R version 2.8.0 (2008-10-20)
Copyright (C) 2008 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
R is free software and comes with ABSOLUTELY NO WARRANTY.
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Type 'license()' or 'licence()' for distribution details.
Natural language support but running in an English locale
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Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> x <- array(list(6.12
+ ,0
+ ,5.99
+ ,5.76
+ ,5.81
+ ,6.03
+ ,0
+ ,6.12
+ ,5.99
+ ,5.76
+ ,6.25
+ ,0
+ ,6.03
+ ,6.12
+ ,5.99
+ ,5.80
+ ,0
+ ,6.25
+ ,6.03
+ ,6.12
+ ,5.67
+ ,0
+ ,5.80
+ ,6.25
+ ,6.03
+ ,5.89
+ ,0
+ ,5.67
+ ,5.80
+ ,6.25
+ ,5.91
+ ,0
+ ,5.89
+ ,5.67
+ ,5.80
+ ,5.86
+ ,0
+ ,5.91
+ ,5.89
+ ,5.67
+ ,6.07
+ ,0
+ ,5.86
+ ,5.91
+ ,5.89
+ ,6.27
+ ,0
+ ,6.07
+ ,5.86
+ ,5.91
+ ,6.68
+ ,0
+ ,6.27
+ ,6.07
+ ,5.86
+ ,6.77
+ ,0
+ ,6.68
+ ,6.27
+ ,6.07
+ ,6.71
+ ,0
+ ,6.77
+ ,6.68
+ ,6.27
+ ,6.62
+ ,0
+ ,6.71
+ ,6.77
+ ,6.68
+ ,6.50
+ ,0
+ ,6.62
+ ,6.71
+ ,6.77
+ ,5.89
+ ,0
+ ,6.50
+ ,6.62
+ ,6.71
+ ,6.05
+ ,0
+ ,5.89
+ ,6.50
+ ,6.62
+ ,6.43
+ ,0
+ ,6.05
+ ,5.89
+ ,6.50
+ ,6.47
+ ,0
+ ,6.43
+ ,6.05
+ ,5.89
+ ,6.62
+ ,0
+ ,6.47
+ ,6.43
+ ,6.05
+ ,6.77
+ ,0
+ ,6.62
+ ,6.47
+ ,6.43
+ ,6.70
+ ,0
+ ,6.77
+ ,6.62
+ ,6.47
+ ,6.95
+ ,0
+ ,6.70
+ ,6.77
+ ,6.62
+ ,6.73
+ ,0
+ ,6.95
+ ,6.70
+ ,6.77
+ ,7.07
+ ,0
+ ,6.73
+ ,6.95
+ ,6.70
+ ,7.28
+ ,0
+ ,7.07
+ ,6.73
+ ,6.95
+ ,7.32
+ ,0
+ ,7.28
+ ,7.07
+ ,6.73
+ ,6.76
+ ,0
+ ,7.32
+ ,7.28
+ ,7.07
+ ,6.93
+ ,0
+ ,6.76
+ ,7.32
+ ,7.28
+ ,6.99
+ ,0
+ ,6.93
+ ,6.76
+ ,7.32
+ ,7.16
+ ,0
+ ,6.99
+ ,6.93
+ ,6.76
+ ,7.28
+ ,0
+ ,7.16
+ ,6.99
+ ,6.93
+ ,7.08
+ ,0
+ ,7.28
+ ,7.16
+ ,6.99
+ ,7.34
+ ,0
+ ,7.08
+ ,7.28
+ ,7.16
+ ,7.87
+ ,0
+ ,7.34
+ ,7.08
+ ,7.28
+ ,6.28
+ ,1
+ ,7.87
+ ,7.34
+ ,7.08
+ ,6.30
+ ,1
+ ,6.28
+ ,7.87
+ ,7.34
+ ,6.36
+ ,1
+ ,6.30
+ ,6.28
+ ,7.87
+ ,6.28
+ ,1
+ ,6.36
+ ,6.30
+ ,6.28
+ ,5.89
+ ,1
+ ,6.28
+ ,6.36
+ ,6.30
+ ,6.04
+ ,1
+ ,5.89
+ ,6.28
+ ,6.36
+ ,5.96
+ ,1
+ ,6.04
+ ,5.89
+ ,6.28
+ ,6.10
+ ,1
+ ,5.96
+ ,6.04
+ ,5.89
+ ,6.26
+ ,1
+ ,6.10
+ ,5.96
+ ,6.04
+ ,6.02
+ ,1
+ ,6.26
+ ,6.10
+ ,5.96
+ ,6.25
+ ,1
+ ,6.02
+ ,6.26
+ ,6.10
+ ,6.41
+ ,1
+ ,6.25
+ ,6.02
+ ,6.26
+ ,6.22
+ ,1
+ ,6.41
+ ,6.25
+ ,6.02
+ ,6.57
+ ,1
+ ,6.22
+ ,6.41
+ ,6.25
+ ,6.18
+ ,1
+ ,6.57
+ ,6.22
+ ,6.41
+ ,6.26
+ ,1
+ ,6.18
+ ,6.57
+ ,6.22
+ ,6.10
+ ,1
+ ,6.26
+ ,6.18
+ ,6.57
+ ,6.02
+ ,1
+ ,6.10
+ ,6.26
+ ,6.18
+ ,6.06
+ ,1
+ ,6.02
+ ,6.10
+ ,6.26
+ ,6.35
+ ,1
+ ,6.06
+ ,6.02
+ ,6.10
+ ,6.21
+ ,1
+ ,6.35
+ ,6.06
+ ,6.02
+ ,6.48
+ ,1
+ ,6.21
+ ,6.35
+ ,6.06
+ ,6.74
+ ,1
+ ,6.48
+ ,6.21
+ ,6.35
+ ,6.53
+ ,1
+ ,6.74
+ ,6.48
+ ,6.21
+ ,6.80
+ ,1
+ ,6.53
+ ,6.74
+ ,6.48
+ ,6.75
+ ,1
+ ,6.80
+ ,6.53
+ ,6.74
+ ,6.56
+ ,1
+ ,6.75
+ ,6.80
+ ,6.53
+ ,6.66
+ ,1
+ ,6.56
+ ,6.75
+ ,6.80
+ ,6.18
+ ,1
+ ,6.66
+ ,6.56
+ ,6.75
+ ,6.40
+ ,1
+ ,6.18
+ ,6.66
+ ,6.56
+ ,6.43
+ ,1
+ ,6.40
+ ,6.18
+ ,6.66
+ ,6.54
+ ,1
+ ,6.43
+ ,6.40
+ ,6.18
+ ,6.44
+ ,1
+ ,6.54
+ ,6.43
+ ,6.40
+ ,6.64
+ ,1
+ ,6.44
+ ,6.54
+ ,6.43
+ ,6.82
+ ,1
+ ,6.64
+ ,6.44
+ ,6.54
+ ,6.97
+ ,1
+ ,6.82
+ ,6.64
+ ,6.44
+ ,7.00
+ ,1
+ ,6.97
+ ,6.82
+ ,6.64
+ ,6.91
+ ,1
+ ,7.00
+ ,6.97
+ ,6.82
+ ,6.74
+ ,1
+ ,6.91
+ ,7.00
+ ,6.97
+ ,6.98
+ ,1
+ ,6.74
+ ,6.91
+ ,7.00
+ ,6.37
+ ,1
+ ,6.98
+ ,6.74
+ ,6.91
+ ,6.56
+ ,1
+ ,6.37
+ ,6.98
+ ,6.74
+ ,6.63
+ ,1
+ ,6.56
+ ,6.37
+ ,6.98
+ ,6.87
+ ,1
+ ,6.63
+ ,6.56
+ ,6.37
+ ,6.68
+ ,1
+ ,6.87
