R version 2.15.2 (2012-10-26) -- "Trick or Treat"
Copyright (C) 2012 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i686-pc-linux-gnu (32-bit)
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
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(109.08
+ ,119.73
+ ,101.52
+ ,112.47
+ ,104.49
+ ,104
+ ,109.55
+ ,90.14
+ ,101.33
+ ,109.47
+ ,108.81
+ ,108.99
+ ,110.4
+ ,119.77
+ ,101.61
+ ,114.97
+ ,104.62
+ ,104.03
+ ,111.69
+ ,89.96
+ ,101.3
+ ,109.47
+ ,108.81
+ ,109.1
+ ,111.03
+ ,119.77
+ ,101.65
+ ,115.65
+ ,104.76
+ ,104.1
+ ,110.76
+ ,89.97
+ ,102.39
+ ,109.47
+ ,109.74
+ ,109.2
+ ,112.05
+ ,119.78
+ ,101.66
+ ,117.44
+ ,104.88
+ ,104.36
+ ,110.78
+ ,89.98
+ ,101.69
+ ,109.47
+ ,109.57
+ ,109.68
+ ,112.28
+ ,119.78
+ ,101.56
+ ,120.13
+ ,105.09
+ ,103.6
+ ,110.76
+ ,90.1
+ ,103.75
+ ,109.47
+ ,110.44
+ ,110.02
+ ,112.8
+ ,119.78
+ ,101.75
+ ,122.87
+ ,105.31
+ ,103.69
+ ,112.38
+ ,90.13
+ ,102.99
+ ,109.47
+ ,111.2
+ ,110.32
+ ,114.17
+ ,121.28
+ ,101.83
+ ,123.67
+ ,105.48
+ ,103.78
+ ,112.86
+ ,89.6
+ ,100.8
+ ,109.47
+ ,111.44
+ ,110.64
+ ,114.92
+ ,122.44
+ ,101.98
+ ,125.68
+ ,105.71
+ ,103.27
+ ,114.74
+ ,89.6
+ ,102.21
+ ,109.47
+ ,111.83
+ ,110.87
+ ,114.65
+ ,122.72
+ ,102.06
+ ,127.68
+ ,105.87
+ ,103.29
+ ,116.21
+ ,89.61
+ ,102.45
+ ,109.47
+ ,112.87
+ ,110.96
+ ,115.49
+ ,122.75
+ ,102.07
+ ,128.41
+ ,105.94
+ ,103.3
+ ,116.86
+ ,89.22
+ ,102.49
+ ,109.47
+ ,115.07
+ ,111.85
+ ,114.67
+ ,122.8
+ ,102.1
+ ,127.03
+ ,106.14
+ ,103.47
+ ,114.51
+ ,89.6
+ ,102.4
+ ,109.47
+ ,115.35
+ ,111.94
+ ,114.71
+ ,122.81
+ ,102.42
+ ,128.57
+ ,106.49
+ ,103.27
+ ,114.11
+ ,88.9
+ ,102.99
+ ,109.47
+ ,113.81
+ ,112.11
+ ,115.15
+ ,122.83
+ ,102.91
+ ,127.54
+ ,106.79
+ ,103.3
+ ,112.12
+ ,89.6
+ ,103.19
+ ,111.29
+ ,114.66
+ ,112.42
+ ,115.03
+ ,122.83
+ ,103.14
+ ,126.27
+ ,107.02
+ ,103.38
+ ,108.9
+ ,89.47
+ ,103.35
+ ,111.29
+ ,114.51
+ ,112.62
+ ,115.07
+ ,122.83
+ ,103.23
+ ,125.69
+ ,107.14
+ ,103.38
+ ,106.62
+ ,89.73
+ ,104.44
+ ,111.29
+ ,115.11
+ ,112.63
+ ,116.46
+ ,122.84
+ ,103.23
+ ,125.8
+ ,107.31
+ ,105.22
+ ,105.95
+ ,88.53
+ ,103.42
+ ,111.29
+ ,114.54
+ ,113.25
+ ,116.37
+ ,122.85
+ ,102.91
+ ,124.36
+ ,107.67
+ ,105.29
+ ,107.03
+ ,90.09
+ ,105.81
+ ,111.29
+ ,115.39
+ ,113.73
+ ,116.2
+ ,123.61
+ ,103.11
+ ,121.18
+ ,108.03
+ ,104.85
+ ,107.1
+ ,90.09
+ ,104.25
+ ,111.29
+ ,115.65
+ ,114.17
+ ,116.5
+ ,124.74
+ ,103.14
+ ,121.08
+ ,108.27
+ ,104.99
+ ,108
+ ,90.28
+ ,103.78
+ ,111.29
+ ,116.46
+ ,114.27
+ ,116.38
+ ,125.1
+ ,103.26
+ ,119.98
+ ,108.41
+ ,104.61
+ ,108.24
+ ,89.69
+ ,104.53
+ ,111.29
+ ,116.18
+ ,114.49
+ ,115.44
+ ,125.29
+ ,103.3
+ ,117.58
+ ,108.56
+ ,104.6
+ ,109.72
+ ,89.69
+ ,105.01
+ ,111.29
+ ,116.63
+ ,114.69
+ ,114.96
+ ,125.45
+ ,103.32
+ ,117.29
+ ,108.62
+ ,103.53
+ ,109.53
+ ,89.67
+ ,104.83
+ ,111.29
+ ,118.84
+ ,114.63
+ ,114.48
+ ,125.51
+ ,103.44
+ ,119.02
+ ,108.83
+ ,103.48
+ ,110.64
+ ,89.66
+ ,104.55
+ ,111.29
+ ,118.77
+ ,114.74
+ ,114.3
+ ,125.55
+ ,103.54
+ ,117.76
+ ,109
+ ,103.54
+ ,110.03
