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.
Natural language support but running in an English locale
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Type 'contributors()' for more information and
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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(97.06
+ ,21.454
+ ,631.923
+ ,130.678
+ ,97.73
+ ,23.899
+ ,654.294
+ ,120.877
+ ,98
+ ,24.939
+ ,671.833
+ ,137.114
+ ,97.76
+ ,23.580
+ ,586.840
+ ,134.406
+ ,97.48
+ ,24.562
+ ,600.969
+ ,120.262
+ ,97.77
+ ,24.696
+ ,625.568
+ ,130.846
+ ,97.96
+ ,23.785
+ ,558.110
+ ,120.343
+ ,98.22
+ ,23.812
+ ,630.577
+ ,98.881
+ ,98.51
+ ,21.917
+ ,628.654
+ ,115.678
+ ,98.19
+ ,19.713
+ ,603.184
+ ,120.796
+ ,98.37
+ ,19.282
+ ,656.255
+ ,94.261
+ ,98.31
+ ,18.788
+ ,600.730
+ ,89.151
+ ,98.6
+ ,21.453
+ ,670.326
+ ,119.880
+ ,98.96
+ ,24.482
+ ,678.423
+ ,131.468
+ ,99.11
+ ,27.474
+ ,641.502
+ ,155.089
+ ,99.64
+ ,27.264
+ ,625.311
+ ,149.581
+ ,100.02
+ ,27.349
+ ,628.177
+ ,122.788
+ ,99.98
+ ,30.632
+ ,589.767
+ ,143.900
+ ,100.32
+ ,29.429
+ ,582.471
+ ,112.115
+ ,100.44
+ ,30.084
+ ,636.248
+ ,109.600
+ ,100.51
+ ,26.290
+ ,599.885
+ ,117.446
+ ,101
+ ,24.379
+ ,621.694
+ ,118.456
+ ,100.88
+ ,23.335
+ ,637.406
+ ,101.901
+ ,100.55
+ ,21.346
+ ,595.994
+ ,89.940
+ ,100.82
+ ,21.106
+ ,696.308
+ ,129.143
+ ,101.5
+ ,24.514
+ ,674.201
+ ,126.102
+ ,102.15
+ ,28.353
+ ,648.861
+ ,143.048
+ ,102.39
+ ,30.805
+ ,649.605
+ ,142.258
+ ,102.54
+ ,31.348
+ ,672.392
+ ,131.011
+ ,102.85
+ ,34.556
+ ,598.396
+ ,146.471
+ ,103.47
+ ,33.855
+ ,613.177
+ ,114.073
+ ,103.56
+ ,34.787
+ ,638.104
+ ,114.642
+ ,103.69
+ ,32.529
+ ,615.632
+ ,118.226
+ ,103.49
+ ,29.998
+ ,634.465
+ ,111.338
+ ,103.47
+ ,29.257
+ ,638.686
+ ,108.701
+ ,103.45
+ ,28.155
+ ,604.243
+ ,80.512
+ ,103.48
+ ,30.466
+ ,706.669
+ ,146.865
+ ,103.93
+ ,35.704
+ ,677.185
+ ,137.179
+ ,103.89
+ ,39.327
+ ,644.328
+ ,166.536
+ ,104.4
+ ,39.351
+ ,664.825
+ ,137.070
+ ,104.79
+ ,42.234
+ ,605.707
+ ,127.090
+ ,104.77
+ ,43.630
+ ,600.136
+ ,139.966
+ ,105.13
+ ,43.722
+ ,612.166
+ ,122.243
+ ,105.26
+ ,43.121
+ ,599.659
+ ,109.097
+ ,104.96
+ ,37.985
+ ,634.210
+ ,116.591
+ ,104.75
+ ,37.135
+ ,618.234
+ ,111.964
+ ,105.01
+ ,34.646
+ ,613.576
+ ,109.754
+ ,105.15
+ ,33.026
+ ,627.200
+ ,77.609
+ ,105.2
+ ,35.087
+ ,668.973
+ ,138.445
+ ,105.77
+ ,38.846
+ ,651.479
+ ,127.901
+ ,105.78
+ ,42.013
+ ,619.661
