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(3.7
+ ,0
+ ,3.7
+ ,3.93
+ ,4.15
+ ,4.24
+ ,0
+ ,0
+ ,0
+ ,3.65
+ ,0
+ ,3.7
+ ,3.7
+ ,3.93
+ ,4.15
+ ,0
+ ,0
+ ,0
+ ,3.55
+ ,0
+ ,3.65
+ ,3.7
+ ,3.7
+ ,3.93
+ ,0
+ ,0
+ ,0
+ ,3.43
+ ,0
+ ,3.55
+ ,3.65
+ ,3.7
+ ,3.7
+ ,0
+ ,0
+ ,0
+ ,3.47
+ ,0
+ ,3.43
+ ,3.55
+ ,3.65
+ ,3.7
+ ,0
+ ,0
+ ,0
+ ,3.58
+ ,0
+ ,3.47
+ ,3.43
+ ,3.55
+ ,3.65
+ ,0
+ ,0
+ ,0
+ ,3.67
+ ,0
+ ,3.58
+ ,3.47
+ ,3.43
+ ,3.55
+ ,0
+ ,0
+ ,0
+ ,3.72
+ ,0
+ ,3.67
+ ,3.58
+ ,3.47
+ ,3.43
+ ,0
+ ,0
+ ,0
+ ,3.8
+ ,0
+ ,3.72
+ ,3.67
+ ,3.58
+ ,3.47
+ ,0
+ ,0
+ ,0
+ ,3.76
+ ,0
+ ,3.8
+ ,3.72
+ ,3.67
+ ,3.58
+ ,0
+ ,0
+ ,0
+ ,3.63
+ ,0
+ ,3.76
+ ,3.8
+ ,3.72
+ ,3.67
+ ,0
+ ,0
+ ,0
+ ,3.48
+ ,0
+ ,3.63
+ ,3.76
+ ,3.8
+ ,3.72
+ ,0
+ ,0
+ ,0
+ ,3.41
+ ,0
+ ,3.48
+ ,3.63
+ ,3.76
+ ,3.8
+ ,0
+ ,0
+ ,0
+ ,3.43
+ ,0
+ ,3.41
+ ,3.48
+ ,3.63
+ ,3.76
+ ,0
+ ,0
+ ,0
+ ,3.5
+ ,0
+ ,3.43
+ ,3.41
+ ,3.48
+ ,3.63
+ ,0
+ ,0
+ ,0
+ ,3.62
+ ,0
+ ,3.5
+ ,3.43
+ ,3.41
+ ,3.48
+ ,0
+ ,0
+ ,0
+ ,3.58
+ ,0
+ ,3.62
+ ,3.5
+ ,3.43
+ ,3.41
+ ,0
+ ,0
+ ,0
+ ,3.52
+ ,0
+ ,3.58
+ ,3.62
+ ,3.5
+ ,3.43
+ ,0
+ ,0
+ ,0
+ ,3.45
+ ,0
+ ,3.52
+ ,3.58
+ ,3.62
+ ,3.5
+ ,0
+ ,0
+ ,0
+ ,3.36
+ ,0
+ ,3.45
+ ,3.52
+ ,3.58
+ ,3.62
+ ,0
+ ,0
+ ,0
+ ,3.27
+ ,0
+ ,3.36
+ ,3.45
+ ,3.52
+ ,3.58
+ ,0
+ ,0
+ ,0
+ ,3.21
+ ,0
+ ,3.27
+ ,3.36
+ ,3.45
+ ,3.52
+ ,0
+ ,0
+ ,0
+ ,3.19
+ ,0
+ ,3.21
+ ,3.27
+ ,3.36
+ ,3.45
+ ,0
+ ,0
+ ,0
+ ,3.16
+ ,0
+ ,3.19
+ ,3.21
+ ,3.27
+ ,3.36
+ ,0
+ ,0
+ ,0
+ ,3.12
+ ,0
+ ,3.16
+ ,3.19
+ ,3.21
+ ,3.27
+ ,0
+ ,0
+ ,0
+ ,3.06
+ ,0
+ ,3.12
+ ,3.16
+ ,3.19
+ ,3.21
+ ,0
+ ,0
+ ,0
+ ,3.01
+ ,0
+ ,3.06
+ ,3.12
+ ,3.16
+ ,3.19
+ ,0
+ ,0
+ ,0
+ ,2.98
+ ,0
+ ,3.01
+ ,3.06
+ ,3.12
+ ,3.16
+ ,0
+ ,0
+ ,0
+ ,2.97
+ ,0
+ ,2.98
+ ,3.01
+ ,3.06
+ ,3.12
+ ,0
+ ,0
+ ,0
+ ,3.02
+ ,0
+ ,2.97
+ ,2.98
+ ,3.01
+ ,3.06
+ ,0
+ ,0
+ ,0
+ ,3.07
+ ,0
+ ,3.02
+ ,2.97
+ ,2.98
+ ,3.01
+ ,0
+ ,0
+ ,0
+ ,3.18
+ ,0
+ ,3.07
+ ,3.02
+ ,2.97
+ ,2.98
+ ,0
+ ,0
+ ,0
+ ,3.29
+ ,1
+ ,3.18
+ ,3.07
+ ,3.02
+ ,2.97
+ ,0
+ ,0
+ ,0
+ ,3.43
+ ,1
+ ,3.29
+ ,3.18
+ ,3.07
+ ,3.02
+ ,0
+ ,0
+ ,0
+ ,3.61
+ ,1
+ ,3.43
+ ,3.29
+ ,3.18
+ ,3.07
+ ,0
+ ,0
+ ,0
+ ,3.74
+ ,1
+ ,3.61
+ ,3.43
+ ,3.29
+ ,3.18
+ ,0
+ ,0
+ ,0
+ ,3.87
+ ,1
+ ,3.74
+ ,3.61
+ ,3.43
+ ,3.29
+ ,0
+ ,0
+ ,0
+ ,3.88
+ ,1
+ ,3.87
+ ,3.74
+ ,3.61
+ ,3.43
+ ,0
+ ,0
+ ,0
+ ,4.09
+ ,1
+ ,3.88
+ ,3.87
+ ,3.74
+ ,3.61
+ ,0
+ ,0
+ ,0
+ ,4.19
+ ,1
+ ,4.09
+ ,3.88
+ ,3.87
+ ,3.74
+ ,0
+ ,0
+ ,0
+ ,4.2
+ ,1
+ ,4.19
+ ,4.09
+ ,3.88
+ ,3.87
+ ,0
+ ,0
+ ,0
+ ,4.29
+ ,1
+ ,4.2
+ ,4.19
+ ,4.09
+ ,3.88
+ ,0
+ ,0
+ ,0
+ ,4.37
+ ,1
+ ,4.29
+ ,4.2
+ ,4.19
+ ,4.09
+ ,0
+ ,0
+ ,0
