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.
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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
'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(44164
+ ,-9
+ ,-7.7
+ ,544686
+ ,2.2
+ ,40399
+ ,-13
+ ,-4.9
+ ,537034
+ ,2.2
+ ,36763
+ ,-8
+ ,-2.4
+ ,551531
+ ,2.2
+ ,37903
+ ,-13
+ ,-3.6
+ ,563250
+ ,1.6
+ ,35532
+ ,-15
+ ,-7
+ ,574761
+ ,1.6
+ ,35533
+ ,-15
+ ,-7
+ ,580112
+ ,1.6
+ ,32110
+ ,-15
+ ,-7.9
+ ,575093
+ ,-0.1
+ ,33374
+ ,-10
+ ,-8.8
+ ,557560
+ ,-0.1
+ ,35462
+ ,-12
+ ,-14.2
+ ,564478
+ ,-0.1
+ ,33508
+ ,-11
+ ,-17.8
+ ,580523
+ ,-2.7
+ ,36080
+ ,-11
+ ,-18.2
+ ,596594
+ ,-2.7
+ ,34560
+ ,-17
+ ,-22.8
+ ,586570
+ ,-2.7
+ ,38737
+ ,-18
+ ,-23.6
+ ,536214
+ ,-4.1
+ ,38144
+ ,-19
+ ,-27.6
+ ,523597
+ ,-4.1
+ ,37594
+ ,-22
+ ,-29.4
+ ,536535
+ ,-4.1
+ ,36424
+ ,-24
+ ,-31.8
+ ,536322
+ ,-3.7
+ ,36843
+ ,-24
+ ,-31.4
+ ,532638
+ ,-3.7
+ ,37246
+ ,-20
+ ,-27.6
+ ,528222
+ ,-3.7
+ ,38661
+ ,-25
+ ,-28.8
+ ,516141
+ ,-1.3
+ ,40454
+ ,-22
+ ,-21.9
+ ,501866
+ ,-1.3
+ ,44928
+ ,-17
+ ,-13.9
+ ,506174
+ ,-1.3
+ ,48441
+ ,-9
+ ,-8
+ ,517945
+ ,1.1
+ ,48140
+ ,-11
+ ,-2.8
+ ,533590
+ ,1.1
+ ,45998
+ ,-13
+ ,-3.3
+ ,528379
+ ,1.1
+ ,47369
+ ,-11
+ ,-1.3
+ ,477580
+ ,1.9
+ ,49554
+ ,-9
+ ,0.5
+ ,469357
+ ,1.9
+ ,47510
+ ,-7
+ ,-1.9
+ ,490243
+ ,1.9
+ ,44873
+ ,-3
+ ,2
+ ,492622
+ ,1.6
+ ,45344
+ ,-3
+ ,1.7
+ ,507561
+ ,1.6
+ ,42413
+ ,-6
+ ,1.9
+ ,516922
+ ,1.6
+ ,36912
+ ,-4
+ ,0.1
+ ,514258
+ ,1.8
+ ,43452
+ ,-8
+ ,2.4
+ ,509846
+ ,1.8
+ ,42142
+ ,-1
+ ,2.3
+ ,527070
+ ,1.8
+ ,44382
+ ,-2
+ ,4.7
+ ,541657
+ ,2.7
+ ,43636
+ ,-2
+ ,5
+ ,564591
+ ,2.7
+ ,44167
+ ,-1
+ ,7.2
+ ,555362
+ ,2.7
+ ,44423
+ ,1
+ ,8.5
+ ,498662
+ ,3.3
+ ,42868
+ ,2
+ ,6.8
+ ,511038
+ ,3.3
+ ,43908
+ ,2
+ ,5.8
+ ,525919
+ ,3.3
+ ,42013
+ ,-1
+ ,3.7
+ ,531673
+ ,3.4
+ ,38846
+ ,1
+ ,4.8
+ ,548854
+ ,3.4
+ ,35087
+ ,-1
+ ,6.1
+ ,560576
+ ,3.4
+ ,33026
+ ,-8
+ ,6.9
+ ,557274
+ ,3
+ ,34646
+ ,1
+ ,5.7
+ ,565742
+ ,3
+ ,37135
+ ,2
+ ,6.9
+ ,587625
+ ,3
+ ,37985
+ ,-2
+ ,5.5
+ ,619916
+ ,2.6
+ ,43121
+ ,-2
+ ,6.5
+ ,625809
+ ,2.6
+ ,43722
+ ,-2
+ ,7.7
+ ,619567
+ ,2.6
+ ,43630
+ ,-2
+ ,6.3
+ ,572942
+ ,2.4
+ ,42234
+ ,-6
+ ,5.5
+ ,572775
+ ,2.4
+ ,39351
+ ,-4
+ ,5.3
+ ,574205
+ ,2.4
+ ,39327
+ ,-5
+ ,3.3
+ ,579799
+ ,2.8
+ ,35704
+ ,-2
+ ,2.2
+ ,590072
+ ,2.8
+ ,30466
+ ,-1
+ ,0.6
+ ,593408
+ ,2.8
+ ,28155
+ ,-5
+ ,0.2
+ ,597141
+ ,2.3
+ ,29257
+ ,-9
+ ,-0.7
+ ,595404
+ ,2.3
+ ,29998
+ ,-8
+ ,-1.7
+ ,612117
+ ,2.3
+ ,32529
+ ,-14
+ ,-3.7
+ ,628232
+ ,1.8
+ ,34787
+ ,-10
+ ,-7.6
+ ,628884
+ ,1.8
+ ,33855
+ ,-11
+ ,-8.2
+ ,620735
+ ,1.8
+ ,34556
+ ,-11
+ ,-7.5
+ ,569028
+ ,2
+ ,31348
+ ,-11
+ ,-8
+ ,567456
+ ,2
+ ,30805
+ ,-5
+ ,-6.9
+ ,573100
+ ,2
+ ,28353
+ ,-2
+ ,-4.2
+ ,584428
+ ,1.9
+ ,24514
+ ,-3
+ ,-3.6
+ ,589379
+ ,1.9
+ ,21106
+ ,-6
+ ,-1.8
+ ,590865
+ ,1.9
+ ,21346
+ ,-6
+ ,-3.2
+ ,595454
+ ,3.1
+ ,23335
+ ,-7
+ ,-1.3
+ ,594167
+ ,3.1
+ ,24379
+ ,-6
+ ,0.6
+ ,611324
+ ,3.1
+ ,26290
+ ,-2
+ ,1.2
+ ,612613
+ ,3.6
+ ,30084
+ ,-2
+ ,0.4
+ ,610763
+ ,3.6
+ ,29429
+ ,-4
+ ,3
+ ,593530
+ ,3.6
+ ,30632
+ ,0
+ ,-0.4
