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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'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> x <- array(list(106370
+ ,100.3
+ ,123297
+ ,116476
+ ,109375
+ ,106370
+ ,109375
+ ,101.9
+ ,106370
+ ,123297
+ ,116476
+ ,109375
+ ,116476
+ ,102.1
+ ,109375
+ ,106370
+ ,123297
+ ,116476
+ ,123297
+ ,103.2
+ ,116476
+ ,109375
+ ,106370
+ ,123297
+ ,114813
+ ,103.7
+ ,123297
+ ,116476
+ ,109375
+ ,106370
+ ,117925
+ ,106.2
+ ,114813
+ ,123297
+ ,116476
+ ,109375
+ ,126466
+ ,107.7
+ ,117925
+ ,114813
+ ,123297
+ ,116476
+ ,131235
+ ,109.9
+ ,126466
+ ,117925
+ ,114813
+ ,123297
+ ,120546
+ ,111.7
+ ,131235
+ ,126466
+ ,117925
+ ,114813
+ ,123791
+ ,114.9
+ ,120546
+ ,131235
+ ,126466
+ ,117925
+ ,129813
+ ,116
+ ,123791
+ ,120546
+ ,131235
+ ,126466
+ ,133463
+ ,118.3
+ ,129813
+ ,123791
+ ,120546
+ ,131235
+ ,122987
+ ,120.4
+ ,133463
+ ,129813
+ ,123791
+ ,120546
+ ,125418
+ ,126
+ ,122987
+ ,133463
+ ,129813
+ ,123791
+ ,130199
+ ,128.1
+ ,125418
+ ,122987
+ ,133463
+ ,129813
+ ,133016
+ ,130.1
+ ,130199
+ ,125418
+ ,122987
+ ,133463
+ ,121454
+ ,130.8
+ ,133016
+ ,130199
+ ,125418
+ ,122987
+ ,122044
+ ,133.6
+ ,121454
+ ,133016
+ ,130199
+ ,125418
+ ,128313
+ ,134.2
+ ,122044
+ ,121454
+ ,133016
+ ,130199
+ ,131556
+ ,135.5
+ ,128313
+ ,122044
+ ,121454
+ ,133016
+ ,120027
+ ,136.2
+ ,131556
+ ,128313
+ ,122044
+ ,121454
+ ,123001
+ ,139.1
+ ,120027
+ ,131556
+ ,128313
+ ,122044
+ ,130111
+ ,139
+ ,123001
+ ,120027
+ ,131556
+ ,128313
+ ,132524
+ ,139.6
+ ,130111
+ ,123001
+ ,120027
+ ,131556
+ ,123742
+ ,138.7
+ ,132524
+ ,130111
+ ,123001
+ ,120027
+ ,124931
+ ,140.9
+ ,123742
+ ,132524
+ ,130111
+ ,123001
+ ,133646
+ ,141.3
+ ,124931
+ ,123742
+ ,132524
+ ,130111
+ ,136557
+ ,141.8
+ ,133646
+ ,124931
+ ,123742
+ ,132524
+ ,127509
+ ,142
+ ,136557
+ ,133646
+ ,124931
+ ,123742
+ ,128945
+ ,144.5
+ ,127509
+ ,136557
+ ,133646
+ ,124931
+ ,137191
+ ,144.6
+ ,128945
+ ,127509
+ ,136557
+ ,133646
+ ,139716
+ ,145.5
+ ,137191
+ ,128945
+ ,127509
+ ,136557
+ ,129083
+ ,146.8
+ ,139716
+ ,137191
+ ,128945
+ ,127509
+ ,131604
+ ,149.5
+ ,129083
+ ,139716
+ ,137191
+ ,128945
+ ,139413
+ ,149.9
+ ,131604
+ ,129083
+ ,139716
+ ,137191
+ ,143125
+ ,150.1
+ ,139413
+ ,131604
+ ,129083
+ ,139716
+ ,133948
+ ,150.9
+ ,143125
+ ,139413
+ ,131604
+ ,129083
+ ,137116
+ ,152.8
+ ,133948
+ ,143125
+ ,139413
+ ,131604
+ ,144864
+ ,153.1
+ ,137116
+ ,133948
+ ,143125
+ ,139413
+ ,149277
+ ,154
+ ,144864
+ ,137116
+ ,133948
+ ,143125
+ ,138796
+ ,154.9
+ ,149277
+ ,144864
+ ,137116
+ ,133948
+ ,143258
+ ,156.9
+ ,138796
+ ,149277
+ ,144864
+ ,137116
+ ,150034
+ ,158.4
+ ,143258
+ ,138796
+ ,149277
+ ,144864
+ ,154708
+ ,159.7
+ ,150034
+ ,143258
+ ,138796
+ ,149277
+ ,144888
+ ,160.2
+ ,154708
+ ,150034
+ ,143258
+ ,138796
+ ,148762
+ ,163.2
+ ,144888
+ ,154708
+ ,150034
+ ,143258
+ ,156500
+ ,163.7
+ ,148762
+ ,144888
+ ,154708
+ ,150034
+ ,161088
+ ,164.4
+ ,156500
+ ,148762
+ ,144888
+ ,154708
+ ,152772
+ ,163.7
+ ,161088
+ ,156500
+ ,148762
+ ,144888
+ ,158011
+ ,165.5
+ ,152772
+ ,161088
+ ,156500
+ ,148762
+ ,163318
+ ,165.6
+ ,158011
+ ,152772
+ ,161088
+ ,156500
+ ,169969
+ ,166.8
+ ,163318
+ ,158011
+ ,152772
+ ,161088
+ ,162269
+ ,167.5
+ ,169969
+ ,163318
+ ,158011
+ ,152772