+ ,156.615
+ ,106.26
+ ,43.908
+ ,644.260
+ ,133.264
+ ,106.13
+ ,42.868
+ ,579.936
+ ,143.521
+ ,106.12
+ ,44.423
+ ,601.752
+ ,152.139
+ ,106.57
+ ,44.167
+ ,595.376
+ ,131.523
+ ,106.44
+ ,43.636
+ ,588.902
+ ,113.925
+ ,106.54
+ ,44.382
+ ,634.341
+ ,86.495
+ ,107.1
+ ,42.142
+ ,594.305
+ ,127.877
+ ,108.1
+ ,43.452
+ ,606.200
+ ,107.017
+ ,108.4
+ ,36.912
+ ,610.926
+ ,78.716
+ ,108.84
+ ,42.413
+ ,633.685
+ ,138.278
+ ,109.62
+ ,45.344
+ ,639.696
+ ,144.238
+ ,110.42
+ ,44.873
+ ,659.451
+ ,143.679
+ ,110.67
+ ,47.510
+ ,593.248
+ ,159.932
+ ,111.66
+ ,49.554
+ ,606.677
+ ,136.781
+ ,112.28
+ ,47.369
+ ,599.434
+ ,148.173
+ ,112.87
+ ,45.998
+ ,569.578
+ ,125.673
+ ,112.18
+ ,48.140
+ ,629.873
+ ,105.573
+ ,112.36
+ ,48.441
+ ,613.438
+ ,122.405
+ ,112.16
+ ,44.928
+ ,604.172
+ ,128.045
+ ,111.49
+ ,40.454
+ ,658.328
+ ,94.467
+ ,111.25
+ ,38.661
+ ,612.633
+ ,85.573
+ ,111.36
+ ,37.246
+ ,707.372
+ ,121.501
+ ,111.74
+ ,36.843
+ ,739.770
+ ,125.074
+ ,111.1
+ ,36.424
+ ,777.535
+ ,144.979
+ ,111.33
+ ,37.594
+ ,685.030
+ ,142.120
+ ,111.25
+ ,38.144
+ ,730.234
+ ,124.213
+ ,111.04
+ ,38.737
+ ,714.154
+ ,144.407
+ ,110.97
+ ,34.560
+ ,630.872
+ ,125.170
+ ,111.31
+ ,36.080
+ ,719.492
+ ,109.267
+ ,111.02
+ ,33.508
+ ,677.023
+ ,122.354
+ ,111.07
+ ,35.462
+ ,679.272
+ ,122.589
+ ,111.36
+ ,33.374
+ ,718.317
+ ,104.982
+ ,111.54
+ ,32.110
+ ,645.672
+ ,90.542)
+ ,dim=c(4
+ ,84)
+ ,dimnames=list(c('CPI'
+ ,'vacatures'
+ ,'werklozen'
+ ,'inschrijvingen')
+ ,1:84))
> y <- array(NA,dim=c(4,84),dimnames=list(c('CPI','vacatures','werklozen','inschrijvingen'),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 = 'No Linear Trend'
> par2 = 'Do not include Seasonal Dummies'
> par1 = '3'
> 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
werklozen CPI vacatures inschrijvingen
1 631.923 97.06 21.454 130.678
2 654.294 97.73 23.899 120.877
3 671.833 98.00 24.939 137.114
4 586.840 97.76 23.580 134.406
5 600.969 97.48 24.562 120.262
6 625.568 97.77 24.696 130.846
7 558.110 97.96 23.785 120.343
8 630.577 98.22 23.812 98.881
9 628.654 98.51 21.917 115.678
10 603.184 98.19 19.713 120.796
11 656.255 98.37 19.282 94.261
12 600.730 98.31 18.788 89.151
13 670.326 98.60 21.453 119.880
14 678.423 98.96 24.482 131.468
15 641.502 99.11 27.474 155.089
16 625.311 99.64 27.264 149.581
17 628.177 100.02 27.349 122.788
18 589.767 99.98 30.632 143.900
19 582.471 100.32 29.429 112.115
20 636.248 100.44 30.084 109.600
