R version 2.9.0 (2009-04-17)
Copyright (C) 2009 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(128332
+ ,0
+ ,128332
+ ,133639
+ ,142773
+ ,149657
+ ,120297
+ ,0
+ ,120297
+ ,128332
+ ,133639
+ ,142773
+ ,118632
+ ,0
+ ,118632
+ ,120297
+ ,128332
+ ,133639
+ ,155276
+ ,0
+ ,155276
+ ,118632
+ ,120297
+ ,128332
+ ,169316
+ ,0
+ ,169316
+ ,155276
+ ,118632
+ ,120297
+ ,167395
+ ,0
+ ,167395
+ ,169316
+ ,155276
+ ,118632
+ ,157939
+ ,0
+ ,157939
+ ,167395
+ ,169316
+ ,155276
+ ,149601
+ ,0
+ ,149601
+ ,157939
+ ,167395
+ ,169316
+ ,146310
+ ,0
+ ,146310
+ ,149601
+ ,157939
+ ,167395
+ ,141579
+ ,0
+ ,141579
+ ,146310
+ ,149601
+ ,157939
+ ,136473
+ ,0
+ ,136473
+ ,141579
+ ,146310
+ ,149601
+ ,129818
+ ,0
+ ,129818
+ ,136473
+ ,141579
+ ,146310
+ ,124226
+ ,0
+ ,124226
+ ,129818
+ ,136473
+ ,141579
+ ,116428
+ ,0
+ ,116428
+ ,124226
+ ,129818
+ ,136473
+ ,116440
+ ,0
+ ,116440
+ ,116428
+ ,124226
+ ,129818
+ ,147747
+ ,0
+ ,147747
+ ,116440
+ ,116428
+ ,124226
+ ,160069
+ ,0
+ ,160069
+ ,147747
+ ,116440
+ ,116428
+ ,163129
+ ,0
+ ,163129
+ ,160069
+ ,147747
+ ,116440
+ ,151108
+ ,0
+ ,151108
+ ,163129
+ ,160069
+ ,147747
+ ,141481
+ ,0
+ ,141481
+ ,151108
+ ,163129
+ ,160069
+ ,139174
+ ,0
+ ,139174
+ ,141481
+ ,151108
+ ,163129
+ ,134066
+ ,0
+ ,134066
+ ,139174
+ ,141481
+ ,151108
+ ,130104
+ ,0
+ ,130104
+ ,134066
+ ,139174
+ ,141481
+ ,123090
+ ,0
+ ,123090
+ ,130104
+ ,134066
+ ,139174
+ ,116598
+ ,0
+ ,116598
+ ,123090
+ ,130104
+ ,134066
+ ,109627
+ ,0
+ ,109627
+ ,116598
+ ,123090
+ ,130104
+ ,105428
+ ,0
+ ,105428
+ ,109627
+ ,116598
+ ,123090
+ ,137272
+ ,0
+ ,137272
+ ,105428
+ ,109627
+ ,116598
+ ,159836
+ ,0
+ ,159836
+ ,137272
+ ,105428
+ ,109627
+ ,155283
+ ,0
+ ,155283
+ ,159836
+ ,137272
+ ,105428
+ ,141514
+ ,0
+ ,141514
+ ,155283
+ ,159836
+ ,137272
+ ,131852
+ ,0
+ ,131852
+ ,141514
+ ,155283
+ ,159836
+ ,130691
+ ,0
+ ,130691
+ ,131852
+ ,141514
+ ,155283
+ ,128461
+ ,0
+ ,128461
+ ,130691
+ ,131852
+ ,141514
+ ,123066
+ ,0
+ ,123066
+ ,128461
+ ,130691
+ ,131852
+ ,117599
+ ,0
+ ,117599
+ ,123066
+ ,128461
+ ,130691
+ ,111599
+ ,0
+ ,111599
+ ,117599
+ ,123066
+ ,128461
+ ,105395
+ ,0
+ ,105395
+ ,111599
+ ,117599
+ ,123066
+ ,102334
+ ,0
+ ,102334
+ ,105395
+ ,111599
+ ,117599
+ ,131305
+ ,0
+ ,131305
+ ,102334
+ ,105395
+ ,111599
+ ,149033
+ ,0
+ ,149033
+ ,131305
+ ,102334
+ ,105395
+ ,144954
+ ,0
+ ,144954
+ ,149033
+ ,131305
+ ,102334
+ ,132404
+ ,0
+ ,132404
+ ,144954
+ ,149033
+ ,131305
+ ,122104
+ ,0
+ ,122104
+ ,132404
+ ,144954
+ ,149033
+ ,118755
+ ,0
+ ,118755
+ ,122104
+ ,132404
+ ,144954
+ ,116222
+ ,1
+ ,116222
+ ,118755
+ ,122104
+ ,132404
+ ,110924
+ ,1
+ ,110924
+ ,116222
+ ,118755
+ ,122104
+ ,103753
+ ,1
+ ,103753
+ ,110924
+ ,116222
+ ,118755
+ ,99983
+ ,1
+ ,99983
+ ,103753
+ ,110924
+ ,116222
+ ,93302
+ ,1
+ ,93302
+ ,99983
+ ,103753
+ ,110924
+ ,91496
+ ,1
+ ,91496
+ ,93302
+ ,99983
+ ,103753
+ ,119321
+ ,1
+ ,119321
+ ,91496
+ ,93302
+ ,99983
+ ,139261
+ ,1
+ ,139261
+ ,119321
+ ,91496