+ ,165765
+ ,170.6
+ ,162269
+ ,169969
+ ,163318
+ ,158011
+ ,170600
+ ,170.9
+ ,165765
+ ,162269
+ ,169969
+ ,163318
+ ,174681
+ ,172
+ ,170600
+ ,165765
+ ,162269
+ ,169969
+ ,166364
+ ,171.8
+ ,174681
+ ,170600
+ ,165765
+ ,162269
+ ,170240
+ ,173.9
+ ,166364
+ ,174681
+ ,170600
+ ,165765
+ ,176150
+ ,174
+ ,170240
+ ,166364
+ ,174681
+ ,170600
+ ,182056
+ ,173.8
+ ,176150
+ ,170240
+ ,166364
+ ,174681
+ ,172218
+ ,173.9
+ ,182056
+ ,176150
+ ,170240
+ ,166364
+ ,177856
+ ,176
+ ,172218
+ ,182056
+ ,176150
+ ,170240
+ ,182253
+ ,176.6
+ ,177856
+ ,172218
+ ,182056
+ ,176150
+ ,188090
+ ,178.2
+ ,182253
+ ,177856
+ ,172218
+ ,182056
+ ,176863
+ ,179.2
+ ,188090
+ ,182253
+ ,177856
+ ,172218
+ ,183273
+ ,181.3
+ ,176863
+ ,188090
+ ,182253
+ ,177856
+ ,187969
+ ,181.8
+ ,183273
+ ,176863
+ ,188090
+ ,182253
+ ,194650
+ ,182.9
+ ,187969
+ ,183273
+ ,176863
+ ,188090
+ ,183036
+ ,183.8
+ ,194650
+ ,187969
+ ,183273
+ ,176863
+ ,189516
+ ,186.3
+ ,183036
+ ,194650
+ ,187969
+ ,183273
+ ,193805
+ ,187.4
+ ,189516
+ ,183036
+ ,194650
+ ,187969
+ ,200499
+ ,189.2
+ ,193805
+ ,189516
+ ,183036
+ ,194650
+ ,188142
+ ,189.7
+ ,200499
+ ,193805
+ ,189516
+ ,183036
+ ,193732
+ ,191.9
+ ,188142
+ ,200499
+ ,193805
+ ,189516
+ ,197126
+ ,192.6
+ ,193732
+ ,188142
+ ,200499
+ ,193805
+ ,205140
+ ,193.7
+ ,197126
+ ,193732
+ ,188142
+ ,200499
+ ,191751
+ ,194.2
+ ,205140
+ ,197126
+ ,193732
+ ,188142
+ ,196700
+ ,197.6
+ ,191751
+ ,205140
+ ,197126
+ ,193732
+ ,199784
+ ,199.3
+ ,196700
+ ,191751
+ ,205140
+ ,197126
+ ,207360
+ ,201.4
+ ,199784
+ ,196700
+ ,191751
+ ,205140
+ ,196101
+ ,203
+ ,207360
+ ,199784
+ ,196700
+ ,191751
+ ,200824
+ ,206.3
+ ,196101
+ ,207360
+ ,199784
+ ,196700
+ ,205743
+ ,207.1
+ ,200824
+ ,196101
+ ,207360
+ ,199784
+ ,212489
+ ,209.8
+ ,205743
+ ,200824
+ ,196101
+ ,207360
+ ,200810
+ ,211.1
+ ,212489
+ ,205743
+ ,200824
+ ,196101
+ ,203683
+ ,215.3
+ ,200810
+ ,212489
+ ,205743
+ ,200824
+ ,207286
+ ,217.4
+ ,203683
+ ,200810
+ ,212489
+ ,205743
+ ,210910
+ ,215.5
+ ,207286
+ ,203683
+ ,200810
+ ,212489
+ ,194915
+ ,210.9
+ ,210910
+ ,207286
+ ,203683
+ ,200810
+ ,217920
+ ,212.6
+ ,194915
+ ,210910
+ ,207286
+ ,203683)
+ ,dim=c(6
+ ,90)
+ ,dimnames=list(c('Y'
+ ,'X'
+ ,'Y1'
+ ,'Y2'
+ ,'Y3'
+ ,'Y4')
+ ,1:90))
> y <- array(NA,dim=c(6,90),dimnames=list(c('Y','X','Y1','Y2','Y3','Y4'),1:90))
> 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
1 106370 100.3 123297 116476 109375 106370 1 0 0 0 0 0 0 0 0 0 0
2 109375 101.9 106370 123297 116476 109375 0 1 0 0 0 0 0 0 0 0 0
3 116476 102.1 109375 106370 123297 116476 0 0 1 0 0 0 0 0 0 0 0
4 123297 103.2 116476 109375 106370 123297 0 0 0 1 0 0 0 0 0 0 0
5 114813 103.7 123297 116476 109375 106370 0 0 0 0 1 0 0 0 0 0 0
6 117925 106.2 114813 123297 116476 109375 0 0 0 0 0 1 0 0 0 0 0
7 126466 107.7 117925 114813 123297 116476 0 0 0 0 0 0 1 0 0 0 0
8 131235 109.9 126466 117925 114813 123297 0 0 0 0 0 0 0 1 0 0 0
9 120546 111.7 131235 126466 117925 114813 0 0 0 0 0 0 0 0 1 0 0
10 123791 114.9 120546 131235 126466 117925 0 0 0 0 0 0 0 0 0 1 0
11 129813 116.0 123791 120546 131235 126466 0 0 0 0 0 0 0 0 0 0 1
12 133463 118.3 129813 123791 120546 131235 0 0 0 0 0 0 0 0 0 0 0
13 122987 120.4 133463 129813 123791 120546 1 0 0 0 0 0 0 0 0 0 0
14 125418 126.0 122987 133463 129813 123791 0 1 0 0 0 0 0 0 0 0 0