+ ,89.56
+ ,105.16
+ ,111.29
+ ,117.83
+ ,114.94
+ ,114.66
+ ,125.57
+ ,103.98
+ ,118.06
+ ,109.21
+ ,103.52
+ ,109.38
+ ,89.6
+ ,105.06
+ ,116.29
+ ,117.66
+ ,114.78
+ ,114.97
+ ,125.81
+ ,104.24
+ ,118.76
+ ,109.45
+ ,103.5
+ ,110.62
+ ,86.62
+ ,105.2
+ ,116.29
+ ,117.36
+ ,114.83
+ ,114.79
+ ,127.41
+ ,104.29
+ ,119.04
+ ,109.59
+ ,103.5
+ ,110.57
+ ,86.98
+ ,105.87
+ ,116.29
+ ,118
+ ,114.91
+ ,116.16
+ ,127.75
+ ,104.29
+ ,120.34
+ ,109.57
+ ,103.83
+ ,111.52
+ ,86.71
+ ,105.41
+ ,116.29
+ ,117.34
+ ,114.84
+ ,116.52
+ ,127.76
+ ,103.98
+ ,120.74
+ ,109.75
+ ,103.2
+ ,111.47
+ ,86.6
+ ,107.89
+ ,116.29
+ ,118.04
+ ,115.13
+ ,117.14
+ ,127.8
+ ,103.98
+ ,122.26
+ ,110.01
+ ,103.24
+ ,112.97
+ ,86.58
+ ,106.06
+ ,116.29
+ ,118.17
+ ,115.45
+ ,117.27
+ ,128.23
+ ,103.89
+ ,123.41
+ ,110.09
+ ,103.11
+ ,114.24
+ ,86.79
+ ,105.5
+ ,116.29
+ ,118.82
+ ,115.5
+ ,117.58
+ ,130.01
+ ,103.86
+ ,124.12
+ ,110.25
+ ,103.13
+ ,114.97
+ ,86.08
+ ,106.71
+ ,116.29
+ ,119
+ ,115.61
+ ,117.21
+ ,130.07
+ ,103.88
+ ,124.29
+ ,110.28
+ ,103.15
+ ,114.82
+ ,87.48
+ ,106.34
+ ,116.29
+ ,118.89
+ ,116.3
+ ,117.08
+ ,130.17
+ ,103.88
+ ,124.02
+ ,110.26
+ ,103.03
+ ,114.61
+ ,87.4
+ ,106.11
+ ,116.29
+ ,121.4
+ ,116.48
+ ,117.06
+ ,130.21
+ ,104.31
+ ,124.35
+ ,110.38
+ ,103.06
+ ,114.68
+ ,87.51
+ ,106.15
+ ,116.29
+ ,121.01
+ ,116.46
+ ,117.55
+ ,130.22
+ ,104.41
+ ,125.56
+ ,110.37
+ ,103.11
+ ,114.9
+ ,87.58
+ ,106.61
+ ,116.29
+ ,120.21
+ ,116.77
+ ,117.61
+ ,130.23
+ ,104.8
+ ,125.99
+ ,110.5
+ ,103.11
+ ,115.05
+ ,87.59
+ ,106.63
+ ,115.72
+ ,120.39
+ ,117.02
+ ,117.74
+ ,130.23
+ ,104.89
+ ,126.35
+ ,110.51
+ ,103.12
+ ,115.67
+ ,87.62
+ ,106.27
+ ,115.72
+ ,120.09
+ ,117.19
+ ,117.87
+ ,130.23
+ ,104.9
+ ,127.53
+ ,110.71
+ ,103.12
+ ,117.17
+ ,88.35
+ ,105.59
+ ,115.72
+ ,120.76
+ ,117.34
+ ,118.59
+ ,130.23
+ ,104.9
+ ,128.42
+ ,110.62
+ ,103.28
+ ,118.17
+ ,88.67
+ ,107.09
+ ,115.72
+ ,120.33
+ ,118.15
+ ,119.09
+ ,130.24
+ ,104.54
+ ,130.11
+ ,110.81
+ ,103.44
+ ,118.61
+ ,87.81
+ ,108.53
+ ,115.72
+ ,120.84
+ ,118.94
+ ,118.93
+ ,130.13
+ ,104.67
+ ,132.15
+ ,110.97
+ ,103.37
+ ,120.38
+ ,87.81
+ ,108.01
+ ,115.72
+ ,121.49
+ ,119.17
+ ,119.62
+ ,130.14
+ ,104.87
+ ,132.91
+ ,111.06
+ ,103.15
+ ,121.27
+ ,87.86
+ ,106.52
+ ,115.72
+ ,122.29
+ ,119.33
+ ,120.09
+ ,130.79
+ ,105.04
+ ,133.84
+ ,111.33
+ ,103.21
+ ,121.55
+ ,87.86
+ ,107.27
+ ,115.72
+ ,121.91
+ ,119.5
+ ,120.38
+ ,131.38
+ ,105.09
+ ,135.52
+ ,111.55
+ ,103.22
+ ,121.08
+ ,87.86
+ ,107.58
+ ,115.72
+ ,122.46
+ ,119.58
+ ,120.49
+ ,131.61
+ ,105.1
+ ,135.29
+ ,111.67
+ ,103.32
+ ,121.01
+ ,87.51
+ ,107.36
+ ,115.72
+ ,124.94
+ ,119.79
+ ,120.02
+ ,131.72
+ ,105.46
+ ,135.13
+ ,111.72
+ ,103.34
+ ,121.15
+ ,87.5
+ ,107.23
+ ,115.72
+ ,124.6
+ ,119.91
+ ,120.17
+ ,131.89
+ ,105.83
+ ,136.43
+ ,112
+ ,103.34
+ ,121.84
+ ,86.72
+ ,107.54
+ ,115.72
+ ,123.09
+ ,120.35
+ ,120.58
+ ,131.89
+ ,106.27
+ ,136.29
+ ,112.42
+ ,103.3
+ ,121.83
+ ,86.74
+ ,107.64
+ ,119.24
+ ,123.25
+ ,120.69
+ ,121.54
+ ,131.96
+ ,106.46