+ ,542722
+ ,3
+ ,27349
+ ,-6
+ ,0
+ ,536662
+ ,3
+ ,27264
+ ,-4
+ ,-1.3
+ ,543599
+ ,3
+ ,27474
+ ,-3
+ ,-3.1
+ ,555332
+ ,2.5
+ ,24482
+ ,-1
+ ,-4
+ ,560854
+ ,2.5
+ ,21453
+ ,-3
+ ,-4.9
+ ,562325
+ ,2.5
+ ,18788
+ ,-6
+ ,-4.6
+ ,554788
+ ,1
+ ,19282
+ ,-6
+ ,-5.4
+ ,547344
+ ,1
+ ,19713
+ ,-15
+ ,-8.1
+ ,565464
+ ,1
+ ,21917
+ ,-5
+ ,-9.4
+ ,577992
+ ,0.5
+ ,23812
+ ,-11
+ ,-12.6
+ ,579714
+ ,0.5
+ ,23785
+ ,-13
+ ,-15.7
+ ,569323
+ ,0.5
+ ,24696
+ ,-10
+ ,-17.3
+ ,506971
+ ,0.6
+ ,24562
+ ,-9
+ ,-14.4
+ ,500857
+ ,0.6
+ ,23580
+ ,-11
+ ,-16.2
+ ,509127
+ ,0.6
+ ,24939
+ ,-18
+ ,-14.9
+ ,509933
+ ,1
+ ,23899
+ ,-13
+ ,-11
+ ,517009
+ ,1
+ ,21454
+ ,-9
+ ,-11.5
+ ,519164
+ ,1
+ ,19761
+ ,-8
+ ,-9.6
+ ,512238
+ ,2.1
+ ,19815
+ ,-4
+ ,-8.8
+ ,509239
+ ,2.1
+ ,20780
+ ,-3
+ ,-9.7
+ ,518585
+ ,2.1
+ ,23462
+ ,-3
+ ,-8.4
+ ,522975
+ ,1.8
+ ,25005
+ ,-3
+ ,-8.4
+ ,525192
+ ,1.8
+ ,24725
+ ,-1
+ ,-6.8
+ ,516847
+ ,1.8
+ ,26198
+ ,0
+ ,-5.3
+ ,455626
+ ,0.9
+ ,27543
+ ,1
+ ,-5.1
+ ,454724
+ ,0.9
+ ,26471
+ ,0
+ ,-6.5
+ ,461251
+ ,0.9
+ ,26558
+ ,2
+ ,-7.3
+ ,470439
+ ,0.6
+ ,25317
+ ,1
+ ,-10.8
+ ,474605
+ ,0.6
+ ,22896
+ ,-1
+ ,-10.9
+ ,476049
+ ,0.6)
+ ,dim=c(5
+ ,102)
+ ,dimnames=list(c('Vacatures'
+ ,'Consumentenvertrouwen'
+ ,'producentenvertrouwen'
+ ,'nietwerkendewerkzoekende'
+ ,'economischegroei')
+ ,1:102))
> y <- array(NA,dim=c(5,102),dimnames=list(c('Vacatures','Consumentenvertrouwen','producentenvertrouwen','nietwerkendewerkzoekende','economischegroei'),1:102))
> 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 = '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
Vacatures Consumentenvertrouwen producentenvertrouwen
1 44164 -9 -7.7
2 40399 -13 -4.9
3 36763 -8 -2.4
4 37903 -13 -3.6
5 35532 -15 -7.0
6 35533 -15 -7.0
7 32110 -15 -7.9
8 33374 -10 -8.8
9 35462 -12 -14.2
10 33508 -11 -17.8
11 36080 -11 -18.2
12 34560 -17 -22.8
13 38737 -18 -23.6
14 38144 -19 -27.6
15 37594 -22 -29.4
16 36424 -24 -31.8
17 36843 -24 -31.4
18 37246 -20 -27.6
19 38661 -25 -28.8
20 40454 -22 -21.9
21 44928 -17 -13.9
22 48441 -9 -8.0
23 48140 -11 -2.8
24 45998 -13 -3.3
25 47369 -11 -1.3
26 49554 -9 0.5
27 47510 -7 -1.9
28 44873 -3 2.0
29 45344 -3 1.7
30 42413 -6 1.9
31 36912 -4 0.1
32 43452 -8 2.4
33 42142 -1 2.3
34 44382 -2 4.7
35 43636 -2 5.0
36 44167 -1 7.2
37 44423 1 8.5
38 42868 2 6.8
39 43908 2 5.8
40 42013 -1 3.7
41 38846 1 4.8
42 35087 -1 6.1
43 33026 -8 6.9
44 34646 1 5.7
45 37135 2 6.9
46 37985 -2 5.5
47 43121 -2 6.5
48 43722 -2 7.7
49 43630 -2 6.3
50 42234 -6 5.5
51 39351 -4 5.3
52 39327 -5 3.3
53 35704 -2 2.2
54 30466 -1 0.6
55 28155 -5 0.2
56 29257 -9 -0.7
57 29998 -8 -1.7
58 32529 -14 -3.7
59 34787 -10 -7.6
60 33855 -11 -8.2
61 34556 -11 -7.5
62 31348 -11 -8.0
63 30805 -5 -6.9
64 28353 -2 -4.2
65 24514 -3 -3.6
66 21106 -6 -1.8
67 21346 -6 -3.2
68 23335 -7 -1.3
69 24379 -6 0.6
70 26290 -2 1.2
71 30084 -2 0.4
72 29429 -4 3.0
73 30632 0 -0.4
74 27349 -6 0.0
75 27264 -4 -1.3
76 27474 -3 -3.1
77 24482 -1 -4.0
78 21453 -3 -4.9
79 18788 -6 -4.6
80 19282 -6 -5.4
81 19713 -15 -8.1
82 21917 -5 -9.4
83 23812 -11 -12.6
84 23785 -13 -15.7
85 24696 -10 -17.3
86 24562 -9 -14.4
