R version 2.9.0 (2009-04-17)
Copyright (C) 2009 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.
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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(100.01
+ ,0
+ ,103.84
+ ,0
+ ,104.48
+ ,0
+ ,95.43
+ ,0
+ ,104.80
+ ,0
+ ,108.64
+ ,0
+ ,105.65
+ ,0
+ ,108.42
+ ,0
+ ,115.35
+ ,0
+ ,113.64
+ ,0
+ ,115.24
+ ,0
+ ,100.33
+ ,0
+ ,101.29
+ ,0
+ ,104.48
+ ,0
+ ,99.26
+ ,0
+ ,100.11
+ ,0
+ ,103.52
+ ,0
+ ,101.18
+ ,0
+ ,96.39
+ ,0
+ ,97.56
+ ,0
+ ,96.39
+ ,0
+ ,85.10
+ ,0
+ ,79.77
+ ,0
+ ,79.13
+ ,0
+ ,80.84
+ ,0
+ ,82.75
+ ,0
+ ,92.55
+ ,0
+ ,96.60
+ ,0
+ ,96.92
+ ,0
+ ,95.32
+ ,0
+ ,98.52
+ ,0
+ ,100.22
+ ,0
+ ,104.91
+ ,0
+ ,103.10
+ ,0
+ ,97.13
+ ,0
+ ,103.42
+ ,0
+ ,111.72
+ ,0
+ ,118.11
+ ,0
+ ,111.62
+ ,0
+ ,100.22
+ ,0
+ ,102.03
+ ,0
+ ,105.76
+ ,0
+ ,107.68
+ ,0
+ ,110.77
+ ,0
+ ,105.44
+ ,0
+ ,112.26
+ ,0
+ ,114.07
+ ,0
+ ,117.90
+ ,0
+ ,124.72
+ ,0
+ ,126.42
+ ,0
+ ,134.73
+ ,0
+ ,135.79
+ ,0
+ ,143.36
+ ,0
+ ,140.37
+ ,0
+ ,144.74
+ ,0
+ ,151.98
+ ,0
+ ,150.92
+ ,0
+ ,163.38
+ ,0
+ ,154.43
+ ,0
+ ,146.66
+ ,0
+ ,157.95
+ ,0
+ ,162.10
+ ,0
+ ,180.42
+ ,0
+ ,179.57
+ ,0
+ ,171.58
+ ,0
+ ,185.43
+ ,0
+ ,190.64
+ ,0
+ ,203.00
+ ,0
+ ,202.36
+ ,0
+ ,193.41
+ ,0
+ ,186.17
+ ,0
+ ,192.24
+ ,0
+ ,209.60
+ ,0
+ ,206.41
+ ,0
+ ,209.82
+ ,0
+ ,230.37
+ ,0
+ ,235.80
+ ,0
+ ,232.07
+ ,0
+ ,244.64
+ ,0
+ ,242.19
+ ,0
+ ,217.48
+ ,0
+ ,209.39
+ ,0
+ ,211.73
+ ,0
+ ,221.00
+ ,0
+ ,203.11
+ ,0
+ ,214.71
+ ,0
+ ,224.19
+ ,0
+ ,238.04
+ ,0
+ ,238.36
+ ,0
+ ,246.24
+ ,0
+ ,259.87
+ ,0
+ ,249.97
+ ,0
+ ,266.48
+ ,0
+ ,282.98
+ ,0
+ ,306.31
+ ,0
+ ,301.73
+ ,1
+ ,314.62
+ ,1
+ ,332.62
+ ,1
+ ,355.51
+ ,1
+ ,370.32
+ ,1
+ ,408.13
+ ,1
+ ,433.58
+ ,1
+ ,440.51
+ ,1
+ ,386.29
+ ,1
+ ,342.84
+ ,1
+ ,254.97
+ ,1
+ ,203.42
+ ,1
+ ,170.09
+ ,1
+ ,174.03
+ ,1
+ ,167.85
+ ,1
+ ,177.01
+ ,1
+ ,188.19
+ ,1
+ ,211.20
+ ,1
+ ,240.91
+ ,1
+ ,230.26
+ ,1
+ ,251.25
+ ,1
+ ,241.66
+ ,1)
+ ,dim=c(2
+ ,117)
+ ,dimnames=list(c('Y'
+ ,'X')
+ ,1:117))
> y <- array(NA,dim=c(2,117),dimnames=list(c('Y','X'),1:117))
> 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 M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 100.01 0 1 0 0 0 0 0 0 0 0 0 0 1
2 103.84 0 0 1 0 0 0 0 0 0 0 0 0 2
3 104.48 0 0 0 1 0 0 0 0 0 0 0 0 3
4 95.43 0 0 0 0 1 0 0 0 0 0 0 0 4