+ ,137.32
+ ,112.84
+ ,103.29
+ ,121.86
+ ,86.74
+ ,108.23
+ ,119.24
+ ,123.01
+ ,121.01
+ ,121.52
+ ,131.99
+ ,106.52
+ ,137.3
+ ,112.99
+ ,103.35
+ ,121.56
+ ,86.76
+ ,108.42
+ ,119.24
+ ,123.82
+ ,121.14
+ ,121.81
+ ,132
+ ,106.53
+ ,138.38
+ ,113.11
+ ,104.02
+ ,122.81
+ ,90.75
+ ,109.33
+ ,119.24
+ ,123.31
+ ,123.78
+ ,122.85
+ ,132.06
+ ,105.96
+ ,139.39
+ ,113.51
+ ,104.07
+ ,123.24
+ ,90.21
+ ,111.3
+ ,119.24
+ ,124.04
+ ,123.95
+ ,122.97
+ ,132.11
+ ,106
+ ,140.03
+ ,113.42
+ ,104.23
+ ,124.52
+ ,90.2
+ ,110.52
+ ,119.24
+ ,124.15
+ ,124.25
+ ,122.96
+ ,132.88
+ ,106.15
+ ,140.05
+ ,113.6
+ ,103.96
+ ,125.03
+ ,89.34
+ ,109.86
+ ,119.24
+ ,125.37
+ ,124.3
+ ,123.4
+ ,135.48
+ ,106.32
+ ,139.47
+ ,113.65
+ ,103.81
+ ,123.56
+ ,89.35
+ ,110.94
+ ,119.24
+ ,125.41
+ ,124.7
+ ,123.23
+ ,136.56
+ ,106.41
+ ,138.31
+ ,113.76
+ ,103.38
+ ,122.58
+ ,88.94
+ ,111.35
+ ,119.24
+ ,126.06
+ ,124.73
+ ,123.24
+ ,136.96
+ ,106.41
+ ,138.5
+ ,113.74
+ ,103.29
+ ,122.95
+ ,88.94
+ ,111.01
+ ,119.24
+ ,128.17
+ ,125.02
+ ,123.72
+ ,137.4
+ ,106.81
+ ,139.31
+ ,114.02
+ ,103.24
+ ,124.73
+ ,88.77
+ ,110.84
+ ,119.24
+ ,128.16
+ ,125.24
+ ,123.99
+ ,138.32
+ ,106.99
+ ,139.66
+ ,114.08
+ ,103.26
+ ,125.75
+ ,88.72
+ ,110.79
+ ,119.24
+ ,126.69
+ ,125.67
+ ,125.1
+ ,138.82
+ ,107.35
+ ,139.63
+ ,114.29
+ ,103.4
+ ,125.16
+ ,89.25
+ ,110.87
+ ,119.79
+ ,126.75
+ ,125.84)
+ ,dim=c(12
+ ,61)
+ ,dimnames=list(c('VoedingsmiddelenEnDranken'
+ ,'Tabak'
+ ,'KledingEnSchoeisel'
+ ,'Huisvesting
+ ,water
+ ,elektriciteit
+ ,gas'
+ ,'StofferingEnOnderhoudVanWoning'
+ ,'Gezondheidsuitgaven'
+ ,'Vervoer'
+ ,'Communicatie'
+ ,'RecreatieEnCultuur'
+ ,'Onderwijs'
+ ,'Hotels
+ ,cafésEnRestaurants'
+ ,'DiverseGoederenEnDiensten')
+ ,1:61))
> y <- array(NA,dim=c(12,61),dimnames=list(c('VoedingsmiddelenEnDranken','Tabak','KledingEnSchoeisel','Huisvesting,water,elektriciteit,gas','StofferingEnOnderhoudVanWoning','Gezondheidsuitgaven','Vervoer','Communicatie','RecreatieEnCultuur','Onderwijs','Hotels,cafésEnRestaurants','DiverseGoederenEnDiensten'),1:61))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par3 = 'No Linear Trend'
> par2 = 'Do not include Seasonal Dummies'
> par1 = '7'
> par3 <- 'No Linear Trend'
> par2 <- 'Do not include Seasonal Dummies'
> par1 <- '7'
> #'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, 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
Vervoer VoedingsmiddelenEnDranken Tabak KledingEnSchoeisel
1 109.55 109.08 119.73 101.52
2 111.69 110.40 119.77 101.61
3 110.76 111.03 119.77 101.65
4 110.78 112.05 119.78 101.66
5 110.76 112.28 119.78 101.56
6 112.38 112.80 119.78 101.75
7 112.86 114.17 121.28 101.83
8 114.74 114.92 122.44 101.98
9 116.21 114.65 122.72 102.06
10 116.86 115.49 122.75 102.07
11 114.51 114.67 122.80 102.10
12 114.11 114.71 122.81 102.42
13 112.12 115.15 122.83 102.91
14 108.90 115.03 122.83 103.14
15 106.62 115.07 122.83 103.23
16 105.95 116.46 122.84 103.23
17 107.03 116.37 122.85 102.91
18 107.10 116.20 123.61 103.11
19 108.00 116.50 124.74 103.14