+ ,4.47
+ ,1
+ ,4.37
+ ,4.29
+ ,4.2
+ ,4.19
+ ,0
+ ,0
+ ,0
+ ,4.61
+ ,1
+ ,4.47
+ ,4.37
+ ,4.29
+ ,4.2
+ ,0
+ ,0
+ ,0
+ ,4.65
+ ,1
+ ,4.61
+ ,4.47
+ ,4.37
+ ,4.29
+ ,0
+ ,0
+ ,0
+ ,4.69
+ ,1
+ ,4.65
+ ,4.61
+ ,4.47
+ ,4.37
+ ,0
+ ,0
+ ,0
+ ,4.82
+ ,1
+ ,4.69
+ ,4.65
+ ,4.61
+ ,4.47
+ ,0
+ ,0
+ ,0
+ ,4.86
+ ,1
+ ,4.82
+ ,4.69
+ ,4.65
+ ,4.61
+ ,0
+ ,0
+ ,0
+ ,4.87
+ ,1
+ ,4.86
+ ,4.82
+ ,4.69
+ ,4.65
+ ,0
+ ,0
+ ,0
+ ,5.01
+ ,1
+ ,4.87
+ ,4.86
+ ,4.82
+ ,4.69
+ ,0
+ ,0
+ ,0
+ ,5.03
+ ,1
+ ,5.01
+ ,4.87
+ ,4.86
+ ,4.82
+ ,0
+ ,0
+ ,0
+ ,5.13
+ ,1
+ ,5.03
+ ,5.01
+ ,4.87
+ ,4.86
+ ,0
+ ,0
+ ,0
+ ,5.18
+ ,1
+ ,5.13
+ ,5.03
+ ,5.01
+ ,4.87
+ ,0
+ ,0
+ ,0
+ ,5.21
+ ,1
+ ,5.18
+ ,5.13
+ ,5.03
+ ,5.01
+ ,0
+ ,0
+ ,0
+ ,5.26
+ ,1
+ ,5.21
+ ,5.18
+ ,5.13
+ ,5.03
+ ,0
+ ,0
+ ,0
+ ,5.25
+ ,1
+ ,5.26
+ ,5.21
+ ,5.18
+ ,5.13
+ ,0
+ ,0
+ ,0
+ ,5.2
+ ,1
+ ,5.25
+ ,5.26
+ ,5.21
+ ,5.18
+ ,0
+ ,0
+ ,0
+ ,5.16
+ ,1
+ ,5.2
+ ,5.25
+ ,5.26
+ ,5.21
+ ,0
+ ,0
+ ,0
+ ,5.19
+ ,1
+ ,5.16
+ ,5.2
+ ,5.25
+ ,5.26
+ ,0
+ ,0
+ ,0
+ ,5.39
+ ,1
+ ,5.19
+ ,5.16
+ ,5.2
+ ,5.25
+ ,0
+ ,0
+ ,0
+ ,5.58
+ ,1
+ ,5.39
+ ,5.19
+ ,5.16
+ ,5.2
+ ,0
+ ,0
+ ,0
+ ,5.76
+ ,1
+ ,5.58
+ ,5.39
+ ,5.19
+ ,5.16
+ ,0
+ ,0
+ ,0
+ ,5.89
+ ,1
+ ,5.76
+ ,5.58
+ ,5.39
+ ,5.19
+ ,0
+ ,0
+ ,1
+ ,5.98
+ ,1
+ ,5.89
+ ,5.76
+ ,5.58
+ ,5.39
+ ,0
+ ,1
+ ,0
+ ,6.02
+ ,1
+ ,5.98
+ ,5.89
+ ,5.76
+ ,5.58
+ ,1
+ ,0
+ ,0
+ ,5.62
+ ,1
+ ,6.02
+ ,5.98
+ ,5.89
+ ,5.76
+ ,0
+ ,0
+ ,0
+ ,4.87
+ ,1
+ ,5.62
+ ,6.02
+ ,5.98
+ ,5.89
+ ,0
+ ,0
+ ,0)
+ ,dim=c(9
+ ,68)
+ ,dimnames=list(c('Y'
+ ,'X'
+ ,'Y1'
+ ,'Y2'
+ ,'Y3'
+ ,'Y4'
+ ,'O1'
+ ,'O2'
+ ,'O3')
+ ,1:68))
> y <- array(NA,dim=c(9,68),dimnames=list(c('Y','X','Y1','Y2','Y3','Y4','O1','O2','O3'),1:68))
> 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 O1 O2 O3 M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 3.70 0 3.70 3.93 4.15 4.24 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1
2 3.65 0 3.70 3.70 3.93 4.15 0 0 0 0 1 0 0 0 0 0 0 0 0 0 2
3 3.55 0 3.65 3.70 3.70 3.93 0 0 0 0 0 1 0 0 0 0 0 0 0 0 3
4 3.43 0 3.55 3.65 3.70 3.70 0 0 0 0 0 0 1 0 0 0 0 0 0 0 4
5 3.47 0 3.43 3.55 3.65 3.70 0 0 0 0 0 0 0 1 0 0 0 0 0 0 5
6 3.58 0 3.47 3.43 3.55 3.65 0 0 0 0 0 0 0 0 1 0 0 0 0 0 6
7 3.67 0 3.58 3.47 3.43 3.55 0 0 0 0 0 0 0 0 0 1 0 0 0 0 7
8 3.72 0 3.67 3.58 3.47 3.43 0 0 0 0 0 0 0 0 0 0 1 0 0 0 8
9 3.80 0 3.72 3.67 3.58 3.47 0 0 0 0 0 0 0 0 0 0 0 1 0 0 9
10 3.76 0 3.80 3.72 3.67 3.58 0 0 0 0 0 0 0 0 0 0 0 0 1 0 10
11 3.63 0 3.76 3.80 3.72 3.67 0 0 0 0 0 0 0 0 0 0 0 0 0 1 11
12 3.48 0 3.63 3.76 3.80 3.72 0 0 0 0 0 0 0 0 0 0 0 0 0 0 12
13 3.41 0 3.48 3.63 3.76 3.80 0 0 0 1 0 0 0 0 0 0 0 0 0 0 13