21 599.885 100.51 26.290 117.446
22 621.694 101.00 24.379 118.456
23 637.406 100.88 23.335 101.901
24 595.994 100.55 21.346 89.940
25 696.308 100.82 21.106 129.143
26 674.201 101.50 24.514 126.102
27 648.861 102.15 28.353 143.048
28 649.605 102.39 30.805 142.258
29 672.392 102.54 31.348 131.011
30 598.396 102.85 34.556 146.471
31 613.177 103.47 33.855 114.073
32 638.104 103.56 34.787 114.642
33 615.632 103.69 32.529 118.226
34 634.465 103.49 29.998 111.338
35 638.686 103.47 29.257 108.701
36 604.243 103.45 28.155 80.512
37 706.669 103.48 30.466 146.865
38 677.185 103.93 35.704 137.179
39 644.328 103.89 39.327 166.536
40 664.825 104.40 39.351 137.070
41 605.707 104.79 42.234 127.090
42 600.136 104.77 43.630 139.966
43 612.166 105.13 43.722 122.243
44 599.659 105.26 43.121 109.097
45 634.210 104.96 37.985 116.591
46 618.234 104.75 37.135 111.964
47 613.576 105.01 34.646 109.754
48 627.200 105.15 33.026 77.609
49 668.973 105.20 35.087 138.445
50 651.479 105.77 38.846 127.901
51 619.661 105.78 42.013 156.615
52 644.260 106.26 43.908 133.264
53 579.936 106.13 42.868 143.521
54 601.752 106.12 44.423 152.139
55 595.376 106.57 44.167 131.523
56 588.902 106.44 43.636 113.925
57 634.341 106.54 44.382 86.495
58 594.305 107.10 42.142 127.877
59 606.200 108.10 43.452 107.017
60 610.926 108.40 36.912 78.716
61 633.685 108.84 42.413 138.278
62 639.696 109.62 45.344 144.238
63 659.451 110.42 44.873 143.679
64 593.248 110.67 47.510 159.932
65 606.677 111.66 49.554 136.781
66 599.434 112.28 47.369 148.173
67 569.578 112.87 45.998 125.673
68 629.873 112.18 48.140 105.573
69 613.438 112.36 48.441 122.405
70 604.172 112.16 44.928 128.045
71 658.328 111.49 40.454 94.467
72 612.633 111.25 38.661 85.573
73 707.372 111.36 37.246 121.501
74 739.770 111.74 36.843 125.074
75 777.535 111.10 36.424 144.979
76 685.030 111.33 37.594 142.120
77 730.234 111.25 38.144 124.213
78 714.154 111.04 38.737 144.407
79 630.872 110.97 34.560 125.170
80 719.492 111.31 36.080 109.267
81 677.023 111.02 33.508 122.354
82 679.272 111.07 35.462 122.589
83 718.317 111.36 33.374 104.982
84 645.672 111.54 32.110 90.542
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) CPI vacatures inschrijvingen
-229.9598 9.0872 -5.1149 0.7179
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-81.0798 -18.6587 -0.6429 23.0928 80.1316
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -229.9598 121.5184 -1.892 0.062057 .