20 108.24 116.38 125.10 103.26
21 109.72 115.44 125.29 103.30
22 109.53 114.96 125.45 103.32
23 110.64 114.48 125.51 103.44
24 110.03 114.30 125.55 103.54
25 109.38 114.66 125.57 103.98
26 110.62 114.97 125.81 104.24
27 110.57 114.79 127.41 104.29
28 111.52 116.16 127.75 104.29
29 111.47 116.52 127.76 103.98
30 112.97 117.14 127.80 103.98
31 114.24 117.27 128.23 103.89
32 114.97 117.58 130.01 103.86
33 114.82 117.21 130.07 103.88
34 114.61 117.08 130.17 103.88
35 114.68 117.06 130.21 104.31
36 114.90 117.55 130.22 104.41
37 115.05 117.61 130.23 104.80
38 115.67 117.74 130.23 104.89
39 117.17 117.87 130.23 104.90
40 118.17 118.59 130.23 104.90
41 118.61 119.09 130.24 104.54
42 120.38 118.93 130.13 104.67
43 121.27 119.62 130.14 104.87
44 121.55 120.09 130.79 105.04
45 121.08 120.38 131.38 105.09
46 121.01 120.49 131.61 105.10
47 121.15 120.02 131.72 105.46
48 121.84 120.17 131.89 105.83
49 121.83 120.58 131.89 106.27
50 121.86 121.54 131.96 106.46
51 121.56 121.52 131.99 106.52
52 122.81 121.81 132.00 106.53
53 123.24 122.85 132.06 105.96
54 124.52 122.97 132.11 106.00
55 125.03 122.96 132.88 106.15
56 123.56 123.40 135.48 106.32
57 122.58 123.23 136.56 106.41
58 122.95 123.24 136.96 106.41
59 124.73 123.72 137.40 106.81
60 125.75 123.99 138.32 106.99
61 125.16 125.10 138.82 107.35
Huisvesting,water,elektriciteit,gas StofferingEnOnderhoudVanWoning
1 112.47 104.49
2 114.97 104.62
3 115.65 104.76
4 117.44 104.88
5 120.13 105.09
6 122.87 105.31
7 123.67 105.48
8 125.68 105.71
9 127.68 105.87
10 128.41 105.94
11 127.03 106.14
12 128.57 106.49
13 127.54 106.79
14 126.27 107.02
15 125.69 107.14
16 125.80 107.31
17 124.36 107.67
18 121.18 108.03
19 121.08 108.27
20 119.98 108.41
21 117.58 108.56
22 117.29 108.62
23 119.02 108.83
24 117.76 109.00
25 118.06 109.21
26 118.76 109.45
27 119.04 109.59
28 120.34 109.57
29 120.74 109.75
30 122.26 110.01
31 123.41 110.09
32 124.12 110.25
33 124.29 110.28
34 124.02 110.26
35 124.35 110.38
36 125.56 110.37
37 125.99 110.50
38 126.35 110.51
39 127.53 110.71
40 128.42 110.62
41 130.11 110.81
42 132.15 110.97
43 132.91 111.06
44 133.84 111.33
45 135.52 111.55
46 135.29 111.67
47 135.13 111.72
48 136.43 112.00
49 136.29 112.42
50 137.32 112.84
51 137.30 112.99
52 138.38 113.11
53 139.39 113.51
54 140.03 113.42
55 140.05 113.60
56 139.47 113.65
57 138.31 113.76
58 138.50 113.74
59 139.31 114.02
60 139.66 114.08
61 139.63 114.29
Gezondheidsuitgaven Communicatie RecreatieEnCultuur Onderwijs
1 104.00 90.14 101.33 109.47
2 104.03 89.96 101.30 109.47
3 104.10 89.97 102.39 109.47
4 104.36 89.98 101.69 109.47
5 103.60 90.10 103.75 109.47
6 103.69 90.13 102.99 109.47
7 103.78 89.60 100.80 109.47
8 103.27 89.60 102.21 109.47
9 103.29 89.61 102.45 109.47
10 103.30 89.22 102.49 109.47
11 103.47 89.60 102.40 109.47
12 103.27 88.90 102.99 109.47
13 103.30 89.60 103.19 111.29
14 103.38 89.47 103.35 111.29
15 103.38 89.73 104.44 111.29
16 105.22 88.53 103.42 111.29
17 105.29 90.09 105.81 111.29
18 104.85 90.09 104.25 111.29
19 104.99 90.28 103.78 111.29