5 104.80 0 0 0 0 0 1 0 0 0 0 0 0 5
6 108.64 0 0 0 0 0 0 1 0 0 0 0 0 6
7 105.65 0 0 0 0 0 0 0 1 0 0 0 0 7
8 108.42 0 0 0 0 0 0 0 0 1 0 0 0 8
9 115.35 0 0 0 0 0 0 0 0 0 1 0 0 9
10 113.64 0 0 0 0 0 0 0 0 0 0 1 0 10
11 115.24 0 0 0 0 0 0 0 0 0 0 0 1 11
12 100.33 0 0 0 0 0 0 0 0 0 0 0 0 12
13 101.29 0 1 0 0 0 0 0 0 0 0 0 0 13
14 104.48 0 0 1 0 0 0 0 0 0 0 0 0 14
15 99.26 0 0 0 1 0 0 0 0 0 0 0 0 15
16 100.11 0 0 0 0 1 0 0 0 0 0 0 0 16
17 103.52 0 0 0 0 0 1 0 0 0 0 0 0 17
18 101.18 0 0 0 0 0 0 1 0 0 0 0 0 18
19 96.39 0 0 0 0 0 0 0 1 0 0 0 0 19
20 97.56 0 0 0 0 0 0 0 0 1 0 0 0 20
21 96.39 0 0 0 0 0 0 0 0 0 1 0 0 21
22 85.10 0 0 0 0 0 0 0 0 0 0 1 0 22
23 79.77 0 0 0 0 0 0 0 0 0 0 0 1 23
24 79.13 0 0 0 0 0 0 0 0 0 0 0 0 24
25 80.84 0 1 0 0 0 0 0 0 0 0 0 0 25
26 82.75 0 0 1 0 0 0 0 0 0 0 0 0 26
27 92.55 0 0 0 1 0 0 0 0 0 0 0 0 27
28 96.60 0 0 0 0 1 0 0 0 0 0 0 0 28
29 96.92 0 0 0 0 0 1 0 0 0 0 0 0 29
30 95.32 0 0 0 0 0 0 1 0 0 0 0 0 30
31 98.52 0 0 0 0 0 0 0 1 0 0 0 0 31
32 100.22 0 0 0 0 0 0 0 0 1 0 0 0 32
33 104.91 0 0 0 0 0 0 0 0 0 1 0 0 33
34 103.10 0 0 0 0 0 0 0 0 0 0 1 0 34
35 97.13 0 0 0 0 0 0 0 0 0 0 0 1 35
36 103.42 0 0 0 0 0 0 0 0 0 0 0 0 36
37 111.72 0 1 0 0 0 0 0 0 0 0 0 0 37
38 118.11 0 0 1 0 0 0 0 0 0 0 0 0 38
39 111.62 0 0 0 1 0 0 0 0 0 0 0 0 39
40 100.22 0 0 0 0 1 0 0 0 0 0 0 0 40
41 102.03 0 0 0 0 0 1 0 0 0 0 0 0 41
42 105.76 0 0 0 0 0 0 1 0 0 0 0 0 42
43 107.68 0 0 0 0 0 0 0 1 0 0 0 0 43
44 110.77 0 0 0 0 0 0 0 0 1 0 0 0 44
45 105.44 0 0 0 0 0 0 0 0 0 1 0 0 45
46 112.26 0 0 0 0 0 0 0 0 0 0 1 0 46
47 114.07 0 0 0 0 0 0 0 0 0 0 0 1 47
48 117.90 0 0 0 0 0 0 0 0 0 0 0 0 48
49 124.72 0 1 0 0 0 0 0 0 0 0 0 0 49
50 126.42 0 0 1 0 0 0 0 0 0 0 0 0 50
51 134.73 0 0 0 1 0 0 0 0 0 0 0 0 51
52 135.79 0 0 0 0 1 0 0 0 0 0 0 0 52
53 143.36 0 0 0 0 0 1 0 0 0 0 0 0 53
54 140.37 0 0 0 0 0 0 1 0 0 0 0 0 54
55 144.74 0 0 0 0 0 0 0 1 0 0 0 0 55
56 151.98 0 0 0 0 0 0 0 0 1 0 0 0 56
57 150.92 0 0 0 0 0 0 0 0 0 1 0 0 57
58 163.38 0 0 0 0 0 0 0 0 0 0 1 0 58
59 154.43 0 0 0 0 0 0 0 0 0 0 0 1 59
60 146.66 0 0 0 0 0 0 0 0 0 0 0 0 60
61 157.95 0 1 0 0 0 0 0 0 0 0 0 0 61
62 162.10 0 0 1 0 0 0 0 0 0 0 0 0 62
63 180.42 0 0 0 1 0 0 0 0 0 0 0 0 63
64 179.57 0 0 0 0 1 0 0 0 0 0 0 0 64
65 171.58 0 0 0 0 0 1 0 0 0 0 0 0 65
66 185.43 0 0 0 0 0 0 1 0 0 0 0 0 66
