,179566
+ ,12953
+ ,181140
+ ,13057.2
+ ,177876
+ ,14350.1
+ ,175041
+ ,13830.2
+ ,169292
+ ,13755.5
+ ,166070
+ ,13574.4
+ ,166972
+ ,12802.6
+ ,206348
+ ,11737.3
+ ,215706
+ ,13850.2
+ ,202108
+ ,15081.8
+ ,195411
+ ,13653.3
+ ,193111
+ ,14019.1
+ ,195198
+ ,13962
+ ,198770
+ ,13768.7
+ ,194163
+ ,14747.1
+ ,190420
+ ,13858.1
+ ,189733
+ ,13188
+ ,186029
+ ,13693.1
+ ,191531
+ ,12970
+ ,232571
+ ,11392.8
+ ,243477
+ ,13985.2
+ ,227247
+ ,14994.7
+ ,217859
+ ,13584.7
+ ,208679
+ ,14257.8
+ ,213188
+ ,13553.4
+ ,216234
+ ,14007.3
+ ,213586
+ ,16535.8
+ ,209465
+ ,14721.4
+ ,204045
+ ,13664.6
+ ,200237
+ ,16805.9
+ ,203666
+ ,13829.4
+ ,241476
+ ,13735.6
+ ,260307
+ ,15870.5
+ ,243324
+ ,15962.4
+ ,244460
+ ,15744.1
+ ,233575
+ ,16083.7
+ ,237217
+ ,14863.9
+ ,235243
+ ,15533.1
+ ,230354
+ ,17473.1
+ ,227184
+ ,15925.5
+ ,221678
+ ,15573.7
+ ,217142
+ ,17495
+ ,219452
+ ,14155.8
+ ,256446
+ ,14913.9
+ ,265845
+ ,17250.4
+ ,248624
+ ,15879.8
+ ,241114
+ ,17647.8
+ ,229245
+ ,17749.9
+ ,231805
+ ,17111.8
+ ,219277
+ ,16934.8
+ ,219313
+ ,20280
+ ,212610
+ ,16238.2
+ ,214771
+ ,17896.1
+ ,211142
+ ,18089.3
+ ,211457
+ ,15660
+ ,240048
+ ,16162.4
+ ,240636
+ ,17850.1
+ ,230580
+ ,18520.4
+ ,208795
+ ,18524.7
+ ,197922
+ ,16843.7
+ ,194596)
+ ,dim=c(2
+ ,84)
+ ,dimnames=list(c('invoer'
+ ,'werkloosheid')
+ ,1:84))
> y <- array(NA,dim=c(2,84),dimnames=list(c('invoer','werkloosheid'),1:84))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par3 = '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
invoer werkloosheid M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 11554.5 180144 1 0 0 0 0 0 0 0 0 0 0 1
2 13182.1 173666 0 1 0 0 0 0 0 0 0 0 0 2
3 14800.1 165688 0 0 1 0 0 0 0 0 0 0 0 3
4 12150.7 161570 0 0 0 1 0 0 0 0 0 0 0 4
5 14478.2 156145 0 0 0 0 1 0 0 0 0 0 0 5
6 13253.9 153730 0 0 0 0 0 1 0 0 0 0 0 6
7 12036.8 182698 0 0 0 0 0 0 1 0 0 0 0 7
8 12653.2 200765 0 0 0 0 0 0 0 1 0 0 0 8
9 14035.4 176512 0 0 0 0 0 0 0 0 1 0 0 9
10 14571.4 166618 0 0 0 0 0 0 0 0 0 1 0 10
11 15400.9 158644 0 0 0 0 0 0 0 0 0 0 1 11
12 14283.2 159585 0 0 0 0 0 0 0 0 0 0 0 12
13 14485.3 163095 1 0 0 0 0 0 0 0 0 0 0 13
14 14196.3 159044 0 1 0 0 0 0 0 0 0 0 0 14
15 15559.1 155511 0 0 1 0 0 0 0 0 0 0 0 15
16 13767.4 153745 0 0 0 1 0 0 0 0 0 0 0 16
17 14634.0 150569 0 0 0 0 1 0 0 0 0 0 0 17
18 14381.1 150605 0 0 0 0 0 1 0 0 0 0 0 18
19 12509.9 179612 0 0 0 0 0 0 1 0 0 0 0 19
20 12122.3 194690 0 0 0 0 0 0 0 1 0 0 0 20
21 13122.3 189917 0 0 0 0 0 0 0 0 1 0 0 21
22 13908.7 184128 0 0 0 0 0 0 0 0 0 1 0 22
23 13456.5 175335 0 0 0 0 0 0 0 0 0 0 1 23
24 12441.6 179566 0 0 0 0 0 0 0 0 0 0 0 24
25 12953.0 181140 1 0 0 0 0 0 0 0 0 0 0 25
26 13057.2 177876 0 1 0 0 0 0 0 0 0 0 0 26
27 14350.1 175041 0 0 1 0 0 0 0 0 0 0 0 27
28 13830.2 169292 0 0 0 1 0 0 0 0 0 0 0 28
29 13755.5 166070 0 0 0 0 1 0 0 0 0 0 0 29
30 13574.4 166972 0 0 0 0 0 1 0 0 0 0 0 30
31 12802.6 206348 0 0 0 0 0 0 1 0 0 0 0 31
32 11737.3 215706 0 0 0 0 0 0 0 1 0 0 0 32