20 104.61 89.69 104.53 111.29
21 104.60 89.69 105.01 111.29
22 103.53 89.67 104.83 111.29
23 103.48 89.66 104.55 111.29
24 103.54 89.56 105.16 111.29
25 103.52 89.60 105.06 116.29
26 103.50 86.62 105.20 116.29
27 103.50 86.98 105.87 116.29
28 103.83 86.71 105.41 116.29
29 103.20 86.60 107.89 116.29
30 103.24 86.58 106.06 116.29
31 103.11 86.79 105.50 116.29
32 103.13 86.08 106.71 116.29
33 103.15 87.48 106.34 116.29
34 103.03 87.40 106.11 116.29
35 103.06 87.51 106.15 116.29
36 103.11 87.58 106.61 116.29
37 103.11 87.59 106.63 115.72
38 103.12 87.62 106.27 115.72
39 103.12 88.35 105.59 115.72
40 103.28 88.67 107.09 115.72
41 103.44 87.81 108.53 115.72
42 103.37 87.81 108.01 115.72
43 103.15 87.86 106.52 115.72
44 103.21 87.86 107.27 115.72
45 103.22 87.86 107.58 115.72
46 103.32 87.51 107.36 115.72
47 103.34 87.50 107.23 115.72
48 103.34 86.72 107.54 115.72
49 103.30 86.74 107.64 119.24
50 103.29 86.74 108.23 119.24
51 103.35 86.76 108.42 119.24
52 104.02 90.75 109.33 119.24
53 104.07 90.21 111.30 119.24
54 104.23 90.20 110.52 119.24
55 103.96 89.34 109.86 119.24
56 103.81 89.35 110.94 119.24
57 103.38 88.94 111.35 119.24
58 103.29 88.94 111.01 119.24
59 103.24 88.77 110.84 119.24
60 103.26 88.72 110.79 119.24
61 103.40 89.25 110.87 119.79
Hotels,caf\303\251sEnRestaurants DiverseGoederenEnDiensten
1 108.81 108.99
2 108.81 109.10
3 109.74 109.20
4 109.57 109.68
5 110.44 110.02
6 111.20 110.32
7 111.44 110.64
8 111.83 110.87
9 112.87 110.96
10 115.07 111.85
11 115.35 111.94
12 113.81 112.11
13 114.66 112.42
14 114.51 112.62
15 115.11 112.63
16 114.54 113.25
17 115.39 113.73
18 115.65 114.17
19 116.46 114.27
20 116.18 114.49
21 116.63 114.69
22 118.84 114.63
23 118.77 114.74
24 117.83 114.94
25 117.66 114.78
26 117.36 114.83
27 118.00 114.91
28 117.34 114.84
29 118.04 115.13
30 118.17 115.45
31 118.82 115.50
32 119.00 115.61
33 118.89 116.30
34 121.40 116.48
35 121.01 116.46
36 120.21 116.77
37 120.39 117.02
38 120.09 117.19
39 120.76 117.34
40 120.33 118.15
41 120.84 118.94
42 121.49 119.17
43 122.29 119.33
44 121.91 119.50
45 122.46 119.58
46 124.94 119.79
47 124.60 119.91
48 123.09 120.35
49 123.25 120.69
50 123.01 121.01
51 123.82 121.14
52 123.31 123.78
53 124.04 123.95
54 124.15 124.25
55 125.37 124.30
56 125.41 124.70
57 126.06 124.73
58 128.17 125.02
59 128.16 125.24
60 126.69 125.67
61 126.75 125.84
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) VoedingsmiddelenEnDranken
571.9047 -1.4046
Tabak KledingEnSchoeisel
0.4843 -3.3689
`Huisvesting,water,elektriciteit,gas` StofferingEnOnderhoudVanWoning
0.5971 0.3673
Gezondheidsuitgaven Communicatie
-1.8058 -0.8124
RecreatieEnCultuur Onderwijs
-1.0326 0.1146
`Hotels,caf\\303\\251sEnRestaurants` DiverseGoederenEnDiensten
-0.8994 2.9465
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-3.6637 -0.7935 0.0757 0.8695 2.9223
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 571.9047 107.0647 5.342 2.37e-06 ***
VoedingsmiddelenEnDranken -1.4046 0.4491 -3.128 0.00296 **
Tabak 0.4843 0.2854 1.697 0.09599 .