67 190.64 0 0 0 0 0 0 0 1 0 0 0 0 67
68 203.00 0 0 0 0 0 0 0 0 1 0 0 0 68
69 202.36 0 0 0 0 0 0 0 0 0 1 0 0 69
70 193.41 0 0 0 0 0 0 0 0 0 0 1 0 70
71 186.17 0 0 0 0 0 0 0 0 0 0 0 1 71
72 192.24 0 0 0 0 0 0 0 0 0 0 0 0 72
73 209.60 0 1 0 0 0 0 0 0 0 0 0 0 73
74 206.41 0 0 1 0 0 0 0 0 0 0 0 0 74
75 209.82 0 0 0 1 0 0 0 0 0 0 0 0 75
76 230.37 0 0 0 0 1 0 0 0 0 0 0 0 76
77 235.80 0 0 0 0 0 1 0 0 0 0 0 0 77
78 232.07 0 0 0 0 0 0 1 0 0 0 0 0 78
79 244.64 0 0 0 0 0 0 0 1 0 0 0 0 79
80 242.19 0 0 0 0 0 0 0 0 1 0 0 0 80
81 217.48 0 0 0 0 0 0 0 0 0 1 0 0 81
82 209.39 0 0 0 0 0 0 0 0 0 0 1 0 82
83 211.73 0 0 0 0 0 0 0 0 0 0 0 1 83
84 221.00 0 0 0 0 0 0 0 0 0 0 0 0 84
85 203.11 0 1 0 0 0 0 0 0 0 0 0 0 85
86 214.71 0 0 1 0 0 0 0 0 0 0 0 0 86
87 224.19 0 0 0 1 0 0 0 0 0 0 0 0 87
88 238.04 0 0 0 0 1 0 0 0 0 0 0 0 88
89 238.36 0 0 0 0 0 1 0 0 0 0 0 0 89
90 246.24 0 0 0 0 0 0 1 0 0 0 0 0 90
91 259.87 0 0 0 0 0 0 0 1 0 0 0 0 91
92 249.97 0 0 0 0 0 0 0 0 1 0 0 0 92
93 266.48 0 0 0 0 0 0 0 0 0 1 0 0 93
94 282.98 0 0 0 0 0 0 0 0 0 0 1 0 94
95 306.31 0 0 0 0 0 0 0 0 0 0 0 1 95
96 301.73 1 0 0 0 0 0 0 0 0 0 0 0 96
97 314.62 1 1 0 0 0 0 0 0 0 0 0 0 97
98 332.62 1 0 1 0 0 0 0 0 0 0 0 0 98
99 355.51 1 0 0 1 0 0 0 0 0 0 0 0 99
100 370.32 1 0 0 0 1 0 0 0 0 0 0 0 100
101 408.13 1 0 0 0 0 1 0 0 0 0 0 0 101
102 433.58 1 0 0 0 0 0 1 0 0 0 0 0 102
103 440.51 1 0 0 0 0 0 0 1 0 0 0 0 103
104 386.29 1 0 0 0 0 0 0 0 1 0 0 0 104
105 342.84 1 0 0 0 0 0 0 0 0 1 0 0 105
106 254.97 1 0 0 0 0 0 0 0 0 0 1 0 106
107 203.42 1 0 0 0 0 0 0 0 0 0 0 1 107
108 170.09 1 0 0 0 0 0 0 0 0 0 0 0 108
109 174.03 1 1 0 0 0 0 0 0 0 0 0 0 109
110 167.85 1 0 1 0 0 0 0 0 0 0 0 0 110
111 177.01 1 0 0 1 0 0 0 0 0 0 0 0 111
112 188.19 1 0 0 0 1 0 0 0 0 0 0 0 112
113 211.20 1 0 0 0 0 1 0 0 0 0 0 0 113
114 240.91 1 0 0 0 0 0 1 0 0 0 0 0 114
115 230.26 1 0 0 0 0 0 0 1 0 0 0 0 115
116 251.25 1 0 0 0 0 0 0 0 1 0 0 0 116
117 241.66 1 0 0 0 0 0 0 0 0 1 0 0 117
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X M1 M2 M3 M4
47.471 29.216 8.039 10.425 15.702 18.453
M5 M6 M7 M8 M9 M10
24.806 30.433 31.619 28.141 20.605 16.279
M11 t
8.974 1.753
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-112.134 -21.028 -4.506 22.036 151.605
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 47.4711 18.7093 2.537 0.0127 *
X 29.2156 15.9316 1.834 0.0696 .