+ ,93302
+ ,133739
+ ,1
+ ,133739
+ ,139261
+ ,119321
+ ,91496
+ ,123913
+ ,1
+ ,123913
+ ,133739
+ ,139261
+ ,119321
+ ,113438
+ ,1
+ ,113438
+ ,123913
+ ,133739
+ ,139261
+ ,109416
+ ,1
+ ,109416
+ ,113438
+ ,123913
+ ,133739
+ ,109406
+ ,1
+ ,109406
+ ,109416
+ ,113438
+ ,123913
+ ,105645
+ ,1
+ ,105645
+ ,109406
+ ,109416
+ ,113438
+ ,101328
+ ,1
+ ,101328
+ ,105645
+ ,109406
+ ,109416
+ ,97686
+ ,1
+ ,97686
+ ,101328
+ ,105645
+ ,109406
+ ,93093
+ ,1
+ ,93093
+ ,97686
+ ,101328
+ ,105645
+ ,91382
+ ,1
+ ,91382
+ ,93093
+ ,97686
+ ,101328
+ ,122257
+ ,1
+ ,122257
+ ,91382
+ ,93093
+ ,97686
+ ,139183
+ ,1
+ ,139183
+ ,122257
+ ,91382
+ ,93093
+ ,139887
+ ,1
+ ,139887
+ ,139183
+ ,122257
+ ,91382
+ ,131822
+ ,1
+ ,131822
+ ,139887
+ ,139183
+ ,122257
+ ,116805
+ ,1
+ ,116805
+ ,131822
+ ,139887
+ ,139183
+ ,113706
+ ,1
+ ,113706
+ ,116805
+ ,131822
+ ,139887
+ ,113012
+ ,1
+ ,113012
+ ,113706
+ ,116805
+ ,131822
+ ,110452
+ ,1
+ ,110452
+ ,113012
+ ,113706
+ ,116805
+ ,107005
+ ,1
+ ,107005
+ ,110452
+ ,113012
+ ,113706
+ ,102841
+ ,1
+ ,102841
+ ,107005
+ ,110452
+ ,113012
+ ,98173
+ ,1
+ ,98173
+ ,102841
+ ,107005
+ ,110452
+ ,98181
+ ,1
+ ,98181
+ ,98173
+ ,102841
+ ,107005
+ ,137277
+ ,1
+ ,137277
+ ,98181
+ ,98173
+ ,102841
+ ,147579
+ ,1
+ ,147579
+ ,137277
+ ,98181
+ ,98173
+ ,146571
+ ,1
+ ,146571
+ ,147579
+ ,137277
+ ,98181
+ ,138920
+ ,1
+ ,138920
+ ,146571
+ ,147579
+ ,137277
+ ,130340
+ ,1
+ ,130340
+ ,138920
+ ,146571
+ ,147579
+ ,128140
+ ,1
+ ,128140
+ ,130340
+ ,138920
+ ,146571
+ ,127059
+ ,1
+ ,127059
+ ,128140
+ ,130340
+ ,138920
+ ,122860
+ ,1
+ ,122860
+ ,127059
+ ,128140
+ ,130340
+ ,117702
+ ,1
+ ,117702
+ ,122860
+ ,127059
+ ,128140
+ ,113537
+ ,1
+ ,113537
+ ,117702
+ ,122860
+ ,127059
+ ,108366
+ ,1
+ ,108366
+ ,113537
+ ,117702
+ ,122860
+ ,111078
+ ,1
+ ,111078
+ ,108366
+ ,113537
+ ,117702
+ ,150739
+ ,1
+ ,150739
+ ,111078
+ ,108366
+ ,113537
+ ,159129
+ ,1
+ ,159129
+ ,150739
+ ,111078
+ ,108366
+ ,157928
+ ,1
+ ,157928
+ ,159129
+ ,150739
+ ,111078
+ ,147768
+ ,1
+ ,147768
+ ,157928
+ ,159129
+ ,150739
+ ,137507
+ ,1
+ ,137507
+ ,147768
+ ,157928
+ ,159129
+ ,136919
+ ,1
+ ,136919
+ ,137507
+ ,147768
+ ,157928)
+ ,dim=c(6
+ ,93)
+ ,dimnames=list(c('Y'
+ ,'X'
+ ,'Y1'
+ ,'Y2'
+ ,'Y3'
+ ,'Y4')
+ ,1:93))
> y <- array(NA,dim=c(6,93),dimnames=list(c('Y','X','Y1','Y2','Y3','Y4'),1:93))
> 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
Y X Y1 Y2 Y3 Y4 M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 128332 0 128332 133639 142773 149657 1 0 0 0 0 0 0 0 0 0 0 1
2 120297 0 120297 128332 133639 142773 0 1 0 0 0 0 0 0 0 0 0 2
3 118632 0 118632 120297 128332 133639 0 0 1 0 0 0 0 0 0 0 0 3
4 155276 0 155276 118632 120297 128332 0 0 0 1 0 0 0 0 0 0 0 4
5 169316 0 169316 155276 118632 120297 0 0 0 0 1 0 0 0 0 0 0 5
6 167395 0 167395 169316 155276 118632 0 0 0 0 0 1 0 0 0 0 0 6
7 157939 0 157939 167395 169316 155276 0 0 0 0 0 0 1 0 0 0 0 7
8 149601 0 149601 157939 167395 169316 0 0 0 0 0 0 0 1 0 0 0 8