KledingEnSchoeisel -3.3689 0.7848 -4.292 8.31e-05 ***
`Huisvesting,water,elektriciteit,gas` 0.5971 0.1361 4.388 6.07e-05 ***
StofferingEnOnderhoudVanWoning 0.3673 1.0278 0.357 0.72237
Gezondheidsuitgaven -1.8058 0.7107 -2.541 0.01428 *
Communicatie -0.8124 0.3640 -2.232 0.03021 *
RecreatieEnCultuur -1.0326 0.3171 -3.257 0.00205 **
Onderwijs 0.1146 0.2544 0.450 0.65445
`Hotels,caf\\303\\251sEnRestaurants` -0.8994 0.2659 -3.382 0.00142 **
DiverseGoederenEnDiensten 2.9465 0.6342 4.646 2.57e-05 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 1.492 on 49 degrees of freedom
Multiple R-squared: 0.9447, Adjusted R-squared: 0.9322
F-statistic: 76.05 on 11 and 49 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,] 0.4119543 0.8239085810 5.880457e-01
[2,] 0.4384809 0.8769618182 5.615191e-01
[3,] 0.9422396 0.1155208274 5.776041e-02
[4,] 0.9919224 0.0161552874 8.077644e-03
[5,] 0.9914087 0.0171825523 8.591276e-03
[6,] 0.9998028 0.0003943259 1.971629e-04
[7,] 0.9999125 0.0001750555 8.752777e-05
[8,] 0.9998520 0.0002960942 1.480471e-04
[9,] 0.9997102 0.0005796707 2.898353e-04
[10,] 0.9994399 0.0011202893 5.601447e-04
[11,] 0.9991601 0.0016798696 8.399348e-04
[12,] 0.9983921 0.0032157235 1.607862e-03
[13,] 0.9983250 0.0033499439 1.674972e-03
[14,] 0.9968549 0.0062902302 3.145115e-03
[15,] 0.9978224 0.0043551398 2.177570e-03
[16,] 0.9984346 0.0031307937 1.565397e-03
[17,] 0.9988614 0.0022772388 1.138619e-03
[18,] 0.9992112 0.0015775770 7.887885e-04
[19,] 0.9985130 0.0029740839 1.487042e-03
[20,] 0.9978589 0.0042822957 2.141148e-03
[21,] 0.9967607 0.0064786838 3.239342e-03
[22,] 0.9951764 0.0096472061 4.823603e-03
[23,] 0.9955853 0.0088294473 4.414724e-03
[24,] 0.9971201 0.0057598808 2.879940e-03
[25,] 0.9967836 0.0064328575 3.216429e-03
[26,] 0.9958414 0.0083172192 4.158610e-03
[27,] 0.9906768 0.0186464545 9.323227e-03
[28,] 0.9922014 0.0155971526 7.798576e-03
[29,] 0.9835303 0.0329394456 1.646972e-02
[30,] 0.9727263 0.0545474071 2.727370e-02
[31,] 0.9401322 0.1197356191 5.986781e-02
[32,] 0.8940090 0.2119820629 1.059910e-01
> postscript(file="/var/fisher/rcomp/tmp/1fkt71353080960.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
> points(x[,1]-mysum$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/2nrxw1353080960.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/3xiqq1353080960.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/4kmxa1353080960.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/563kz1353080960.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
> qqline(mysum$resid)
> grid()
> dev.off()
null device
1
> (myerror <- as.ts(mysum$resid))
Time Series:
Start = 1
End = 61
Frequency = 1
1 2 3 4 5 6
-0.80192388 1.48827458 2.92233897 1.47854510 0.39427764 0.86952142
7 8 9 10 11 12
-0.97985569 0.82052305 1.75441923 2.24060571 0.07566394 -2.44959768
13 14 15 16 17 18
-1.20374072 -3.66371453 -3.43511925 -3.33060831 0.47964176 -1.08494180
19 20 21 22 23 24
0.11745026 -0.26689663 1.60653446 0.91338101 -0.16038337 -0.79345667
25 26 27 28 29 30
-0.08263609 -0.88333206 -0.68704416 0.76789875 0.97838006 -0.33295321
31 32 33 34 35 36
-0.31304533 -0.04694424 -2.13144787 -1.19605048 -0.07300229 -0.56228169
37 38 39 40 41 42
0.19585236 -0.01701959 0.97268366 1.81008803 -0.13594784 -0.13281435
43 44 45 46 47 48
0.26119172 0.84492210 0.17809591 1.55890082 1.50982021 -0.27250144
49 50 51 52 53 54
0.49111362 1.13888950 1.62149848 -0.22756952 0.80541297 0.70574158
55 56 57 58 59 60
0.33816398 -1.16252623 -2.13894785 -1.52516557 0.41581003 -0.90036731
61
1.23619473