M1 8.0385 22.6075 0.356 0.7229
M2 10.4251 22.6027 0.461 0.6456
M3 15.7017 22.5994 0.695 0.4888
M4 18.4533 22.5976 0.817 0.4160
M5 24.8060 22.5973 1.098 0.2749
M6 30.4326 22.5985 1.347 0.1810
M7 31.6192 22.6013 1.399 0.1648
M8 28.1408 22.6055 1.245 0.2160
M9 20.6054 22.6112 0.911 0.3643
M10 16.2785 23.2341 0.701 0.4851
M11 8.9740 23.2415 0.386 0.7002
t 1.7534 0.1841 9.525 8.4e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 49.18 on 103 degrees of freedom
Multiple R-squared: 0.6874, Adjusted R-squared: 0.648
F-statistic: 17.42 on 13 and 103 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,] 2.744357e-04 5.488715e-04 0.9997256
[2,] 4.563515e-05 9.127031e-05 0.9999544
[3,] 7.972513e-06 1.594503e-05 0.9999920
[4,] 1.466278e-06 2.932557e-06 0.9999985
[5,] 1.158950e-06 2.317899e-06 0.9999988
[6,] 2.233958e-06 4.467917e-06 0.9999978
[7,] 3.625753e-06 7.251506e-06 0.9999964
[8,] 8.350713e-07 1.670143e-06 0.9999992
[9,] 1.410069e-07 2.820138e-07 0.9999999
[10,] 2.347306e-08 4.694612e-08 1.0000000
[11,] 4.692349e-09 9.384698e-09 1.0000000
[12,] 1.781668e-09 3.563335e-09 1.0000000
[13,] 3.357165e-10 6.714330e-10 1.0000000
[14,] 5.392531e-11 1.078506e-10 1.0000000
[15,] 1.315154e-11 2.630308e-11 1.0000000
[16,] 2.856120e-12 5.712240e-12 1.0000000
[17,] 6.712242e-13 1.342448e-12 1.0000000
[18,] 2.383382e-13 4.766764e-13 1.0000000
[19,] 4.994730e-14 9.989461e-14 1.0000000
[20,] 5.813901e-14 1.162780e-13 1.0000000
[21,] 1.450867e-13 2.901733e-13 1.0000000
[22,] 2.662585e-13 5.325171e-13 1.0000000
[23,] 1.076647e-13 2.153294e-13 1.0000000
[24,] 2.183394e-14 4.366789e-14 1.0000000
[25,] 4.174738e-15 8.349476e-15 1.0000000
[26,] 8.951583e-16 1.790317e-15 1.0000000
[27,] 2.261422e-16 4.522844e-16 1.0000000
[28,] 5.783939e-17 1.156788e-16 1.0000000
[29,] 1.080889e-17 2.161778e-17 1.0000000
[30,] 3.101455e-18 6.202911e-18 1.0000000
[31,] 1.280538e-18 2.561076e-18 1.0000000
[32,] 1.022298e-18 2.044597e-18 1.0000000
[33,] 9.038353e-19 1.807671e-18 1.0000000
[34,] 4.735543e-19 9.471085e-19 1.0000000
[35,] 5.902846e-19 1.180569e-18 1.0000000
[36,] 1.063091e-18 2.126182e-18 1.0000000
[37,] 2.225826e-18 4.451651e-18 1.0000000
[38,] 2.514531e-18 5.029061e-18 1.0000000
[39,] 4.325446e-18 8.650892e-18 1.0000000
[40,] 9.346773e-18 1.869355e-17 1.0000000
[41,] 1.160293e-17 2.320585e-17 1.0000000
[42,] 4.704554e-17 9.409109e-17 1.0000000
[43,] 6.470880e-17 1.294176e-16 1.0000000
[44,] 4.257624e-17 8.515248e-17 1.0000000
[45,] 3.194987e-17 6.389973e-17 1.0000000
[46,] 2.265023e-17 4.530047e-17 1.0000000
[47,] 5.493682e-17 1.098736e-16 1.0000000
[48,] 1.341980e-16 2.683961e-16 1.0000000
[49,] 1.602018e-16 3.204037e-16 1.0000000
[50,] 5.425077e-16 1.085015e-15 1.0000000
[51,] 2.863242e-15 5.726484e-15 1.0000000
[52,] 1.944593e-14 3.889186e-14 1.0000000
[53,] 8.501814e-14 1.700363e-13 1.0000000
[54,] 1.844913e-13 3.689826e-13 1.0000000
[55,] 4.239924e-13 8.479849e-13 1.0000000
[56,] 4.669267e-13 9.338533e-13 1.0000000
[57,] 5.659147e-13 1.131829e-12 1.0000000
[58,] 4.937194e-13 9.874388e-13 1.0000000
[59,] 4.746228e-13 9.492455e-13 1.0000000
[60,] 1.307829e-12 2.615659e-12 1.0000000
[61,] 5.083102e-12 1.016620e-11 1.0000000
[62,] 3.202474e-11 6.404947e-11 1.0000000
[63,] 3.818774e-10 7.637548e-10 1.0000000
[64,] 3.593996e-09 7.187992e-09 1.0000000