9 146310 0 146310 149601 157939 167395 0 0 0 0 0 0 0 0 1 0 0 9
10 141579 0 141579 146310 149601 157939 0 0 0 0 0 0 0 0 0 1 0 10
11 136473 0 136473 141579 146310 149601 0 0 0 0 0 0 0 0 0 0 1 11
12 129818 0 129818 136473 141579 146310 0 0 0 0 0 0 0 0 0 0 0 12
13 124226 0 124226 129818 136473 141579 1 0 0 0 0 0 0 0 0 0 0 13
14 116428 0 116428 124226 129818 136473 0 1 0 0 0 0 0 0 0 0 0 14
15 116440 0 116440 116428 124226 129818 0 0 1 0 0 0 0 0 0 0 0 15
16 147747 0 147747 116440 116428 124226 0 0 0 1 0 0 0 0 0 0 0 16
17 160069 0 160069 147747 116440 116428 0 0 0 0 1 0 0 0 0 0 0 17
18 163129 0 163129 160069 147747 116440 0 0 0 0 0 1 0 0 0 0 0 18
19 151108 0 151108 163129 160069 147747 0 0 0 0 0 0 1 0 0 0 0 19
20 141481 0 141481 151108 163129 160069 0 0 0 0 0 0 0 1 0 0 0 20
21 139174 0 139174 141481 151108 163129 0 0 0 0 0 0 0 0 1 0 0 21
22 134066 0 134066 139174 141481 151108 0 0 0 0 0 0 0 0 0 1 0 22
23 130104 0 130104 134066 139174 141481 0 0 0 0 0 0 0 0 0 0 1 23
24 123090 0 123090 130104 134066 139174 0 0 0 0 0 0 0 0 0 0 0 24
25 116598 0 116598 123090 130104 134066 1 0 0 0 0 0 0 0 0 0 0 25
26 109627 0 109627 116598 123090 130104 0 1 0 0 0 0 0 0 0 0 0 26
27 105428 0 105428 109627 116598 123090 0 0 1 0 0 0 0 0 0 0 0 27
28 137272 0 137272 105428 109627 116598 0 0 0 1 0 0 0 0 0 0 0 28
29 159836 0 159836 137272 105428 109627 0 0 0 0 1 0 0 0 0 0 0 29
30 155283 0 155283 159836 137272 105428 0 0 0 0 0 1 0 0 0 0 0 30
31 141514 0 141514 155283 159836 137272 0 0 0 0 0 0 1 0 0 0 0 31
32 131852 0 131852 141514 155283 159836 0 0 0 0 0 0 0 1 0 0 0 32
33 130691 0 130691 131852 141514 155283 0 0 0 0 0 0 0 0 1 0 0 33
34 128461 0 128461 130691 131852 141514 0 0 0 0 0 0 0 0 0 1 0 34
35 123066 0 123066 128461 130691 131852 0 0 0 0 0 0 0 0 0 0 1 35
36 117599 0 117599 123066 128461 130691 0 0 0 0 0 0 0 0 0 0 0 36
37 111599 0 111599 117599 123066 128461 1 0 0 0 0 0 0 0 0 0 0 37
38 105395 0 105395 111599 117599 123066 0 1 0 0 0 0 0 0 0 0 0 38
39 102334 0 102334 105395 111599 117599 0 0 1 0 0 0 0 0 0 0 0 39
40 131305 0 131305 102334 105395 111599 0 0 0 1 0 0 0 0 0 0 0 40
41 149033 0 149033 131305 102334 105395 0 0 0 0 1 0 0 0 0 0 0 41
42 144954 0 144954 149033 131305 102334 0 0 0 0 0 1 0 0 0 0 0 42
43 132404 0 132404 144954 149033 131305 0 0 0 0 0 0 1 0 0 0 0 43
44 122104 0 122104 132404 144954 149033 0 0 0 0 0 0 0 1 0 0 0 44
45 118755 0 118755 122104 132404 144954 0 0 0 0 0 0 0 0 1 0 0 45
46 116222 1 116222 118755 122104 132404 0 0 0 0 0 0 0 0 0 1 0 46
47 110924 1 110924 116222 118755 122104 0 0 0 0 0 0 0 0 0 0 1 47
48 103753 1 103753 110924 116222 118755 0 0 0 0 0 0 0 0 0 0 0 48
49 99983 1 99983 103753 110924 116222 1 0 0 0 0 0 0 0 0 0 0 49
50 93302 1 93302 99983 103753 110924 0 1 0 0 0 0 0 0 0 0 0 50
51 91496 1 91496 93302 99983 103753 0 0 1 0 0 0 0 0 0 0 0 51
52 119321 1 119321 91496 93302 99983 0 0 0 1 0 0 0 0 0 0 0 52
53 139261 1 139261 119321 91496 93302 0 0 0 0 1 0 0 0 0 0 0 53
54 133739 1 133739 139261 119321 91496 0 0 0 0 0 1 0 0 0 0 0 54