CPI 9.0872 1.2724 7.142 3.79e-10 ***
vacatures -5.1149 0.7607 -6.724 2.40e-09 ***
inschrijvingen 0.7179 0.1958 3.667 0.000441 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 32.59 on 80 degrees of freedom
Multiple R-squared: 0.4087, Adjusted R-squared: 0.3865
F-statistic: 18.43 on 3 and 80 DF, p-value: 3.49e-09
> 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,] 0.904101303 0.191797394 0.09589870
[2,] 0.922829974 0.154340053 0.07717003
[3,] 0.868359188 0.263281624 0.13164081
[4,] 0.814819350 0.370361299 0.18518065
[5,] 0.810493892 0.379012217 0.18950611
[6,] 0.773785114 0.452429772 0.22621489
[7,] 0.769336017 0.461327967 0.23066398
[8,] 0.717578307 0.564843387 0.28242169
[9,] 0.687440323 0.625119354 0.31255968
[10,] 0.680879657 0.638240687 0.31912034
[11,] 0.615069789 0.769860423 0.38493021
[12,] 0.644545948 0.710908104 0.35545405
[13,] 0.612089565 0.775820871 0.38791044
[14,] 0.599551084 0.800897831 0.40044892
[15,] 0.587755751 0.824488498 0.41224425
[16,] 0.539504058 0.920991885 0.46049594
[17,] 0.474302601 0.948605202 0.52569740
[18,] 0.513389696 0.973220608 0.48661030
[19,] 0.536119016 0.927761967 0.46388098
[20,] 0.491258769 0.982517538 0.50874123
[21,] 0.434062292 0.868124583 0.56593771
[22,] 0.372557659 0.745115317 0.62744234
[23,] 0.375690093 0.751380186 0.62430991
[24,] 0.417403452 0.834806904 0.58259655
[25,] 0.361276028 0.722552057 0.63872397
[26,] 0.325588647 0.651177294 0.67441135
[27,] 0.297272835 0.594545671 0.70272716
[28,] 0.255506891 0.511013782 0.74449311
[29,] 0.219608397 0.439216794 0.78039160
[30,] 0.236294082 0.472588164 0.76370592
[31,] 0.246421912 0.492843825 0.75357809
[32,] 0.257407990 0.514815980 0.74259201
[33,] 0.207720317 0.415440634 0.79227968
[34,] 0.222347612 0.444695224 0.77765239
[35,] 0.177498715 0.354997430 0.82250129
[36,] 0.142643595 0.285287189 0.85735641
[37,] 0.116576941 0.233153883 0.88342306
[38,] 0.089714305 0.179428610 0.91028569
[39,] 0.067947163 0.135894327 0.93205284
[40,] 0.049479032 0.098958064 0.95052097
[41,] 0.044950775 0.089901549 0.95504923
[42,] 0.034184431 0.068368862 0.96581557
[43,] 0.023755833 0.047511667 0.97624417
[44,] 0.016967738 0.033935477 0.98303226
[45,] 0.014266423 0.028532846 0.98573358
[46,] 0.013659163 0.027318326 0.98634084
[47,] 0.023185501 0.046371002 0.97681450
[48,] 0.019463318 0.038926635 0.98053668
[49,] 0.015159241 0.030318481 0.98484076
[50,] 0.011017765 0.022035530 0.98898224
[51,] 0.026943985 0.053887970 0.97305602
[52,] 0.026138578 0.052277157 0.97386142
[53,] 0.017852233 0.035704466 0.98214777
[54,] 0.013389899 0.026779798 0.98661010
[55,] 0.009889800 0.019779600 0.99011020
[56,] 0.006145934 0.012291867 0.99385407
[57,] 0.003804358 0.007608716 0.99619564
[58,] 0.011735446 0.023470892 0.98826455
[59,] 0.009227231 0.018454463 0.99077277
[60,] 0.011979538 0.023959075 0.98802046
[61,] 0.027109898 0.054219796 0.97289010
[62,] 0.020970145 0.041940289 0.97902986
[63,] 0.012790933 0.025581866 0.98720907
[64,] 0.130602667 0.261205335 0.86939733
[65,] 0.095670033 0.191340066 0.90432997
[66,] 0.094096698 0.188193396 0.90590330
[67,] 0.075180258 0.150360516 0.92481974
[68,] 0.062633204 0.125266408 0.93736680
[69,] 0.472613381 0.945226762 0.52738662
[70,] 0.383224403 0.766448806 0.61677560
[71,] 0.257224855 0.514449710 0.74277515