87 23580 -11 -16.2
88 24939 -18 -14.9
89 23899 -13 -11.0
90 21454 -9 -11.5
91 19761 -8 -9.6
92 19815 -4 -8.8
93 20780 -3 -9.7
94 23462 -3 -8.4
95 25005 -3 -8.4
96 24725 -1 -6.8
97 26198 0 -5.3
98 27543 1 -5.1
99 26471 0 -6.5
100 26558 2 -7.3
101 25317 1 -10.8
102 22896 -1 -10.9
nietwerkendewerkzoekende economischegroei t
1 544686 2.2 1
2 537034 2.2 2
3 551531 2.2 3
4 563250 1.6 4
5 574761 1.6 5
6 580112 1.6 6
7 575093 -0.1 7
8 557560 -0.1 8
9 564478 -0.1 9
10 580523 -2.7 10
11 596594 -2.7 11
12 586570 -2.7 12
13 536214 -4.1 13
14 523597 -4.1 14
15 536535 -4.1 15
16 536322 -3.7 16
17 532638 -3.7 17
18 528222 -3.7 18
19 516141 -1.3 19
20 501866 -1.3 20
21 506174 -1.3 21
22 517945 1.1 22
23 533590 1.1 23
24 528379 1.1 24
25 477580 1.9 25
26 469357 1.9 26
27 490243 1.9 27
28 492622 1.6 28
29 507561 1.6 29
30 516922 1.6 30
31 514258 1.8 31
32 509846 1.8 32
33 527070 1.8 33
34 541657 2.7 34
35 564591 2.7 35
36 555362 2.7 36
37 498662 3.3 37
38 511038 3.3 38
39 525919 3.3 39
40 531673 3.4 40
41 548854 3.4 41
42 560576 3.4 42
43 557274 3.0 43
44 565742 3.0 44
45 587625 3.0 45
46 619916 2.6 46
47 625809 2.6 47
48 619567 2.6 48
49 572942 2.4 49
50 572775 2.4 50
51 574205 2.4 51
52 579799 2.8 52
53 590072 2.8 53
54 593408 2.8 54
55 597141 2.3 55
56 595404 2.3 56
57 612117 2.3 57
58 628232 1.8 58
59 628884 1.8 59
60 620735 1.8 60
61 569028 2.0 61
62 567456 2.0 62
63 573100 2.0 63
64 584428 1.9 64
65 589379 1.9 65
66 590865 1.9 66
67 595454 3.1 67
68 594167 3.1 68
69 611324 3.1 69
70 612613 3.6 70
71 610763 3.6 71
72 593530 3.6 72
73 542722 3.0 73
74 536662 3.0 74
75 543599 3.0 75
76 555332 2.5 76
77 560854 2.5 77
78 562325 2.5 78
79 554788 1.0 79
80 547344 1.0 80
81 565464 1.0 81
82 577992 0.5 82
83 579714 0.5 83
84 569323 0.5 84
85 506971 0.6 85
86 500857 0.6 86
87 509127 0.6 87
88 509933 1.0 88
89 517009 1.0 89
90 519164 1.0 90
91 512238 2.1 91
92 509239 2.1 92
93 518585 2.1 93
94 522975 1.8 94
95 525192 1.8 95
96 516847 1.8 96
97 455626 0.9 97
98 454724 0.9 98
99 461251 0.9 99
100 470439 0.6 100
101 474605 0.6 101
102 476049 0.6 102
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Consumentenvertrouwen producentenvertrouwen
7.826e+04 -1.226e+02 5.898e+02
nietwerkendewerkzoekende economischegroei t
-5.473e-02 -1.137e+03 -2.142e+02
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-10471.4 -2883.6 313.1 2739.8 8886.3
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 7.826e+04 5.867e+03 13.340 < 2e-16 ***
Consumentenvertrouwen -1.226e+02 1.336e+02 -0.918 0.361
producentenvertrouwen 5.898e+02 1.412e+02 4.176 6.52e-05 ***
nietwerkendewerkzoekende -5.473e-02 1.068e-02 -5.122 1.56e-06 ***
economischegroei -1.137e+03 5.951e+02 -1.911 0.059 .
t -2.142e+02 2.115e+01 -10.127 < 2e-16 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 4187 on 96 degrees of freedom
Multiple R-squared: 0.769, Adjusted R-squared: 0.7569
F-statistic: 63.91 on 5 and 96 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,] 0.085826694 1.716534e-01 9.141733e-01
[2,] 0.030466156 6.093231e-02 9.695338e-01
[3,] 0.048390666 9.678133e-02 9.516093e-01
[4,] 0.020215525 4.043105e-02 9.797845e-01