55 123913 1 123913 133739 139261 119321 0 0 0 0 0 0 1 0 0 0 0 55
56 113438 1 113438 123913 133739 139261 0 0 0 0 0 0 0 1 0 0 0 56
57 109416 1 109416 113438 123913 133739 0 0 0 0 0 0 0 0 1 0 0 57
58 109406 1 109406 109416 113438 123913 0 0 0 0 0 0 0 0 0 1 0 58
59 105645 1 105645 109406 109416 113438 0 0 0 0 0 0 0 0 0 0 1 59
60 101328 1 101328 105645 109406 109416 0 0 0 0 0 0 0 0 0 0 0 60
61 97686 1 97686 101328 105645 109406 1 0 0 0 0 0 0 0 0 0 0 61
62 93093 1 93093 97686 101328 105645 0 1 0 0 0 0 0 0 0 0 0 62
63 91382 1 91382 93093 97686 101328 0 0 1 0 0 0 0 0 0 0 0 63
64 122257 1 122257 91382 93093 97686 0 0 0 1 0 0 0 0 0 0 0 64
65 139183 1 139183 122257 91382 93093 0 0 0 0 1 0 0 0 0 0 0 65
66 139887 1 139887 139183 122257 91382 0 0 0 0 0 1 0 0 0 0 0 66
67 131822 1 131822 139887 139183 122257 0 0 0 0 0 0 1 0 0 0 0 67
68 116805 1 116805 131822 139887 139183 0 0 0 0 0 0 0 1 0 0 0 68
69 113706 1 113706 116805 131822 139887 0 0 0 0 0 0 0 0 1 0 0 69
70 113012 1 113012 113706 116805 131822 0 0 0 0 0 0 0 0 0 1 0 70
71 110452 1 110452 113012 113706 116805 0 0 0 0 0 0 0 0 0 0 1 71
72 107005 1 107005 110452 113012 113706 0 0 0 0 0 0 0 0 0 0 0 72
73 102841 1 102841 107005 110452 113012 1 0 0 0 0 0 0 0 0 0 0 73
74 98173 1 98173 102841 107005 110452 0 1 0 0 0 0 0 0 0 0 0 74
75 98181 1 98181 98173 102841 107005 0 0 1 0 0 0 0 0 0 0 0 75
76 137277 1 137277 98181 98173 102841 0 0 0 1 0 0 0 0 0 0 0 76
77 147579 1 147579 137277 98181 98173 0 0 0 0 1 0 0 0 0 0 0 77
78 146571 1 146571 147579 137277 98181 0 0 0 0 0 1 0 0 0 0 0 78
79 138920 1 138920 146571 147579 137277 0 0 0 0 0 0 1 0 0 0 0 79
80 130340 1 130340 138920 146571 147579 0 0 0 0 0 0 0 1 0 0 0 80
81 128140 1 128140 130340 138920 146571 0 0 0 0 0 0 0 0 1 0 0 81
82 127059 1 127059 128140 130340 138920 0 0 0 0 0 0 0 0 0 1 0 82
83 122860 1 122860 127059 128140 130340 0 0 0 0 0 0 0 0 0 0 1 83
84 117702 1 117702 122860 127059 128140 0 0 0 0 0 0 0 0 0 0 0 84
85 113537 1 113537 117702 122860 127059 1 0 0 0 0 0 0 0 0 0 0 85
86 108366 1 108366 113537 117702 122860 0 1 0 0 0 0 0 0 0 0 0 86
87 111078 1 111078 108366 113537 117702 0 0 1 0 0 0 0 0 0 0 0 87
88 150739 1 150739 111078 108366 113537 0 0 0 1 0 0 0 0 0 0 0 88
89 159129 1 159129 150739 111078 108366 0 0 0 0 1 0 0 0 0 0 0 89
90 157928 1 157928 159129 150739 111078 0 0 0 0 0 1 0 0 0 0 0 90
91 147768 1 147768 157928 159129 150739 0 0 0 0 0 0 1 0 0 0 0 91
92 137507 1 137507 147768 157928 159129 0 0 0 0 0 0 0 1 0 0 0 92
93 136919 1 136919 137507 147768 157928 0 0 0 0 0 0 0 0 1 0 0 93
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X Y1 Y2 Y3 Y4
4.985e-11 -3.019e-12 1.000e+00 -2.498e-16 4.417e-16 -9.483e-17
M1 M2 M3 M4 M5 M6
-1.302e-12 1.402e-12 1.795e-11 2.060e-12 9.606e-12 -2.834e-13
M7 M8 M9 M10 M11 t
-3.559e-12 -4.093e-12 -1.366e-12 9.013e-14 4.517e-13 -1.236e-13
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-1.956e-11 -2.085e-12 6.811e-13 2.117e-12 1.069e-10
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 4.985e-11 2.733e-11 1.824e+00 0.0722 .