> postscript(file="/var/www/html/freestat/rcomp/tmp/1inyf1292698687.ps",horizontal=F,onefile=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/freestat/rcomp/tmp/2inyf1292698687.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/3inyf1292698687.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/4bwf01292698687.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/5bwf01292698687.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$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
-4.199515611 31.625202951 40.373489835 -47.445636307 -15.595309564
6 7 8 9 10
-0.544531968 -66.848586363 18.801578495 -7.508130087 -45.017713763
11 12 13 14 15
23.262748376 -30.575271860 27.956062948 39.955585617 0.017585319
16 17 18 19 20
-18.109518893 0.973012412 -35.437756656 -29.157930895 28.684401532
21 22 23 24 25
-33.353324628 -26.496702930 -3.149233276 -43.149098978 25.339654468
26 27 28 29 30
16.668092101 -7.108152198 4.563797277 36.839414304 -34.663874988
31 32 33 34 35
-5.843706627 22.624041128 -15.151712233 -2.502131961 0.003595199
36 37 38 39 40
-19.657181653 46.681410073 46.853659058 11.815807248 48.954962042
41 42 43 44 45
8.203924207 0.711286865 22.663944705 15.339169522 20.966214947
46 47 48 49 50
5.872620413 -12.292452506 14.850345788 23.036165396 27.158983246
51 52 53 54 55
-9.165006644 37.528731895 -38.297004382 -14.623394582 -11.597661508
56 57 58 59 60
-6.972600083 61.065598574 -25.225048105 -0.741170898 -11.875254114
61 62 63 64 65
-7.737577762 1.898448976 12.375890827 -54.279074099 -22.771264197
66 67 68 69 70
-55.002775282 -81.079821385 10.871391413 -17.743538684 -47.209733389
71 72 73 74 75
14.256533439 -32.043481964 28.665364832 52.983845401 80.131555023
76 77 78 79 80
-6.426571147 55.173168153 29.537186882 -60.663247981 44.058635179
81 82 83 84
-18.325851703 -6.705410238 31.664597602 -38.714741573
> postscript(file="/var/www/html/freestat/rcomp/tmp/6bwf01292698687.ps",horizontal=F,onefile=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 -4.199515611 NA
1 31.625202951 -4.199515611
2 40.373489835 31.625202951
3 -47.445636307 40.373489835
4 -15.595309564 -47.445636307
5 -0.544531968 -15.595309564
6 -66.848586363 -0.544531968
7 18.801578495 -66.848586363
8 -7.508130087 18.801578495
9 -45.017713763 -7.508130087
10 23.262748376 -45.017713763
11 -30.575271860 23.262748376
12 27.956062948 -30.575271860
13 39.955585617 27.956062948
14 0.017585319 39.955585617
15 -18.109518893 0.017585319
16 0.973012412 -18.109518893
17 -35.437756656 0.973012412
18 -29.157930895 -35.437756656
19 28.684401532 -29.157930895
20 -33.353324628 28.684401532
21 -26.496702930 -33.353324628
22 -3.149233276 -26.496702930
23 -43.149098978 -3.149233276
24 25.339654468 -43.149098978
25 16.668092101 25.339654468
26 -7.108152198 16.668092101
27 4.563797277 -7.108152198
28 36.839414304 4.563797277
29 -34.663874988 36.839414304
30 -5.843706627 -34.663874988
31 22.624041128 -5.843706627
32 -15.151712233 22.624041128
33 -2.502131961 -15.151712233
34 0.003595199 -2.502131961
35 -19.657181653 0.003595199
36 46.681410073 -19.657181653
37 46.853659058 46.681410073
38 11.815807248 46.853659058
39 48.954962042 11.815807248
40 8.203924207 48.954962042
41 0.711286865 8.203924207
42 22.663944705 0.711286865
43 15.339169522 22.663944705