14 3.43 0 3.41 3.48 3.63 3.76 0 0 0 0 1 0 0 0 0 0 0 0 0 0 14
15 3.50 0 3.43 3.41 3.48 3.63 0 0 0 0 0 1 0 0 0 0 0 0 0 0 15
16 3.62 0 3.50 3.43 3.41 3.48 0 0 0 0 0 0 1 0 0 0 0 0 0 0 16
17 3.58 0 3.62 3.50 3.43 3.41 0 0 0 0 0 0 0 1 0 0 0 0 0 0 17
18 3.52 0 3.58 3.62 3.50 3.43 0 0 0 0 0 0 0 0 1 0 0 0 0 0 18
19 3.45 0 3.52 3.58 3.62 3.50 0 0 0 0 0 0 0 0 0 1 0 0 0 0 19
20 3.36 0 3.45 3.52 3.58 3.62 0 0 0 0 0 0 0 0 0 0 1 0 0 0 20
21 3.27 0 3.36 3.45 3.52 3.58 0 0 0 0 0 0 0 0 0 0 0 1 0 0 21
22 3.21 0 3.27 3.36 3.45 3.52 0 0 0 0 0 0 0 0 0 0 0 0 1 0 22
23 3.19 0 3.21 3.27 3.36 3.45 0 0 0 0 0 0 0 0 0 0 0 0 0 1 23
24 3.16 0 3.19 3.21 3.27 3.36 0 0 0 0 0 0 0 0 0 0 0 0 0 0 24
25 3.12 0 3.16 3.19 3.21 3.27 0 0 0 1 0 0 0 0 0 0 0 0 0 0 25
26 3.06 0 3.12 3.16 3.19 3.21 0 0 0 0 1 0 0 0 0 0 0 0 0 0 26
27 3.01 0 3.06 3.12 3.16 3.19 0 0 0 0 0 1 0 0 0 0 0 0 0 0 27
28 2.98 0 3.01 3.06 3.12 3.16 0 0 0 0 0 0 1 0 0 0 0 0 0 0 28
29 2.97 0 2.98 3.01 3.06 3.12 0 0 0 0 0 0 0 1 0 0 0 0 0 0 29
30 3.02 0 2.97 2.98 3.01 3.06 0 0 0 0 0 0 0 0 1 0 0 0 0 0 30
31 3.07 0 3.02 2.97 2.98 3.01 0 0 0 0 0 0 0 0 0 1 0 0 0 0 31
32 3.18 0 3.07 3.02 2.97 2.98 0 0 0 0 0 0 0 0 0 0 1 0 0 0 32
33 3.29 1 3.18 3.07 3.02 2.97 0 0 0 0 0 0 0 0 0 0 0 1 0 0 33
34 3.43 1 3.29 3.18 3.07 3.02 0 0 0 0 0 0 0 0 0 0 0 0 1 0 34
35 3.61 1 3.43 3.29 3.18 3.07 0 0 0 0 0 0 0 0 0 0 0 0 0 1 35
36 3.74 1 3.61 3.43 3.29 3.18 0 0 0 0 0 0 0 0 0 0 0 0 0 0 36
37 3.87 1 3.74 3.61 3.43 3.29 0 0 0 1 0 0 0 0 0 0 0 0 0 0 37
38 3.88 1 3.87 3.74 3.61 3.43 0 0 0 0 1 0 0 0 0 0 0 0 0 0 38
39 4.09 1 3.88 3.87 3.74 3.61 0 0 0 0 0 1 0 0 0 0 0 0 0 0 39
40 4.19 1 4.09 3.88 3.87 3.74 0 0 0 0 0 0 1 0 0 0 0 0 0 0 40
41 4.20 1 4.19 4.09 3.88 3.87 0 0 0 0 0 0 0 1 0 0 0 0 0 0 41
42 4.29 1 4.20 4.19 4.09 3.88 0 0 0 0 0 0 0 0 1 0 0 0 0 0 42
43 4.37 1 4.29 4.20 4.19 4.09 0 0 0 0 0 0 0 0 0 1 0 0 0 0 43
44 4.47 1 4.37 4.29 4.20 4.19 0 0 0 0 0 0 0 0 0 0 1 0 0 0 44
45 4.61 1 4.47 4.37 4.29 4.20 0 0 0 0 0 0 0 0 0 0 0 1 0 0 45
46 4.65 1 4.61 4.47 4.37 4.29 0 0 0 0 0 0 0 0 0 0 0 0 1 0 46
47 4.69 1 4.65 4.61 4.47 4.37 0 0 0 0 0 0 0 0 0 0 0 0 0 1 47
48 4.82 1 4.69 4.65 4.61 4.47 0 0 0 0 0 0 0 0 0 0 0 0 0 0 48
49 4.86 1 4.82 4.69 4.65 4.61 0 0 0 1 0 0 0 0 0 0 0 0 0 0 49
50 4.87 1 4.86 4.82 4.69 4.65 0 0 0 0 1 0 0 0 0 0 0 0 0 0 50
51 5.01 1 4.87 4.86 4.82 4.69 0 0 0 0 0 1 0 0 0 0 0 0 0 0 51
52 5.03 1 5.01 4.87 4.86 4.82 0 0 0 0 0 0 1 0 0 0 0 0 0 0 52
53 5.13 1 5.03 5.01 4.87 4.86 0 0 0 0 0 0 0 1 0 0 0 0 0 0 53
54 5.18 1 5.13 5.03 5.01 4.87 0 0 0 0 0 0 0 0 1 0 0 0 0 0 54
55 5.21 1 5.18 5.13 5.03 5.01 0 0 0 0 0 0 0 0 0 1 0 0 0 0 55
56 5.26 1 5.21 5.18 5.13 5.03 0 0 0 0 0 0 0 0 0 0 1 0 0 0 56