[65,] 1.036759e-07 2.073518e-07 0.9999999
[66,] 1.504801e-06 3.009602e-06 0.9999985
[67,] 2.893832e-05 5.787664e-05 0.9999711
[68,] 1.788520e-05 3.577039e-05 0.9999821
[69,] 8.990019e-06 1.798004e-05 0.9999910
[70,] 4.251328e-06 8.502655e-06 0.9999957
[71,] 2.102419e-06 4.204838e-06 0.9999979
[72,] 1.163022e-06 2.326044e-06 0.9999988
[73,] 1.226192e-06 2.452384e-06 0.9999988
[74,] 5.395907e-06 1.079181e-05 0.9999946
[75,] 4.422587e-05 8.845174e-05 0.9999558
[76,] 2.120177e-03 4.240353e-03 0.9978798
[77,] 2.983137e-01 5.966274e-01 0.7016863
[78,] 4.290103e-01 8.580207e-01 0.5709897
[79,] 4.101784e-01 8.203568e-01 0.5898216
[80,] 3.804112e-01 7.608224e-01 0.6195888
[81,] 3.249482e-01 6.498964e-01 0.6750518
[82,] 2.240348e-01 4.480695e-01 0.7759652
[83,] 1.423876e-01 2.847752e-01 0.8576124
[84,] 8.261620e-02 1.652324e-01 0.9173838
> postscript(file="/var/www/html/rcomp/tmp/1x4mb1258726645.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2pkij1258726645.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3kjiy1258726645.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/45gh91258726645.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5xmio1258726645.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 = 117
Frequency = 1
1 2 3 4 5 6
42.746989 42.436989 36.046989 22.491989 23.755989 20.215989
7 8 9 10 11 12
14.285989 18.780989 31.492989 32.356506 39.507617 31.818239
13 14 15 16 17 18
22.986351 22.036351 9.786351 6.131351 1.435351 -8.284649
19 20 21 22 23 24
-16.014649 -13.119649 -8.507649 -17.224132 -17.003020 -10.422399
25 26 27 28 29 30
-18.504287 -20.734287 -17.964287 -18.419287 -26.205287 -35.185287
31 32 33 34 35 36
-34.925287 -31.500287 -21.028287 -20.264769 -20.683658 -7.173037
37 38 39 40 41 42
-8.664925 -6.414925 -19.934925 -35.839925 -42.135925 -45.785925
43 44 45 46 47 48
-46.805925 -41.990925 -41.538925 -32.145407 -24.784296 -13.733675
49 50 51 52 53 54
-16.705563 -19.145563 -17.865563 -21.310563 -21.846563 -32.216563
55 56 57 58 59 60
-30.786563 -21.821563 -17.099563 -2.066045 -5.464934 -6.014313
61 62 63 64 65 66
-4.516201 -4.506201 6.783799 1.428799 -14.667201 -8.197201
67 68 69 70 71 72
-5.927201 8.157799 13.299799 6.923317 5.234428 18.525049
73 74 75 76 77 78
26.093162 18.763162 15.143162 31.188162 28.512162 17.402162
79 80 81 82 83 84
27.032162 26.307162 7.379162 1.862679 9.753790 26.244411
85 86 87 88 89 90
-1.437476 6.022524 8.472524 17.817524 10.031524 10.531524
91 92 93 94 95 96
21.221524 13.046524 35.338524 54.412041 83.293152 56.718181
97 98 99 100 101 102
59.816294 73.676294 89.536294 99.841294 129.545294 147.615294
103 104 105 106 107 108
151.605294 99.110294 61.442294 -23.854189 -69.853078 -95.962457
109 110 111 112 113 114
-101.814344 -112.134344 -110.004344 -103.329344 -88.425344 -66.095344
115 116 117
-79.685344 -56.970344 -60.778344
> postscript(file="/var/www/html/rcomp/tmp/6ubd31258726645.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 = 117
Frequency = 1
lag(myerror, k = 1) myerror
0 42.746989 NA
1 42.436989 42.746989
2 36.046989 42.436989
3 22.491989 36.046989
4 23.755989 22.491989
5 20.215989 23.755989
6 14.285989 20.215989
7 18.780989 14.285989
8 31.492989 18.780989
9 32.356506 31.492989
10 39.507617 32.356506
11 31.818239 39.507617
12 22.986351 31.818239
13 22.036351 22.986351
14 9.786351 22.036351