X -3.019e-12 6.557e-12 -4.610e-01 0.6465
Y1 1.000e+00 6.432e-16 1.555e+15 <2e-16 ***
Y2 -2.498e-16 7.685e-16 -3.250e-01 0.7461
Y3 4.417e-16 7.698e-16 5.740e-01 0.5679
Y4 -9.483e-17 6.530e-16 -1.450e-01 0.8849
M1 -1.302e-12 7.351e-12 -1.770e-01 0.8599
M2 1.402e-12 7.608e-12 1.840e-01 0.8543
M3 1.795e-11 8.078e-12 2.223e+00 0.0293 *
M4 2.060e-12 2.666e-11 7.700e-02 0.9386
M5 9.606e-12 3.263e-11 2.940e-01 0.7693
M6 -2.834e-13 3.081e-11 -9.000e-03 0.9927
M7 -3.559e-12 1.370e-11 -2.600e-01 0.7958
M8 -4.093e-12 1.032e-11 -3.970e-01 0.6928
M9 -1.366e-12 1.072e-11 -1.270e-01 0.8989
M10 9.013e-14 9.066e-12 1.000e-02 0.9921
M11 4.517e-13 7.531e-12 6.000e-02 0.9523
t -1.236e-13 1.099e-13 -1.125e+00 0.2643
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 1.372e-11 on 75 degrees of freedom
Multiple R-squared: 1, Adjusted R-squared: 1
F-statistic: 1.077e+31 on 17 and 75 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,] 1.988130e-01 3.976260e-01 8.011870e-01
[2,] 5.569832e-01 8.860336e-01 4.430168e-01
[3,] 1.000000e+00 2.966678e-28 1.483339e-28
[4,] 1.000000e+00 9.097091e-18 4.548546e-18
[5,] 1.920381e-08 3.840762e-08 1.000000e+00
[6,] 9.372758e-01 1.254484e-01 6.272422e-02
[7,] 8.945498e-01 2.109003e-01 1.054502e-01
[8,] 2.016930e-06 4.033860e-06 9.999980e-01
[9,] 2.830618e-01 5.661237e-01 7.169382e-01
[10,] 1.000000e+00 5.859789e-08 2.929895e-08
[11,] 8.091120e-05 1.618224e-04 9.999191e-01
[12,] 8.774910e-10 1.754982e-09 1.000000e+00
[13,] 9.860908e-01 2.781834e-02 1.390917e-02
[14,] 1.699967e-01 3.399934e-01 8.300033e-01
[15,] 8.543097e-08 1.708619e-07 9.999999e-01
[16,] 1.877045e-04 3.754090e-04 9.998123e-01
[17,] 8.946327e-01 2.107347e-01 1.053673e-01
[18,] 1.000000e+00 4.007946e-10 2.003973e-10
[19,] 1.109643e-07 2.219286e-07 9.999999e-01
[20,] 9.999999e-01 2.040632e-07 1.020316e-07
[21,] 1.000000e+00 8.282285e-11 4.141142e-11
[22,] 1.393906e-04 2.787812e-04 9.998606e-01
[23,] 1.759231e-13 3.518462e-13 1.000000e+00
[24,] 9.999477e-01 1.046713e-04 5.233566e-05
[25,] 8.975782e-02 1.795156e-01 9.102422e-01
[26,] 9.997919e-01 4.161205e-04 2.080602e-04
[27,] 6.154995e-01 7.690009e-01 3.845005e-01
[28,] 3.632035e-06 7.264070e-06 9.999964e-01
[29,] 8.145306e-01 3.709389e-01 1.854694e-01
[30,] 4.198512e-01 8.397023e-01 5.801488e-01
[31,] 9.956250e-01 8.750048e-03 4.375024e-03
[32,] 9.429568e-01 1.140863e-01 5.704317e-02
[33,] 4.801435e-02 9.602870e-02 9.519857e-01
[34,] 1.825629e-01 3.651257e-01 8.174371e-01
[35,] 7.974155e-01 4.051689e-01 2.025845e-01
[36,] 9.984289e-01 3.142242e-03 1.571121e-03
[37,] 9.797687e-02 1.959537e-01 9.020231e-01
[38,] 1.000000e+00 3.233873e-17 1.616937e-17
[39,] 8.740843e-02 1.748169e-01 9.125916e-01
[40,] 9.997123e-01 5.753438e-04 2.876719e-04
[41,] 2.271194e-01 4.542388e-01 7.728806e-01
[42,] 9.999931e-01 1.383009e-05 6.915046e-06
[43,] 9.999981e-01 3.828235e-06 1.914118e-06
[44,] 9.999991e-01 1.881381e-06 9.406906e-07
[45,] 3.683558e-01 7.367117e-01 6.316442e-01
[46,] 4.128132e-01 8.256264e-01 5.871868e-01
[47,] 1.285623e-07 2.571247e-07 9.999999e-01
[48,] 2.685243e-09 5.370487e-09 1.000000e+00
[49,] 9.961352e-01 7.729653e-03 3.864826e-03
[50,] 5.108969e-07 1.021794e-06 9.999995e-01
[51,] 4.145027e-01 8.290054e-01 5.854973e-01
[52,] 9.548500e-01 9.029994e-02 4.514997e-02
> postscript(file="/var/www/html/rcomp/tmp/13ewq1258546716.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2apc01258546716.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3qfrw1258546716.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4yevk1258546716.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5o23v1258546716.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 = 93
Frequency = 1
1 2 3 4 5
-1.608597e-11 -1.376058e-11 1.068879e-10 -6.397474e-12 -1.276148e-12
6 7 8 9 10
-2.575780e-12 -5.797745e-12 -5.985644e-12 -4.067262e-12 -3.321806e-12
11 12 13 14 15
