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(8310,0,7649,0,7279,0,6857,0,6496,0,6280,0,8962,0,11205,0,10363,0,9175,0,8234,0,8121,0,7438,0,6876,0,6489,0,6319,0,5952,0,6055,0,9107,0,11493,0,10213,0,9238,0,8218,0,7995,0,7581,0,7051,0,6668,0,6433,0,6135,0,6365,0,10095,0,12029,0,12184,0,11331,0,9961,0,9739,0,9080,0,8507,0,8097,0,7772,0,7440,0,7902,0,13539,0,14992,0,15436,0,14156,0,12846,0,12302,0,11691,0,10648,0,10064,0,10016,0,9691,0,10260,0,16882,0,18573,0,18227,0,16346,0,14694,0,14453,0,13949,0,13277,0,12726,0,12279,0,11819,0,12207,0,18637,0,20519,0,19974,0,17802,0,15997,0,15430,0,14452,0,13614,0,13080,0,12290,0,11890,0,12292,0,18700,1,20388,1,19170,1,17530,1,15564,1,15163,1,13406,1,12763,1,12083,1,12054,1,11770,1,12266,1,17549,1,18655,1,17279,1,14788,1,13138,1,12494,1,11767,1,10928,1,10104,1,9760,1,9536,1,9978,1,14846,1,15565,1,13587,1,11804,1,10611,1,10915,1,9988,1,9376,1,9319,1,8852,1,8392,1,9050,1,13250,1,14037,1,12486,1,11182,1,10287,1),dim=c(2,119),dimnames=list(c('NWWZm','Dummy'),1:119))
> y <- array(NA,dim=c(2,119),dimnames=list(c('NWWZm','Dummy'),1:119))
> 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
NWWZm Dummy M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 8310 0 1 0 0 0 0 0 0 0 0 0 0 1
2 7649 0 0 1 0 0 0 0 0 0 0 0 0 2
3 7279 0 0 0 1 0 0 0 0 0 0 0 0 3
4 6857 0 0 0 0 1 0 0 0 0 0 0 0 4
5 6496 0 0 0 0 0 1 0 0 0 0 0 0 5
6 6280 0 0 0 0 0 0 1 0 0 0 0 0 6
7 8962 0 0 0 0 0 0 0 1 0 0 0 0 7
8 11205 0 0 0 0 0 0 0 0 1 0 0 0 8
9 10363 0 0 0 0 0 0 0 0 0 1 0 0 9
10 9175 0 0 0 0 0 0 0 0 0 0 1 0 10
11 8234 0 0 0 0 0 0 0 0 0 0 0 1 11
12 8121 0 0 0 0 0 0 0 0 0 0 0 0 12
13 7438 0 1 0 0 0 0 0 0 0 0 0 0 13
14 6876 0 0 1 0 0 0 0 0 0 0 0 0 14
15 6489 0 0 0 1 0 0 0 0 0 0 0 0 15
16 6319 0 0 0 0 1 0 0 0 0 0 0 0 16
17 5952 0 0 0 0 0 1 0 0 0 0 0 0 17
18 6055 0 0 0 0 0 0 1 0 0 0 0 0 18
19 9107 0 0 0 0 0 0 0 1 0 0 0 0 19
20 11493 0 0 0 0 0 0 0 0 1 0 0 0 20
21 10213 0 0 0 0 0 0 0 0 0 1 0 0 21
22 9238 0 0 0 0 0 0 0 0 0 0 1 0 22
23 8218 0 0 0 0 0 0 0 0 0 0 0 1 23
24 7995 0 0 0 0 0 0 0 0 0 0 0 0 24
25 7581 0 1 0 0 0 0 0 0 0 0 0 0 25
26 7051 0 0 1 0 0 0 0 0 0 0 0 0 26
27 6668 0 0 0 1 0 0 0 0 0 0 0 0 27
28 6433 0 0 0 0 1 0 0 0 0 0 0 0 28
29 6135 0 0 0 0 0 1 0 0 0 0 0 0 29
30 6365 0 0 0 0 0 0 1 0 0 0 0 0 30
31 10095 0 0 0 0 0 0 0 1 0 0 0 0 31
32 12029 0 0 0 0 0 0 0 0 1 0 0 0 32
33 12184 0 0 0 0 0 0 0 0 0 1 0 0 33
34 11331 0 0 0 0 0 0 0 0 0 0 1 0 34
35 9961 0 0 0 0 0 0 0 0 0 0 0 1 35
36 9739 0 0 0 0 0 0 0 0 0 0 0 0 36
37 9080 0 1 0 0 0 0 0 0 0 0 0 0 37
38 8507 0 0 1 0 0 0 0 0 0 0 0 0 38
39 8097 0 0 0 1 0 0 0 0 0 0 0 0 39
40 7772 0 0 0 0 1 0 0 0 0 0 0 0 40
41 7440 0 0 0 0 0 1 0 0 0 0 0 0 41
42 7902 0 0 0 0 0 0 1 0 0 0 0 0 42
43 13539 0 0 0 0 0 0 0 1 0 0 0 0 43
