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.
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(32.68
+ ,10967.87
+ ,0
+ ,31.54
+ ,10433.56
+ ,0
+ ,32.43
+ ,10665.78
+ ,0
+ ,26.54
+ ,10666.71
+ ,0
+ ,25.85
+ ,10682.74
+ ,0
+ ,27.6
+ ,10777.22
+ ,0
+ ,25.71
+ ,10052.6
+ ,0
+ ,25.38
+ ,10213.97
+ ,0
+ ,28.57
+ ,10546.82
+ ,0
+ ,27.64
+ ,10767.2
+ ,0
+ ,25.36
+ ,10444.5
+ ,0
+ ,25.9
+ ,10314.68
+ ,0
+ ,26.29
+ ,9042.56
+ ,1
+ ,21.74
+ ,9220.75
+ ,1
+ ,19.2
+ ,9721.84
+ ,1
+ ,19.32
+ ,9978.53
+ ,1
+ ,19.82
+ ,9923.81
+ ,1
+ ,20.36
+ ,9892.56
+ ,1
+ ,24.31
+ ,10500.98
+ ,1
+ ,25.97
+ ,10179.35
+ ,1
+ ,25.61
+ ,10080.48
+ ,1
+ ,24.67
+ ,9492.44
+ ,1
+ ,25.59
+ ,8616.49
+ ,1
+ ,26.09
+ ,8685.4
+ ,1
+ ,28.37
+ ,8160.67
+ ,1
+ ,27.34
+ ,8048.1
+ ,1
+ ,24.46
+ ,8641.21
+ ,1
+ ,27.46
+ ,8526.63
+ ,1
+ ,30.23
+ ,8474.21
+ ,1
+ ,32.33
+ ,7916.13
+ ,1
+ ,29.87
+ ,7977.64
+ ,1
+ ,24.87
+ ,8334.59
+ ,1
+ ,25.48
+ ,8623.36
+ ,1
+ ,27.28
+ ,9098.03
+ ,1
+ ,28.24
+ ,9154.34
+ ,1
+ ,29.58
+ ,9284.73
+ ,1
+ ,26.95
+ ,9492.49
+ ,1
+ ,29.08
+ ,9682.35
+ ,1
+ ,28.76
+ ,9762.12
+ ,1
+ ,29.59
+ ,10124.63
+ ,1
+ ,30.7
+ ,10540.05
+ ,1
+ ,30.52
+ ,10601.61
+ ,1
+ ,32.67
+ ,10323.73
+ ,1
+ ,33.19
+ ,10418.4
+ ,1
+ ,37.13
+ ,10092.96
+ ,1
+ ,35.54
+ ,10364.91
+ ,1
+ ,37.75
+ ,10152.09
+ ,1
+ ,41.84
+ ,10032.8
+ ,1
+ ,42.94
+ ,10204.59
+ ,1
+ ,49.14
+ ,10001.6
+ ,1
+ ,44.61
+ ,10411.75
+ ,1
+ ,40.22
+ ,10673.38
+ ,1
+ ,44.23
+ ,10539.51
+ ,1
+ ,45.85
+ ,10723.78
+ ,1
+ ,53.38
+ ,10682.06
+ ,1
+ ,53.26
+ ,10283.19
+ ,1
+ ,51.8
+ ,10377.18
+ ,1
+ ,55.3
+ ,10486.64
+ ,1
+ ,57.81
+ ,10545.38
+ ,1
+ ,63.96
+ ,10554.27
+ ,1
+ ,63.77
+ ,10532.54
+ ,1
+ ,59.15
+ ,10324.31
+ ,1
+ ,56.12
+ ,10695.25
+ ,1
+ ,57.42
+ ,10827.81
+ ,1
+ ,63.52
+ ,10872.48
+ ,1
+ ,61.71
+ ,10971.19
+ ,1
+ ,63.01
+ ,11145.65
+ ,1
+ ,68.18
+ ,11234.68
+ ,1
+ ,72.03
+ ,11333.88
+ ,1
+ ,69.75
+ ,10997.97
+ ,1
+ ,74.41
+ ,11036.89
+ ,1
+ ,74.33
+ ,11257.35
+ ,1
+ ,64.24
+ ,11533.59
+ ,1
+ ,60.03
+ ,11963.12
+ ,1
+ ,59.44
+ ,12185.15
+ ,1
+ ,62.5
+ ,12377.62
+ ,1
+ ,55.04
+ ,12512.89
+ ,1
+ ,58.34
+ ,12631.48
+ ,1
+ ,61.92
+ ,12268.53
+ ,1
+ ,67.65
+ ,12754.8
+ ,1
+ ,67.68
+ ,13407.75
+ ,1
+ ,70.3
+ ,13480.21
+ ,1
+ ,75.26
+ ,13673.28
+ ,1
+ ,71.44
+ ,13239.71
+ ,1
+ ,76.36
+ ,13557.69
+ ,1
+ ,81.71
+ ,13901.28
+ ,1
+ ,92.6
+ ,13200.58
+ ,1
+ ,90.6
+ ,13406.97
+ ,1
+ ,92.23
+ ,12538.12
+ ,1
+ ,94.09
+ ,12419.57
+ ,1
+ ,102.79
+ ,12193.88
+ ,1
+ ,109.65
+ ,12656.63
+ ,1
+ ,124.05
+ ,12812.48
+ ,1
+ ,132.69
+ ,12056.67
+ ,1
+ ,135.81
+ ,11322.38
+ ,1
+ ,116.07
+ ,11530.75
+ ,1
+ ,101.42
+ ,11114.08
+ ,1
+ ,75.73
+ ,9181.73
+ ,1
+ ,55.48
+ ,8614.55
+ ,1)
+ ,dim=c(3
+ ,99)
+ ,dimnames=list(c('Olieprijs'
+ ,'DowJones'
+ ,'Dummy(9/11)')
+ ,1:99))
> y <- array(NA,dim=c(3,99),dimnames=list(c('Olieprijs','DowJones','Dummy(9/11)'),1:99))
> 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
Olieprijs DowJones Dummy(9/11) M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 32.68 10967.87 0 1 0 0 0 0 0 0 0 0 0 0 1