57 5.25 1 5.26 5.21 5.18 5.13 0 0 0 0 0 0 0 0 0 0 0 1 0 0 57
58 5.20 1 5.25 5.26 5.21 5.18 0 0 0 0 0 0 0 0 0 0 0 0 1 0 58
59 5.16 1 5.20 5.25 5.26 5.21 0 0 0 0 0 0 0 0 0 0 0 0 0 1 59
60 5.19 1 5.16 5.20 5.25 5.26 0 0 0 0 0 0 0 0 0 0 0 0 0 0 60
61 5.39 1 5.19 5.16 5.20 5.25 0 0 0 1 0 0 0 0 0 0 0 0 0 0 61
62 5.58 1 5.39 5.19 5.16 5.20 0 0 0 0 1 0 0 0 0 0 0 0 0 0 62
63 5.76 1 5.58 5.39 5.19 5.16 0 0 0 0 0 1 0 0 0 0 0 0 0 0 63
64 5.89 1 5.76 5.58 5.39 5.19 0 0 1 0 0 0 1 0 0 0 0 0 0 0 64
65 5.98 1 5.89 5.76 5.58 5.39 0 1 0 0 0 0 0 1 0 0 0 0 0 0 65
66 6.02 1 5.98 5.89 5.76 5.58 1 0 0 0 0 0 0 0 1 0 0 0 0 0 66
67 5.62 1 6.02 5.98 5.89 5.76 0 0 0 0 0 0 0 0 0 1 0 0 0 0 67
68 4.87 1 5.62 6.02 5.98 5.89 0 0 0 0 0 0 0 0 0 0 1 0 0 0 68
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X Y1 Y2 Y3 Y4
0.2057026 0.1127320 2.0113964 -1.4959688 0.3491965 0.0804554
O1 O2 O3 M1 M2 M3
0.0525626 0.0942235 0.1473695 0.0334034 -0.0510167 0.0589097
M4 M5 M6 M7 M8 M9
-0.0626460 0.0066517 0.0244183 -0.0680214 -0.0260023 -0.0090469
M10 M11 t
-0.0453841 -0.0001017 -0.0007973
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-0.259896 -0.045571 0.003107 0.058051 0.133051
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.2057026 0.0911777 2.256 0.0288 *
X 0.1127320 0.0626107 1.801 0.0782 .
Y1 2.0113964 0.1698601 11.841 1.04e-15 ***
Y2 -1.4959688 0.3393943 -4.408 6.03e-05 ***
Y3 0.3491965 0.3803620 0.918 0.3633
Y4 0.0804554 0.2092979 0.384 0.7024
O1 0.0525626 0.1128683 0.466 0.6436
O2 0.0942235 0.1161697 0.811 0.4214
O3 0.1473695 0.1155369 1.276 0.2084
M1 0.0334034 0.0589822 0.566 0.5739
M2 -0.0510167 0.0599731 -0.851 0.3993
M3 0.0589097 0.0611491 0.963 0.3403
M4 -0.0626460 0.0618923 -1.012 0.3166
M5 0.0066517 0.0640051 0.104 0.9177
M6 0.0244183 0.0615229 0.397 0.6932
M7 -0.0680214 0.0597748 -1.138 0.2609
M8 -0.0260023 0.0606276 -0.429 0.6700
M9 -0.0090469 0.0612088 -0.148 0.8831
M10 -0.0453841 0.0614815 -0.738 0.4641
M11 -0.0001017 0.0615389 -0.002 0.9987
t -0.0007973 0.0014625 -0.545 0.5882
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.09613 on 47 degrees of freedom
Multiple R-squared: 0.9919, Adjusted R-squared: 0.9885
F-statistic: 288.1 on 20 and 47 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,] 0.72219960 0.55560080 0.2778004
[2,] 0.67261261 0.65477478 0.3273874
[3,] 0.52684594 0.94630812 0.4731541
[4,] 0.52346845 0.95306311 0.4765316
[5,] 0.40281268 0.80562537 0.5971873
[6,] 0.31332412 0.62664824 0.6866759
[7,] 0.26850135 0.53700270 0.7314987
[8,] 0.18488199 0.36976398 0.8151180
[9,] 0.15199510 0.30399020 0.8480049