+ ,6.63
+ ,6.56
+ ,6.75
+ ,1
+ ,6.68
+ ,6.87
+ ,6.63
+ ,6.84
+ ,1
+ ,6.75
+ ,6.68
+ ,6.87
+ ,7.15
+ ,1
+ ,6.84
+ ,6.75
+ ,6.68
+ ,7.09
+ ,1
+ ,7.15
+ ,6.84
+ ,6.75
+ ,6.97
+ ,1
+ ,7.09
+ ,7.15
+ ,6.84
+ ,7.15
+ ,1
+ ,6.97
+ ,7.09
+ ,7.15)
+ ,dim=c(5
+ ,86)
+ ,dimnames=list(c('Y'
+ ,'X'
+ ,'Y1'
+ ,'Y2'
+ ,'Y3')
+ ,1:86))
> y <- array(NA,dim=c(5,86),dimnames=list(c('Y','X','Y1','Y2','Y3'),1:86))
> 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 M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 6.12 0 5.99 5.76 5.81 1 0 0 0 0 0 0 0 0 0 0 1
2 6.03 0 6.12 5.99 5.76 0 1 0 0 0 0 0 0 0 0 0 2
3 6.25 0 6.03 6.12 5.99 0 0 1 0 0 0 0 0 0 0 0 3
4 5.80 0 6.25 6.03 6.12 0 0 0 1 0 0 0 0 0 0 0 4
5 5.67 0 5.80 6.25 6.03 0 0 0 0 1 0 0 0 0 0 0 5
6 5.89 0 5.67 5.80 6.25 0 0 0 0 0 1 0 0 0 0 0 6
7 5.91 0 5.89 5.67 5.80 0 0 0 0 0 0 1 0 0 0 0 7
8 5.86 0 5.91 5.89 5.67 0 0 0 0 0 0 0 1 0 0 0 8
9 6.07 0 5.86 5.91 5.89 0 0 0 0 0 0 0 0 1 0 0 9
10 6.27 0 6.07 5.86 5.91 0 0 0 0 0 0 0 0 0 1 0 10
11 6.68 0 6.27 6.07 5.86 0 0 0 0 0 0 0 0 0 0 1 11
12 6.77 0 6.68 6.27 6.07 0 0 0 0 0 0 0 0 0 0 0 12
13 6.71 0 6.77 6.68 6.27 1 0 0 0 0 0 0 0 0 0 0 13
14 6.62 0 6.71 6.77 6.68 0 1 0 0 0 0 0 0 0 0 0 14
15 6.50 0 6.62 6.71 6.77 0 0 1 0 0 0 0 0 0 0 0 15
16 5.89 0 6.50 6.62 6.71 0 0 0 1 0 0 0 0 0 0 0 16
17 6.05 0 5.89 6.50 6.62 0 0 0 0 1 0 0 0 0 0 0 17
18 6.43 0 6.05 5.89 6.50 0 0 0 0 0 1 0 0 0 0 0 18
19 6.47 0 6.43 6.05 5.89 0 0 0 0 0 0 1 0 0 0 0 19
20 6.62 0 6.47 6.43 6.05 0 0 0 0 0 0 0 1 0 0 0 20
21 6.77 0 6.62 6.47 6.43 0 0 0 0 0 0 0 0 1 0 0 21
22 6.70 0 6.77 6.62 6.47 0 0 0 0 0 0 0 0 0 1 0 22
23 6.95 0 6.70 6.77 6.62 0 0 0 0 0 0 0 0 0 0 1 23
24 6.73 0 6.95 6.70 6.77 0 0 0 0 0 0 0 0 0 0 0 24
25 7.07 0 6.73 6.95 6.70 1 0 0 0 0 0 0 0 0 0 0 25
26 7.28 0 7.07 6.73 6.95 0 1 0 0 0 0 0 0 0 0 0 26
27 7.32 0 7.28 7.07 6.73 0 0 1 0 0 0 0 0 0 0 0 27
28 6.76 0 7.32 7.28 7.07 0 0 0 1 0 0 0 0 0 0 0 28
29 6.93 0 6.76 7.32 7.28 0 0 0 0 1 0 0 0 0 0 0 29
30 6.99 0 6.93 6.76 7.32 0 0 0 0 0 1 0 0 0 0 0 30
31 7.16 0 6.99 6.93 6.76 0 0 0 0 0 0 1 0 0 0 0 31
32 7.28 0 7.16 6.99 6.93 0 0 0 0 0 0 0 1 0 0 0 32
33 7.08 0 7.28 7.16 6.99 0 0 0 0 0 0 0 0 1 0 0 33
34 7.34 0 7.08 7.28 7.16 0 0 0 0 0 0 0 0 0 1 0 34
35 7.87 0 7.34 7.08 7.28 0 0 0 0 0 0 0 0 0 0 1 35
36 6.28 1 7.87 7.34 7.08 0 0 0 0 0 0 0 0 0 0 0 36
37 6.30 1 6.28 7.87 7.34 1 0 0 0 0 0 0 0 0 0 0 37
38 6.36 1 6.30 6.28 7.87 0 1 0 0 0 0 0 0 0 0 0 38
39 6.28 1 6.36 6.30 6.28 0 0 1 0 0 0 0 0 0 0 0 39
40 5.89 1 6.28 6.36 6.30 0 0 0 1 0 0 0 0 0 0 0 40
41 6.04 1 5.89 6.28 6.36 0 0 0 0 1 0 0 0 0 0 0 41
42 5.96 1 6.04 5.89 6.28 0 0 0 0 0 1 0 0 0 0 0 42
43 6.10 1 5.96 6.04 5.89 0 0 0 0 0 0 1 0 0 0 0 43
44 6.26 1 6.10 5.96 6.04 0 0 0 0 0 0 0 1 0 0 0 44
45 6.02 1 6.26 6.10 5.96 0 0 0 0 0 0 0 0 1 0 0 45
46 6.25 1 6.02 6.26 6.10 0 0 0 0 0 0 0 0 0 1 0 46
47 6.41 1 6.25 6.02 6.26 0 0 0 0 0 0 0 0 0 0 1 47
48 6.22 1 6.41 6.25 6.02 0 0 0 0 0 0 0 0 0 0 0 48
49 6.57 1 6.22 6.41 6.25 1 0 0 0 0 0 0 0 0 0 0 49
50 6.18 1 6.57 6.22 6.41 0 1 0 0 0 0 0 0 0 0 0 50
51 6.26 1 6.18 6.57 6.22 0 0 1 0 0 0 0 0 0 0 0 51
52 6.10 1 6.26 6.18 6.57 0 0 0 1 0 0 0 0 0 0 0 52
53 6.02 1 6.10 6.26 6.18 0 0 0 0 1 0 0 0 0 0 0 53
54 6.06 1 6.02 6.10 6.26 0 0 0 0 0 1 0 0 0 0 0 54
55 6.35 1 6.06 6.02 6.10 0 0 0 0 0 0 1 0 0 0 0 55
56 6.21 1 6.35 6.06 6.02 0 0 0 0 0 0 0 1 0 0 0 56
57 6.48 1 6.21 6.35 6.06 0 0 0 0 0 0 0 0 1 0 0 57
58 6.74 1 6.48 6.21 6.35 0 0 0 0 0 0 0 0 0 1 0 58