44 14992 0 0 0 0 0 0 0 0 1 0 0 0 44
45 15436 0 0 0 0 0 0 0 0 0 1 0 0 45
46 14156 0 0 0 0 0 0 0 0 0 0 1 0 46
47 12846 0 0 0 0 0 0 0 0 0 0 0 1 47
48 12302 0 0 0 0 0 0 0 0 0 0 0 0 48
49 11691 0 1 0 0 0 0 0 0 0 0 0 0 49
50 10648 0 0 1 0 0 0 0 0 0 0 0 0 50
51 10064 0 0 0 1 0 0 0 0 0 0 0 0 51
52 10016 0 0 0 0 1 0 0 0 0 0 0 0 52
53 9691 0 0 0 0 0 1 0 0 0 0 0 0 53
54 10260 0 0 0 0 0 0 1 0 0 0 0 0 54
55 16882 0 0 0 0 0 0 0 1 0 0 0 0 55
56 18573 0 0 0 0 0 0 0 0 1 0 0 0 56
57 18227 0 0 0 0 0 0 0 0 0 1 0 0 57
58 16346 0 0 0 0 0 0 0 0 0 0 1 0 58
59 14694 0 0 0 0 0 0 0 0 0 0 0 1 59
60 14453 0 0 0 0 0 0 0 0 0 0 0 0 60
61 13949 0 1 0 0 0 0 0 0 0 0 0 0 61
62 13277 0 0 1 0 0 0 0 0 0 0 0 0 62
63 12726 0 0 0 1 0 0 0 0 0 0 0 0 63
64 12279 0 0 0 0 1 0 0 0 0 0 0 0 64
65 11819 0 0 0 0 0 1 0 0 0 0 0 0 65
66 12207 0 0 0 0 0 0 1 0 0 0 0 0 66
67 18637 0 0 0 0 0 0 0 1 0 0 0 0 67
68 20519 0 0 0 0 0 0 0 0 1 0 0 0 68
69 19974 0 0 0 0 0 0 0 0 0 1 0 0 69
70 17802 0 0 0 0 0 0 0 0 0 0 1 0 70
71 15997 0 0 0 0 0 0 0 0 0 0 0 1 71
72 15430 0 0 0 0 0 0 0 0 0 0 0 0 72
73 14452 0 1 0 0 0 0 0 0 0 0 0 0 73
74 13614 0 0 1 0 0 0 0 0 0 0 0 0 74
75 13080 0 0 0 1 0 0 0 0 0 0 0 0 75
76 12290 0 0 0 0 1 0 0 0 0 0 0 0 76
77 11890 0 0 0 0 0 1 0 0 0 0 0 0 77
78 12292 0 0 0 0 0 0 1 0 0 0 0 0 78
79 18700 1 0 0 0 0 0 0 1 0 0 0 0 79
80 20388 1 0 0 0 0 0 0 0 1 0 0 0 80
81 19170 1 0 0 0 0 0 0 0 0 1 0 0 81
82 17530 1 0 0 0 0 0 0 0 0 0 1 0 82
83 15564 1 0 0 0 0 0 0 0 0 0 0 1 83
84 15163 1 0 0 0 0 0 0 0 0 0 0 0 84
85 13406 1 1 0 0 0 0 0 0 0 0 0 0 85
86 12763 1 0 1 0 0 0 0 0 0 0 0 0 86
87 12083 1 0 0 1 0 0 0 0 0 0 0 0 87
88 12054 1 0 0 0 1 0 0 0 0 0 0 0 88
89 11770 1 0 0 0 0 1 0 0 0 0 0 0 89
90 12266 1 0 0 0 0 0 1 0 0 0 0 0 90
91 17549 1 0 0 0 0 0 0 1 0 0 0 0 91
92 18655 1 0 0 0 0 0 0 0 1 0 0 0 92
93 17279 1 0 0 0 0 0 0 0 0 1 0 0 93
94 14788 1 0 0 0 0 0 0 0 0 0 1 0 94
95 13138 1 0 0 0 0 0 0 0 0 0 0 1 95
96 12494 1 0 0 0 0 0 0 0 0 0 0 0 96
97 11767 1 1 0 0 0 0 0 0 0 0 0 0 97
98 10928 1 0 1 0 0 0 0 0 0 0 0 0 98
99 10104 1 0 0 1 0 0 0 0 0 0 0 0 99
100 9760 1 0 0 0 1 0 0 0 0 0 0 0 100
101 9536 1 0 0 0 0 1 0 0 0 0 0 0 101
102 9978 1 0 0 0 0 0 1 0 0 0 0 0 102
103 14846 1 0 0 0 0 0 0 1 0 0 0 0 103
104 15565 1 0 0 0 0 0 0 0 1 0 0 0 104
105 13587 1 0 0 0 0 0 0 0 0 1 0 0 105
106 11804 1 0 0 0 0 0 0 0 0 0 1 0 106
107 10611 1 0 0 0 0 0 0 0 0 0 0 1 107
108 10915 1 0 0 0 0 0 0 0 0 0 0 0 108
109 9988 1 1 0 0 0 0 0 0 0 0 0 0 109
110 9376 1 0 1 0 0 0 0 0 0 0 0 0 110
111 9319 1 0 0 1 0 0 0 0 0 0 0 0 111
112 8852 1 0 0 0 1 0 0 0 0 0 0 0 112
113 8392 1 0 0 0 0 1 0 0 0 0 0 0 113
114 9050 1 0 0 0 0 0 1 0 0 0 0 0 114
115 13250 1 0 0 0 0 0 0 1 0 0 0 0 115
116 14037 1 0 0 0 0 0 0 0 1 0 0 0 116
117 12486 1 0 0 0 0 0 0 0 0 1 0 0 117
118 11182 1 0 0 0 0 0 0 0 0 0 1 0 118