[10,] 0.11293977 0.22587954 0.8870602
[11,] 0.08892208 0.17784417 0.9110779
[12,] 0.06589214 0.13178428 0.9341079
[13,] 0.05619029 0.11238058 0.9438097
[14,] 0.03523949 0.07047898 0.9647605
[15,] 0.01869531 0.03739062 0.9813047
[16,] 0.03660117 0.07320233 0.9633988
[17,] 0.02277970 0.04555941 0.9772203
[18,] 0.04103896 0.08207793 0.9589610
[19,] 0.02794827 0.05589655 0.9720517
[20,] 0.01333440 0.02666880 0.9866656
[21,] 0.02026638 0.04053276 0.9797336
> postscript(file="/var/www/html/rcomp/tmp/180ls1293571155.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
> points(x[,1]-mysum$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/280ls1293571155.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/3ia3v1293571155.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4ia3v1293571155.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5ia3v1293571155.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 = 68
Frequency = 1
1 2 3 4 5
1.083856e-01 -1.164056e-01 -1.269494e-01 2.024952e-02 1.009796e-01
6 7 8 9 10
-2.701939e-02 4.475194e-02 3.274778e-02 8.902726e-02 -4.022925e-02
11 12 13 14 15
-3.928184e-02 -1.890190e-02 -6.743030e-03 6.349061e-02 -5.774553e-02
16 17 18 19 20
1.102412e-01 -1.362611e-01 2.068887e-02 5.723553e-02 -1.863346e-02
21 22 23 24 25
-2.431365e-02 2.848046e-02 -1.289854e-02 -5.306443e-02 -6.705522e-02
26 27 28 29 30
5.550268e-03 -8.064876e-02 3.889747e-02 -2.988953e-02 6.632393e-04
31 32 33 34 35
4.286947e-02 9.178189e-02 -9.021866e-02 8.736246e-03 -1.522222e-02
36 37 38 39 40
-8.440401e-02 -3.695485e-02 -8.286212e-02 1.324933e-01 -1.084420e-01
41 42 43 44 45
-6.787983e-02 6.049799e-02 1.585380e-02 3.681995e-02 4.696751e-02
46 47 48 49 50
-4.307327e-02 4.006527e-02 9.321076e-02 -1.262697e-01 6.578174e-02
51 52 53 54 55
8.776370e-02 -6.094615e-02 1.330509e-01 -5.483070e-02 9.918575e-02
56 57 58 59 60
8.589172e-02 -2.146246e-02 4.608582e-02 2.733732e-02 6.315958e-02
61 62 63 64 65
1.286372e-01 6.444507e-02 4.508676e-02 6.418477e-17 3.989864e-17
66 67 68
-2.255141e-17 -2.598965e-01 -2.286079e-01
> postscript(file="/var/www/html/rcomp/tmp/6b1ky1293571155.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 = 68
Frequency = 1
lag(myerror, k = 1) myerror
0 1.083856e-01 NA
1 -1.164056e-01 1.083856e-01
2 -1.269494e-01 -1.164056e-01
3 2.024952e-02 -1.269494e-01
4 1.009796e-01 2.024952e-02
5 -2.701939e-02 1.009796e-01
6 4.475194e-02 -2.701939e-02
7 3.274778e-02 4.475194e-02
8 8.902726e-02 3.274778e-02
9 -4.022925e-02 8.902726e-02
10 -3.928184e-02 -4.022925e-02
11 -1.890190e-02 -3.928184e-02
12 -6.743030e-03 -1.890190e-02
13 6.349061e-02 -6.743030e-03
14 -5.774553e-02 6.349061e-02