33 13850.2 202108 0 0 0 0 0 0 0 0 1 0 0 33
34 15081.8 195411 0 0 0 0 0 0 0 0 0 1 0 34
35 13653.3 193111 0 0 0 0 0 0 0 0 0 0 1 35
36 14019.1 195198 0 0 0 0 0 0 0 0 0 0 0 36
37 13962.0 198770 1 0 0 0 0 0 0 0 0 0 0 37
38 13768.7 194163 0 1 0 0 0 0 0 0 0 0 0 38
39 14747.1 190420 0 0 1 0 0 0 0 0 0 0 0 39
40 13858.1 189733 0 0 0 1 0 0 0 0 0 0 0 40
41 13188.0 186029 0 0 0 0 1 0 0 0 0 0 0 41
42 13693.1 191531 0 0 0 0 0 1 0 0 0 0 0 42
43 12970.0 232571 0 0 0 0 0 0 1 0 0 0 0 43
44 11392.8 243477 0 0 0 0 0 0 0 1 0 0 0 44
45 13985.2 227247 0 0 0 0 0 0 0 0 1 0 0 45
46 14994.7 217859 0 0 0 0 0 0 0 0 0 1 0 46
47 13584.7 208679 0 0 0 0 0 0 0 0 0 0 1 47
48 14257.8 213188 0 0 0 0 0 0 0 0 0 0 0 48
49 13553.4 216234 1 0 0 0 0 0 0 0 0 0 0 49
50 14007.3 213586 0 1 0 0 0 0 0 0 0 0 0 50
51 16535.8 209465 0 0 1 0 0 0 0 0 0 0 0 51
52 14721.4 204045 0 0 0 1 0 0 0 0 0 0 0 52
53 13664.6 200237 0 0 0 0 1 0 0 0 0 0 0 53
54 16805.9 203666 0 0 0 0 0 1 0 0 0 0 0 54
55 13829.4 241476 0 0 0 0 0 0 1 0 0 0 0 55
56 13735.6 260307 0 0 0 0 0 0 0 1 0 0 0 56
57 15870.5 243324 0 0 0 0 0 0 0 0 1 0 0 57
58 15962.4 244460 0 0 0 0 0 0 0 0 0 1 0 58
59 15744.1 233575 0 0 0 0 0 0 0 0 0 0 1 59
60 16083.7 237217 0 0 0 0 0 0 0 0 0 0 0 60
61 14863.9 235243 1 0 0 0 0 0 0 0 0 0 0 61
62 15533.1 230354 0 1 0 0 0 0 0 0 0 0 0 62
63 17473.1 227184 0 0 1 0 0 0 0 0 0 0 0 63
64 15925.5 221678 0 0 0 1 0 0 0 0 0 0 0 64
65 15573.7 217142 0 0 0 0 1 0 0 0 0 0 0 65
66 17495.0 219452 0 0 0 0 0 1 0 0 0 0 0 66
67 14155.8 256446 0 0 0 0 0 0 1 0 0 0 0 67
68 14913.9 265845 0 0 0 0 0 0 0 1 0 0 0 68
69 17250.4 248624 0 0 0 0 0 0 0 0 1 0 0 69
70 15879.8 241114 0 0 0 0 0 0 0 0 0 1 0 70
71 17647.8 229245 0 0 0 0 0 0 0 0 0 0 1 71
72 17749.9 231805 0 0 0 0 0 0 0 0 0 0 0 72
73 17111.8 219277 1 0 0 0 0 0 0 0 0 0 0 73
74 16934.8 219313 0 1 0 0 0 0 0 0 0 0 0 74
75 20280.0 212610 0 0 1 0 0 0 0 0 0 0 0 75
76 16238.2 214771 0 0 0 1 0 0 0 0 0 0 0 76
77 17896.1 211142 0 0 0 0 1 0 0 0 0 0 0 77
78 18089.3 211457 0 0 0 0 0 1 0 0 0 0 0 78
79 15660.0 240048 0 0 0 0 0 0 1 0 0 0 0 79
80 16162.4 240636 0 0 0 0 0 0 0 1 0 0 0 80
81 17850.1 230580 0 0 0 0 0 0 0 0 1 0 0 81
82 18520.4 208795 0 0 0 0 0 0 0 0 0 1 0 82
83 18524.7 197922 0 0 0 0 0 0 0 0 0 0 1 83
84 16843.7 194596 0 0 0 0 0 0 0 0 0 0 0 84
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) werkloosheid M1 M2 M3
1.662e+04 -2.642e-02 -2.215e+02 -8.482e+01 1.581e+03
M4 M5 M6 M7 M8
-4.708e+02 -2.683e+02 2.766e+02 -7.942e+02 -7.412e+02
M9 M10 M11 t
6.828e+02 7.996e+02 3.572e+02 7.922e+01
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-1603.15 -642.37 -51.82 617.36 1855.51
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1.662e+04 1.340e+03 12.399 < 2e-16 ***
werkloosheid -2.642e-02 8.124e-03 -3.252 0.00177 **
M1 -2.215e+02 5.073e+02 -0.437 0.66371
M2 -8.482e+01 5.036e+02 -0.168 0.86674
M3 1.581e+03 5.030e+02 3.144 0.00245 **
M4 -4.708e+02 5.050e+02 -0.932 0.35442
M5 -2.683e+02 5.103e+02 -0.526 0.60073
M6 2.766e+02 5.093e+02 0.543 0.58875
M7 -7.942e+02 5.351e+02 -1.484 0.14227