[5,] 0.031563308 6.312662e-02 9.684367e-01
[6,] 0.016063044 3.212609e-02 9.839370e-01
[7,] 0.007028764 1.405753e-02 9.929712e-01
[8,] 0.003411381 6.822762e-03 9.965886e-01
[9,] 0.001682387 3.364774e-03 9.983176e-01
[10,] 0.003595073 7.190147e-03 9.964049e-01
[11,] 0.002333491 4.666982e-03 9.976665e-01
[12,] 0.005346887 1.069377e-02 9.946531e-01
[13,] 0.033427161 6.685432e-02 9.665728e-01
[14,] 0.034698486 6.939697e-02 9.653015e-01
[15,] 0.037716250 7.543250e-02 9.622838e-01
[16,] 0.023656794 4.731359e-02 9.763432e-01
[17,] 0.030569067 6.113813e-02 9.694309e-01
[18,] 0.024304979 4.860996e-02 9.756950e-01
[19,] 0.023882216 4.776443e-02 9.761178e-01
[20,] 0.040524243 8.104849e-02 9.594758e-01
[21,] 0.033786265 6.757253e-02 9.662137e-01
[22,] 0.038085224 7.617045e-02 9.619148e-01
[23,] 0.205261305 4.105226e-01 7.947387e-01
[24,] 0.168975664 3.379513e-01 8.310243e-01
[25,] 0.139973925 2.799478e-01 8.600261e-01
[26,] 0.115348697 2.306974e-01 8.846513e-01
[27,] 0.099014330 1.980287e-01 9.009857e-01
[28,] 0.077096149 1.541923e-01 9.229039e-01
[29,] 0.070514792 1.410296e-01 9.294852e-01
[30,] 0.063670108 1.273402e-01 9.363299e-01
[31,] 0.047144200 9.428840e-02 9.528558e-01
[32,] 0.037107555 7.421511e-02 9.628924e-01
[33,] 0.032587714 6.517543e-02 9.674123e-01
[34,] 0.050137629 1.002753e-01 9.498624e-01
[35,] 0.115463712 2.309274e-01 8.845363e-01
[36,] 0.140871311 2.817426e-01 8.591287e-01
[37,] 0.126009452 2.520189e-01 8.739905e-01
[38,] 0.151688665 3.033773e-01 8.483113e-01
[39,] 0.343552659 6.871053e-01 6.564473e-01
[40,] 0.515858748 9.682825e-01 4.841413e-01
[41,] 0.534266654 9.314667e-01 4.657333e-01
[42,] 0.554645360 8.907093e-01 4.453546e-01
[43,] 0.549586043 9.008279e-01 4.504140e-01
[44,] 0.586898897 8.262022e-01 4.131011e-01
[45,] 0.577564272 8.448715e-01 4.224357e-01
[46,] 0.612413633 7.751727e-01 3.875864e-01
[47,] 0.702207434 5.955851e-01 2.977926e-01
[48,] 0.718346604 5.633068e-01 2.816534e-01
[49,] 0.678833986 6.423320e-01 3.211660e-01
[50,] 0.710609210 5.787816e-01 2.893908e-01
[51,] 0.828428721 3.431426e-01 1.715713e-01
[52,] 0.911793414 1.764132e-01 8.820659e-02
[53,] 0.945953000 1.080940e-01 5.404700e-02
[54,] 0.957582427 8.483515e-02 4.241757e-02
[55,] 0.964516484 7.096703e-02 3.548352e-02
[56,] 0.967435658 6.512868e-02 3.256434e-02
[57,] 0.972533898 5.493220e-02 2.746610e-02
[58,] 0.990506190 1.898762e-02 9.493810e-03
[59,] 0.995152948 9.694105e-03 4.847052e-03
[60,] 0.995472617 9.054767e-03 4.527383e-03
[61,] 0.993857647 1.228471e-02 6.142353e-03
[62,] 0.990161018 1.967796e-02 9.838982e-03
[63,] 0.992932206 1.413559e-02 7.067794e-03
[64,] 0.995946244 8.107512e-03 4.053756e-03
[65,] 0.996917153 6.165693e-03 3.082847e-03
[66,] 0.997030543 5.938914e-03 2.969457e-03
[67,] 0.997782838 4.434323e-03 2.217162e-03
[68,] 0.999526877 9.462465e-04 4.731232e-04
[69,] 0.999831634 3.367329e-04 1.683665e-04
[70,] 0.999913522 1.729558e-04 8.647791e-05
[71,] 0.999918825 1.623510e-04 8.117549e-05
[72,] 0.999931001 1.379974e-04 6.899868e-05
[73,] 0.999956977 8.604638e-05 4.302319e-05
[74,] 0.999954027 9.194605e-05 4.597303e-05
[75,] 0.999894183 2.116334e-04 1.058167e-04