15 1.102412e-01 -5.774553e-02
16 -1.362611e-01 1.102412e-01
17 2.068887e-02 -1.362611e-01
18 5.723553e-02 2.068887e-02
19 -1.863346e-02 5.723553e-02
20 -2.431365e-02 -1.863346e-02
21 2.848046e-02 -2.431365e-02
22 -1.289854e-02 2.848046e-02
23 -5.306443e-02 -1.289854e-02
24 -6.705522e-02 -5.306443e-02
25 5.550268e-03 -6.705522e-02
26 -8.064876e-02 5.550268e-03
27 3.889747e-02 -8.064876e-02
28 -2.988953e-02 3.889747e-02
29 6.632393e-04 -2.988953e-02
30 4.286947e-02 6.632393e-04
31 9.178189e-02 4.286947e-02
32 -9.021866e-02 9.178189e-02
33 8.736246e-03 -9.021866e-02
34 -1.522222e-02 8.736246e-03
35 -8.440401e-02 -1.522222e-02
36 -3.695485e-02 -8.440401e-02
37 -8.286212e-02 -3.695485e-02
38 1.324933e-01 -8.286212e-02
39 -1.084420e-01 1.324933e-01
40 -6.787983e-02 -1.084420e-01
41 6.049799e-02 -6.787983e-02
42 1.585380e-02 6.049799e-02
43 3.681995e-02 1.585380e-02
44 4.696751e-02 3.681995e-02
45 -4.307327e-02 4.696751e-02
46 4.006527e-02 -4.307327e-02
47 9.321076e-02 4.006527e-02
48 -1.262697e-01 9.321076e-02
49 6.578174e-02 -1.262697e-01
50 8.776370e-02 6.578174e-02
51 -6.094615e-02 8.776370e-02
52 1.330509e-01 -6.094615e-02
53 -5.483070e-02 1.330509e-01
54 9.918575e-02 -5.483070e-02
55 8.589172e-02 9.918575e-02
56 -2.146246e-02 8.589172e-02
57 4.608582e-02 -2.146246e-02
58 2.733732e-02 4.608582e-02
59 6.315958e-02 2.733732e-02
60 1.286372e-01 6.315958e-02
61 6.444507e-02 1.286372e-01
62 4.508676e-02 6.444507e-02
63 6.418477e-17 4.508676e-02
64 3.989864e-17 6.418477e-17
65 -2.255141e-17 3.989864e-17
66 -2.598965e-01 -2.255141e-17
67 -2.286079e-01 -2.598965e-01
68 NA -2.286079e-01
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -1.164056e-01 1.083856e-01
[2,] -1.269494e-01 -1.164056e-01
[3,] 2.024952e-02 -1.269494e-01
[4,] 1.009796e-01 2.024952e-02
[5,] -2.701939e-02 1.009796e-01
[6,] 4.475194e-02 -2.701939e-02
[7,] 3.274778e-02 4.475194e-02
[8,] 8.902726e-02 3.274778e-02
[9,] -4.022925e-02 8.902726e-02
[10,] -3.928184e-02 -4.022925e-02
[11,] -1.890190e-02 -3.928184e-02
[12,] -6.743030e-03 -1.890190e-02
[13,] 6.349061e-02 -6.743030e-03
[14,] -5.774553e-02 6.349061e-02
[15,] 1.102412e-01 -5.774553e-02
[16,] -1.362611e-01 1.102412e-01
[17,] 2.068887e-02 -1.362611e-01
[18,] 5.723553e-02 2.068887e-02
[19,] -1.863346e-02 5.723553e-02
[20,] -2.431365e-02 -1.863346e-02
[21,] 2.848046e-02 -2.431365e-02
[22,] -1.289854e-02 2.848046e-02
[23,] -5.306443e-02 -1.289854e-02
[24,] -6.705522e-02 -5.306443e-02
[25,] 5.550268e-03 -6.705522e-02
[26,] -8.064876e-02 5.550268e-03
[27,] 3.889747e-02 -8.064876e-02
[28,] -2.988953e-02 3.889747e-02
[29,] 6.632393e-04 -2.988953e-02