-4.122048e-12 -3.223862e-12 -4.028610e-13 -3.016388e-12 -1.956389e-11
16 17 18 19 20
-1.809069e-12 -4.652573e-12 -4.177070e-12 -2.300974e-13 -2.399461e-12
21 22 23 24 25
-2.706549e-12 -8.628738e-13 -2.084510e-12 -3.560463e-13 2.742259e-13
26 27 28 29 30
2.504091e-12 -1.740987e-11 2.356433e-13 2.256382e-12 -2.230352e-13
31 32 33 34 35
-1.264298e-12 3.665479e-14 6.811054e-13 2.424732e-12 9.572479e-13
36 37 38 39 40
1.757437e-12 5.108813e-12 4.215124e-12 -1.648033e-11 2.526189e-12
41 42 43 44 45
8.680475e-13 3.638694e-12 1.680018e-12 3.691852e-12 4.509130e-12
46 47 48 49 50
-1.656893e-12 -1.461566e-12 -2.997467e-12 1.726230e-12 2.529664e-12
51 52 53 54 55
-1.678878e-11 -3.165826e-15 -4.359464e-13 1.018770e-12 -1.704088e-12
56 57 58 59 60
9.508747e-13 9.181292e-13 4.648996e-13 2.171177e-12 1.215631e-12
61 62 63 64 65
2.473086e-12 4.175786e-12 -1.084437e-11 1.044498e-12 -1.764557e-12
66 67 68 69 70
1.756709e-12 1.722437e-12 1.745404e-12 -3.411757e-13 2.151751e-12
71 72 73 74 75
2.805823e-12 1.849972e-12 3.143353e-12 8.667903e-13 -1.158427e-11
76 77 78 79 80
2.383529e-12 1.567064e-12 1.323334e-12 2.419560e-12 2.116661e-12
81 82 83 84 85
-3.297577e-13 8.001905e-13 1.733876e-12 1.754337e-12 3.763127e-12
86 87 88 89 90
2.485515e-12 -1.421635e-11 2.019849e-12 3.437729e-12 -7.616217e-13
91 92 93
3.174214e-12 -1.563424e-13 1.336380e-12
> postscript(file="/var/www/html/rcomp/tmp/6rak41258546716.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 = 93
Frequency = 1
lag(myerror, k = 1) myerror
0 -1.608597e-11 NA
1 -1.376058e-11 -1.608597e-11
2 1.068879e-10 -1.376058e-11
3 -6.397474e-12 1.068879e-10
4 -1.276148e-12 -6.397474e-12
5 -2.575780e-12 -1.276148e-12
6 -5.797745e-12 -2.575780e-12
7 -5.985644e-12 -5.797745e-12
8 -4.067262e-12 -5.985644e-12
9 -3.321806e-12 -4.067262e-12
10 -4.122048e-12 -3.321806e-12
11 -3.223862e-12 -4.122048e-12
12 -4.028610e-13 -3.223862e-12
13 -3.016388e-12 -4.028610e-13
14 -1.956389e-11 -3.016388e-12
15 -1.809069e-12 -1.956389e-11
16 -4.652573e-12 -1.809069e-12
17 -4.177070e-12 -4.652573e-12
18 -2.300974e-13 -4.177070e-12
19 -2.399461e-12 -2.300974e-13
20 -2.706549e-12 -2.399461e-12
21 -8.628738e-13 -2.706549e-12
22 -2.084510e-12 -8.628738e-13
23 -3.560463e-13 -2.084510e-12
24 2.742259e-13 -3.560463e-13
25 2.504091e-12 2.742259e-13
26 -1.740987e-11 2.504091e-12
27 2.356433e-13 -1.740987e-11
28 2.256382e-12 2.356433e-13
29 -2.230352e-13 2.256382e-12
30 -1.264298e-12 -2.230352e-13
31 3.665479e-14 -1.264298e-12
32 6.811054e-13 3.665479e-14
33 2.424732e-12 6.811054e-13
34 9.572479e-13 2.424732e-12
35 1.757437e-12 9.572479e-13
36 5.108813e-12 1.757437e-12
37 4.215124e-12 5.108813e-12
38 -1.648033e-11 4.215124e-12
39 2.526189e-12 -1.648033e-11
40 8.680475e-13 2.526189e-12
41 3.638694e-12 8.680475e-13
42 1.680018e-12 3.638694e-12
43 3.691852e-12 1.680018e-12
44 4.509130e-12 3.691852e-12
45 -1.656893e-12 4.509130e-12
46 -1.461566e-12 -1.656893e-12
47 -2.997467e-12 -1.461566e-12
48 1.726230e-12 -2.997467e-12
49 2.529664e-12 1.726230e-12
50 -1.678878e-11 2.529664e-12
51 -3.165826e-15 -1.678878e-11
52 -4.359464e-13 -3.165826e-15
53 1.018770e-12 -4.359464e-13
54 -1.704088e-12 1.018770e-12
55 9.508747e-13 -1.704088e-12
56 9.181292e-13 9.508747e-13
57 4.648996e-13 9.181292e-13
58 2.171177e-12 4.648996e-13
59 1.215631e-12 2.171177e-12
60 2.473086e-12 1.215631e-12
61 4.175786e-12 2.473086e-12
62 -1.084437e-11 4.175786e-12
63 1.044498e-12 -1.084437e-11
64 -1.764557e-12 1.044498e-12
65 1.756709e-12 -1.764557e-12
66 1.722437e-12 1.756709e-12
67 1.745404e-12 1.722437e-12
68 -3.411757e-13 1.745404e-12
69 2.151751e-12 -3.411757e-13
70 2.805823e-12 2.151751e-12
71 1.849972e-12 2.805823e-12
72 3.143353e-12 1.849972e-12
73 8.667903e-13 3.143353e-12
74 -1.158427e-11 8.667903e-13
75 2.383529e-12 -1.158427e-11
76 1.567064e-12 2.383529e-12
77 1.323334e-12 1.567064e-12
78 2.419560e-12 1.323334e-12
79 2.116661e-12 2.419560e-12