M8 -7.412e+02 5.715e+02 -1.297 0.19892
M9 6.828e+02 5.225e+02 1.307 0.19552
M10 7.996e+02 5.061e+02 1.580 0.11866
M11 3.572e+02 5.013e+02 0.713 0.47844
t 7.922e+01 8.651e+00 9.158 1.36e-13 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 937.7 on 70 degrees of freedom
Multiple R-squared: 0.7779, Adjusted R-squared: 0.7366
F-statistic: 18.86 on 13 and 70 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,] 0.41409553 0.8281911 0.5859045
[2,] 0.36670069 0.7334014 0.6332993
[3,] 0.24468570 0.4893714 0.7553143
[4,] 0.36045359 0.7209072 0.6395464
[5,] 0.27633936 0.5526787 0.7236606
[6,] 0.23195158 0.4639032 0.7680484
[7,] 0.20289435 0.4057887 0.7971056
[8,] 0.13696945 0.2739389 0.8630305
[9,] 0.10570939 0.2114188 0.8942906
[10,] 0.06745232 0.1349046 0.9325477
[11,] 0.04146660 0.0829332 0.9585334
[12,] 0.12077891 0.2415578 0.8792211
[13,] 0.10316717 0.2063343 0.8968328
[14,] 0.07890956 0.1578191 0.9210904
[15,] 0.28615464 0.5723093 0.7138454
[16,] 0.22474356 0.4494871 0.7752564
[17,] 0.22238702 0.4447740 0.7776130
[18,] 0.39928007 0.7985601 0.6007199
[19,] 0.32980014 0.6596003 0.6701999
[20,] 0.42421968 0.8484394 0.5757803
[21,] 0.54799803 0.9040039 0.4520020
[22,] 0.53936167 0.9212767 0.4606383
[23,] 0.48012622 0.9602524 0.5198738
[24,] 0.51329639 0.9734072 0.4867036
[25,] 0.48859851 0.9771970 0.5114015
[26,] 0.48732092 0.9746418 0.5126791
[27,] 0.59684326 0.8063135 0.4031567
[28,] 0.56851064 0.8629787 0.4314894
[29,] 0.53107644 0.9378471 0.4689236
[30,] 0.55012874 0.8997425 0.4498713
[31,] 0.56015030 0.8796994 0.4398497
[32,] 0.52478713 0.9504257 0.4752129
[33,] 0.46756700 0.9351340 0.5324330
[34,] 0.40831030 0.8166206 0.5916897
[35,] 0.47197169 0.9439434 0.5280283
[36,] 0.45994051 0.9198810 0.5400595
[37,] 0.53319816 0.9336037 0.4668018
[38,] 0.73569499 0.5286100 0.2643050
[39,] 0.73006146 0.5398771 0.2699385
[40,] 0.70600517 0.5879897 0.2939948
[41,] 0.69910415 0.6017917 0.3008959
[42,] 0.67168315 0.6566337 0.3283169
[43,] 0.61557598 0.7688480 0.3844240
[44,] 0.61387244 0.7722551 0.3861276
[45,] 0.57059269 0.8588146 0.4294073
[46,] 0.47590599 0.9518120 0.5240940
[47,] 0.55663135 0.8867373 0.4433687
[48,] 0.53990275 0.9201945 0.4600973
[49,] 0.47763082 0.9552616 0.5223692
[50,] 0.42315792 0.8463158 0.5768421
[51,] 0.27263364 0.5452673 0.7273664
> postscript(file="/var/www/html/rcomp/tmp/1s2rn1229262814.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/24p731229262814.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/34mmg1229262814.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4cviv1229262814.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5j6e21229262814.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 = 84
Frequency = 1
1 2 3 4 5 6
-164.06676 1076.49345 738.27243 -46.94099 1855.51357 -56.70590
7 8 9 10 11 12
483.00452 1444.51035 682.78495 761.41394 1743.36842 928.54817
13 14 15 16 17 18
1365.65367 753.72793 277.73047 412.34982 913.31622 37.24481
19 20 21 22 23 24