119 10287 1 0 0 0 0 0 0 0 0 0 0 1 119
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Dummy M1 M2 M3 M4
7816.04 -3678.68 -764.20 -1549.10 -2114.70 -2530.00
M5 M6 M7 M8 M9 M10
-2968.70 -2702.90 2468.57 3969.87 3028.57 1384.27
M11 t
-83.53 87.60
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-4929 -1341 -245 1348 5273
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 7816.04 873.76 8.945 1.42e-14 ***
Dummy -3678.68 766.88 -4.797 5.35e-06 ***
M1 -764.20 1033.35 -0.740 0.461228
M2 -1549.10 1033.07 -1.500 0.136742
M3 -2114.70 1032.91 -2.047 0.043122 *
M4 -2530.00 1032.85 -2.450 0.015959 *
M5 -2968.70 1032.90 -2.874 0.004905 **
M6 -2702.90 1033.07 -2.616 0.010196 *
M7 2468.57 1033.64 2.388 0.018716 *
M8 3969.87 1033.37 3.842 0.000209 ***
M9 3028.57 1033.21 2.931 0.004144 **
M10 1384.27 1033.16 1.340 0.183189
M11 -83.53 1033.22 -0.081 0.935720
t 87.60 10.60 8.267 4.53e-13 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 2248 on 105 degrees of freedom
Multiple R-squared: 0.6617, Adjusted R-squared: 0.6198
F-statistic: 15.8 on 13 and 105 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,] 1.933605e-04 3.867209e-04 9.998066e-01
[2,] 7.436336e-05 1.487267e-04 9.999256e-01
[3,] 6.555168e-05 1.311034e-04 9.999344e-01
[4,] 3.396544e-05 6.793087e-05 9.999660e-01
[5,] 5.248605e-06 1.049721e-05 9.999948e-01
[6,] 1.061790e-06 2.123579e-06 9.999989e-01
[7,] 1.730654e-07 3.461308e-07 9.999998e-01
[8,] 2.420426e-08 4.840853e-08 1.000000e+00
[9,] 3.190084e-09 6.380168e-09 1.000000e+00
[10,] 4.394484e-10 8.788969e-10 1.000000e+00
[11,] 5.694880e-11 1.138976e-10 1.000000e+00
[12,] 7.758861e-12 1.551772e-11 1.000000e+00
[13,] 1.153896e-12 2.307791e-12 1.000000e+00
[14,] 4.262181e-13 8.524362e-13 1.000000e+00
[15,] 1.908107e-11 3.816213e-11 1.000000e+00
[16,] 2.126251e-11 4.252502e-11 1.000000e+00
[17,] 1.919824e-09 3.839648e-09 1.000000e+00
[18,] 2.760433e-08 5.520865e-08 1.000000e+00
[19,] 5.154964e-08 1.030993e-07 9.999999e-01
[20,] 7.396397e-08 1.479279e-07 9.999999e-01
[21,] 5.073831e-08 1.014766e-07 9.999999e-01
[22,] 3.428431e-08 6.856862e-08 1.000000e+00
[23,] 2.300973e-08 4.601946e-08 1.000000e+00
[24,] 1.614148e-08 3.228296e-08 1.000000e+00
[25,] 1.289903e-08 2.579806e-08 1.000000e+00
[26,] 1.840148e-08 3.680295e-08 1.000000e+00
[27,] 5.867591e-06 1.173518e-05 9.999941e-01
[28,] 5.905445e-05 1.181089e-04 9.999409e-01
[29,] 9.229747e-04 1.845949e-03 9.990770e-01
[30,] 3.766583e-03 7.533167e-03 9.962334e-01
[31,] 9.121297e-03 1.824259e-02 9.908787e-01
[32,] 1.821901e-02 3.643802e-02 9.817810e-01
[33,] 2.667233e-02 5.334467e-02 9.733277e-01
[34,] 4.212133e-02 8.424266e-02 9.578787e-01
[35,] 7.538094e-02 1.507619e-01 9.246191e-01
[36,] 1.362907e-01 2.725815e-01 8.637093e-01