80 -3.297577e-13 2.116661e-12
81 8.001905e-13 -3.297577e-13
82 1.733876e-12 8.001905e-13
83 1.754337e-12 1.733876e-12
84 3.763127e-12 1.754337e-12
85 2.485515e-12 3.763127e-12
86 -1.421635e-11 2.485515e-12
87 2.019849e-12 -1.421635e-11
88 3.437729e-12 2.019849e-12
89 -7.616217e-13 3.437729e-12
90 3.174214e-12 -7.616217e-13
91 -1.563424e-13 3.174214e-12
92 1.336380e-12 -1.563424e-13
93 NA 1.336380e-12
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -1.376058e-11 -1.608597e-11
[2,] 1.068879e-10 -1.376058e-11
[3,] -6.397474e-12 1.068879e-10
[4,] -1.276148e-12 -6.397474e-12
[5,] -2.575780e-12 -1.276148e-12
[6,] -5.797745e-12 -2.575780e-12
[7,] -5.985644e-12 -5.797745e-12
[8,] -4.067262e-12 -5.985644e-12
[9,] -3.321806e-12 -4.067262e-12
[10,] -4.122048e-12 -3.321806e-12
[11,] -3.223862e-12 -4.122048e-12
[12,] -4.028610e-13 -3.223862e-12
[13,] -3.016388e-12 -4.028610e-13
[14,] -1.956389e-11 -3.016388e-12
[15,] -1.809069e-12 -1.956389e-11
[16,] -4.652573e-12 -1.809069e-12
[17,] -4.177070e-12 -4.652573e-12
[18,] -2.300974e-13 -4.177070e-12
[19,] -2.399461e-12 -2.300974e-13
[20,] -2.706549e-12 -2.399461e-12
[21,] -8.628738e-13 -2.706549e-12
[22,] -2.084510e-12 -8.628738e-13
[23,] -3.560463e-13 -2.084510e-12
[24,] 2.742259e-13 -3.560463e-13
[25,] 2.504091e-12 2.742259e-13
[26,] -1.740987e-11 2.504091e-12
[27,] 2.356433e-13 -1.740987e-11
[28,] 2.256382e-12 2.356433e-13
[29,] -2.230352e-13 2.256382e-12
[30,] -1.264298e-12 -2.230352e-13
[31,] 3.665479e-14 -1.264298e-12
[32,] 6.811054e-13 3.665479e-14
[33,] 2.424732e-12 6.811054e-13
[34,] 9.572479e-13 2.424732e-12
[35,] 1.757437e-12 9.572479e-13
[36,] 5.108813e-12 1.757437e-12
[37,] 4.215124e-12 5.108813e-12
[38,] -1.648033e-11 4.215124e-12
[39,] 2.526189e-12 -1.648033e-11
[40,] 8.680475e-13 2.526189e-12
[41,] 3.638694e-12 8.680475e-13
[42,] 1.680018e-12 3.638694e-12
[43,] 3.691852e-12 1.680018e-12
[44,] 4.509130e-12 3.691852e-12
[45,] -1.656893e-12 4.509130e-12
[46,] -1.461566e-12 -1.656893e-12
[47,] -2.997467e-12 -1.461566e-12
[48,] 1.726230e-12 -2.997467e-12
[49,] 2.529664e-12 1.726230e-12
[50,] -1.678878e-11 2.529664e-12
[51,] -3.165826e-15 -1.678878e-11
[52,] -4.359464e-13 -3.165826e-15
[53,] 1.018770e-12 -4.359464e-13
[54,] -1.704088e-12 1.018770e-12
[55,] 9.508747e-13 -1.704088e-12
[56,] 9.181292e-13 9.508747e-13
[57,] 4.648996e-13 9.181292e-13
[58,] 2.171177e-12 4.648996e-13
[59,] 1.215631e-12 2.171177e-12
[60,] 2.473086e-12 1.215631e-12
[61,] 4.175786e-12 2.473086e-12
[62,] -1.084437e-11 4.175786e-12
[63,] 1.044498e-12 -1.084437e-11
[64,] -1.764557e-12 1.044498e-12
[65,] 1.756709e-12 -1.764557e-12
[66,] 1.722437e-12 1.756709e-12
[67,] 1.745404e-12 1.722437e-12
[68,] -3.411757e-13 1.745404e-12
[69,] 2.151751e-12 -3.411757e-13
[70,] 2.805823e-12 2.151751e-12
[71,] 1.849972e-12 2.805823e-12
[72,] 3.143353e-12 1.849972e-12
[73,] 8.667903e-13 3.143353e-12
[74,] -1.158427e-11 8.667903e-13
[75,] 2.383529e-12 -1.158427e-11
[76,] 1.567064e-12 2.383529e-12
[77,] 1.323334e-12 1.567064e-12
[78,] 2.419560e-12 1.323334e-12
[79,] 2.116661e-12 2.419560e-12
[80,] -3.297577e-13 2.116661e-12
[81,] 8.001905e-13 -3.297577e-13
[82,] 1.733876e-12 8.001905e-13
[83,] 1.754337e-12 1.733876e-12
[84,] 3.763127e-12 1.754337e-12
[85,] 2.485515e-12 3.763127e-12
[86,] -1.421635e-11 2.485515e-12
[87,] 2.019849e-12 -1.421635e-11
[88,] 3.437729e-12 2.019849e-12
[89,] -7.616217e-13 3.437729e-12
[90,] 3.174214e-12 -7.616217e-13
[91,] -1.563424e-13 3.174214e-12
[92,] 1.336380e-12 -1.563424e-13
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -1.376058e-11 -1.608597e-11
2 1.068879e-10 -1.376058e-11
3 -6.397474e-12 1.068879e-10
4 -1.276148e-12 -6.397474e-12
5 -2.575780e-12 -1.276148e-12
6 -5.797745e-12 -2.575780e-12
7 -5.985644e-12 -5.797745e-12
8 -4.067262e-12 -5.985644e-12
9 -3.321806e-12 -4.067262e-12
10 -4.122048e-12 -3.321806e-12
11 -3.223862e-12 -4.122048e-12