15 6.131351 9.786351
16 1.435351 6.131351
17 -8.284649 1.435351
18 -16.014649 -8.284649
19 -13.119649 -16.014649
20 -8.507649 -13.119649
21 -17.224132 -8.507649
22 -17.003020 -17.224132
23 -10.422399 -17.003020
24 -18.504287 -10.422399
25 -20.734287 -18.504287
26 -17.964287 -20.734287
27 -18.419287 -17.964287
28 -26.205287 -18.419287
29 -35.185287 -26.205287
30 -34.925287 -35.185287
31 -31.500287 -34.925287
32 -21.028287 -31.500287
33 -20.264769 -21.028287
34 -20.683658 -20.264769
35 -7.173037 -20.683658
36 -8.664925 -7.173037
37 -6.414925 -8.664925
38 -19.934925 -6.414925
39 -35.839925 -19.934925
40 -42.135925 -35.839925
41 -45.785925 -42.135925
42 -46.805925 -45.785925
43 -41.990925 -46.805925
44 -41.538925 -41.990925
45 -32.145407 -41.538925
46 -24.784296 -32.145407
47 -13.733675 -24.784296
48 -16.705563 -13.733675
49 -19.145563 -16.705563
50 -17.865563 -19.145563
51 -21.310563 -17.865563
52 -21.846563 -21.310563
53 -32.216563 -21.846563
54 -30.786563 -32.216563
55 -21.821563 -30.786563
56 -17.099563 -21.821563
57 -2.066045 -17.099563
58 -5.464934 -2.066045
59 -6.014313 -5.464934
60 -4.516201 -6.014313
61 -4.506201 -4.516201
62 6.783799 -4.506201
63 1.428799 6.783799
64 -14.667201 1.428799
65 -8.197201 -14.667201
66 -5.927201 -8.197201
67 8.157799 -5.927201
68 13.299799 8.157799
69 6.923317 13.299799
70 5.234428 6.923317
71 18.525049 5.234428
72 26.093162 18.525049
73 18.763162 26.093162
74 15.143162 18.763162
75 31.188162 15.143162
76 28.512162 31.188162
77 17.402162 28.512162
78 27.032162 17.402162
79 26.307162 27.032162
80 7.379162 26.307162
81 1.862679 7.379162
82 9.753790 1.862679
83 26.244411 9.753790
84 -1.437476 26.244411
85 6.022524 -1.437476
86 8.472524 6.022524
87 17.817524 8.472524
88 10.031524 17.817524
89 10.531524 10.031524
90 21.221524 10.531524
91 13.046524 21.221524
92 35.338524 13.046524
93 54.412041 35.338524
94 83.293152 54.412041
95 56.718181 83.293152
96 59.816294 56.718181
97 73.676294 59.816294
98 89.536294 73.676294
99 99.841294 89.536294
100 129.545294 99.841294
101 147.615294 129.545294
102 151.605294 147.615294
103 99.110294 151.605294
104 61.442294 99.110294
105 -23.854189 61.442294
106 -69.853078 -23.854189
107 -95.962457 -69.853078
108 -101.814344 -95.962457
109 -112.134344 -101.814344
110 -110.004344 -112.134344
111 -103.329344 -110.004344
112 -88.425344 -103.329344
113 -66.095344 -88.425344
114 -79.685344 -66.095344
115 -56.970344 -79.685344
116 -60.778344 -56.970344
117 NA -60.778344
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 42.436989 42.746989
[2,] 36.046989 42.436989
[3,] 22.491989 36.046989
[4,] 23.755989 22.491989
[5,] 20.215989 23.755989
[6,] 14.285989 20.215989
[7,] 18.780989 14.285989
[8,] 31.492989 18.780989
[9,] 32.356506 31.492989
[10,] 39.507617 32.356506
[11,] 31.818239 39.507617
[12,] 22.986351 31.818239
[13,] 22.036351 22.986351
[14,] 9.786351 22.036351
[15,] 6.131351 9.786351
[16,] 1.435351 6.131351
[17,] -8.284649 1.435351
[18,] -16.014649 -8.284649
[19,] -13.119649 -16.014649
[20,] -8.507649 -13.119649
[21,] -17.224132 -8.507649
[22,] -17.003020 -17.224132
[23,] -10.422399 -17.003020
[24,] -18.504287 -10.422399
[25,] -20.734287 -18.504287
[26,] -17.964287 -20.734287
[27,] -18.419287 -17.964287
[28,] -26.205287 -18.419287
[29,] -35.185287 -26.205287
[30,] -34.925287 -35.185287