-76.11451 -197.56909 -826.89137 -389.42059 -710.80164 -1335.90996
25 26 27 28 29 30
-640.64778 -838.58333 -1366.04173 -64.84128 -506.39007 -1287.78436
31 32 33 34 35 36
-27.82582 -978.08563 -727.63792 131.04622 -995.10925 -296.15562
37 38 39 40 41 42
-116.61227 -647.52586 -1513.47089 -447.64760 -1497.32938 -1471.00547
43 44 45 46 47 48
-118.38906 -1539.65535 -879.23718 -313.74118 -1603.14560 -532.91000
49 50 51 52 53 54
-1014.56199 -846.52468 -172.35534 -156.96369 -1596.09284 1011.66862
55 56 57 58 59 60
25.55814 297.04655 480.07272 405.98121 263.23581 977.06787
61 62 63 64 65 66
-152.59745 171.53937 282.33128 562.25106 -191.10967 1167.09118
67 68 69 70 71 72
-203.27558 670.94772 1049.28664 -715.70624 1101.85403 1549.60290
73 74 75 76 77 78
722.83258 330.87312 1753.53378 -258.20732 1022.09217 599.49111
79 80 81 82 83 84
-82.95768 302.80544 221.62216 120.42663 200.59823 -1290.24335
> postscript(file="/var/www/html/rcomp/tmp/6nfno1229262814.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 = 84
Frequency = 1
lag(myerror, k = 1) myerror
0 -164.06676 NA
1 1076.49345 -164.06676
2 738.27243 1076.49345
3 -46.94099 738.27243
4 1855.51357 -46.94099
5 -56.70590 1855.51357
6 483.00452 -56.70590
7 1444.51035 483.00452
8 682.78495 1444.51035
9 761.41394 682.78495
10 1743.36842 761.41394
11 928.54817 1743.36842
12 1365.65367 928.54817
13 753.72793 1365.65367
14 277.73047 753.72793
15 412.34982 277.73047
16 913.31622 412.34982
17 37.24481 913.31622
18 -76.11451 37.24481
19 -197.56909 -76.11451
20 -826.89137 -197.56909
21 -389.42059 -826.89137
22 -710.80164 -389.42059
23 -1335.90996 -710.80164
24 -640.64778 -1335.90996
25 -838.58333 -640.64778
26 -1366.04173 -838.58333
27 -64.84128 -1366.04173
28 -506.39007 -64.84128
29 -1287.78436 -506.39007
30 -27.82582 -1287.78436
31 -978.08563 -27.82582
32 -727.63792 -978.08563
33 131.04622 -727.63792
34 -995.10925 131.04622
35 -296.15562 -995.10925
36 -116.61227 -296.15562
37 -647.52586 -116.61227
38 -1513.47089 -647.52586
39 -447.64760 -1513.47089
40 -1497.32938 -447.64760
41 -1471.00547 -1497.32938
42 -118.38906 -1471.00547
43 -1539.65535 -118.38906
44 -879.23718 -1539.65535
45 -313.74118 -879.23718
46 -1603.14560 -313.74118
47 -532.91000 -1603.14560
48 -1014.56199 -532.91000
49 -846.52468 -1014.56199
50 -172.35534 -846.52468
51 -156.96369 -172.35534
52 -1596.09284 -156.96369
53 1011.66862 -1596.09284
54 25.55814 1011.66862
55 297.04655 25.55814
56 480.07272 297.04655
57 405.98121 480.07272
58 263.23581 405.98121
59 977.06787 263.23581
60 -152.59745 977.06787
61 171.53937 -152.59745
62 282.33128 171.53937
63 562.25106 282.33128
64 -191.10967 562.25106
65 1167.09118 -191.10967
66 -203.27558 1167.09118
67 670.94772 -203.27558
68 1049.28664 670.94772
69 -715.70624 1049.28664
70 1101.85403 -715.70624
71 1549.60290 1101.85403
72 722.83258 1549.60290
73 330.87312 722.83258
74 1753.53378 330.87312
75 -258.20732 1753.53378
76 1022.09217 -258.20732
77 599.49111 1022.09217
78 -82.95768 599.49111
79 302.80544 -82.95768