59 6.53 1 6.74 6.48 6.21 0 0 0 0 0 0 0 0 0 0 1 59
60 6.80 1 6.53 6.74 6.48 0 0 0 0 0 0 0 0 0 0 0 60
61 6.75 1 6.80 6.53 6.74 1 0 0 0 0 0 0 0 0 0 0 61
62 6.56 1 6.75 6.80 6.53 0 1 0 0 0 0 0 0 0 0 0 62
63 6.66 1 6.56 6.75 6.80 0 0 1 0 0 0 0 0 0 0 0 63
64 6.18 1 6.66 6.56 6.75 0 0 0 1 0 0 0 0 0 0 0 64
65 6.40 1 6.18 6.66 6.56 0 0 0 0 1 0 0 0 0 0 0 65
66 6.43 1 6.40 6.18 6.66 0 0 0 0 0 1 0 0 0 0 0 66
67 6.54 1 6.43 6.40 6.18 0 0 0 0 0 0 1 0 0 0 0 67
68 6.44 1 6.54 6.43 6.40 0 0 0 0 0 0 0 1 0 0 0 68
69 6.64 1 6.44 6.54 6.43 0 0 0 0 0 0 0 0 1 0 0 69
70 6.82 1 6.64 6.44 6.54 0 0 0 0 0 0 0 0 0 1 0 70
71 6.97 1 6.82 6.64 6.44 0 0 0 0 0 0 0 0 0 0 1 71
72 7.00 1 6.97 6.82 6.64 0 0 0 0 0 0 0 0 0 0 0 72
73 6.91 1 7.00 6.97 6.82 1 0 0 0 0 0 0 0 0 0 0 73
74 6.74 1 6.91 7.00 6.97 0 1 0 0 0 0 0 0 0 0 0 74
75 6.98 1 6.74 6.91 7.00 0 0 1 0 0 0 0 0 0 0 0 75
76 6.37 1 6.98 6.74 6.91 0 0 0 1 0 0 0 0 0 0 0 76
77 6.56 1 6.37 6.98 6.74 0 0 0 0 1 0 0 0 0 0 0 77
78 6.63 1 6.56 6.37 6.98 0 0 0 0 0 1 0 0 0 0 0 78
79 6.87 1 6.63 6.56 6.37 0 0 0 0 0 0 1 0 0 0 0 79
80 6.68 1 6.87 6.63 6.56 0 0 0 0 0 0 0 1 0 0 0 80
81 6.75 1 6.68 6.87 6.63 0 0 0 0 0 0 0 0 1 0 0 81
82 6.84 1 6.75 6.68 6.87 0 0 0 0 0 0 0 0 0 1 0 82
83 7.15 1 6.84 6.75 6.68 0 0 0 0 0 0 0 0 0 0 1 83
84 7.09 1 7.15 6.84 6.75 0 0 0 0 0 0 0 0 0 0 0 84
85 6.97 1 7.09 7.15 6.84 1 0 0 0 0 0 0 0 0 0 0 85
86 7.15 1 6.97 7.09 7.15 0 1 0 0 0 0 0 0 0 0 0 86
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X Y1 Y2 Y3 M1
3.1111828 -0.7166413 0.2820845 0.0001321 0.2226483 0.0644415
M2 M3 M4 M5 M6 M7
-0.0712678 0.0476063 -0.4720544 -0.2368167 -0.1908273 0.0138622
M8 M9 M10 M11 t
-0.0698832 -0.0393335 0.0600317 0.2295829 0.0142595
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-0.42521 -0.08949 -0.00634 0.09670 0.33784
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 3.1111828 0.4829237 6.442 1.34e-08 ***
X -0.7166413 0.0986775 -7.262 4.44e-10 ***
Y1 0.2820845 0.0994599 2.836 0.00599 **
Y2 0.0001321 0.1026669 0.001 0.99898
Y3 0.2226483 0.0863697 2.578 0.01208 *
M1 0.0644415 0.0953424 0.676 0.50137
M2 -0.0712678 0.0958379 -0.744 0.45963
M3 0.0476063 0.0973118 0.489 0.62624
M4 -0.4720544 0.0967343 -4.880 6.57e-06 ***
M5 -0.2368167 0.1177050 -2.012 0.04813 *
M6 -0.1908273 0.1160300 -1.645 0.10459
M7 0.0138622 0.1010293 0.137 0.89126
M8 -0.0698832 0.0975532 -0.716 0.47619
M9 -0.0393335 0.0990905 -0.397 0.69263
M10 0.0600317 0.0987666 0.608 0.54531
M11 0.2295829 0.0945924 2.427 0.01784 *
t 0.0142595 0.0020708 6.886 2.14e-09 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 0.1694 on 69 degrees of freedom
Multiple R-squared: 0.8739, Adjusted R-squared: 0.8447
F-statistic: 29.9 on 16 and 69 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,] 0.7871187 0.42576263 0.212881316
[2,] 0.6550457 0.68990869 0.344954343
[3,] 0.6076809 0.78463822 0.392319112
[4,] 0.5357975 0.92840503 0.464202514
[5,] 0.8426715 0.31465707 0.157328536
[6,] 0.8813615 0.23727691 0.118638453
[7,] 0.8796334 0.24073318 0.120366591
[8,] 0.8482693 0.30346150 0.151730750
[9,] 0.7986317 0.40273664 0.201368319
[10,] 0.8764135 0.24717307 0.123586534
[11,] 0.8474755 0.30504908 0.152524538
[12,] 0.8727240 0.25455207 0.127276036
[13,] 0.8569226 0.28615487 0.143077434
[14,] 0.9185019 0.16299623 0.081498113
[15,] 0.9524039 0.09519215 0.047596073
[16,] 0.9445497 0.11090052 0.055450258
[17,] 0.9188093 0.16238141 0.081190705
[18,] 0.9626587 0.07468264 0.037341321