2 31.54 10433.56 0 0 1 0 0 0 0 0 0 0 0 0 2
3 32.43 10665.78 0 0 0 1 0 0 0 0 0 0 0 0 3
4 26.54 10666.71 0 0 0 0 1 0 0 0 0 0 0 0 4
5 25.85 10682.74 0 0 0 0 0 1 0 0 0 0 0 0 5
6 27.60 10777.22 0 0 0 0 0 0 1 0 0 0 0 0 6
7 25.71 10052.60 0 0 0 0 0 0 0 1 0 0 0 0 7
8 25.38 10213.97 0 0 0 0 0 0 0 0 1 0 0 0 8
9 28.57 10546.82 0 0 0 0 0 0 0 0 0 1 0 0 9
10 27.64 10767.20 0 0 0 0 0 0 0 0 0 0 1 0 10
11 25.36 10444.50 0 0 0 0 0 0 0 0 0 0 0 1 11
12 25.90 10314.68 0 0 0 0 0 0 0 0 0 0 0 0 12
13 26.29 9042.56 1 1 0 0 0 0 0 0 0 0 0 0 13
14 21.74 9220.75 1 0 1 0 0 0 0 0 0 0 0 0 14
15 19.20 9721.84 1 0 0 1 0 0 0 0 0 0 0 0 15
16 19.32 9978.53 1 0 0 0 1 0 0 0 0 0 0 0 16
17 19.82 9923.81 1 0 0 0 0 1 0 0 0 0 0 0 17
18 20.36 9892.56 1 0 0 0 0 0 1 0 0 0 0 0 18
19 24.31 10500.98 1 0 0 0 0 0 0 1 0 0 0 0 19
20 25.97 10179.35 1 0 0 0 0 0 0 0 1 0 0 0 20
21 25.61 10080.48 1 0 0 0 0 0 0 0 0 1 0 0 21
22 24.67 9492.44 1 0 0 0 0 0 0 0 0 0 1 0 22
23 25.59 8616.49 1 0 0 0 0 0 0 0 0 0 0 1 23
24 26.09 8685.40 1 0 0 0 0 0 0 0 0 0 0 0 24
25 28.37 8160.67 1 1 0 0 0 0 0 0 0 0 0 0 25
26 27.34 8048.10 1 0 1 0 0 0 0 0 0 0 0 0 26
27 24.46 8641.21 1 0 0 1 0 0 0 0 0 0 0 0 27
28 27.46 8526.63 1 0 0 0 1 0 0 0 0 0 0 0 28
29 30.23 8474.21 1 0 0 0 0 1 0 0 0 0 0 0 29
30 32.33 7916.13 1 0 0 0 0 0 1 0 0 0 0 0 30
31 29.87 7977.64 1 0 0 0 0 0 0 1 0 0 0 0 31
32 24.87 8334.59 1 0 0 0 0 0 0 0 1 0 0 0 32
33 25.48 8623.36 1 0 0 0 0 0 0 0 0 1 0 0 33
34 27.28 9098.03 1 0 0 0 0 0 0 0 0 0 1 0 34
35 28.24 9154.34 1 0 0 0 0 0 0 0 0 0 0 1 35
36 29.58 9284.73 1 0 0 0 0 0 0 0 0 0 0 0 36
37 26.95 9492.49 1 1 0 0 0 0 0 0 0 0 0 0 37
38 29.08 9682.35 1 0 1 0 0 0 0 0 0 0 0 0 38
39 28.76 9762.12 1 0 0 1 0 0 0 0 0 0 0 0 39
40 29.59 10124.63 1 0 0 0 1 0 0 0 0 0 0 0 40
41 30.70 10540.05 1 0 0 0 0 1 0 0 0 0 0 0 41
42 30.52 10601.61 1 0 0 0 0 0 1 0 0 0 0 0 42
43 32.67 10323.73 1 0 0 0 0 0 0 1 0 0 0 0 43
44 33.19 10418.40 1 0 0 0 0 0 0 0 1 0 0 0 44
45 37.13 10092.96 1 0 0 0 0 0 0 0 0 1 0 0 45
46 35.54 10364.91 1 0 0 0 0 0 0 0 0 0 1 0 46
47 37.75 10152.09 1 0 0 0 0 0 0 0 0 0 0 1 47
48 41.84 10032.80 1 0 0 0 0 0 0 0 0 0 0 0 48
49 42.94 10204.59 1 1 0 0 0 0 0 0 0 0 0 0 49
50 49.14 10001.60 1 0 1 0 0 0 0 0 0 0 0 0 50
51 44.61 10411.75 1 0 0 1 0 0 0 0 0 0 0 0 51
52 40.22 10673.38 1 0 0 0 1 0 0 0 0 0 0 0 52
53 44.23 10539.51 1 0 0 0 0 1 0 0 0 0 0 0 53
54 45.85 10723.78 1 0 0 0 0 0 1 0 0 0 0 0 54
55 53.38 10682.06 1 0 0 0 0 0 0 1 0 0 0 0 55
56 53.26 10283.19 1 0 0 0 0 0 0 0 1 0 0 0 56
57 51.80 10377.18 1 0 0 0 0 0 0 0 0 1 0 0 57
58 55.30 10486.64 1 0 0 0 0 0 0 0 0 0 1 0 58
59 57.81 10545.38 1 0 0 0 0 0 0 0 0 0 0 1 59
60 63.96 10554.27 1 0 0 0 0 0 0 0 0 0 0 0 60
61 63.77 10532.54 1 1 0 0 0 0 0 0 0 0 0 0 61
62 59.15 10324.31 1 0 1 0 0 0 0 0 0 0 0 0 62
63 56.12 10695.25 1 0 0 1 0 0 0 0 0 0 0 0 63
64 57.42 10827.81 1 0 0 0 1 0 0 0 0 0 0 0 64
65 63.52 10872.48 1 0 0 0 0 1 0 0 0 0 0 0 65
66 61.71 10971.19 1 0 0 0 0 0 1 0 0 0 0 0 66
67 63.01 11145.65 1 0 0 0 0 0 0 1 0 0 0 0 67
68 68.18 11234.68 1 0 0 0 0 0 0 0 1 0 0 0 68