15 130199 128.1 125418 122987 133463 129813 0 0 1 0 0 0 0 0 0 0 0
16 133016 130.1 130199 125418 122987 133463 0 0 0 1 0 0 0 0 0 0 0
17 121454 130.8 133016 130199 125418 122987 0 0 0 0 1 0 0 0 0 0 0
18 122044 133.6 121454 133016 130199 125418 0 0 0 0 0 1 0 0 0 0 0
19 128313 134.2 122044 121454 133016 130199 0 0 0 0 0 0 1 0 0 0 0
20 131556 135.5 128313 122044 121454 133016 0 0 0 0 0 0 0 1 0 0 0
21 120027 136.2 131556 128313 122044 121454 0 0 0 0 0 0 0 0 1 0 0
22 123001 139.1 120027 131556 128313 122044 0 0 0 0 0 0 0 0 0 1 0
23 130111 139.0 123001 120027 131556 128313 0 0 0 0 0 0 0 0 0 0 1
24 132524 139.6 130111 123001 120027 131556 0 0 0 0 0 0 0 0 0 0 0
25 123742 138.7 132524 130111 123001 120027 1 0 0 0 0 0 0 0 0 0 0
26 124931 140.9 123742 132524 130111 123001 0 1 0 0 0 0 0 0 0 0 0
27 133646 141.3 124931 123742 132524 130111 0 0 1 0 0 0 0 0 0 0 0
28 136557 141.8 133646 124931 123742 132524 0 0 0 1 0 0 0 0 0 0 0
29 127509 142.0 136557 133646 124931 123742 0 0 0 0 1 0 0 0 0 0 0
30 128945 144.5 127509 136557 133646 124931 0 0 0 0 0 1 0 0 0 0 0
31 137191 144.6 128945 127509 136557 133646 0 0 0 0 0 0 1 0 0 0 0
32 139716 145.5 137191 128945 127509 136557 0 0 0 0 0 0 0 1 0 0 0
33 129083 146.8 139716 137191 128945 127509 0 0 0 0 0 0 0 0 1 0 0
34 131604 149.5 129083 139716 137191 128945 0 0 0 0 0 0 0 0 0 1 0
35 139413 149.9 131604 129083 139716 137191 0 0 0 0 0 0 0 0 0 0 1
36 143125 150.1 139413 131604 129083 139716 0 0 0 0 0 0 0 0 0 0 0
37 133948 150.9 143125 139413 131604 129083 1 0 0 0 0 0 0 0 0 0 0
38 137116 152.8 133948 143125 139413 131604 0 1 0 0 0 0 0 0 0 0 0
39 144864 153.1 137116 133948 143125 139413 0 0 1 0 0 0 0 0 0 0 0
40 149277 154.0 144864 137116 133948 143125 0 0 0 1 0 0 0 0 0 0 0
41 138796 154.9 149277 144864 137116 133948 0 0 0 0 1 0 0 0 0 0 0
42 143258 156.9 138796 149277 144864 137116 0 0 0 0 0 1 0 0 0 0 0
43 150034 158.4 143258 138796 149277 144864 0 0 0 0 0 0 1 0 0 0 0
44 154708 159.7 150034 143258 138796 149277 0 0 0 0 0 0 0 1 0 0 0
45 144888 160.2 154708 150034 143258 138796 0 0 0 0 0 0 0 0 1 0 0
46 148762 163.2 144888 154708 150034 143258 0 0 0 0 0 0 0 0 0 1 0
47 156500 163.7 148762 144888 154708 150034 0 0 0 0 0 0 0 0 0 0 1
48 161088 164.4 156500 148762 144888 154708 0 0 0 0 0 0 0 0 0 0 0
49 152772 163.7 161088 156500 148762 144888 1 0 0 0 0 0 0 0 0 0 0
50 158011 165.5 152772 161088 156500 148762 0 1 0 0 0 0 0 0 0 0 0
51 163318 165.6 158011 152772 161088 156500 0 0 1 0 0 0 0 0 0 0 0
52 169969 166.8 163318 158011 152772 161088 0 0 0 1 0 0 0 0 0 0 0
53 162269 167.5 169969 163318 158011 152772 0 0 0 0 1 0 0 0 0 0 0
54 165765 170.6 162269 169969 163318 158011 0 0 0 0 0 1 0 0 0 0 0
55 170600 170.9 165765 162269 169969 163318 0 0 0 0 0 0 1 0 0 0 0
56 174681 172.0 170600 165765 162269 169969 0 0 0 0 0 0 0 1 0 0 0
57 166364 171.8 174681 170600 165765 162269 0 0 0 0 0 0 0 0 1 0 0
58 170240 173.9 166364 174681 170600 165765 0 0 0 0 0 0 0 0 0 1 0
59 176150 174.0 170240 166364 174681 170600 0 0 0 0 0 0 0 0 0 0 1
60 182056 173.8 176150 170240 166364 174681 0 0 0 0 0 0 0 0 0 0 0
61 172218 173.9 182056 176150 170240 166364 1 0 0 0 0 0 0 0 0 0 0
62 177856 176.0 172218 182056 176150 170240 0 1 0 0 0 0 0 0 0 0 0
63 182253 176.6 177856 172218 182056 176150 0 0 1 0 0 0 0 0 0 0 0
64 188090 178.2 182253 177856 172218 182056 0 0 0 1 0 0 0 0 0 0 0