[19,] 0.9675409 0.06491811 0.032459053
[20,] 0.9602244 0.07955129 0.039775644
[21,] 0.9533513 0.09329734 0.046648669
[22,] 0.9360995 0.12780094 0.063900470
[23,] 0.9290730 0.14185407 0.070927033
[24,] 0.9033291 0.19334179 0.096670893
[25,] 0.9117786 0.17644288 0.088221441
[26,] 0.9232758 0.15344832 0.076724160
[27,] 0.9036690 0.19266192 0.096330961
[28,] 0.9367755 0.12644895 0.063224475
[29,] 0.9657397 0.06852056 0.034260281
[30,] 0.9571519 0.08569618 0.042848089
[31,] 0.9901090 0.01978191 0.009890955
[32,] 0.9896718 0.02065641 0.010328205
[33,] 0.9831693 0.03366150 0.016830749
[34,] 0.9839588 0.03208245 0.016041225
[35,] 0.9792240 0.04155190 0.020775951
[36,] 0.9782474 0.04350520 0.021752602
[37,] 0.9798401 0.04031986 0.020159929
[38,] 0.9657300 0.06854008 0.034270038
[39,] 0.9773896 0.04522090 0.022610448
[40,] 0.9878949 0.02421022 0.012105109
[41,] 0.9814818 0.03703639 0.018518196
[42,] 0.9695297 0.06094070 0.030470350
[43,] 0.9432043 0.11359149 0.056795745
[44,] 0.9199369 0.16012621 0.080063104
[45,] 0.8557387 0.28852260 0.144261301
[46,] 0.7493163 0.50136732 0.250683658
[47,] 0.5892863 0.82142736 0.410713679
> postscript(file="/var/www/html/freestat/rcomp/tmp/1xmex1290946634.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
> points(x[,1]-mysum$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/2qvv01290946634.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/3qvv01290946634.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/4qvv01290946634.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/5qvv01290946634.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 = 86
Frequency = 1
1 2 3 4 5
-0.0539174417 -0.0480365797 0.0129911941 -0.0225985957 -0.2551484242
6 7 8 9 10
-0.1076494906 -0.2684481298 -0.2256887098 -0.0953788989 -0.0726877027
11 12 13 14 15
0.1081894296 0.2510756590 0.0424032752 -0.0005195414 -0.2482958988
16 17 18 19 20
-0.3056737954 -0.2030451864 0.0983708231 -0.0519759172 0.1205526621
21 22 23 24 25
0.0988192100 -0.1360439195 -0.0835257192 -0.1921114028 0.1467985791
26 27 28 29 30
0.3267066724 0.2232731026 0.0816627291 0.1133714808 0.0563363093
31 32 33 34 35
0.1151228569 0.2187962569 -0.0732443794 0.0916817332 0.3378377599
36 37 38 39 40
-0.4252069540 -0.0933522118 -0.0353375987 0.0886119685 0.2221190089
41 42 43 44 45
0.2192865064 0.0545883586 0.0850191594 0.2416265577 -0.0705227290
46 47 48 49 50
0.0823609257 -0.0419211612 -0.0083260425 0.2653388044 -0.1375395627
51 52 53 54 55
-0.0384032316 0.2065558134 0.0090144856 -0.0064583584 0.0889435870
56 57 58 59 60
-0.0455684269 0.2101700049 0.2158329818 -0.2201845330 0.2642272304
61 62 63 64 65
0.0015026689 -0.0062228231 -0.0458687526 -0.0375184987 0.1106748934
66 67 68 69 70
-0.0038339701 -0.0144033604 -0.1249333449 0.0517719758 0.0372522752
71 72 73 74 75
-0.0250951666 0.1333621463 -0.0838978495 -0.1404616436 0.0076916179
76 77 78 79 80
-0.1445466617 0.0058462444 -0.0913536718 0.0457418042 -0.1847849951
81 82 83 84 85
-0.1216151834 -0.2183962937 -0.0753006094 -0.0230206365 -0.2248758248
86
0.0414110768
> postscript(file="/var/www/html/freestat/rcomp/tmp/6j5ul1290946634.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 = 86
Frequency = 1
lag(myerror, k = 1) myerror
0 -0.0539174417 NA
1 -0.0480365797 -0.0539174417
2 0.0129911941 -0.0480365797
3 -0.0225985957 0.0129911941
4 -0.2551484242 -0.0225985957
5 -0.1076494906 -0.2551484242