69 72.03 11333.88 1 0 0 0 0 0 0 0 0 1 0 0 69
70 69.75 10997.97 1 0 0 0 0 0 0 0 0 0 1 0 70
71 74.41 11036.89 1 0 0 0 0 0 0 0 0 0 0 1 71
72 74.33 11257.35 1 0 0 0 0 0 0 0 0 0 0 0 72
73 64.24 11533.59 1 1 0 0 0 0 0 0 0 0 0 0 73
74 60.03 11963.12 1 0 1 0 0 0 0 0 0 0 0 0 74
75 59.44 12185.15 1 0 0 1 0 0 0 0 0 0 0 0 75
76 62.50 12377.62 1 0 0 0 1 0 0 0 0 0 0 0 76
77 55.04 12512.89 1 0 0 0 0 1 0 0 0 0 0 0 77
78 58.34 12631.48 1 0 0 0 0 0 1 0 0 0 0 0 78
79 61.92 12268.53 1 0 0 0 0 0 0 1 0 0 0 0 79
80 67.65 12754.80 1 0 0 0 0 0 0 0 1 0 0 0 80
81 67.68 13407.75 1 0 0 0 0 0 0 0 0 1 0 0 81
82 70.30 13480.21 1 0 0 0 0 0 0 0 0 0 1 0 82
83 75.26 13673.28 1 0 0 0 0 0 0 0 0 0 0 1 83
84 71.44 13239.71 1 0 0 0 0 0 0 0 0 0 0 0 84
85 76.36 13557.69 1 1 0 0 0 0 0 0 0 0 0 0 85
86 81.71 13901.28 1 0 1 0 0 0 0 0 0 0 0 0 86
87 92.60 13200.58 1 0 0 1 0 0 0 0 0 0 0 0 87
88 90.60 13406.97 1 0 0 0 1 0 0 0 0 0 0 0 88
89 92.23 12538.12 1 0 0 0 0 1 0 0 0 0 0 0 89
90 94.09 12419.57 1 0 0 0 0 0 1 0 0 0 0 0 90
91 102.79 12193.88 1 0 0 0 0 0 0 1 0 0 0 0 91
92 109.65 12656.63 1 0 0 0 0 0 0 0 1 0 0 0 92
93 124.05 12812.48 1 0 0 0 0 0 0 0 0 1 0 0 93
94 132.69 12056.67 1 0 0 0 0 0 0 0 0 0 1 0 94
95 135.81 11322.38 1 0 0 0 0 0 0 0 0 0 0 1 95
96 116.07 11530.75 1 0 0 0 0 0 0 0 0 0 0 0 96
97 101.42 11114.08 1 1 0 0 0 0 0 0 0 0 0 0 97
98 75.73 9181.73 1 0 1 0 0 0 0 0 0 0 0 0 98
99 55.48 8614.55 1 0 0 1 0 0 0 0 0 0 0 0 99
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) DowJones `Dummy(9/11)` M1 M2
11.917089 0.001130 -20.945328 0.382293 -3.384150
M3 M4 M5 M6 M7
-6.948364 -4.691191 -4.560961 -4.328671 -2.296223
M8 M9 M10 M11 t
-1.552867 0.366271 0.857324 2.307488 0.936438
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-30.9865 -7.1264 -0.0591 5.5339 40.7731
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 11.917089 14.185746 0.840 0.403251
DowJones 0.001130 0.001318 0.857 0.393781
`Dummy(9/11)` -20.945328 5.199131 -4.029 0.000123 ***
M1 0.382293 5.688499 0.067 0.946579
M2 -3.384150 5.683693 -0.595 0.553168
M3 -6.948364 5.680549 -1.223 0.224680
M4 -4.691191 5.904899 -0.794 0.429168
M5 -4.560961 5.885013 -0.775 0.440508
M6 -4.328671 5.873888 -0.737 0.463216
M7 -2.296223 5.857311 -0.392 0.696031
M8 -1.552867 5.861558 -0.265 0.791717
M9 0.366271 5.871855 0.062 0.950410
M10 0.857324 5.858196 0.146 0.883999
M11 2.307488 5.842513 0.395 0.693882
t 0.936438 0.078526 11.925 < 2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 11.68 on 84 degrees of freedom
Multiple R-squared: 0.8441, Adjusted R-squared: 0.8182
F-statistic: 32.5 on 14 and 84 DF, p-value: < 2.2e-16
> if (n > n25) {
+ kp3 <- k + 3
+ nmkm3 <- n - k - 3
+ gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
+ numgqtests <- 0
+ numsignificant1 <- 0
+ numsignificant5 <- 0
+ numsignificant10 <- 0
+ for (mypoint in kp3:nmkm3) {
+ j <- 0
+ numgqtests <- numgqtests + 1
+ for (myalt in c('greater', 'two.sided', 'less')) {
+ j <- j + 1
+ gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