44 20.966214947 15.339169522
45 5.872620413 20.966214947
46 -12.292452506 5.872620413
47 14.850345788 -12.292452506
48 23.036165396 14.850345788
49 27.158983246 23.036165396
50 -9.165006644 27.158983246
51 37.528731895 -9.165006644
52 -38.297004382 37.528731895
53 -14.623394582 -38.297004382
54 -11.597661508 -14.623394582
55 -6.972600083 -11.597661508
56 61.065598574 -6.972600083
57 -25.225048105 61.065598574
58 -0.741170898 -25.225048105
59 -11.875254114 -0.741170898
60 -7.737577762 -11.875254114
61 1.898448976 -7.737577762
62 12.375890827 1.898448976
63 -54.279074099 12.375890827
64 -22.771264197 -54.279074099
65 -55.002775282 -22.771264197
66 -81.079821385 -55.002775282
67 10.871391413 -81.079821385
68 -17.743538684 10.871391413
69 -47.209733389 -17.743538684
70 14.256533439 -47.209733389
71 -32.043481964 14.256533439
72 28.665364832 -32.043481964
73 52.983845401 28.665364832
74 80.131555023 52.983845401
75 -6.426571147 80.131555023
76 55.173168153 -6.426571147
77 29.537186882 55.173168153
78 -60.663247981 29.537186882
79 44.058635179 -60.663247981
80 -18.325851703 44.058635179
81 -6.705410238 -18.325851703
82 31.664597602 -6.705410238
83 -38.714741573 31.664597602
84 NA -38.714741573
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 31.625202951 -4.199515611
[2,] 40.373489835 31.625202951
[3,] -47.445636307 40.373489835
[4,] -15.595309564 -47.445636307
[5,] -0.544531968 -15.595309564
[6,] -66.848586363 -0.544531968
[7,] 18.801578495 -66.848586363
[8,] -7.508130087 18.801578495
[9,] -45.017713763 -7.508130087
[10,] 23.262748376 -45.017713763
[11,] -30.575271860 23.262748376
[12,] 27.956062948 -30.575271860
[13,] 39.955585617 27.956062948
[14,] 0.017585319 39.955585617
[15,] -18.109518893 0.017585319
[16,] 0.973012412 -18.109518893
[17,] -35.437756656 0.973012412
[18,] -29.157930895 -35.437756656
[19,] 28.684401532 -29.157930895
[20,] -33.353324628 28.684401532
[21,] -26.496702930 -33.353324628
[22,] -3.149233276 -26.496702930
[23,] -43.149098978 -3.149233276
[24,] 25.339654468 -43.149098978
[25,] 16.668092101 25.339654468
[26,] -7.108152198 16.668092101
[27,] 4.563797277 -7.108152198
[28,] 36.839414304 4.563797277
[29,] -34.663874988 36.839414304
[30,] -5.843706627 -34.663874988
[31,] 22.624041128 -5.843706627
[32,] -15.151712233 22.624041128
[33,] -2.502131961 -15.151712233
[34,] 0.003595199 -2.502131961
[35,] -19.657181653 0.003595199
[36,] 46.681410073 -19.657181653
[37,] 46.853659058 46.681410073
[38,] 11.815807248 46.853659058
[39,] 48.954962042 11.815807248
[40,] 8.203924207 48.954962042
[41,] 0.711286865 8.203924207
[42,] 22.663944705 0.711286865
[43,] 15.339169522 22.663944705
[44,] 20.966214947 15.339169522
[45,] 5.872620413 20.966214947
[46,] -12.292452506 5.872620413
[47,] 14.850345788 -12.292452506
[48,] 23.036165396 14.850345788
[49,] 27.158983246 23.036165396
[50,] -9.165006644 27.158983246
[51,] 37.528731895 -9.165006644
[52,] -38.297004382 37.528731895
[53,] -14.623394582 -38.297004382
[54,] -11.597661508 -14.623394582
[55,] -6.972600083 -11.597661508
[56,] 61.065598574 -6.972600083
[57,] -25.225048105 61.065598574
[58,] -0.741170898 -25.225048105
[59,] -11.875254114 -0.741170898
[60,] -7.737577762 -11.875254114
[61,] 1.898448976 -7.737577762
[62,] 12.375890827 1.898448976
[63,] -54.279074099 12.375890827