[76,] 0.999739532 5.209366e-04 2.604683e-04
[77,] 0.999528822 9.423558e-04 4.711779e-04
[78,] 0.998844099 2.311802e-03 1.155901e-03
[79,] 0.998621034 2.757932e-03 1.378966e-03
[80,] 0.999890393 2.192150e-04 1.096075e-04
[81,] 0.999836413 3.271747e-04 1.635873e-04
[82,] 0.999273560 1.452881e-03 7.264404e-04
[83,] 0.997156513 5.686975e-03 2.843487e-03
[84,] 0.991731032 1.653794e-02 8.268968e-03
[85,] 0.982711595 3.457681e-02 1.728840e-02
> postscript(file="/var/www/html/freestat/rcomp/tmp/1tcg51290245591.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/2mmg81290245591.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/freestat/rcomp/tmp/3mmg81290245591.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/4mmg81290245591.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/5wvxb1290245591.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 = 102
Frequency = 1
1 2 3 4 5 6
1866.55633 -4244.94570 -7734.51308 -6326.74572 -6093.60950 -5585.52951
7 8 9 10 11 12
-10471.41279 -8808.70934 -3188.39794 -4760.92260 -859.24509 -736.54813
13 14 15 16 17 18
-344.12200 823.03613 1888.98852 2546.59312 2742.29301 1367.29663
19 20 21 22 23 24
5159.09802 2683.59537 3502.65679 8104.87448 5562.22351 3398.85341
25 26 27 28 29 30
2179.43446 3312.33585 4286.36773 -156.88311 1522.86466 -1167.48953
31 32 33 34 35 36
-5065.73737 -400.03350 364.34336 3102.26809 3648.70691 2713.99591
37 38 39 40 41 42
242.02635 703.83214 3362.24569 2980.67939 564.74226 -3350.49970
43 44 45 46 47 48
-7163.20715 -3053.98999 261.78190 2973.46220 8056.43354 7822.32089
49 50 51 52 53 54
5991.07714 4781.39479 2554.13280 4562.28388 2732.42684 -1042.48967
55 56 57 58 59 60
-3758.23483 -2496.86369 85.45935 3587.70218 8886.30984 7953.77170
61 62 63 64 65 66
5853.75404 3068.83472 3136.08344 180.11431 -3650.20694 -8192.18199
67 68 69 70 71 72
-5296.49661 -4406.91681 -3207.63159 -306.53832 4072.25929 909.65228
73 74 75 76 77 78
1359.73415 -3012.48265 -1491.60648 190.39089 -1509.08227 -3957.84831
79 80 81 82 83 84
-9071.76645 -8299.11976 -6173.65215 -1645.20854 1709.64870 2911.19105
85 86 87 88 89 90
2049.28537 207.21345 708.34044 1155.32399 -970.06324 -2297.42170
91 92 93 94 95 96
-3902.25227 -3779.38404 -1435.22261 593.40333 2471.96436 1251.14317
97 98 99 100 101 102
-2197.64049 -683.08479 -480.61108 699.41598 1842.19590 -471.86498
> postscript(file="/var/www/html/freestat/rcomp/tmp/6wvxb1290245591.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 = 102
Frequency = 1
lag(myerror, k = 1) myerror
0 1866.55633 NA
1 -4244.94570 1866.55633
2 -7734.51308 -4244.94570
3 -6326.74572 -7734.51308
4 -6093.60950 -6326.74572
5 -5585.52951 -6093.60950
6 -10471.41279 -5585.52951
7 -8808.70934 -10471.41279
8 -3188.39794 -8808.70934
9 -4760.92260 -3188.39794
10 -859.24509 -4760.92260
11 -736.54813 -859.24509
12 -344.12200 -736.54813
13 823.03613 -344.12200
14 1888.98852 823.03613
15 2546.59312 1888.98852
16 2742.29301 2546.59312
17 1367.29663 2742.29301
18 5159.09802 1367.29663
19 2683.59537 5159.09802
20 3502.65679 2683.59537
21 8104.87448 3502.65679
22 5562.22351 8104.87448
23 3398.85341 5562.22351