+ }
+ if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
+ }
+ gqarr
+ }
[,1] [,2] [,3]
[1,] 1.142766e-02 2.285531e-02 0.9885723
[2,] 4.266922e-03 8.533845e-03 0.9957331
[3,] 1.875573e-03 3.751145e-03 0.9981244
[4,] 4.476331e-04 8.952663e-04 0.9995524
[5,] 1.931982e-04 3.863965e-04 0.9998068
[6,] 2.327827e-04 4.655653e-04 0.9997672
[7,] 1.222394e-04 2.444788e-04 0.9998778
[8,] 3.183903e-05 6.367806e-05 0.9999682
[9,] 8.744020e-06 1.748804e-05 0.9999913
[10,] 2.381082e-06 4.762164e-06 0.9999976
[11,] 1.185662e-06 2.371324e-06 0.9999988
[12,] 1.035413e-06 2.070827e-06 0.9999990
[13,] 8.260342e-07 1.652068e-06 0.9999992
[14,] 2.387524e-07 4.775049e-07 0.9999998
[15,] 9.141089e-08 1.828218e-07 0.9999999
[16,] 3.634349e-08 7.268699e-08 1.0000000
[17,] 8.807268e-09 1.761454e-08 1.0000000
[18,] 2.209215e-09 4.418430e-09 1.0000000
[19,] 5.487030e-10 1.097406e-09 1.0000000
[20,] 4.361065e-10 8.722131e-10 1.0000000
[21,] 1.046231e-10 2.092462e-10 1.0000000
[22,] 2.717526e-11 5.435052e-11 1.0000000
[23,] 7.771769e-12 1.554354e-11 1.0000000
[24,] 2.214545e-12 4.429090e-12 1.0000000
[25,] 4.726851e-13 9.453702e-13 1.0000000
[26,] 1.258111e-13 2.516222e-13 1.0000000
[27,] 4.793675e-14 9.587351e-14 1.0000000
[28,] 3.989487e-14 7.978973e-14 1.0000000
[29,] 1.686234e-14 3.372468e-14 1.0000000
[30,] 1.519621e-14 3.039242e-14 1.0000000
[31,] 3.708245e-14 7.416489e-14 1.0000000
[32,] 1.524871e-14 3.049743e-14 1.0000000
[33,] 1.614785e-13 3.229570e-13 1.0000000
[34,] 1.749530e-13 3.499060e-13 1.0000000
[35,] 4.659564e-14 9.319129e-14 1.0000000
[36,] 2.106645e-14 4.213289e-14 1.0000000
[37,] 9.449632e-15 1.889926e-14 1.0000000
[38,] 4.962671e-14 9.925341e-14 1.0000000
[39,] 1.749456e-13 3.498912e-13 1.0000000
[40,] 1.317330e-13 2.634660e-13 1.0000000
[41,] 2.627146e-13 5.254292e-13 1.0000000
[42,] 6.567793e-13 1.313559e-12 1.0000000
[43,] 4.666499e-12 9.332999e-12 1.0000000
[44,] 5.543724e-12 1.108745e-11 1.0000000
[45,] 4.162142e-12 8.324283e-12 1.0000000
[46,] 3.718482e-12 7.436963e-12 1.0000000
[47,] 1.664567e-12 3.329134e-12 1.0000000
[48,] 2.675179e-12 5.350358e-12 1.0000000
[49,] 1.997777e-12 3.995553e-12 1.0000000
[50,] 1.018995e-12 2.037991e-12 1.0000000
[51,] 1.252409e-12 2.504819e-12 1.0000000
[52,] 2.222444e-12 4.444888e-12 1.0000000
[53,] 1.621473e-12 3.242946e-12 1.0000000
[54,] 2.149455e-12 4.298910e-12 1.0000000
[55,] 6.247509e-12 1.249502e-11 1.0000000
[56,] 2.126837e-11 4.253673e-11 1.0000000
[57,] 4.440227e-10 8.880454e-10 1.0000000
[58,] 3.768126e-08 7.536251e-08 1.0000000
[59,] 4.571244e-07 9.142488e-07 0.9999995
[60,] 1.303336e-06 2.606673e-06 0.9999987
[61,] 3.276360e-06 6.552719e-06 0.9999967
[62,] 1.151120e-05 2.302239e-05 0.9999885
[63,] 3.864108e-04 7.728217e-04 0.9996136
[64,] 9.783257e-04 1.956651e-03 0.9990217
> postscript(file="/var/www/html/rcomp/tmp/1gg6v1229183101.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