6 -0.2684481298 -0.1076494906
7 -0.2256887098 -0.2684481298
8 -0.0953788989 -0.2256887098
9 -0.0726877027 -0.0953788989
10 0.1081894296 -0.0726877027
11 0.2510756590 0.1081894296
12 0.0424032752 0.2510756590
13 -0.0005195414 0.0424032752
14 -0.2482958988 -0.0005195414
15 -0.3056737954 -0.2482958988
16 -0.2030451864 -0.3056737954
17 0.0983708231 -0.2030451864
18 -0.0519759172 0.0983708231
19 0.1205526621 -0.0519759172
20 0.0988192100 0.1205526621
21 -0.1360439195 0.0988192100
22 -0.0835257192 -0.1360439195
23 -0.1921114028 -0.0835257192
24 0.1467985791 -0.1921114028
25 0.3267066724 0.1467985791
26 0.2232731026 0.3267066724
27 0.0816627291 0.2232731026
28 0.1133714808 0.0816627291
29 0.0563363093 0.1133714808
30 0.1151228569 0.0563363093
31 0.2187962569 0.1151228569
32 -0.0732443794 0.2187962569
33 0.0916817332 -0.0732443794
34 0.3378377599 0.0916817332
35 -0.4252069540 0.3378377599
36 -0.0933522118 -0.4252069540
37 -0.0353375987 -0.0933522118
38 0.0886119685 -0.0353375987
39 0.2221190089 0.0886119685
40 0.2192865064 0.2221190089
41 0.0545883586 0.2192865064
42 0.0850191594 0.0545883586
43 0.2416265577 0.0850191594
44 -0.0705227290 0.2416265577
45 0.0823609257 -0.0705227290
46 -0.0419211612 0.0823609257
47 -0.0083260425 -0.0419211612
48 0.2653388044 -0.0083260425
49 -0.1375395627 0.2653388044
50 -0.0384032316 -0.1375395627
51 0.2065558134 -0.0384032316
52 0.0090144856 0.2065558134
53 -0.0064583584 0.0090144856
54 0.0889435870 -0.0064583584
55 -0.0455684269 0.0889435870
56 0.2101700049 -0.0455684269
57 0.2158329818 0.2101700049
58 -0.2201845330 0.2158329818
59 0.2642272304 -0.2201845330
60 0.0015026689 0.2642272304
61 -0.0062228231 0.0015026689
62 -0.0458687526 -0.0062228231
63 -0.0375184987 -0.0458687526
64 0.1106748934 -0.0375184987
65 -0.0038339701 0.1106748934
66 -0.0144033604 -0.0038339701
67 -0.1249333449 -0.0144033604
68 0.0517719758 -0.1249333449
69 0.0372522752 0.0517719758
70 -0.0250951666 0.0372522752
71 0.1333621463 -0.0250951666
72 -0.0838978495 0.1333621463
73 -0.1404616436 -0.0838978495
74 0.0076916179 -0.1404616436
75 -0.1445466617 0.0076916179
76 0.0058462444 -0.1445466617
77 -0.0913536718 0.0058462444
78 0.0457418042 -0.0913536718
79 -0.1847849951 0.0457418042
80 -0.1216151834 -0.1847849951
81 -0.2183962937 -0.1216151834
82 -0.0753006094 -0.2183962937
83 -0.0230206365 -0.0753006094
84 -0.2248758248 -0.0230206365
85 0.0414110768 -0.2248758248
86 NA 0.0414110768
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -0.0480365797 -0.0539174417
[2,] 0.0129911941 -0.0480365797
[3,] -0.0225985957 0.0129911941
[4,] -0.2551484242 -0.0225985957
[5,] -0.1076494906 -0.2551484242
[6,] -0.2684481298 -0.1076494906
[7,] -0.2256887098 -0.2684481298
[8,] -0.0953788989 -0.2256887098
[9,] -0.0726877027 -0.0953788989
[10,] 0.1081894296 -0.0726877027
[11,] 0.2510756590 0.1081894296
[12,] 0.0424032752 0.2510756590
[13,] -0.0005195414 0.0424032752
[14,] -0.2482958988 -0.0005195414
[15,] -0.3056737954 -0.2482958988
[16,] -0.2030451864 -0.3056737954
[17,] 0.0983708231 -0.2030451864
[18,] -0.0519759172 0.0983708231
[19,] 0.1205526621 -0.0519759172
[20,] 0.0988192100 0.1205526621
[21,] -0.1360439195 0.0988192100
[22,] -0.0835257192 -0.1360439195
[23,] -0.1921114028 -0.0835257192
[24,] 0.1467985791 -0.1921114028
[25,] 0.3267066724 0.1467985791
[26,] 0.2232731026 0.3267066724
[27,] 0.0816627291 0.2232731026
[28,] 0.1133714808 0.0816627291