65 176863 179.2 188090 182253 177856 172218 0 0 0 0 1 0 0 0 0 0 0
66 183273 181.3 176863 188090 182253 177856 0 0 0 0 0 1 0 0 0 0 0
67 187969 181.8 183273 176863 188090 182253 0 0 0 0 0 0 1 0 0 0 0
68 194650 182.9 187969 183273 176863 188090 0 0 0 0 0 0 0 1 0 0 0
69 183036 183.8 194650 187969 183273 176863 0 0 0 0 0 0 0 0 1 0 0
70 189516 186.3 183036 194650 187969 183273 0 0 0 0 0 0 0 0 0 1 0
71 193805 187.4 189516 183036 194650 187969 0 0 0 0 0 0 0 0 0 0 1
72 200499 189.2 193805 189516 183036 194650 0 0 0 0 0 0 0 0 0 0 0
73 188142 189.7 200499 193805 189516 183036 1 0 0 0 0 0 0 0 0 0 0
74 193732 191.9 188142 200499 193805 189516 0 1 0 0 0 0 0 0 0 0 0
75 197126 192.6 193732 188142 200499 193805 0 0 1 0 0 0 0 0 0 0 0
76 205140 193.7 197126 193732 188142 200499 0 0 0 1 0 0 0 0 0 0 0
77 191751 194.2 205140 197126 193732 188142 0 0 0 0 1 0 0 0 0 0 0
78 196700 197.6 191751 205140 197126 193732 0 0 0 0 0 1 0 0 0 0 0
79 199784 199.3 196700 191751 205140 197126 0 0 0 0 0 0 1 0 0 0 0
80 207360 201.4 199784 196700 191751 205140 0 0 0 0 0 0 0 1 0 0 0
81 196101 203.0 207360 199784 196700 191751 0 0 0 0 0 0 0 0 1 0 0
82 200824 206.3 196101 207360 199784 196700 0 0 0 0 0 0 0 0 0 1 0
83 205743 207.1 200824 196101 207360 199784 0 0 0 0 0 0 0 0 0 0 1
84 212489 209.8 205743 200824 196101 207360 0 0 0 0 0 0 0 0 0 0 0
85 200810 211.1 212489 205743 200824 196101 1 0 0 0 0 0 0 0 0 0 0
86 203683 215.3 200810 212489 205743 200824 0 1 0 0 0 0 0 0 0 0 0
87 207286 217.4 203683 200810 212489 205743 0 0 1 0 0 0 0 0 0 0 0
88 210910 215.5 207286 203683 200810 212489 0 0 0 1 0 0 0 0 0 0 0
89 194915 210.9 210910 207286 203683 200810 0 0 0 0 1 0 0 0 0 0 0
90 217920 212.6 194915 210910 207286 203683 0 0 0 0 0 1 0 0 0 0 0
t
1 1
2 2
3 3
4 4
5 5
6 6
7 7
8 8
9 9
10 10
11 11
12 12
13 13
14 14
15 15
16 16
17 17
18 18
19 19
20 20
21 21
22 22
23 23
24 24
25 25
26 26
27 27
28 28
29 29
30 30
31 31
32 32
33 33
34 34
35 35
36 36
37 37
38 38
39 39
40 40
41 41
42 42
43 43
44 44
45 45
46 46
47 47
48 48
49 49
50 50
51 51
52 52
53 53
54 54
55 55
56 56
57 57
58 58
59 59
60 60
61 61
62 62
63 63
64 64
65 65
66 66
67 67
68 68
69 69
70 70
71 71
72 72
73 73
74 74
75 75
76 76
77 77
78 78
79 79
80 80
81 81
82 82
83 83
84 84
85 85
86 86
87 87
88 88
89 89
90 90
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X Y1 Y2 Y3 Y4
5.931e+04 -3.453e+02 2.139e-01 5.076e-01 -2.152e-01 3.256e-01
M1 M2 M3 M4 M5 M6
-1.111e+04 -7.270e+03 1.810e+03 -4.566e+02 -1.168e+04 -5.739e+03
M7 M8 M9 M10 M11 t
2.126e+03 -2.365e+02 -1.110e+04 -6.802e+03 2.588e+03 6.258e+02
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-7465.07 -642.99 -38.29 665.49 10979.70
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 5.931e+04 1.194e+04 4.966 4.44e-06 ***
X -3.453e+02 7.921e+01 -4.359 4.27e-05 ***
Y1 2.139e-01 1.595e-01 1.341 0.184215
Y2 5.076e-01 1.940e-01 2.617 0.010808 *
Y3 -2.152e-01 1.886e-01 -1.141 0.257633
Y4 3.256e-01 1.666e-01 1.954 0.054594 .
M1 -1.111e+04 2.850e+03 -3.897 0.000216 ***
M2 -7.270e+03 4.646e+03 -1.565 0.122032
M3 1.810e+03 3.337e+03 0.542 0.589281
M4 -4.566e+02 1.159e+03 -0.394 0.694668
M5 -1.168e+04 2.757e+03 -4.237 6.60e-05 ***
M6 -5.739e+03 4.555e+03 -1.260 0.211766
M7 2.126e+03 3.349e+03 0.635 0.527550
M8 -2.365e+02 1.191e+03 -0.199 0.843167
M9 -1.110e+04 2.810e+03 -3.948 0.000182 ***