> points(x[,1]-mysum$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/27igi1229183101.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/3rmoj1229183101.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/45xe51229183101.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5kg5n1229183101.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 = 99
Frequency = 1
1 2 3 4 5 6
7.04885974 9.34271367 12.59804675 3.51338374 1.73859933 2.21309449
7 8 9 10 11 12
-1.82686342 -4.01902943 -4.06077594 -6.66732903 -10.96923271 -8.91146718
13 14 15 16 17 18
12.54281453 10.62143776 10.14290786 6.77919811 6.27437170 5.68096041
19 20 21 22 23 24
5.97446954 6.31816518 3.21432632 1.51140776 1.03475865 2.82792980
25 26 27 28 29 30
4.38222159 6.30944676 5.38692060 5.32280103 7.08537527 8.64736004
31 32 33 34 35 36
3.14895861 -3.93424182 -6.50617139 -6.67010990 -8.16035111 -5.59666147
37 38 39 40 41 42
-9.78019205 -5.03475765 -2.81713345 -5.59043550 -6.01658986 -7.43489022
43 44 45 46 47 48
-7.93973060 -9.20651572 -7.75429687 -11.07913171 -11.01521609 -5.41935102
49 50 51 52 53 54
-5.83223016 3.42718302 1.06142881 -6.81786388 -3.72323905 -3.48021991
55 56 57 58 59 60
1.12804387 -0.22096783 -4.64276710 -2.69396414 -2.63695161 4.87405105
61 62 63 64 65 66
3.38987822 1.83521338 1.01377229 -1.02965215 3.95319599 0.86291062
67 68 69 70 71 72
-1.00314107 2.38644785 3.26876050 -0.05910236 2.17030971 3.21220689
73 74 75 76 77 78
-8.50871625 -10.37414451 -8.58729521 -8.93842683 -17.61797013 -15.62072285
79 80 81 82 83 84
-14.59942152 -11.09877272 -14.66227972 -13.55166126 -11.19646156 -13.15541346
85 86 87 88 89 90
-9.91350899 -2.12181230 12.18785879 6.76099549 8.30625676 9.13150742
91 92 93 94 95 96
15.11768459 19.77491447 31.14320422 39.20989065 40.77314472 22.16870539
97 98 99
6.67087335 -14.00528013 -30.98650645
> postscript(file="/var/www/html/rcomp/tmp/626no1229183101.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 = 99
Frequency = 1
lag(myerror, k = 1) myerror
0 7.04885974 NA
1 9.34271367 7.04885974
2 12.59804675 9.34271367
3 3.51338374 12.59804675
4 1.73859933 3.51338374
5 2.21309449 1.73859933
6 -1.82686342 2.21309449
7 -4.01902943 -1.82686342
8 -4.06077594 -4.01902943
9 -6.66732903 -4.06077594
10 -10.96923271 -6.66732903
11 -8.91146718 -10.96923271
12 12.54281453 -8.91146718
13 10.62143776 12.54281453
14 10.14290786 10.62143776
15 6.77919811 10.14290786
16 6.27437170 6.77919811
17 5.68096041 6.27437170
18 5.97446954 5.68096041
19 6.31816518 5.97446954
20 3.21432632 6.31816518
21 1.51140776 3.21432632
22 1.03475865 1.51140776
23 2.82792980 1.03475865
24 4.38222159 2.82792980
25 6.30944676 4.38222159
26 5.38692060 6.30944676
27 5.32280103 5.38692060
28 7.08537527 5.32280103
29 8.64736004 7.08537527
30 3.14895861 8.64736004
31 -3.93424182 3.14895861
32 -6.50617139 -3.93424182
33 -6.67010990 -6.50617139
34 -8.16035111 -6.67010990
35 -5.59666147 -8.16035111
36 -9.78019205 -5.59666147
37 -5.03475765 -9.78019205
38 -2.81713345 -5.03475765
39 -5.59043550 -2.81713345
40 -6.01658986 -5.59043550
41 -7.43489022 -6.01658986