[29,] 0.0563363093 0.1133714808
[30,] 0.1151228569 0.0563363093
[31,] 0.2187962569 0.1151228569
[32,] -0.0732443794 0.2187962569
[33,] 0.0916817332 -0.0732443794
[34,] 0.3378377599 0.0916817332
[35,] -0.4252069540 0.3378377599
[36,] -0.0933522118 -0.4252069540
[37,] -0.0353375987 -0.0933522118
[38,] 0.0886119685 -0.0353375987
[39,] 0.2221190089 0.0886119685
[40,] 0.2192865064 0.2221190089
[41,] 0.0545883586 0.2192865064
[42,] 0.0850191594 0.0545883586
[43,] 0.2416265577 0.0850191594
[44,] -0.0705227290 0.2416265577
[45,] 0.0823609257 -0.0705227290
[46,] -0.0419211612 0.0823609257
[47,] -0.0083260425 -0.0419211612
[48,] 0.2653388044 -0.0083260425
[49,] -0.1375395627 0.2653388044
[50,] -0.0384032316 -0.1375395627
[51,] 0.2065558134 -0.0384032316
[52,] 0.0090144856 0.2065558134
[53,] -0.0064583584 0.0090144856
[54,] 0.0889435870 -0.0064583584
[55,] -0.0455684269 0.0889435870
[56,] 0.2101700049 -0.0455684269
[57,] 0.2158329818 0.2101700049
[58,] -0.2201845330 0.2158329818
[59,] 0.2642272304 -0.2201845330
[60,] 0.0015026689 0.2642272304
[61,] -0.0062228231 0.0015026689
[62,] -0.0458687526 -0.0062228231
[63,] -0.0375184987 -0.0458687526
[64,] 0.1106748934 -0.0375184987
[65,] -0.0038339701 0.1106748934
[66,] -0.0144033604 -0.0038339701
[67,] -0.1249333449 -0.0144033604
[68,] 0.0517719758 -0.1249333449
[69,] 0.0372522752 0.0517719758
[70,] -0.0250951666 0.0372522752
[71,] 0.1333621463 -0.0250951666
[72,] -0.0838978495 0.1333621463
[73,] -0.1404616436 -0.0838978495
[74,] 0.0076916179 -0.1404616436
[75,] -0.1445466617 0.0076916179
[76,] 0.0058462444 -0.1445466617
[77,] -0.0913536718 0.0058462444
[78,] 0.0457418042 -0.0913536718
[79,] -0.1847849951 0.0457418042
[80,] -0.1216151834 -0.1847849951
[81,] -0.2183962937 -0.1216151834
[82,] -0.0753006094 -0.2183962937
[83,] -0.0230206365 -0.0753006094
[84,] -0.2248758248 -0.0230206365
[85,] 0.0414110768 -0.2248758248
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -0.0480365797 -0.0539174417
2 0.0129911941 -0.0480365797
3 -0.0225985957 0.0129911941
4 -0.2551484242 -0.0225985957
5 -0.1076494906 -0.2551484242
6 -0.2684481298 -0.1076494906
7 -0.2256887098 -0.2684481298
8 -0.0953788989 -0.2256887098
9 -0.0726877027 -0.0953788989
10 0.1081894296 -0.0726877027
11 0.2510756590 0.1081894296
12 0.0424032752 0.2510756590
13 -0.0005195414 0.0424032752
14 -0.2482958988 -0.0005195414
15 -0.3056737954 -0.2482958988
16 -0.2030451864 -0.3056737954
17 0.0983708231 -0.2030451864
18 -0.0519759172 0.0983708231
19 0.1205526621 -0.0519759172
20 0.0988192100 0.1205526621
21 -0.1360439195 0.0988192100
22 -0.0835257192 -0.1360439195
23 -0.1921114028 -0.0835257192
24 0.1467985791 -0.1921114028
25 0.3267066724 0.1467985791
26 0.2232731026 0.3267066724
27 0.0816627291 0.2232731026
28 0.1133714808 0.0816627291
29 0.0563363093 0.1133714808
30 0.1151228569 0.0563363093
31 0.2187962569 0.1151228569
32 -0.0732443794 0.2187962569
33 0.0916817332 -0.0732443794
34 0.3378377599 0.0916817332
35 -0.4252069540 0.3378377599
36 -0.0933522118 -0.4252069540
37 -0.0353375987 -0.0933522118
38 0.0886119685 -0.0353375987
39 0.2221190089 0.0886119685
40 0.2192865064 0.2221190089
41 0.0545883586 0.2192865064
42 0.0850191594 0.0545883586
43 0.2416265577 0.0850191594
44 -0.0705227290 0.2416265577
45 0.0823609257 -0.0705227290
46 -0.0419211612 0.0823609257
47 -0.0083260425 -0.0419211612
48 0.2653388044 -0.0083260425
49 -0.1375395627 0.2653388044