[30,] 4.286947e-02 6.632393e-04
[31,] 9.178189e-02 4.286947e-02
[32,] -9.021866e-02 9.178189e-02
[33,] 8.736246e-03 -9.021866e-02
[34,] -1.522222e-02 8.736246e-03
[35,] -8.440401e-02 -1.522222e-02
[36,] -3.695485e-02 -8.440401e-02
[37,] -8.286212e-02 -3.695485e-02
[38,] 1.324933e-01 -8.286212e-02
[39,] -1.084420e-01 1.324933e-01
[40,] -6.787983e-02 -1.084420e-01
[41,] 6.049799e-02 -6.787983e-02
[42,] 1.585380e-02 6.049799e-02
[43,] 3.681995e-02 1.585380e-02
[44,] 4.696751e-02 3.681995e-02
[45,] -4.307327e-02 4.696751e-02
[46,] 4.006527e-02 -4.307327e-02
[47,] 9.321076e-02 4.006527e-02
[48,] -1.262697e-01 9.321076e-02
[49,] 6.578174e-02 -1.262697e-01
[50,] 8.776370e-02 6.578174e-02
[51,] -6.094615e-02 8.776370e-02
[52,] 1.330509e-01 -6.094615e-02
[53,] -5.483070e-02 1.330509e-01
[54,] 9.918575e-02 -5.483070e-02
[55,] 8.589172e-02 9.918575e-02
[56,] -2.146246e-02 8.589172e-02
[57,] 4.608582e-02 -2.146246e-02
[58,] 2.733732e-02 4.608582e-02
[59,] 6.315958e-02 2.733732e-02
[60,] 1.286372e-01 6.315958e-02
[61,] 6.444507e-02 1.286372e-01
[62,] 4.508676e-02 6.444507e-02
[63,] 6.418477e-17 4.508676e-02
[64,] 3.989864e-17 6.418477e-17
[65,] -2.255141e-17 3.989864e-17
[66,] -2.598965e-01 -2.255141e-17
[67,] -2.286079e-01 -2.598965e-01
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -1.164056e-01 1.083856e-01
2 -1.269494e-01 -1.164056e-01
3 2.024952e-02 -1.269494e-01
4 1.009796e-01 2.024952e-02
5 -2.701939e-02 1.009796e-01
6 4.475194e-02 -2.701939e-02
7 3.274778e-02 4.475194e-02
8 8.902726e-02 3.274778e-02
9 -4.022925e-02 8.902726e-02
10 -3.928184e-02 -4.022925e-02
11 -1.890190e-02 -3.928184e-02
12 -6.743030e-03 -1.890190e-02
13 6.349061e-02 -6.743030e-03
14 -5.774553e-02 6.349061e-02
15 1.102412e-01 -5.774553e-02
16 -1.362611e-01 1.102412e-01
17 2.068887e-02 -1.362611e-01
18 5.723553e-02 2.068887e-02
19 -1.863346e-02 5.723553e-02
20 -2.431365e-02 -1.863346e-02
21 2.848046e-02 -2.431365e-02
22 -1.289854e-02 2.848046e-02
23 -5.306443e-02 -1.289854e-02
24 -6.705522e-02 -5.306443e-02
25 5.550268e-03 -6.705522e-02
26 -8.064876e-02 5.550268e-03
27 3.889747e-02 -8.064876e-02
28 -2.988953e-02 3.889747e-02
29 6.632393e-04 -2.988953e-02
30 4.286947e-02 6.632393e-04
31 9.178189e-02 4.286947e-02
32 -9.021866e-02 9.178189e-02
33 8.736246e-03 -9.021866e-02
34 -1.522222e-02 8.736246e-03
35 -8.440401e-02 -1.522222e-02
36 -3.695485e-02 -8.440401e-02
37 -8.286212e-02 -3.695485e-02
38 1.324933e-01 -8.286212e-02
39 -1.084420e-01 1.324933e-01
40 -6.787983e-02 -1.084420e-01
41 6.049799e-02 -6.787983e-02
42 1.585380e-02 6.049799e-02
43 3.681995e-02 1.585380e-02
44 4.696751e-02 3.681995e-02