12 -4.028610e-13 -3.223862e-12
13 -3.016388e-12 -4.028610e-13
14 -1.956389e-11 -3.016388e-12
15 -1.809069e-12 -1.956389e-11
16 -4.652573e-12 -1.809069e-12
17 -4.177070e-12 -4.652573e-12
18 -2.300974e-13 -4.177070e-12
19 -2.399461e-12 -2.300974e-13
20 -2.706549e-12 -2.399461e-12
21 -8.628738e-13 -2.706549e-12
22 -2.084510e-12 -8.628738e-13
23 -3.560463e-13 -2.084510e-12
24 2.742259e-13 -3.560463e-13
25 2.504091e-12 2.742259e-13
26 -1.740987e-11 2.504091e-12
27 2.356433e-13 -1.740987e-11
28 2.256382e-12 2.356433e-13
29 -2.230352e-13 2.256382e-12
30 -1.264298e-12 -2.230352e-13
31 3.665479e-14 -1.264298e-12
32 6.811054e-13 3.665479e-14
33 2.424732e-12 6.811054e-13
34 9.572479e-13 2.424732e-12
35 1.757437e-12 9.572479e-13
36 5.108813e-12 1.757437e-12
37 4.215124e-12 5.108813e-12
38 -1.648033e-11 4.215124e-12
39 2.526189e-12 -1.648033e-11
40 8.680475e-13 2.526189e-12
41 3.638694e-12 8.680475e-13
42 1.680018e-12 3.638694e-12
43 3.691852e-12 1.680018e-12
44 4.509130e-12 3.691852e-12
45 -1.656893e-12 4.509130e-12
46 -1.461566e-12 -1.656893e-12
47 -2.997467e-12 -1.461566e-12
48 1.726230e-12 -2.997467e-12
49 2.529664e-12 1.726230e-12
50 -1.678878e-11 2.529664e-12
51 -3.165826e-15 -1.678878e-11
52 -4.359464e-13 -3.165826e-15
53 1.018770e-12 -4.359464e-13
54 -1.704088e-12 1.018770e-12
55 9.508747e-13 -1.704088e-12
56 9.181292e-13 9.508747e-13
57 4.648996e-13 9.181292e-13
58 2.171177e-12 4.648996e-13
59 1.215631e-12 2.171177e-12
60 2.473086e-12 1.215631e-12
61 4.175786e-12 2.473086e-12
62 -1.084437e-11 4.175786e-12
63 1.044498e-12 -1.084437e-11
64 -1.764557e-12 1.044498e-12
65 1.756709e-12 -1.764557e-12
66 1.722437e-12 1.756709e-12
67 1.745404e-12 1.722437e-12
68 -3.411757e-13 1.745404e-12
69 2.151751e-12 -3.411757e-13
70 2.805823e-12 2.151751e-12
71 1.849972e-12 2.805823e-12
72 3.143353e-12 1.849972e-12
73 8.667903e-13 3.143353e-12
74 -1.158427e-11 8.667903e-13
75 2.383529e-12 -1.158427e-11
76 1.567064e-12 2.383529e-12
77 1.323334e-12 1.567064e-12
78 2.419560e-12 1.323334e-12
79 2.116661e-12 2.419560e-12
80 -3.297577e-13 2.116661e-12
81 8.001905e-13 -3.297577e-13
82 1.733876e-12 8.001905e-13
83 1.754337e-12 1.733876e-12
84 3.763127e-12 1.754337e-12
85 2.485515e-12 3.763127e-12
86 -1.421635e-11 2.485515e-12
87 2.019849e-12 -1.421635e-11
88 3.437729e-12 2.019849e-12
89 -7.616217e-13 3.437729e-12
90 3.174214e-12 -7.616217e-13
91 -1.563424e-13 3.174214e-12
92 1.336380e-12 -1.563424e-13
> 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/782zy1258546716.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/88pxo1258546716.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9kw6m1258546716.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/101mcd1258546716.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11a3v01258546716.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/12wjzu1258546716.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/13s1ys1258546716.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/14j7jv1258546716.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/15c8pp1258546716.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/167ptw1258546716.tab")
+ }
>
> system("convert tmp/13ewq1258546716.ps tmp/13ewq1258546716.png")
> system("convert tmp/2apc01258546716.ps tmp/2apc01258546716.png")
> system("convert tmp/3qfrw1258546716.ps tmp/3qfrw1258546716.png")
> system("convert tmp/4yevk1258546716.ps tmp/4yevk1258546716.png")
> system("convert tmp/5o23v1258546716.ps tmp/5o23v1258546716.png")
> system("convert tmp/6rak41258546716.ps tmp/6rak41258546716.png")
> system("convert tmp/782zy1258546716.ps tmp/782zy1258546716.png")
> system("convert tmp/88pxo1258546716.ps tmp/88pxo1258546716.png")
> system("convert tmp/9kw6m1258546716.ps tmp/9kw6m1258546716.png")
> system("convert tmp/101mcd1258546716.ps tmp/101mcd1258546716.png")
>
>
> proc.time()
user system elapsed
2.928 1.614 3.779