50 -0.0384032316 -0.1375395627
51 0.2065558134 -0.0384032316
52 0.0090144856 0.2065558134
53 -0.0064583584 0.0090144856
54 0.0889435870 -0.0064583584
55 -0.0455684269 0.0889435870
56 0.2101700049 -0.0455684269
57 0.2158329818 0.2101700049
58 -0.2201845330 0.2158329818
59 0.2642272304 -0.2201845330
60 0.0015026689 0.2642272304
61 -0.0062228231 0.0015026689
62 -0.0458687526 -0.0062228231
63 -0.0375184987 -0.0458687526
64 0.1106748934 -0.0375184987
65 -0.0038339701 0.1106748934
66 -0.0144033604 -0.0038339701
67 -0.1249333449 -0.0144033604
68 0.0517719758 -0.1249333449
69 0.0372522752 0.0517719758
70 -0.0250951666 0.0372522752
71 0.1333621463 -0.0250951666
72 -0.0838978495 0.1333621463
73 -0.1404616436 -0.0838978495
74 0.0076916179 -0.1404616436
75 -0.1445466617 0.0076916179
76 0.0058462444 -0.1445466617
77 -0.0913536718 0.0058462444
78 0.0457418042 -0.0913536718
79 -0.1847849951 0.0457418042
80 -0.1216151834 -0.1847849951
81 -0.2183962937 -0.1216151834
82 -0.0753006094 -0.2183962937
83 -0.0230206365 -0.0753006094
84 -0.2248758248 -0.0230206365
85 0.0414110768 -0.2248758248
> plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
> lines(lowess(z))
> abline(lm(z))
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/7bec61290946634.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/8mnb91290946634.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/9mnb91290946634.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/freestat/rcomp/tmp/10mnb91290946634.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/freestat/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
+ myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ')
+ if (rownames(mysum$coefficients)[i] != '(Intercept)') {
+ myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
+ if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
+ }
+ }
> myeq <- paste(myeq, ' + e[t]')
> a<-table.row.start(a)
> a<-table.element(a, myeq)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/freestat/rcomp/tmp/11porf1290946634.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Variable',header=TRUE)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
> a<-table.element(a,'2-tail p-value',header=TRUE)
> a<-table.element(a,'1-tail p-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:k){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
+ a<-table.element(a,mysum$coefficients[i,1])
+ a<-table.element(a, round(mysum$coefficients[i,2],6))
+ a<-table.element(a, round(mysum$coefficients[i,3],4))
+ a<-table.element(a, round(mysum$coefficients[i,4],6))
+ a<-table.element(a, round(mysum$coefficients[i,4]/2,6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/html/freestat/rcomp/tmp/12b6ql1290946634.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple R',1,TRUE)
> a<-table.element(a, sqrt(mysum$r.squared))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'R-squared',1,TRUE)
> a<-table.element(a, mysum$r.squared)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Adjusted R-squared',1,TRUE)
> a<-table.element(a, mysum$adj.r.squared)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (value)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[1])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[2])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[3])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'p-value',1,TRUE)
> a<-table.element(a, 1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