> postscript(file="/var/fisher/rcomp/tmp/6jbqb1353080960.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> dum <- cbind(lag(myerror,k=1),myerror)
> dum
Time Series:
Start = 0
End = 61
Frequency = 1
lag(myerror, k = 1) myerror
0 -0.80192388 NA
1 1.48827458 -0.80192388
2 2.92233897 1.48827458
3 1.47854510 2.92233897
4 0.39427764 1.47854510
5 0.86952142 0.39427764
6 -0.97985569 0.86952142
7 0.82052305 -0.97985569
8 1.75441923 0.82052305
9 2.24060571 1.75441923
10 0.07566394 2.24060571
11 -2.44959768 0.07566394
12 -1.20374072 -2.44959768
13 -3.66371453 -1.20374072
14 -3.43511925 -3.66371453
15 -3.33060831 -3.43511925
16 0.47964176 -3.33060831
17 -1.08494180 0.47964176
18 0.11745026 -1.08494180
19 -0.26689663 0.11745026
20 1.60653446 -0.26689663
21 0.91338101 1.60653446
22 -0.16038337 0.91338101
23 -0.79345667 -0.16038337
24 -0.08263609 -0.79345667
25 -0.88333206 -0.08263609
26 -0.68704416 -0.88333206
27 0.76789875 -0.68704416
28 0.97838006 0.76789875
29 -0.33295321 0.97838006
30 -0.31304533 -0.33295321
31 -0.04694424 -0.31304533
32 -2.13144787 -0.04694424
33 -1.19605048 -2.13144787
34 -0.07300229 -1.19605048
35 -0.56228169 -0.07300229
36 0.19585236 -0.56228169
37 -0.01701959 0.19585236
38 0.97268366 -0.01701959
39 1.81008803 0.97268366
40 -0.13594784 1.81008803
41 -0.13281435 -0.13594784
42 0.26119172 -0.13281435
43 0.84492210 0.26119172
44 0.17809591 0.84492210
45 1.55890082 0.17809591
46 1.50982021 1.55890082
47 -0.27250144 1.50982021
48 0.49111362 -0.27250144
49 1.13888950 0.49111362
50 1.62149848 1.13888950
51 -0.22756952 1.62149848
52 0.80541297 -0.22756952
53 0.70574158 0.80541297
54 0.33816398 0.70574158
55 -1.16252623 0.33816398
56 -2.13894785 -1.16252623
57 -1.52516557 -2.13894785
58 0.41581003 -1.52516557
59 -0.90036731 0.41581003
60 1.23619473 -0.90036731
61 NA 1.23619473
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 1.48827458 -0.80192388
[2,] 2.92233897 1.48827458
[3,] 1.47854510 2.92233897
[4,] 0.39427764 1.47854510
[5,] 0.86952142 0.39427764
[6,] -0.97985569 0.86952142
[7,] 0.82052305 -0.97985569
[8,] 1.75441923 0.82052305
[9,] 2.24060571 1.75441923
[10,] 0.07566394 2.24060571
[11,] -2.44959768 0.07566394
[12,] -1.20374072 -2.44959768
[13,] -3.66371453 -1.20374072
[14,] -3.43511925 -3.66371453
[15,] -3.33060831 -3.43511925
[16,] 0.47964176 -3.33060831
[17,] -1.08494180 0.47964176
[18,] 0.11745026 -1.08494180
[19,] -0.26689663 0.11745026
[20,] 1.60653446 -0.26689663
[21,] 0.91338101 1.60653446
[22,] -0.16038337 0.91338101
[23,] -0.79345667 -0.16038337
[24,] -0.08263609 -0.79345667
[25,] -0.88333206 -0.08263609
[26,] -0.68704416 -0.88333206
[27,] 0.76789875 -0.68704416
[28,] 0.97838006 0.76789875
[29,] -0.33295321 0.97838006
[30,] -0.31304533 -0.33295321
[31,] -0.04694424 -0.31304533
[32,] -2.13144787 -0.04694424
[33,] -1.19605048 -2.13144787
[34,] -0.07300229 -1.19605048
[35,] -0.56228169 -0.07300229
[36,] 0.19585236 -0.56228169
[37,] -0.01701959 0.19585236
[38,] 0.97268366 -0.01701959
[39,] 1.81008803 0.97268366
[40,] -0.13594784 1.81008803
[41,] -0.13281435 -0.13594784
[42,] 0.26119172 -0.13281435
[43,] 0.84492210 0.26119172
[44,] 0.17809591 0.84492210
[45,] 1.55890082 0.17809591
[46,] 1.50982021 1.55890082
[47,] -0.27250144 1.50982021
[48,] 0.49111362 -0.27250144
[49,] 1.13888950 0.49111362
[50,] 1.62149848 1.13888950
[51,] -0.22756952 1.62149848
[52,] 0.80541297 -0.22756952
[53,] 0.70574158 0.80541297
[54,] 0.33816398 0.70574158
[55,] -1.16252623 0.33816398
[56,] -2.13894785 -1.16252623
[57,] -1.52516557 -2.13894785
[58,] 0.41581003 -1.52516557
[59,] -0.90036731 0.41581003
[60,] 1.23619473 -0.90036731