24 2179.43446 3398.85341
25 3312.33585 2179.43446
26 4286.36773 3312.33585
27 -156.88311 4286.36773
28 1522.86466 -156.88311
29 -1167.48953 1522.86466
30 -5065.73737 -1167.48953
31 -400.03350 -5065.73737
32 364.34336 -400.03350
33 3102.26809 364.34336
34 3648.70691 3102.26809
35 2713.99591 3648.70691
36 242.02635 2713.99591
37 703.83214 242.02635
38 3362.24569 703.83214
39 2980.67939 3362.24569
40 564.74226 2980.67939
41 -3350.49970 564.74226
42 -7163.20715 -3350.49970
43 -3053.98999 -7163.20715
44 261.78190 -3053.98999
45 2973.46220 261.78190
46 8056.43354 2973.46220
47 7822.32089 8056.43354
48 5991.07714 7822.32089
49 4781.39479 5991.07714
50 2554.13280 4781.39479
51 4562.28388 2554.13280
52 2732.42684 4562.28388
53 -1042.48967 2732.42684
54 -3758.23483 -1042.48967
55 -2496.86369 -3758.23483
56 85.45935 -2496.86369
57 3587.70218 85.45935
58 8886.30984 3587.70218
59 7953.77170 8886.30984
60 5853.75404 7953.77170
61 3068.83472 5853.75404
62 3136.08344 3068.83472
63 180.11431 3136.08344
64 -3650.20694 180.11431
65 -8192.18199 -3650.20694
66 -5296.49661 -8192.18199
67 -4406.91681 -5296.49661
68 -3207.63159 -4406.91681
69 -306.53832 -3207.63159
70 4072.25929 -306.53832
71 909.65228 4072.25929
72 1359.73415 909.65228
73 -3012.48265 1359.73415
74 -1491.60648 -3012.48265
75 190.39089 -1491.60648
76 -1509.08227 190.39089
77 -3957.84831 -1509.08227
78 -9071.76645 -3957.84831
79 -8299.11976 -9071.76645
80 -6173.65215 -8299.11976
81 -1645.20854 -6173.65215
82 1709.64870 -1645.20854
83 2911.19105 1709.64870
84 2049.28537 2911.19105
85 207.21345 2049.28537
86 708.34044 207.21345
87 1155.32399 708.34044
88 -970.06324 1155.32399
89 -2297.42170 -970.06324
90 -3902.25227 -2297.42170
91 -3779.38404 -3902.25227
92 -1435.22261 -3779.38404
93 593.40333 -1435.22261
94 2471.96436 593.40333
95 1251.14317 2471.96436
96 -2197.64049 1251.14317
97 -683.08479 -2197.64049
98 -480.61108 -683.08479
99 699.41598 -480.61108
100 1842.19590 699.41598
101 -471.86498 1842.19590
102 NA -471.86498
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -4244.94570 1866.55633
[2,] -7734.51308 -4244.94570
[3,] -6326.74572 -7734.51308
[4,] -6093.60950 -6326.74572
[5,] -5585.52951 -6093.60950
[6,] -10471.41279 -5585.52951
[7,] -8808.70934 -10471.41279
[8,] -3188.39794 -8808.70934
[9,] -4760.92260 -3188.39794
[10,] -859.24509 -4760.92260
[11,] -736.54813 -859.24509
[12,] -344.12200 -736.54813
[13,] 823.03613 -344.12200
[14,] 1888.98852 823.03613
[15,] 2546.59312 1888.98852
[16,] 2742.29301 2546.59312
[17,] 1367.29663 2742.29301
[18,] 5159.09802 1367.29663
[19,] 2683.59537 5159.09802
[20,] 3502.65679 2683.59537
[21,] 8104.87448 3502.65679
[22,] 5562.22351 8104.87448
[23,] 3398.85341 5562.22351
[24,] 2179.43446 3398.85341
[25,] 3312.33585 2179.43446
[26,] 4286.36773 3312.33585
[27,] -156.88311 4286.36773
[28,] 1522.86466 -156.88311
[29,] -1167.48953 1522.86466
[30,] -5065.73737 -1167.48953
[31,] -400.03350 -5065.73737
[32,] 364.34336 -400.03350
[33,] 3102.26809 364.34336
[34,] 3648.70691 3102.26809
[35,] 2713.99591 3648.70691
[36,] 242.02635 2713.99591
[37,] 703.83214 242.02635
[38,] 3362.24569 703.83214