[64,] -22.771264197 -54.279074099
[65,] -55.002775282 -22.771264197
[66,] -81.079821385 -55.002775282
[67,] 10.871391413 -81.079821385
[68,] -17.743538684 10.871391413
[69,] -47.209733389 -17.743538684
[70,] 14.256533439 -47.209733389
[71,] -32.043481964 14.256533439
[72,] 28.665364832 -32.043481964
[73,] 52.983845401 28.665364832
[74,] 80.131555023 52.983845401
[75,] -6.426571147 80.131555023
[76,] 55.173168153 -6.426571147
[77,] 29.537186882 55.173168153
[78,] -60.663247981 29.537186882
[79,] 44.058635179 -60.663247981
[80,] -18.325851703 44.058635179
[81,] -6.705410238 -18.325851703
[82,] 31.664597602 -6.705410238
[83,] -38.714741573 31.664597602
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 31.625202951 -4.199515611
2 40.373489835 31.625202951
3 -47.445636307 40.373489835
4 -15.595309564 -47.445636307
5 -0.544531968 -15.595309564
6 -66.848586363 -0.544531968
7 18.801578495 -66.848586363
8 -7.508130087 18.801578495
9 -45.017713763 -7.508130087
10 23.262748376 -45.017713763
11 -30.575271860 23.262748376
12 27.956062948 -30.575271860
13 39.955585617 27.956062948
14 0.017585319 39.955585617
15 -18.109518893 0.017585319
16 0.973012412 -18.109518893
17 -35.437756656 0.973012412
18 -29.157930895 -35.437756656
19 28.684401532 -29.157930895
20 -33.353324628 28.684401532
21 -26.496702930 -33.353324628
22 -3.149233276 -26.496702930
23 -43.149098978 -3.149233276
24 25.339654468 -43.149098978
25 16.668092101 25.339654468
26 -7.108152198 16.668092101
27 4.563797277 -7.108152198
28 36.839414304 4.563797277
29 -34.663874988 36.839414304
30 -5.843706627 -34.663874988
31 22.624041128 -5.843706627
32 -15.151712233 22.624041128
33 -2.502131961 -15.151712233
34 0.003595199 -2.502131961
35 -19.657181653 0.003595199
36 46.681410073 -19.657181653
37 46.853659058 46.681410073
38 11.815807248 46.853659058
39 48.954962042 11.815807248
40 8.203924207 48.954962042
41 0.711286865 8.203924207
42 22.663944705 0.711286865
43 15.339169522 22.663944705
44 20.966214947 15.339169522
45 5.872620413 20.966214947
46 -12.292452506 5.872620413
47 14.850345788 -12.292452506
48 23.036165396 14.850345788
49 27.158983246 23.036165396
50 -9.165006644 27.158983246
51 37.528731895 -9.165006644
52 -38.297004382 37.528731895
53 -14.623394582 -38.297004382
54 -11.597661508 -14.623394582
55 -6.972600083 -11.597661508
56 61.065598574 -6.972600083
57 -25.225048105 61.065598574
58 -0.741170898 -25.225048105
59 -11.875254114 -0.741170898
60 -7.737577762 -11.875254114
61 1.898448976 -7.737577762
62 12.375890827 1.898448976
63 -54.279074099 12.375890827
64 -22.771264197 -54.279074099
65 -55.002775282 -22.771264197
66 -81.079821385 -55.002775282
67 10.871391413 -81.079821385
68 -17.743538684 10.871391413
69 -47.209733389 -17.743538684
70 14.256533439 -47.209733389
71 -32.043481964 14.256533439
72 28.665364832 -32.043481964
73 52.983845401 28.665364832
74 80.131555023 52.983845401
75 -6.426571147 80.131555023
76 55.173168153 -6.426571147
77 29.537186882 55.173168153
78 -60.663247981 29.537186882
79 44.058635179 -60.663247981
80 -18.325851703 44.058635179
81 -6.705410238 -18.325851703
82 31.664597602 -6.705410238
83 -38.714741573 31.664597602