[37,] 2.683539e-01 5.367078e-01 7.316461e-01
[38,] 5.418708e-01 9.162585e-01 4.581292e-01
[39,] 8.757480e-01 2.485039e-01 1.242520e-01
[40,] 9.711186e-01 5.776289e-02 2.888145e-02
[41,] 9.902958e-01 1.940848e-02 9.704239e-03
[42,] 9.955546e-01 8.890842e-03 4.445421e-03
[43,] 9.982690e-01 3.461980e-03 1.730990e-03
[44,] 9.993738e-01 1.252455e-03 6.262277e-04
[45,] 9.995951e-01 8.098267e-04 4.049134e-04
[46,] 9.997580e-01 4.840117e-04 2.420059e-04
[47,] 9.998835e-01 2.330824e-04 1.165412e-04
[48,] 9.999612e-01 7.760789e-05 3.880395e-05
[49,] 9.999947e-01 1.059802e-05 5.299008e-06
[50,] 9.999999e-01 2.077059e-07 1.038529e-07
[51,] 1.000000e+00 8.626591e-08 4.313295e-08
[52,] 9.999999e-01 1.007359e-07 5.036796e-08
[53,] 1.000000e+00 6.675690e-08 3.337845e-08
[54,] 9.999999e-01 1.027980e-07 5.139900e-08
[55,] 9.999999e-01 2.368875e-07 1.184437e-07
[56,] 9.999997e-01 5.567369e-07 2.783684e-07
[57,] 9.999995e-01 1.064457e-06 5.322284e-07
[58,] 9.999990e-01 2.067908e-06 1.033954e-06
[59,] 9.999982e-01 3.607787e-06 1.803893e-06
[60,] 9.999964e-01 7.231109e-06 3.615554e-06
[61,] 9.999928e-01 1.447795e-05 7.238974e-06
[62,] 9.999850e-01 3.003936e-05 1.501968e-05
[63,] 9.999711e-01 5.775274e-05 2.887637e-05
[64,] 9.999428e-01 1.144818e-04 5.724088e-05
[65,] 9.999308e-01 1.384392e-04 6.921960e-05
[66,] 9.999518e-01 9.635334e-05 4.817667e-05
[67,] 9.999221e-01 1.558354e-04 7.791769e-05
[68,] 9.998925e-01 2.149746e-04 1.074873e-04
[69,] 9.998262e-01 3.476629e-04 1.738315e-04
[70,] 9.996854e-01 6.292765e-04 3.146382e-04
[71,] 9.994699e-01 1.060165e-03 5.300825e-04
[72,] 9.989549e-01 2.090263e-03 1.045132e-03
[73,] 9.979392e-01 4.121604e-03 2.060802e-03
[74,] 9.959234e-01 8.153294e-03 4.076647e-03
[75,] 9.944317e-01 1.113652e-02 5.568261e-03
[76,] 9.960979e-01 7.804221e-03 3.902111e-03
[77,] 9.997221e-01 5.557619e-04 2.778810e-04
[78,] 9.999495e-01 1.009796e-04 5.048979e-05
[79,] 9.999744e-01 5.121481e-05 2.560740e-05
[80,] 9.999451e-01 1.097933e-04 5.489665e-05
[81,] 9.999337e-01 1.326368e-04 6.631838e-05
[82,] 9.998679e-01 2.641615e-04 1.320808e-04
[83,] 9.995130e-01 9.740586e-04 4.870293e-04
[84,] 9.980111e-01 3.977711e-03 1.988856e-03
[85,] 9.919008e-01 1.619835e-02 8.099177e-03
[86,] 9.680381e-01 6.392388e-02 3.196194e-02
> postscript(file="/var/www/html/rcomp/tmp/19vdi1229106254.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2hqmu1229106254.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3tvcc1229106254.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4ie0z1229106254.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5zmqe1229106254.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 = 119
Frequency = 1
1 2 3 4 5 6