[39,] 2980.67939 3362.24569
[40,] 564.74226 2980.67939
[41,] -3350.49970 564.74226
[42,] -7163.20715 -3350.49970
[43,] -3053.98999 -7163.20715
[44,] 261.78190 -3053.98999
[45,] 2973.46220 261.78190
[46,] 8056.43354 2973.46220
[47,] 7822.32089 8056.43354
[48,] 5991.07714 7822.32089
[49,] 4781.39479 5991.07714
[50,] 2554.13280 4781.39479
[51,] 4562.28388 2554.13280
[52,] 2732.42684 4562.28388
[53,] -1042.48967 2732.42684
[54,] -3758.23483 -1042.48967
[55,] -2496.86369 -3758.23483
[56,] 85.45935 -2496.86369
[57,] 3587.70218 85.45935
[58,] 8886.30984 3587.70218
[59,] 7953.77170 8886.30984
[60,] 5853.75404 7953.77170
[61,] 3068.83472 5853.75404
[62,] 3136.08344 3068.83472
[63,] 180.11431 3136.08344
[64,] -3650.20694 180.11431
[65,] -8192.18199 -3650.20694
[66,] -5296.49661 -8192.18199
[67,] -4406.91681 -5296.49661
[68,] -3207.63159 -4406.91681
[69,] -306.53832 -3207.63159
[70,] 4072.25929 -306.53832
[71,] 909.65228 4072.25929
[72,] 1359.73415 909.65228
[73,] -3012.48265 1359.73415
[74,] -1491.60648 -3012.48265
[75,] 190.39089 -1491.60648
[76,] -1509.08227 190.39089
[77,] -3957.84831 -1509.08227
[78,] -9071.76645 -3957.84831
[79,] -8299.11976 -9071.76645
[80,] -6173.65215 -8299.11976
[81,] -1645.20854 -6173.65215
[82,] 1709.64870 -1645.20854
[83,] 2911.19105 1709.64870
[84,] 2049.28537 2911.19105
[85,] 207.21345 2049.28537
[86,] 708.34044 207.21345
[87,] 1155.32399 708.34044
[88,] -970.06324 1155.32399
[89,] -2297.42170 -970.06324
[90,] -3902.25227 -2297.42170
[91,] -3779.38404 -3902.25227
[92,] -1435.22261 -3779.38404
[93,] 593.40333 -1435.22261
[94,] 2471.96436 593.40333
[95,] 1251.14317 2471.96436
[96,] -2197.64049 1251.14317
[97,] -683.08479 -2197.64049
[98,] -480.61108 -683.08479
[99,] 699.41598 -480.61108
[100,] 1842.19590 699.41598
[101,] -471.86498 1842.19590
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -4244.94570 1866.55633
2 -7734.51308 -4244.94570
3 -6326.74572 -7734.51308
4 -6093.60950 -6326.74572
5 -5585.52951 -6093.60950
6 -10471.41279 -5585.52951
7 -8808.70934 -10471.41279
8 -3188.39794 -8808.70934
9 -4760.92260 -3188.39794
10 -859.24509 -4760.92260
11 -736.54813 -859.24509
12 -344.12200 -736.54813
13 823.03613 -344.12200
14 1888.98852 823.03613
15 2546.59312 1888.98852
16 2742.29301 2546.59312
17 1367.29663 2742.29301
18 5159.09802 1367.29663
19 2683.59537 5159.09802
20 3502.65679 2683.59537
21 8104.87448 3502.65679
22 5562.22351 8104.87448
23 3398.85341 5562.22351
24 2179.43446 3398.85341
25 3312.33585 2179.43446
26 4286.36773 3312.33585
27 -156.88311 4286.36773
28 1522.86466 -156.88311
29 -1167.48953 1522.86466
30 -5065.73737 -1167.48953
31 -400.03350 -5065.73737
32 364.34336 -400.03350
33 3102.26809 364.34336
34 3648.70691 3102.26809
35 2713.99591 3648.70691
36 242.02635 2713.99591
37 703.83214 242.02635
38 3362.24569 703.83214
39 2980.67939 3362.24569
40 564.74226 2980.67939
41 -3350.49970 564.74226
42 -7163.20715 -3350.49970
43 -3053.98999 -7163.20715
44 261.78190 -3053.98999
45 2973.46220 261.78190
46 8056.43354 2973.46220
47 7822.32089 8056.43354
48 5991.07714 7822.32089
49 4781.39479 5991.07714
50 2554.13280 4781.39479