M10 -6.802e+03 4.566e+03 -1.490 0.140660
M11 2.588e+03 3.265e+03 0.793 0.430570
t 6.258e+02 1.298e+02 4.821 7.73e-06 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 2217 on 72 degrees of freedom
Multiple R-squared: 0.9959, Adjusted R-squared: 0.9949
F-statistic: 1031 on 17 and 72 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,] 3.731561e-03 7.463121e-03 0.9962684
[2,] 6.790234e-04 1.358047e-03 0.9993210
[3,] 1.134339e-04 2.268679e-04 0.9998866
[4,] 1.656925e-02 3.313850e-02 0.9834308
[5,] 1.594203e-02 3.188406e-02 0.9840580
[6,] 1.933163e-01 3.866325e-01 0.8066837
[7,] 1.789412e-01 3.578824e-01 0.8210588
[8,] 2.160274e-01 4.320548e-01 0.7839726
[9,] 2.626029e-01 5.252058e-01 0.7373971
[10,] 2.132599e-01 4.265199e-01 0.7867401
[11,] 1.931560e-01 3.863119e-01 0.8068440
[12,] 1.971849e-01 3.943698e-01 0.8028151
[13,] 1.564257e-01 3.128515e-01 0.8435743
[14,] 1.203321e-01 2.406641e-01 0.8796679
[15,] 8.215557e-02 1.643111e-01 0.9178444
[16,] 5.533092e-02 1.106618e-01 0.9446691
[17,] 4.158077e-02 8.316153e-02 0.9584192
[18,] 2.852193e-02 5.704387e-02 0.9714781
[19,] 1.821856e-02 3.643713e-02 0.9817814
[20,] 1.094979e-02 2.189959e-02 0.9890502
[21,] 8.104075e-03 1.620815e-02 0.9918959
[22,] 9.343997e-03 1.868799e-02 0.9906560
[23,] 5.860510e-03 1.172102e-02 0.9941395
[24,] 3.371385e-03 6.742771e-03 0.9966286
[25,] 2.253743e-03 4.507487e-03 0.9977463
[26,] 1.558097e-03 3.116195e-03 0.9984419
[27,] 8.076363e-04 1.615273e-03 0.9991924
[28,] 5.073028e-04 1.014606e-03 0.9994927
[29,] 3.998619e-04 7.997238e-04 0.9996001
[30,] 2.932947e-04 5.865894e-04 0.9997067
[31,] 3.812604e-04 7.625207e-04 0.9996187
[32,] 1.900583e-04 3.801166e-04 0.9998099
[33,] 9.494291e-04 1.898858e-03 0.9990506
[34,] 4.780875e-04 9.561750e-04 0.9995219
[35,] 7.874043e-04 1.574809e-03 0.9992126
[36,] 5.795102e-04 1.159020e-03 0.9994205
[37,] 3.099553e-04 6.199106e-04 0.9996900
[38,] 1.649445e-04 3.298890e-04 0.9998351
[39,] 1.295776e-04 2.591553e-04 0.9998704
[40,] 1.927083e-04 3.854167e-04 0.9998073
[41,] 8.717572e-05 1.743514e-04 0.9999128
[42,] 6.346122e-05 1.269224e-04 0.9999365
[43,] 5.355030e-05 1.071006e-04 0.9999464
[44,] 3.041443e-05 6.082886e-05 0.9999696
[45,] 1.161168e-04 2.322336e-04 0.9998839
[46,] 1.580354e-04 3.160707e-04 0.9998420
[47,] 1.027526e-04 2.055053e-04 0.9998972
[48,] 7.980578e-05 1.596116e-04 0.9999202
[49,] 1.286645e-04 2.573291e-04 0.9998713
> postscript(file="/var/www/html/rcomp/tmp/10x0l1258927845.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2q2971258927845.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3z5w61258927845.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/49t6p1258927845.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/54ppd1258927845.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 = 90
Frequency = 1
1 2 3 4 5 6
-4419.223748 -4616.610659 -47.958825 -113.771367 3269.348635 -422.160438
7 8 9 10 11 12
2942.371542 2754.864822 997.524283 1118.245209 481.181164 99.510415
13 14 15 16 17 18
1171.525431 1700.548131 1122.803539 571.859178 756.061357 -2975.574279
19 20 21 22 23 24
-198.283918 184.849302 -853.225467 179.382891 1111.689227 -873.015660
25 26 27 28 29 30
784.721653 -514.360334 1040.369651 621.685454 311.635033 -2012.144782
31 32 33 34 35 36