1170.566757 1206.866757 1314.866757 1220.566757 1210.666757 641.266757
7 8 9 10 11 12
-1935.801173 -1281.701173 -1270.001173 -901.301173 -462.101173 -746.230392
13 14 15 16 17 18
-752.626698 -617.326698 -526.326698 -368.626698 -384.526698 -634.926698
19 20 21 22 23 24
-2841.994628 -2044.894628 -2471.194628 -1889.494628 -1529.294628 -1923.423846
25 26 27 28 29 30
-1660.820153 -1493.520153 -1398.520153 -1305.820153 -1252.720153 -1376.120153
31 32 33 34 35 36
-2905.188083 -2560.088083 -1551.388083 -847.688083 -837.488083 -1230.617301
37 38 39 40 41 42
-1213.013608 -1088.713608 -1020.713608 -1018.013608 -998.913608 -890.313608
43 44 45 46 47 48
-512.381538 -648.281538 649.418462 926.118462 996.318462 281.189244
49 50 51 52 53 54
346.792937 1.092937 -104.907063 174.792937 200.892937 416.492937
55 56 57 58 59 60
1779.425008 1881.525008 2389.225008 2064.925008 1793.125008 1380.995789
61 62 63 64 65 66
1553.599483 1578.899483 1505.899483 1386.599483 1277.699483 1312.299483
67 68 69 70 71 72
2483.231553 2776.331553 3085.031553 2469.731553 2044.931553 1306.802334
73 74 75 76 77 78
1005.406028 864.706028 808.706028 346.406028 297.506028 346.106028
79 80 81 82 83 84
5173.717398 5272.817398 4908.517398 4825.217398 4239.417398 3667.288179
85 86 87 88 89 90
2586.891873 2641.191873 2439.191873 2737.891873 2804.991873 2947.591873
91 92 93 94 95 96
2971.523943 2488.623943 1966.323943 1032.023943 762.223943 -52.905276
97 98 99 100 101 102
-103.301582 -245.001582 -591.001582 -607.301582 -480.201582 -391.601582
103 104 105 106 107 108
-782.669512 -1652.569512 -2776.869512 -3003.169512 -2815.969512 -2683.098731
109 110 111 112 113 114
-2933.495037 -2848.195037 -2427.195037 -2566.495037 -2675.395037 -2370.795037
115 116 117 118 119
-3429.862967 -4231.762967 -4929.062967 -4676.362967 -4191.162967
> postscript(file="/var/www/html/rcomp/tmp/6alhb1229106254.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 = 119
Frequency = 1
lag(myerror, k = 1) myerror
0 1170.566757 NA
1 1206.866757 1170.566757
2 1314.866757 1206.866757
3 1220.566757 1314.866757
4 1210.666757 1220.566757
5 641.266757 1210.666757
6 -1935.801173 641.266757
7 -1281.701173 -1935.801173
8 -1270.001173 -1281.701173
9 -901.301173 -1270.001173
10 -462.101173 -901.301173
11 -746.230392 -462.101173
12 -752.626698 -746.230392
13 -617.326698 -752.626698
14 -526.326698 -617.326698
15 -368.626698 -526.326698
16 -384.526698 -368.626698
17 -634.926698 -384.526698
18 -2841.994628 -634.926698
19 -2044.894628 -2841.994628
20 -2471.194628 -2044.894628
21 -1889.494628 -2471.194628
22 -1529.294628 -1889.494628
23 -1923.423846 -1529.294628
24 -1660.820153 -1923.423846
25 -1493.520153 -1660.820153
26 -1398.520153 -1493.520153
27 -1305.820153 -1398.520153
28 -1252.720153 -1305.820153