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 1.48827458 -0.80192388
2 2.92233897 1.48827458
3 1.47854510 2.92233897
4 0.39427764 1.47854510
5 0.86952142 0.39427764
6 -0.97985569 0.86952142
7 0.82052305 -0.97985569
8 1.75441923 0.82052305
9 2.24060571 1.75441923
10 0.07566394 2.24060571
11 -2.44959768 0.07566394
12 -1.20374072 -2.44959768
13 -3.66371453 -1.20374072
14 -3.43511925 -3.66371453
15 -3.33060831 -3.43511925
16 0.47964176 -3.33060831
17 -1.08494180 0.47964176
18 0.11745026 -1.08494180
19 -0.26689663 0.11745026
20 1.60653446 -0.26689663
21 0.91338101 1.60653446
22 -0.16038337 0.91338101
23 -0.79345667 -0.16038337
24 -0.08263609 -0.79345667
25 -0.88333206 -0.08263609
26 -0.68704416 -0.88333206
27 0.76789875 -0.68704416
28 0.97838006 0.76789875
29 -0.33295321 0.97838006
30 -0.31304533 -0.33295321
31 -0.04694424 -0.31304533
32 -2.13144787 -0.04694424
33 -1.19605048 -2.13144787
34 -0.07300229 -1.19605048
35 -0.56228169 -0.07300229
36 0.19585236 -0.56228169
37 -0.01701959 0.19585236
38 0.97268366 -0.01701959
39 1.81008803 0.97268366
40 -0.13594784 1.81008803
41 -0.13281435 -0.13594784
42 0.26119172 -0.13281435
43 0.84492210 0.26119172
44 0.17809591 0.84492210
45 1.55890082 0.17809591
46 1.50982021 1.55890082
47 -0.27250144 1.50982021
48 0.49111362 -0.27250144
49 1.13888950 0.49111362
50 1.62149848 1.13888950
51 -0.22756952 1.62149848
52 0.80541297 -0.22756952
53 0.70574158 0.80541297
54 0.33816398 0.70574158
55 -1.16252623 0.33816398
56 -2.13894785 -1.16252623
57 -1.52516557 -2.13894785
58 0.41581003 -1.52516557
59 -0.90036731 0.41581003
60 1.23619473 -0.90036731
> 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/fisher/rcomp/tmp/7ra0g1353080960.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/8ooq61353080960.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/9koa71353080960.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/fisher/rcomp/tmp/10bpfv1353080960.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/fisher/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/fisher/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/fisher/rcomp/tmp/11sfp61353080960.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/fisher/rcomp/tmp/12vbp01353080960.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/fisher/rcomp/tmp/1342ik1353080960.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/fisher/rcomp/tmp/145r281353080960.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/fisher/rcomp/tmp/15gtfw1353080960.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/fisher/rcomp/tmp/16mqhw1353080960.tab")
+ }
>
> try(system("convert tmp/1fkt71353080960.ps tmp/1fkt71353080960.png",intern=TRUE))
character(0)
> try(system("convert tmp/2nrxw1353080960.ps tmp/2nrxw1353080960.png",intern=TRUE))
character(0)
> try(system("convert tmp/3xiqq1353080960.ps tmp/3xiqq1353080960.png",intern=TRUE))
character(0)
> try(system("convert tmp/4kmxa1353080960.ps tmp/4kmxa1353080960.png",intern=TRUE))
character(0)
> try(system("convert tmp/563kz1353080960.ps tmp/563kz1353080960.png",intern=TRUE))
character(0)
> try(system("convert tmp/6jbqb1353080960.ps tmp/6jbqb1353080960.png",intern=TRUE))
character(0)
> try(system("convert tmp/7ra0g1353080960.ps tmp/7ra0g1353080960.png",intern=TRUE))
character(0)
> try(system("convert tmp/8ooq61353080960.ps tmp/8ooq61353080960.png",intern=TRUE))
character(0)
> try(system("convert tmp/9koa71353080960.ps tmp/9koa71353080960.png",intern=TRUE))
character(0)
> try(system("convert tmp/10bpfv1353080960.ps tmp/10bpfv1353080960.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
6.088 1.287 7.394