-148.096938 -962.993697 -2384.261175 -1550.993676 -903.114699 -1219.950983
37 38 39 40 41 42
-392.072259 -92.656540 289.648622 205.528884 -571.856636 -1350.531318
43 44 45 46 47 48
245.022688 -301.571332 218.068712 -58.258525 792.142987 327.648949
49 50 51 52 53 54
1373.692507 2624.994738 -171.124155 1457.363696 4317.441708 22.289224
55 56 57 58 59 60
-666.030797 -1099.502745 680.097809 -28.614258 -1403.217464 46.005183
61 62 63 64 65 66
3.221228 1019.716277 -947.828439 -759.725412 -105.671831 -990.270993
67 68 69 70 71 72
-460.554494 -237.178041 -84.956936 355.329723 -573.874641 -177.004156
73 74 75 76 77 78
-312.686971 -367.458643 -1317.342577 315.428809 -511.887307 -3251.309003
79 80 81 82 83 84
-1714.428084 -338.468308 1426.752774 -15.091364 495.193427 1796.806253
85 86 87 88 89 90
1790.822159 245.827030 31.432184 -2298.369242 -7465.070959 10979.701589
> postscript(file="/var/www/html/rcomp/tmp/6uc6m1258927845.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 = 90
Frequency = 1
lag(myerror, k = 1) myerror
0 -4419.223748 NA
1 -4616.610659 -4419.223748
2 -47.958825 -4616.610659
3 -113.771367 -47.958825
4 3269.348635 -113.771367
5 -422.160438 3269.348635
6 2942.371542 -422.160438
7 2754.864822 2942.371542
8 997.524283 2754.864822
9 1118.245209 997.524283
10 481.181164 1118.245209
11 99.510415 481.181164
12 1171.525431 99.510415
13 1700.548131 1171.525431
14 1122.803539 1700.548131
15 571.859178 1122.803539
16 756.061357 571.859178
17 -2975.574279 756.061357
18 -198.283918 -2975.574279
19 184.849302 -198.283918
20 -853.225467 184.849302
21 179.382891 -853.225467
22 1111.689227 179.382891
23 -873.015660 1111.689227
24 784.721653 -873.015660
25 -514.360334 784.721653
26 1040.369651 -514.360334
27 621.685454 1040.369651
28 311.635033 621.685454
29 -2012.144782 311.635033
30 -148.096938 -2012.144782
31 -962.993697 -148.096938
32 -2384.261175 -962.993697
33 -1550.993676 -2384.261175
34 -903.114699 -1550.993676
35 -1219.950983 -903.114699
36 -392.072259 -1219.950983
37 -92.656540 -392.072259
38 289.648622 -92.656540
39 205.528884 289.648622
40 -571.856636 205.528884
41 -1350.531318 -571.856636
42 245.022688 -1350.531318
43 -301.571332 245.022688
44 218.068712 -301.571332
45 -58.258525 218.068712
46 792.142987 -58.258525
47 327.648949 792.142987
48 1373.692507 327.648949
49 2624.994738 1373.692507
50 -171.124155 2624.994738
51 1457.363696 -171.124155
52 4317.441708 1457.363696
53 22.289224 4317.441708
54 -666.030797 22.289224
55 -1099.502745 -666.030797
56 680.097809 -1099.502745
57 -28.614258 680.097809
58 -1403.217464 -28.614258
59 46.005183 -1403.217464
60 3.221228 46.005183
61 1019.716277 3.221228
62 -947.828439 1019.716277
63 -759.725412 -947.828439
64 -105.671831 -759.725412
65 -990.270993 -105.671831
66 -460.554494 -990.270993
67 -237.178041 -460.554494
68 -84.956936 -237.178041
69 355.329723 -84.956936
70 -573.874641 355.329723
71 -177.004156 -573.874641
72 -312.686971 -177.004156
73 -367.458643 -312.686971
74 -1317.342577 -367.458643
75 315.428809 -1317.342577
76 -511.887307 315.428809
77 -3251.309003 -511.887307
78 -1714.428084 -3251.309003
79 -338.468308 -1714.428084
80 1426.752774 -338.468308
81 -15.091364 1426.752774
82 495.193427 -15.091364
83 1796.806253 495.193427
84 1790.822159 1796.806253
85 245.827030 1790.822159
86 31.432184 245.827030
87 -2298.369242 31.432184