29 -1376.120153 -1252.720153
30 -2905.188083 -1376.120153
31 -2560.088083 -2905.188083
32 -1551.388083 -2560.088083
33 -847.688083 -1551.388083
34 -837.488083 -847.688083
35 -1230.617301 -837.488083
36 -1213.013608 -1230.617301
37 -1088.713608 -1213.013608
38 -1020.713608 -1088.713608
39 -1018.013608 -1020.713608
40 -998.913608 -1018.013608
41 -890.313608 -998.913608
42 -512.381538 -890.313608
43 -648.281538 -512.381538
44 649.418462 -648.281538
45 926.118462 649.418462
46 996.318462 926.118462
47 281.189244 996.318462
48 346.792937 281.189244
49 1.092937 346.792937
50 -104.907063 1.092937
51 174.792937 -104.907063
52 200.892937 174.792937
53 416.492937 200.892937
54 1779.425008 416.492937
55 1881.525008 1779.425008
56 2389.225008 1881.525008
57 2064.925008 2389.225008
58 1793.125008 2064.925008
59 1380.995789 1793.125008
60 1553.599483 1380.995789
61 1578.899483 1553.599483
62 1505.899483 1578.899483
63 1386.599483 1505.899483
64 1277.699483 1386.599483
65 1312.299483 1277.699483
66 2483.231553 1312.299483
67 2776.331553 2483.231553
68 3085.031553 2776.331553
69 2469.731553 3085.031553
70 2044.931553 2469.731553
71 1306.802334 2044.931553
72 1005.406028 1306.802334
73 864.706028 1005.406028
74 808.706028 864.706028
75 346.406028 808.706028
76 297.506028 346.406028
77 346.106028 297.506028
78 5173.717398 346.106028
79 5272.817398 5173.717398
80 4908.517398 5272.817398
81 4825.217398 4908.517398
82 4239.417398 4825.217398
83 3667.288179 4239.417398
84 2586.891873 3667.288179
85 2641.191873 2586.891873
86 2439.191873 2641.191873
87 2737.891873 2439.191873
88 2804.991873 2737.891873
89 2947.591873 2804.991873
90 2971.523943 2947.591873
91 2488.623943 2971.523943
92 1966.323943 2488.623943
93 1032.023943 1966.323943
94 762.223943 1032.023943
95 -52.905276 762.223943
96 -103.301582 -52.905276
97 -245.001582 -103.301582
98 -591.001582 -245.001582
99 -607.301582 -591.001582
100 -480.201582 -607.301582
101 -391.601582 -480.201582
102 -782.669512 -391.601582
103 -1652.569512 -782.669512
104 -2776.869512 -1652.569512
105 -3003.169512 -2776.869512
106 -2815.969512 -3003.169512
107 -2683.098731 -2815.969512
108 -2933.495037 -2683.098731
109 -2848.195037 -2933.495037
110 -2427.195037 -2848.195037
111 -2566.495037 -2427.195037
112 -2675.395037 -2566.495037
113 -2370.795037 -2675.395037
114 -3429.862967 -2370.795037
115 -4231.762967 -3429.862967
116 -4929.062967 -4231.762967
117 -4676.362967 -4929.062967
118 -4191.162967 -4676.362967
119 NA -4191.162967
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 1206.866757 1170.566757
[2,] 1314.866757 1206.866757
[3,] 1220.566757 1314.866757
[4,] 1210.666757 1220.566757
[5,] 641.266757 1210.666757
[6,] -1935.801173 641.266757