42 -7.93973060 -7.43489022
43 -9.20651572 -7.93973060
44 -7.75429687 -9.20651572
45 -11.07913171 -7.75429687
46 -11.01521609 -11.07913171
47 -5.41935102 -11.01521609
48 -5.83223016 -5.41935102
49 3.42718302 -5.83223016
50 1.06142881 3.42718302
51 -6.81786388 1.06142881
52 -3.72323905 -6.81786388
53 -3.48021991 -3.72323905
54 1.12804387 -3.48021991
55 -0.22096783 1.12804387
56 -4.64276710 -0.22096783
57 -2.69396414 -4.64276710
58 -2.63695161 -2.69396414
59 4.87405105 -2.63695161
60 3.38987822 4.87405105
61 1.83521338 3.38987822
62 1.01377229 1.83521338
63 -1.02965215 1.01377229
64 3.95319599 -1.02965215
65 0.86291062 3.95319599
66 -1.00314107 0.86291062
67 2.38644785 -1.00314107
68 3.26876050 2.38644785
69 -0.05910236 3.26876050
70 2.17030971 -0.05910236
71 3.21220689 2.17030971
72 -8.50871625 3.21220689
73 -10.37414451 -8.50871625
74 -8.58729521 -10.37414451
75 -8.93842683 -8.58729521
76 -17.61797013 -8.93842683
77 -15.62072285 -17.61797013
78 -14.59942152 -15.62072285
79 -11.09877272 -14.59942152
80 -14.66227972 -11.09877272
81 -13.55166126 -14.66227972
82 -11.19646156 -13.55166126
83 -13.15541346 -11.19646156
84 -9.91350899 -13.15541346
85 -2.12181230 -9.91350899
86 12.18785879 -2.12181230
87 6.76099549 12.18785879
88 8.30625676 6.76099549
89 9.13150742 8.30625676
90 15.11768459 9.13150742
91 19.77491447 15.11768459
92 31.14320422 19.77491447
93 39.20989065 31.14320422
94 40.77314472 39.20989065
95 22.16870539 40.77314472
96 6.67087335 22.16870539
97 -14.00528013 6.67087335
98 -30.98650645 -14.00528013
99 NA -30.98650645
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 9.34271367 7.04885974
[2,] 12.59804675 9.34271367
[3,] 3.51338374 12.59804675
[4,] 1.73859933 3.51338374
[5,] 2.21309449 1.73859933
[6,] -1.82686342 2.21309449
[7,] -4.01902943 -1.82686342
[8,] -4.06077594 -4.01902943
[9,] -6.66732903 -4.06077594
[10,] -10.96923271 -6.66732903
[11,] -8.91146718 -10.96923271
[12,] 12.54281453 -8.91146718
[13,] 10.62143776 12.54281453
[14,] 10.14290786 10.62143776
[15,] 6.77919811 10.14290786
[16,] 6.27437170 6.77919811
[17,] 5.68096041 6.27437170
[18,] 5.97446954 5.68096041
[19,] 6.31816518 5.97446954
[20,] 3.21432632 6.31816518
[21,] 1.51140776 3.21432632
[22,] 1.03475865 1.51140776
[23,] 2.82792980 1.03475865
[24,] 4.38222159 2.82792980
[25,] 6.30944676 4.38222159
[26,] 5.38692060 6.30944676
[27,] 5.32280103 5.38692060
[28,] 7.08537527 5.32280103
[29,] 8.64736004 7.08537527
[30,] 3.14895861 8.64736004
[31,] -3.93424182 3.14895861
[32,] -6.50617139 -3.93424182
[33,] -6.67010990 -6.50617139
[34,] -8.16035111 -6.67010990
[35,] -5.59666147 -8.16035111
[36,] -9.78019205 -5.59666147
[37,] -5.03475765 -9.78019205
[38,] -2.81713345 -5.03475765
[39,] -5.59043550 -2.81713345
[40,] -6.01658986 -5.59043550
[41,] -7.43489022 -6.01658986
[42,] -7.93973060 -7.43489022
[43,] -9.20651572 -7.93973060
[44,] -7.75429687 -9.20651572
[45,] -11.07913171 -7.75429687
[46,] -11.01521609 -11.07913171
[47,] -5.41935102 -11.01521609
[48,] -5.83223016 -5.41935102