88 -7465.070959 -2298.369242
89 10979.701589 -7465.070959
90 NA 10979.701589
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -4616.610659 -4419.223748
[2,] -47.958825 -4616.610659
[3,] -113.771367 -47.958825
[4,] 3269.348635 -113.771367
[5,] -422.160438 3269.348635
[6,] 2942.371542 -422.160438
[7,] 2754.864822 2942.371542
[8,] 997.524283 2754.864822
[9,] 1118.245209 997.524283
[10,] 481.181164 1118.245209
[11,] 99.510415 481.181164
[12,] 1171.525431 99.510415
[13,] 1700.548131 1171.525431
[14,] 1122.803539 1700.548131
[15,] 571.859178 1122.803539
[16,] 756.061357 571.859178
[17,] -2975.574279 756.061357
[18,] -198.283918 -2975.574279
[19,] 184.849302 -198.283918
[20,] -853.225467 184.849302
[21,] 179.382891 -853.225467
[22,] 1111.689227 179.382891
[23,] -873.015660 1111.689227
[24,] 784.721653 -873.015660
[25,] -514.360334 784.721653
[26,] 1040.369651 -514.360334
[27,] 621.685454 1040.369651
[28,] 311.635033 621.685454
[29,] -2012.144782 311.635033
[30,] -148.096938 -2012.144782
[31,] -962.993697 -148.096938
[32,] -2384.261175 -962.993697
[33,] -1550.993676 -2384.261175
[34,] -903.114699 -1550.993676
[35,] -1219.950983 -903.114699
[36,] -392.072259 -1219.950983
[37,] -92.656540 -392.072259
[38,] 289.648622 -92.656540
[39,] 205.528884 289.648622
[40,] -571.856636 205.528884
[41,] -1350.531318 -571.856636
[42,] 245.022688 -1350.531318
[43,] -301.571332 245.022688
[44,] 218.068712 -301.571332
[45,] -58.258525 218.068712
[46,] 792.142987 -58.258525
[47,] 327.648949 792.142987
[48,] 1373.692507 327.648949
[49,] 2624.994738 1373.692507
[50,] -171.124155 2624.994738
[51,] 1457.363696 -171.124155
[52,] 4317.441708 1457.363696
[53,] 22.289224 4317.441708
[54,] -666.030797 22.289224
[55,] -1099.502745 -666.030797
[56,] 680.097809 -1099.502745
[57,] -28.614258 680.097809
[58,] -1403.217464 -28.614258
[59,] 46.005183 -1403.217464
[60,] 3.221228 46.005183
[61,] 1019.716277 3.221228
[62,] -947.828439 1019.716277
[63,] -759.725412 -947.828439
[64,] -105.671831 -759.725412
[65,] -990.270993 -105.671831
[66,] -460.554494 -990.270993
[67,] -237.178041 -460.554494
[68,] -84.956936 -237.178041
[69,] 355.329723 -84.956936
[70,] -573.874641 355.329723
[71,] -177.004156 -573.874641
[72,] -312.686971 -177.004156
[73,] -367.458643 -312.686971
[74,] -1317.342577 -367.458643
[75,] 315.428809 -1317.342577
[76,] -511.887307 315.428809
[77,] -3251.309003 -511.887307
[78,] -1714.428084 -3251.309003
[79,] -338.468308 -1714.428084
[80,] 1426.752774 -338.468308
[81,] -15.091364 1426.752774
[82,] 495.193427 -15.091364
[83,] 1796.806253 495.193427
[84,] 1790.822159 1796.806253
[85,] 245.827030 1790.822159
[86,] 31.432184 245.827030
[87,] -2298.369242 31.432184
[88,] -7465.070959 -2298.369242
[89,] 10979.701589 -7465.070959
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -4616.610659 -4419.223748
2 -47.958825 -4616.610659
3 -113.771367 -47.958825
4 3269.348635 -113.771367
5 -422.160438 3269.348635
6 2942.371542 -422.160438
7 2754.864822 2942.371542
8 997.524283 2754.864822
9 1118.245209 997.524283
10 481.181164 1118.245209
11 99.510415 481.181164
12 1171.525431 99.510415
13 1700.548131 1171.525431
14 1122.803539 1700.548131
15 571.859178 1122.803539
16 756.061357 571.859178
17 -2975.574279 756.061357
18 -198.283918 -2975.574279
19 184.849302 -198.283918