[7,] -1281.701173 -1935.801173
[8,] -1270.001173 -1281.701173
[9,] -901.301173 -1270.001173
[10,] -462.101173 -901.301173
[11,] -746.230392 -462.101173
[12,] -752.626698 -746.230392
[13,] -617.326698 -752.626698
[14,] -526.326698 -617.326698
[15,] -368.626698 -526.326698
[16,] -384.526698 -368.626698
[17,] -634.926698 -384.526698
[18,] -2841.994628 -634.926698
[19,] -2044.894628 -2841.994628
[20,] -2471.194628 -2044.894628
[21,] -1889.494628 -2471.194628
[22,] -1529.294628 -1889.494628
[23,] -1923.423846 -1529.294628
[24,] -1660.820153 -1923.423846
[25,] -1493.520153 -1660.820153
[26,] -1398.520153 -1493.520153
[27,] -1305.820153 -1398.520153
[28,] -1252.720153 -1305.820153
[29,] -1376.120153 -1252.720153
[30,] -2905.188083 -1376.120153
[31,] -2560.088083 -2905.188083
[32,] -1551.388083 -2560.088083
[33,] -847.688083 -1551.388083
[34,] -837.488083 -847.688083
[35,] -1230.617301 -837.488083
[36,] -1213.013608 -1230.617301
[37,] -1088.713608 -1213.013608
[38,] -1020.713608 -1088.713608
[39,] -1018.013608 -1020.713608
[40,] -998.913608 -1018.013608
[41,] -890.313608 -998.913608
[42,] -512.381538 -890.313608
[43,] -648.281538 -512.381538
[44,] 649.418462 -648.281538
[45,] 926.118462 649.418462
[46,] 996.318462 926.118462
[47,] 281.189244 996.318462
[48,] 346.792937 281.189244
[49,] 1.092937 346.792937
[50,] -104.907063 1.092937
[51,] 174.792937 -104.907063
[52,] 200.892937 174.792937
[53,] 416.492937 200.892937
[54,] 1779.425008 416.492937
[55,] 1881.525008 1779.425008
[56,] 2389.225008 1881.525008
[57,] 2064.925008 2389.225008
[58,] 1793.125008 2064.925008
[59,] 1380.995789 1793.125008
[60,] 1553.599483 1380.995789
[61,] 1578.899483 1553.599483
[62,] 1505.899483 1578.899483
[63,] 1386.599483 1505.899483
[64,] 1277.699483 1386.599483
[65,] 1312.299483 1277.699483
[66,] 2483.231553 1312.299483
[67,] 2776.331553 2483.231553
[68,] 3085.031553 2776.331553
[69,] 2469.731553 3085.031553
[70,] 2044.931553 2469.731553
[71,] 1306.802334 2044.931553
[72,] 1005.406028 1306.802334
[73,] 864.706028 1005.406028
[74,] 808.706028 864.706028
[75,] 346.406028 808.706028
[76,] 297.506028 346.406028
[77,] 346.106028 297.506028
[78,] 5173.717398 346.106028
[79,] 5272.817398 5173.717398
[80,] 4908.517398 5272.817398
[81,] 4825.217398 4908.517398
[82,] 4239.417398 4825.217398
[83,] 3667.288179 4239.417398
[84,] 2586.891873 3667.288179
[85,] 2641.191873 2586.891873
[86,] 2439.191873 2641.191873
[87,] 2737.891873 2439.191873
[88,] 2804.991873 2737.891873
[89,] 2947.591873 2804.991873
[90,] 2971.523943 2947.591873
[91,] 2488.623943 2971.523943
[92,] 1966.323943 2488.623943
[93,] 1032.023943 1966.323943
[94,] 762.223943 1032.023943
[95,] -52.905276 762.223943
[96,] -103.301582 -52.905276