> 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/freestat/rcomp/tmp/74oxl1292698687.ps",horizontal=F,onefile=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/freestat/rcomp/tmp/8wfwo1292698687.ps",horizontal=F,onefile=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/freestat/rcomp/tmp/9wfwo1292698687.ps",horizontal=F,onefile=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/freestat/rcomp/tmp/10wfwo1292698687.ps",horizontal=F,onefile=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/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/freestat/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$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
+ }
+ }
> myeq <- paste(myeq, ' + e[t]')
> a<-table.row.start(a)
> a<-table.element(a, myeq)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/freestat/rcomp/tmp/110xuc1292698687.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Variable',header=TRUE)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
> a<-table.element(a,'2-tail p-value',header=TRUE)
> a<-table.element(a,'1-tail p-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:k){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(mysum$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$coefficients[i,4]/2,6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/html/freestat/rcomp/tmp/123gbi1292698687.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple R',1,TRUE)
> a<-table.element(a, sqrt(mysum$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$sigma)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a, sum(myerror*myerror))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/freestat/rcomp/tmp/13szqt1292698687.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Time or Index', 1, TRUE)
> a<-table.element(a, 'Actuals', 1, TRUE)
> a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
> a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
> a<-table.row.end(a)
> for (i in 1:n) {
+ a<-table.row.start(a)
+ a<-table.element(a,i, 1, TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]-mysum$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/freestat/rcomp/tmp/1438pw1292698687.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/freestat/rcomp/tmp/15o96k1292698687.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/freestat/rcomp/tmp/16203t1292698687.tab")
+ }
>
> try(system("convert tmp/1inyf1292698687.ps tmp/1inyf1292698687.png",intern=TRUE))
character(0)
> try(system("convert tmp/2inyf1292698687.ps tmp/2inyf1292698687.png",intern=TRUE))
character(0)
> try(system("convert tmp/3inyf1292698687.ps tmp/3inyf1292698687.png",intern=TRUE))
character(0)
> try(system("convert tmp/4bwf01292698687.ps tmp/4bwf01292698687.png",intern=TRUE))
character(0)
> try(system("convert tmp/5bwf01292698687.ps tmp/5bwf01292698687.png",intern=TRUE))
character(0)
> try(system("convert tmp/6bwf01292698687.ps tmp/6bwf01292698687.png",intern=TRUE))
character(0)
> try(system("convert tmp/74oxl1292698687.ps tmp/74oxl1292698687.png",intern=TRUE))
character(0)
> try(system("convert tmp/8wfwo1292698687.ps tmp/8wfwo1292698687.png",intern=TRUE))
character(0)
> try(system("convert tmp/9wfwo1292698687.ps tmp/9wfwo1292698687.png",intern=TRUE))
character(0)
> try(system("convert tmp/10wfwo1292698687.ps tmp/10wfwo1292698687.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
4.194 2.503 4.677