[49,] 3.42718302 -5.83223016
[50,] 1.06142881 3.42718302
[51,] -6.81786388 1.06142881
[52,] -3.72323905 -6.81786388
[53,] -3.48021991 -3.72323905
[54,] 1.12804387 -3.48021991
[55,] -0.22096783 1.12804387
[56,] -4.64276710 -0.22096783
[57,] -2.69396414 -4.64276710
[58,] -2.63695161 -2.69396414
[59,] 4.87405105 -2.63695161
[60,] 3.38987822 4.87405105
[61,] 1.83521338 3.38987822
[62,] 1.01377229 1.83521338
[63,] -1.02965215 1.01377229
[64,] 3.95319599 -1.02965215
[65,] 0.86291062 3.95319599
[66,] -1.00314107 0.86291062
[67,] 2.38644785 -1.00314107
[68,] 3.26876050 2.38644785
[69,] -0.05910236 3.26876050
[70,] 2.17030971 -0.05910236
[71,] 3.21220689 2.17030971
[72,] -8.50871625 3.21220689
[73,] -10.37414451 -8.50871625
[74,] -8.58729521 -10.37414451
[75,] -8.93842683 -8.58729521
[76,] -17.61797013 -8.93842683
[77,] -15.62072285 -17.61797013
[78,] -14.59942152 -15.62072285
[79,] -11.09877272 -14.59942152
[80,] -14.66227972 -11.09877272
[81,] -13.55166126 -14.66227972
[82,] -11.19646156 -13.55166126
[83,] -13.15541346 -11.19646156
[84,] -9.91350899 -13.15541346
[85,] -2.12181230 -9.91350899
[86,] 12.18785879 -2.12181230
[87,] 6.76099549 12.18785879
[88,] 8.30625676 6.76099549
[89,] 9.13150742 8.30625676
[90,] 15.11768459 9.13150742
[91,] 19.77491447 15.11768459
[92,] 31.14320422 19.77491447
[93,] 39.20989065 31.14320422
[94,] 40.77314472 39.20989065
[95,] 22.16870539 40.77314472
[96,] 6.67087335 22.16870539
[97,] -14.00528013 6.67087335
[98,] -30.98650645 -14.00528013
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 9.34271367 7.04885974
2 12.59804675 9.34271367
3 3.51338374 12.59804675
4 1.73859933 3.51338374
5 2.21309449 1.73859933
6 -1.82686342 2.21309449
7 -4.01902943 -1.82686342
8 -4.06077594 -4.01902943
9 -6.66732903 -4.06077594
10 -10.96923271 -6.66732903
11 -8.91146718 -10.96923271
12 12.54281453 -8.91146718
13 10.62143776 12.54281453
14 10.14290786 10.62143776
15 6.77919811 10.14290786
16 6.27437170 6.77919811
17 5.68096041 6.27437170
18 5.97446954 5.68096041
19 6.31816518 5.97446954
20 3.21432632 6.31816518
21 1.51140776 3.21432632
22 1.03475865 1.51140776
23 2.82792980 1.03475865
24 4.38222159 2.82792980
25 6.30944676 4.38222159
26 5.38692060 6.30944676
27 5.32280103 5.38692060
28 7.08537527 5.32280103
29 8.64736004 7.08537527
30 3.14895861 8.64736004
31 -3.93424182 3.14895861
32 -6.50617139 -3.93424182
33 -6.67010990 -6.50617139
34 -8.16035111 -6.67010990
35 -5.59666147 -8.16035111
36 -9.78019205 -5.59666147
37 -5.03475765 -9.78019205
38 -2.81713345 -5.03475765
39 -5.59043550 -2.81713345
40 -6.01658986 -5.59043550
41 -7.43489022 -6.01658986
42 -7.93973060 -7.43489022
43 -9.20651572 -7.93973060
44 -7.75429687 -9.20651572
45 -11.07913171 -7.75429687
46 -11.01521609 -11.07913171
47 -5.41935102 -11.01521609
48 -5.83223016 -5.41935102
49 3.42718302 -5.83223016
50 1.06142881 3.42718302
51 -6.81786388 1.06142881
52 -3.72323905 -6.81786388
53 -3.48021991 -3.72323905
54 1.12804387 -3.48021991
55 -0.22096783 1.12804387