51 4562.28388 2554.13280
52 2732.42684 4562.28388
53 -1042.48967 2732.42684
54 -3758.23483 -1042.48967
55 -2496.86369 -3758.23483
56 85.45935 -2496.86369
57 3587.70218 85.45935
58 8886.30984 3587.70218
59 7953.77170 8886.30984
60 5853.75404 7953.77170
61 3068.83472 5853.75404
62 3136.08344 3068.83472
63 180.11431 3136.08344
64 -3650.20694 180.11431
65 -8192.18199 -3650.20694
66 -5296.49661 -8192.18199
67 -4406.91681 -5296.49661
68 -3207.63159 -4406.91681
69 -306.53832 -3207.63159
70 4072.25929 -306.53832
71 909.65228 4072.25929
72 1359.73415 909.65228
73 -3012.48265 1359.73415
74 -1491.60648 -3012.48265
75 190.39089 -1491.60648
76 -1509.08227 190.39089
77 -3957.84831 -1509.08227
78 -9071.76645 -3957.84831
79 -8299.11976 -9071.76645
80 -6173.65215 -8299.11976
81 -1645.20854 -6173.65215
82 1709.64870 -1645.20854
83 2911.19105 1709.64870
84 2049.28537 2911.19105
85 207.21345 2049.28537
86 708.34044 207.21345
87 1155.32399 708.34044
88 -970.06324 1155.32399
89 -2297.42170 -970.06324
90 -3902.25227 -2297.42170
91 -3779.38404 -3902.25227
92 -1435.22261 -3779.38404
93 593.40333 -1435.22261
94 2471.96436 593.40333
95 1251.14317 2471.96436
96 -2197.64049 1251.14317
97 -683.08479 -2197.64049
98 -480.61108 -683.08479
99 699.41598 -480.61108
100 1842.19590 699.41598
101 -471.86498 1842.19590
> 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/774we1290245591.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/874we1290245591.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/90vvz1290245591.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/freestat/rcomp/tmp/100vvz1290245591.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/freestat/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11lwc51290245591.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/12pwat1290245591.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/13vfpm1290245591.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/14op7q1290245591.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/15r75d1290245591.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/166zl41290245591.tab")
+ }
>
> try(system("convert tmp/1tcg51290245591.ps tmp/1tcg51290245591.png",intern=TRUE))
character(0)
> try(system("convert tmp/2mmg81290245591.ps tmp/2mmg81290245591.png",intern=TRUE))
character(0)
> try(system("convert tmp/3mmg81290245591.ps tmp/3mmg81290245591.png",intern=TRUE))
character(0)
> try(system("convert tmp/4mmg81290245591.ps tmp/4mmg81290245591.png",intern=TRUE))
character(0)
> try(system("convert tmp/5wvxb1290245591.ps tmp/5wvxb1290245591.png",intern=TRUE))
character(0)
> try(system("convert tmp/6wvxb1290245591.ps tmp/6wvxb1290245591.png",intern=TRUE))
character(0)
> try(system("convert tmp/774we1290245591.ps tmp/774we1290245591.png",intern=TRUE))
character(0)
> try(system("convert tmp/874we1290245591.ps tmp/874we1290245591.png",intern=TRUE))
character(0)
> try(system("convert tmp/90vvz1290245591.ps tmp/90vvz1290245591.png",intern=TRUE))
character(0)
> try(system("convert tmp/100vvz1290245591.ps tmp/100vvz1290245591.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
4.622 2.610 6.179