45 -4.307327e-02 4.696751e-02
46 4.006527e-02 -4.307327e-02
47 9.321076e-02 4.006527e-02
48 -1.262697e-01 9.321076e-02
49 6.578174e-02 -1.262697e-01
50 8.776370e-02 6.578174e-02
51 -6.094615e-02 8.776370e-02
52 1.330509e-01 -6.094615e-02
53 -5.483070e-02 1.330509e-01
54 9.918575e-02 -5.483070e-02
55 8.589172e-02 9.918575e-02
56 -2.146246e-02 8.589172e-02
57 4.608582e-02 -2.146246e-02
58 2.733732e-02 4.608582e-02
59 6.315958e-02 2.733732e-02
60 1.286372e-01 6.315958e-02
61 6.444507e-02 1.286372e-01
62 4.508676e-02 6.444507e-02
63 6.418477e-17 4.508676e-02
64 3.989864e-17 6.418477e-17
65 -2.255141e-17 3.989864e-17
66 -2.598965e-01 -2.255141e-17
67 -2.286079e-01 -2.598965e-01
> 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/7ma111293571155.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8ma111293571155.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9ma111293571155.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
Warning messages:
1: Not plotting observations with leverage one:
64, 65, 66
2: Not plotting observations with leverage one:
64, 65, 66
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10e1141293571155.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11au251293571156.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/12ec0b1293571156.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/13a4y11293571156.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/14d5xp1293571156.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/15z5vd1293571156.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/1626bj1293571156.tab")
+ }
>
> try(system("convert tmp/180ls1293571155.ps tmp/180ls1293571155.png",intern=TRUE))
character(0)
> try(system("convert tmp/280ls1293571155.ps tmp/280ls1293571155.png",intern=TRUE))
character(0)
> try(system("convert tmp/3ia3v1293571155.ps tmp/3ia3v1293571155.png",intern=TRUE))
character(0)
> try(system("convert tmp/4ia3v1293571155.ps tmp/4ia3v1293571155.png",intern=TRUE))
character(0)
> try(system("convert tmp/5ia3v1293571155.ps tmp/5ia3v1293571155.png",intern=TRUE))
character(0)
> try(system("convert tmp/6b1ky1293571155.ps tmp/6b1ky1293571155.png",intern=TRUE))
character(0)
> try(system("convert tmp/7ma111293571155.ps tmp/7ma111293571155.png",intern=TRUE))
character(0)
> try(system("convert tmp/8ma111293571155.ps tmp/8ma111293571155.png",intern=TRUE))
character(0)
> try(system("convert tmp/9ma111293571155.ps tmp/9ma111293571155.png",intern=TRUE))
character(0)
> try(system("convert tmp/10e1141293571155.ps tmp/10e1141293571155.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
2.572 1.613 5.858