[31,] -31.500287 -34.925287
[32,] -21.028287 -31.500287
[33,] -20.264769 -21.028287
[34,] -20.683658 -20.264769
[35,] -7.173037 -20.683658
[36,] -8.664925 -7.173037
[37,] -6.414925 -8.664925
[38,] -19.934925 -6.414925
[39,] -35.839925 -19.934925
[40,] -42.135925 -35.839925
[41,] -45.785925 -42.135925
[42,] -46.805925 -45.785925
[43,] -41.990925 -46.805925
[44,] -41.538925 -41.990925
[45,] -32.145407 -41.538925
[46,] -24.784296 -32.145407
[47,] -13.733675 -24.784296
[48,] -16.705563 -13.733675
[49,] -19.145563 -16.705563
[50,] -17.865563 -19.145563
[51,] -21.310563 -17.865563
[52,] -21.846563 -21.310563
[53,] -32.216563 -21.846563
[54,] -30.786563 -32.216563
[55,] -21.821563 -30.786563
[56,] -17.099563 -21.821563
[57,] -2.066045 -17.099563
[58,] -5.464934 -2.066045
[59,] -6.014313 -5.464934
[60,] -4.516201 -6.014313
[61,] -4.506201 -4.516201
[62,] 6.783799 -4.506201
[63,] 1.428799 6.783799
[64,] -14.667201 1.428799
[65,] -8.197201 -14.667201
[66,] -5.927201 -8.197201
[67,] 8.157799 -5.927201
[68,] 13.299799 8.157799
[69,] 6.923317 13.299799
[70,] 5.234428 6.923317
[71,] 18.525049 5.234428
[72,] 26.093162 18.525049
[73,] 18.763162 26.093162
[74,] 15.143162 18.763162
[75,] 31.188162 15.143162
[76,] 28.512162 31.188162
[77,] 17.402162 28.512162
[78,] 27.032162 17.402162
[79,] 26.307162 27.032162
[80,] 7.379162 26.307162
[81,] 1.862679 7.379162
[82,] 9.753790 1.862679
[83,] 26.244411 9.753790
[84,] -1.437476 26.244411
[85,] 6.022524 -1.437476
[86,] 8.472524 6.022524
[87,] 17.817524 8.472524
[88,] 10.031524 17.817524
[89,] 10.531524 10.031524
[90,] 21.221524 10.531524
[91,] 13.046524 21.221524
[92,] 35.338524 13.046524
[93,] 54.412041 35.338524
[94,] 83.293152 54.412041
[95,] 56.718181 83.293152
[96,] 59.816294 56.718181
[97,] 73.676294 59.816294
[98,] 89.536294 73.676294
[99,] 99.841294 89.536294
[100,] 129.545294 99.841294
[101,] 147.615294 129.545294
[102,] 151.605294 147.615294
[103,] 99.110294 151.605294
[104,] 61.442294 99.110294
[105,] -23.854189 61.442294
[106,] -69.853078 -23.854189
[107,] -95.962457 -69.853078
[108,] -101.814344 -95.962457
[109,] -112.134344 -101.814344
[110,] -110.004344 -112.134344
[111,] -103.329344 -110.004344
[112,] -88.425344 -103.329344
[113,] -66.095344 -88.425344
[114,] -79.685344 -66.095344
[115,] -56.970344 -79.685344
[116,] -60.778344 -56.970344
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 42.436989 42.746989
2 36.046989 42.436989
3 22.491989 36.046989
4 23.755989 22.491989
5 20.215989 23.755989
6 14.285989 20.215989
7 18.780989 14.285989
8 31.492989 18.780989
9 32.356506 31.492989
10 39.507617 32.356506
11 31.818239 39.507617
12 22.986351 31.818239
13 22.036351 22.986351
14 9.786351 22.036351
15 6.131351 9.786351
16 1.435351 6.131351
17 -8.284649 1.435351
18 -16.014649 -8.284649
19 -13.119649 -16.014649
20 -8.507649 -13.119649
21 -17.224132 -8.507649
22 -17.003020 -17.224132
23 -10.422399 -17.003020
24 -18.504287 -10.422399
25 -20.734287 -18.504287
26 -17.964287 -20.734287
27 -18.419287 -17.964287
28 -26.205287 -18.419287
29 -35.185287 -26.205287
30 -34.925287 -35.185287
31 -31.500287 -34.925287
32 -21.028287 -31.500287
33 -20.264769 -21.028287
34 -20.683658 -20.264769
35 -7.173037 -20.683658
36 -8.664925 -7.173037
37 -6.414925 -8.664925
38 -19.934925 -6.414925
39 -35.839925 -19.934925