56 -4.64276710 -0.22096783
57 -2.69396414 -4.64276710
58 -2.63695161 -2.69396414
59 4.87405105 -2.63695161
60 3.38987822 4.87405105
61 1.83521338 3.38987822
62 1.01377229 1.83521338
63 -1.02965215 1.01377229
64 3.95319599 -1.02965215
65 0.86291062 3.95319599
66 -1.00314107 0.86291062
67 2.38644785 -1.00314107
68 3.26876050 2.38644785
69 -0.05910236 3.26876050
70 2.17030971 -0.05910236
71 3.21220689 2.17030971
72 -8.50871625 3.21220689
73 -10.37414451 -8.50871625
74 -8.58729521 -10.37414451
75 -8.93842683 -8.58729521
76 -17.61797013 -8.93842683
77 -15.62072285 -17.61797013
78 -14.59942152 -15.62072285
79 -11.09877272 -14.59942152
80 -14.66227972 -11.09877272
81 -13.55166126 -14.66227972
82 -11.19646156 -13.55166126
83 -13.15541346 -11.19646156
84 -9.91350899 -13.15541346
85 -2.12181230 -9.91350899
86 12.18785879 -2.12181230
87 6.76099549 12.18785879
88 8.30625676 6.76099549
89 9.13150742 8.30625676
90 15.11768459 9.13150742
91 19.77491447 15.11768459
92 31.14320422 19.77491447
93 39.20989065 31.14320422
94 40.77314472 39.20989065
95 22.16870539 40.77314472
96 6.67087335 22.16870539
97 -14.00528013 6.67087335
98 -30.98650645 -14.00528013
> 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/76to61229183101.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/84wgv1229183101.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9ypcd1229183101.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/104oc11229183101.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
+ myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ')
+ if (rownames(mysum$coefficients)[i] != '(Intercept)') {
+ myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
+ if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
+ }
+ }
> myeq <- paste(myeq, ' + e[t]')
> a<-table.row.start(a)
> a<-table.element(a, myeq)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/110tp41229183101.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/122k711229183101.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/139y371229183102.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/141asc1229183102.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/15ct4z1229183102.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/16egjd1229183102.tab")
+ }
>
> system("convert tmp/1gg6v1229183101.ps tmp/1gg6v1229183101.png")
> system("convert tmp/27igi1229183101.ps tmp/27igi1229183101.png")
> system("convert tmp/3rmoj1229183101.ps tmp/3rmoj1229183101.png")
> system("convert tmp/45xe51229183101.ps tmp/45xe51229183101.png")
> system("convert tmp/5kg5n1229183101.ps tmp/5kg5n1229183101.png")
> system("convert tmp/626no1229183101.ps tmp/626no1229183101.png")
> system("convert tmp/76to61229183101.ps tmp/76to61229183101.png")
> system("convert tmp/84wgv1229183101.ps tmp/84wgv1229183101.png")
> system("convert tmp/9ypcd1229183101.ps tmp/9ypcd1229183101.png")
> system("convert tmp/104oc11229183101.ps tmp/104oc11229183101.png")
>
>
> proc.time()
user system elapsed
2.997 1.684 3.962