80 221.62216 302.80544
81 120.42663 221.62216
82 200.59823 120.42663
83 -1290.24335 200.59823
84 NA -1290.24335
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 1076.49345 -164.06676
[2,] 738.27243 1076.49345
[3,] -46.94099 738.27243
[4,] 1855.51357 -46.94099
[5,] -56.70590 1855.51357
[6,] 483.00452 -56.70590
[7,] 1444.51035 483.00452
[8,] 682.78495 1444.51035
[9,] 761.41394 682.78495
[10,] 1743.36842 761.41394
[11,] 928.54817 1743.36842
[12,] 1365.65367 928.54817
[13,] 753.72793 1365.65367
[14,] 277.73047 753.72793
[15,] 412.34982 277.73047
[16,] 913.31622 412.34982
[17,] 37.24481 913.31622
[18,] -76.11451 37.24481
[19,] -197.56909 -76.11451
[20,] -826.89137 -197.56909
[21,] -389.42059 -826.89137
[22,] -710.80164 -389.42059
[23,] -1335.90996 -710.80164
[24,] -640.64778 -1335.90996
[25,] -838.58333 -640.64778
[26,] -1366.04173 -838.58333
[27,] -64.84128 -1366.04173
[28,] -506.39007 -64.84128
[29,] -1287.78436 -506.39007
[30,] -27.82582 -1287.78436
[31,] -978.08563 -27.82582
[32,] -727.63792 -978.08563
[33,] 131.04622 -727.63792
[34,] -995.10925 131.04622
[35,] -296.15562 -995.10925
[36,] -116.61227 -296.15562
[37,] -647.52586 -116.61227
[38,] -1513.47089 -647.52586
[39,] -447.64760 -1513.47089
[40,] -1497.32938 -447.64760
[41,] -1471.00547 -1497.32938
[42,] -118.38906 -1471.00547
[43,] -1539.65535 -118.38906
[44,] -879.23718 -1539.65535
[45,] -313.74118 -879.23718
[46,] -1603.14560 -313.74118
[47,] -532.91000 -1603.14560
[48,] -1014.56199 -532.91000
[49,] -846.52468 -1014.56199
[50,] -172.35534 -846.52468
[51,] -156.96369 -172.35534
[52,] -1596.09284 -156.96369
[53,] 1011.66862 -1596.09284
[54,] 25.55814 1011.66862
[55,] 297.04655 25.55814
[56,] 480.07272 297.04655
[57,] 405.98121 480.07272
[58,] 263.23581 405.98121
[59,] 977.06787 263.23581
[60,] -152.59745 977.06787
[61,] 171.53937 -152.59745
[62,] 282.33128 171.53937
[63,] 562.25106 282.33128
[64,] -191.10967 562.25106
[65,] 1167.09118 -191.10967
[66,] -203.27558 1167.09118
[67,] 670.94772 -203.27558
[68,] 1049.28664 670.94772
[69,] -715.70624 1049.28664
[70,] 1101.85403 -715.70624
[71,] 1549.60290 1101.85403
[72,] 722.83258 1549.60290
[73,] 330.87312 722.83258
[74,] 1753.53378 330.87312
[75,] -258.20732 1753.53378
[76,] 1022.09217 -258.20732
[77,] 599.49111 1022.09217
[78,] -82.95768 599.49111
[79,] 302.80544 -82.95768
[80,] 221.62216 302.80544
[81,] 120.42663 221.62216
[82,] 200.59823 120.42663
[83,] -1290.24335 200.59823
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 1076.49345 -164.06676
2 738.27243 1076.49345
3 -46.94099 738.27243
4 1855.51357 -46.94099
5 -56.70590 1855.51357
6 483.00452 -56.70590
7 1444.51035 483.00452
8 682.78495 1444.51035
9 761.41394 682.78495
10 1743.36842 761.41394
11 928.54817 1743.36842
12 1365.65367 928.54817
13 753.72793 1365.65367
14 277.73047 753.72793
15 412.34982 277.73047
16 913.31622 412.34982
17 37.24481 913.31622
18 -76.11451 37.24481
19 -197.56909 -76.11451
20 -826.89137 -197.56909
21 -389.42059 -826.89137