> a<-table.element(a, mysum$sigma)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a, sum(myerror*myerror))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/freestat/rcomp/tmp/13pgoc1290946634.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Time or Index', 1, TRUE)
> a<-table.element(a, 'Actuals', 1, TRUE)
> a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
> a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
> a<-table.row.end(a)
> for (i in 1:n) {
+ a<-table.row.start(a)
+ a<-table.element(a,i, 1, TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]-mysum$resid[i])
+ a<-table.element(a,mysum$resid[i])
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/html/freestat/rcomp/tmp/14szmh1290946634.tab")
> if (n > n25) {
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'p-values',header=TRUE)
+ a<-table.element(a,'Alternative Hypothesis',3,header=TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'breakpoint index',header=TRUE)
+ a<-table.element(a,'greater',header=TRUE)
+ a<-table.element(a,'2-sided',header=TRUE)
+ a<-table.element(a,'less',header=TRUE)
+ a<-table.row.end(a)
+ for (mypoint in kp3:nmkm3) {
+ a<-table.row.start(a)
+ a<-table.element(a,mypoint,header=TRUE)
+ a<-table.element(a,gqarr[mypoint-kp3+1,1])
+ a<-table.element(a,gqarr[mypoint-kp3+1,2])
+ a<-table.element(a,gqarr[mypoint-kp3+1,3])
+ a<-table.row.end(a)
+ }
+ a<-table.end(a)
+ table.save(a,file="/var/www/html/freestat/rcomp/tmp/15eh351290946634.tab")
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'Description',header=TRUE)
+ a<-table.element(a,'# significant tests',header=TRUE)
+ a<-table.element(a,'% significant tests',header=TRUE)
+ a<-table.element(a,'OK/NOK',header=TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'1% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant1)
+ a<-table.element(a,numsignificant1/numgqtests)
+ if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'5% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant5)
+ a<-table.element(a,numsignificant5/numgqtests)
+ if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'10% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant10)
+ a<-table.element(a,numsignificant10/numgqtests)
+ if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.end(a)
+ table.save(a,file="/var/www/html/freestat/rcomp/tmp/16h0jb1290946634.tab")
+ }
>
> try(system("convert tmp/1xmex1290946634.ps tmp/1xmex1290946634.png",intern=TRUE))
character(0)
> try(system("convert tmp/2qvv01290946634.ps tmp/2qvv01290946634.png",intern=TRUE))
character(0)
> try(system("convert tmp/3qvv01290946634.ps tmp/3qvv01290946634.png",intern=TRUE))
character(0)
> try(system("convert tmp/4qvv01290946634.ps tmp/4qvv01290946634.png",intern=TRUE))
character(0)
> try(system("convert tmp/5qvv01290946634.ps tmp/5qvv01290946634.png",intern=TRUE))
character(0)
> try(system("convert tmp/6j5ul1290946634.ps tmp/6j5ul1290946634.png",intern=TRUE))
character(0)
> try(system("convert tmp/7bec61290946634.ps tmp/7bec61290946634.png",intern=TRUE))
character(0)
> try(system("convert tmp/8mnb91290946634.ps tmp/8mnb91290946634.png",intern=TRUE))
character(0)
> try(system("convert tmp/9mnb91290946634.ps tmp/9mnb91290946634.png",intern=TRUE))
character(0)
> try(system("convert tmp/10mnb91290946634.ps tmp/10mnb91290946634.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
4.216 2.495 4.513