20 -853.225467 184.849302
21 179.382891 -853.225467
22 1111.689227 179.382891
23 -873.015660 1111.689227
24 784.721653 -873.015660
25 -514.360334 784.721653
26 1040.369651 -514.360334
27 621.685454 1040.369651
28 311.635033 621.685454
29 -2012.144782 311.635033
30 -148.096938 -2012.144782
31 -962.993697 -148.096938
32 -2384.261175 -962.993697
33 -1550.993676 -2384.261175
34 -903.114699 -1550.993676
35 -1219.950983 -903.114699
36 -392.072259 -1219.950983
37 -92.656540 -392.072259
38 289.648622 -92.656540
39 205.528884 289.648622
40 -571.856636 205.528884
41 -1350.531318 -571.856636
42 245.022688 -1350.531318
43 -301.571332 245.022688
44 218.068712 -301.571332
45 -58.258525 218.068712
46 792.142987 -58.258525
47 327.648949 792.142987
48 1373.692507 327.648949
49 2624.994738 1373.692507
50 -171.124155 2624.994738
51 1457.363696 -171.124155
52 4317.441708 1457.363696
53 22.289224 4317.441708
54 -666.030797 22.289224
55 -1099.502745 -666.030797
56 680.097809 -1099.502745
57 -28.614258 680.097809
58 -1403.217464 -28.614258
59 46.005183 -1403.217464
60 3.221228 46.005183
61 1019.716277 3.221228
62 -947.828439 1019.716277
63 -759.725412 -947.828439
64 -105.671831 -759.725412
65 -990.270993 -105.671831
66 -460.554494 -990.270993
67 -237.178041 -460.554494
68 -84.956936 -237.178041
69 355.329723 -84.956936
70 -573.874641 355.329723
71 -177.004156 -573.874641
72 -312.686971 -177.004156
73 -367.458643 -312.686971
74 -1317.342577 -367.458643
75 315.428809 -1317.342577
76 -511.887307 315.428809
77 -3251.309003 -511.887307
78 -1714.428084 -3251.309003
79 -338.468308 -1714.428084
80 1426.752774 -338.468308
81 -15.091364 1426.752774
82 495.193427 -15.091364
83 1796.806253 495.193427
84 1790.822159 1796.806253
85 245.827030 1790.822159
86 31.432184 245.827030
87 -2298.369242 31.432184
88 -7465.070959 -2298.369242
89 10979.701589 -7465.070959
> 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/78u1s1258927845.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8yg931258927845.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9bzbv1258927845.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10hhfy1258927845.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11y3n41258927845.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/12bvgq1258927845.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/13wugy1258927845.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/143wki1258927845.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/15njou1258927845.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/16dirn1258927845.tab")
+ }
>
> system("convert tmp/10x0l1258927845.ps tmp/10x0l1258927845.png")
> system("convert tmp/2q2971258927845.ps tmp/2q2971258927845.png")
> system("convert tmp/3z5w61258927845.ps tmp/3z5w61258927845.png")
> system("convert tmp/49t6p1258927845.ps tmp/49t6p1258927845.png")
> system("convert tmp/54ppd1258927845.ps tmp/54ppd1258927845.png")
> system("convert tmp/6uc6m1258927845.ps tmp/6uc6m1258927845.png")
> system("convert tmp/78u1s1258927845.ps tmp/78u1s1258927845.png")
> system("convert tmp/8yg931258927845.ps tmp/8yg931258927845.png")
> system("convert tmp/9bzbv1258927845.ps tmp/9bzbv1258927845.png")
> system("convert tmp/10hhfy1258927845.ps tmp/10hhfy1258927845.png")
>
>
> proc.time()
user system elapsed
2.785 1.610 3.394