22 -710.80164 -389.42059
23 -1335.90996 -710.80164
24 -640.64778 -1335.90996
25 -838.58333 -640.64778
26 -1366.04173 -838.58333
27 -64.84128 -1366.04173
28 -506.39007 -64.84128
29 -1287.78436 -506.39007
30 -27.82582 -1287.78436
31 -978.08563 -27.82582
32 -727.63792 -978.08563
33 131.04622 -727.63792
34 -995.10925 131.04622
35 -296.15562 -995.10925
36 -116.61227 -296.15562
37 -647.52586 -116.61227
38 -1513.47089 -647.52586
39 -447.64760 -1513.47089
40 -1497.32938 -447.64760
41 -1471.00547 -1497.32938
42 -118.38906 -1471.00547
43 -1539.65535 -118.38906
44 -879.23718 -1539.65535
45 -313.74118 -879.23718
46 -1603.14560 -313.74118
47 -532.91000 -1603.14560
48 -1014.56199 -532.91000
49 -846.52468 -1014.56199
50 -172.35534 -846.52468
51 -156.96369 -172.35534
52 -1596.09284 -156.96369
53 1011.66862 -1596.09284
54 25.55814 1011.66862
55 297.04655 25.55814
56 480.07272 297.04655
57 405.98121 480.07272
58 263.23581 405.98121
59 977.06787 263.23581
60 -152.59745 977.06787
61 171.53937 -152.59745
62 282.33128 171.53937
63 562.25106 282.33128
64 -191.10967 562.25106
65 1167.09118 -191.10967
66 -203.27558 1167.09118
67 670.94772 -203.27558
68 1049.28664 670.94772
69 -715.70624 1049.28664
70 1101.85403 -715.70624
71 1549.60290 1101.85403
72 722.83258 1549.60290
73 330.87312 722.83258
74 1753.53378 330.87312
75 -258.20732 1753.53378
76 1022.09217 -258.20732
77 599.49111 1022.09217
78 -82.95768 599.49111
79 302.80544 -82.95768
80 221.62216 302.80544
81 120.42663 221.62216
82 200.59823 120.42663
83 -1290.24335 200.59823
> 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/7l8el1229262814.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8hsar1229262814.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/92sgi1229262814.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10emq21229262814.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11mo291229262814.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/12naof1229262814.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/13g18x1229262814.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/143efl1229262814.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/15nld31229262814.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/16ixym1229262815.tab")
+ }
>
> system("convert tmp/1s2rn1229262814.ps tmp/1s2rn1229262814.png")
> system("convert tmp/24p731229262814.ps tmp/24p731229262814.png")
> system("convert tmp/34mmg1229262814.ps tmp/34mmg1229262814.png")
> system("convert tmp/4cviv1229262814.ps tmp/4cviv1229262814.png")
> system("convert tmp/5j6e21229262814.ps tmp/5j6e21229262814.png")
> system("convert tmp/6nfno1229262814.ps tmp/6nfno1229262814.png")
> system("convert tmp/7l8el1229262814.ps tmp/7l8el1229262814.png")
> system("convert tmp/8hsar1229262814.ps tmp/8hsar1229262814.png")
> system("convert tmp/92sgi1229262814.ps tmp/92sgi1229262814.png")
> system("convert tmp/10emq21229262814.ps tmp/10emq21229262814.png")
>
>
> proc.time()
user system elapsed
5.561 2.818 5.946