40 -42.135925 -35.839925
41 -45.785925 -42.135925
42 -46.805925 -45.785925
43 -41.990925 -46.805925
44 -41.538925 -41.990925
45 -32.145407 -41.538925
46 -24.784296 -32.145407
47 -13.733675 -24.784296
48 -16.705563 -13.733675
49 -19.145563 -16.705563
50 -17.865563 -19.145563
51 -21.310563 -17.865563
52 -21.846563 -21.310563
53 -32.216563 -21.846563
54 -30.786563 -32.216563
55 -21.821563 -30.786563
56 -17.099563 -21.821563
57 -2.066045 -17.099563
58 -5.464934 -2.066045
59 -6.014313 -5.464934
60 -4.516201 -6.014313
61 -4.506201 -4.516201
62 6.783799 -4.506201
63 1.428799 6.783799
64 -14.667201 1.428799
65 -8.197201 -14.667201
66 -5.927201 -8.197201
67 8.157799 -5.927201
68 13.299799 8.157799
69 6.923317 13.299799
70 5.234428 6.923317
71 18.525049 5.234428
72 26.093162 18.525049
73 18.763162 26.093162
74 15.143162 18.763162
75 31.188162 15.143162
76 28.512162 31.188162
77 17.402162 28.512162
78 27.032162 17.402162
79 26.307162 27.032162
80 7.379162 26.307162
81 1.862679 7.379162
82 9.753790 1.862679
83 26.244411 9.753790
84 -1.437476 26.244411
85 6.022524 -1.437476
86 8.472524 6.022524
87 17.817524 8.472524
88 10.031524 17.817524
89 10.531524 10.031524
90 21.221524 10.531524
91 13.046524 21.221524
92 35.338524 13.046524
93 54.412041 35.338524
94 83.293152 54.412041
95 56.718181 83.293152
96 59.816294 56.718181
97 73.676294 59.816294
98 89.536294 73.676294
99 99.841294 89.536294
100 129.545294 99.841294
101 147.615294 129.545294
102 151.605294 147.615294
103 99.110294 151.605294
104 61.442294 99.110294
105 -23.854189 61.442294
106 -69.853078 -23.854189
107 -95.962457 -69.853078
108 -101.814344 -95.962457
109 -112.134344 -101.814344
110 -110.004344 -112.134344
111 -103.329344 -110.004344
112 -88.425344 -103.329344
113 -66.095344 -88.425344
114 -79.685344 -66.095344
115 -56.970344 -79.685344
116 -60.778344 -56.970344
> 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/7tmyn1258726645.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/85g7d1258726645.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9ms9i1258726645.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10kcrt1258726645.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11mzrs1258726645.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/1200at1258726645.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/13oe241258726645.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/14aazo1258726645.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/15nar81258726645.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/16yuwk1258726645.tab")
+ }
> system("convert tmp/1x4mb1258726645.ps tmp/1x4mb1258726645.png")
> system("convert tmp/2pkij1258726645.ps tmp/2pkij1258726645.png")
> system("convert tmp/3kjiy1258726645.ps tmp/3kjiy1258726645.png")
> system("convert tmp/45gh91258726645.ps tmp/45gh91258726645.png")
> system("convert tmp/5xmio1258726645.ps tmp/5xmio1258726645.png")
> system("convert tmp/6ubd31258726645.ps tmp/6ubd31258726645.png")
> system("convert tmp/7tmyn1258726645.ps tmp/7tmyn1258726645.png")
> system("convert tmp/85g7d1258726645.ps tmp/85g7d1258726645.png")
> system("convert tmp/9ms9i1258726645.ps tmp/9ms9i1258726645.png")
> system("convert tmp/10kcrt1258726645.ps tmp/10kcrt1258726645.png")
>
>
> proc.time()
user system elapsed
3.307 1.637 4.399