[97,] -245.001582 -103.301582
[98,] -591.001582 -245.001582
[99,] -607.301582 -591.001582
[100,] -480.201582 -607.301582
[101,] -391.601582 -480.201582
[102,] -782.669512 -391.601582
[103,] -1652.569512 -782.669512
[104,] -2776.869512 -1652.569512
[105,] -3003.169512 -2776.869512
[106,] -2815.969512 -3003.169512
[107,] -2683.098731 -2815.969512
[108,] -2933.495037 -2683.098731
[109,] -2848.195037 -2933.495037
[110,] -2427.195037 -2848.195037
[111,] -2566.495037 -2427.195037
[112,] -2675.395037 -2566.495037
[113,] -2370.795037 -2675.395037
[114,] -3429.862967 -2370.795037
[115,] -4231.762967 -3429.862967
[116,] -4929.062967 -4231.762967
[117,] -4676.362967 -4929.062967
[118,] -4191.162967 -4676.362967
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 1206.866757 1170.566757
2 1314.866757 1206.866757
3 1220.566757 1314.866757
4 1210.666757 1220.566757
5 641.266757 1210.666757
6 -1935.801173 641.266757
7 -1281.701173 -1935.801173
8 -1270.001173 -1281.701173
9 -901.301173 -1270.001173
10 -462.101173 -901.301173
11 -746.230392 -462.101173
12 -752.626698 -746.230392
13 -617.326698 -752.626698
14 -526.326698 -617.326698
15 -368.626698 -526.326698
16 -384.526698 -368.626698
17 -634.926698 -384.526698
18 -2841.994628 -634.926698
19 -2044.894628 -2841.994628
20 -2471.194628 -2044.894628
21 -1889.494628 -2471.194628
22 -1529.294628 -1889.494628
23 -1923.423846 -1529.294628
24 -1660.820153 -1923.423846
25 -1493.520153 -1660.820153
26 -1398.520153 -1493.520153
27 -1305.820153 -1398.520153
28 -1252.720153 -1305.820153
29 -1376.120153 -1252.720153
30 -2905.188083 -1376.120153
31 -2560.088083 -2905.188083
32 -1551.388083 -2560.088083
33 -847.688083 -1551.388083
34 -837.488083 -847.688083
35 -1230.617301 -837.488083
36 -1213.013608 -1230.617301
37 -1088.713608 -1213.013608
38 -1020.713608 -1088.713608
39 -1018.013608 -1020.713608
40 -998.913608 -1018.013608
41 -890.313608 -998.913608
42 -512.381538 -890.313608
43 -648.281538 -512.381538
44 649.418462 -648.281538
45 926.118462 649.418462
46 996.318462 926.118462
47 281.189244 996.318462
48 346.792937 281.189244
49 1.092937 346.792937
50 -104.907063 1.092937
51 174.792937 -104.907063
52 200.892937 174.792937
53 416.492937 200.892937
54 1779.425008 416.492937
55 1881.525008 1779.425008
56 2389.225008 1881.525008
57 2064.925008 2389.225008
58 1793.125008 2064.925008
59 1380.995789 1793.125008
60 1553.599483 1380.995789
61 1578.899483 1553.599483
62 1505.899483 1578.899483
63 1386.599483 1505.899483
64 1277.699483 1386.599483
65 1312.299483 1277.699483
66 2483.231553 1312.299483
67 2776.331553 2483.231553
68 3085.031553 2776.331553
69 2469.731553 3085.031553
70 2044.931553 2469.731553
71 1306.802334 2044.931553
72 1005.406028 1306.802334
73 864.706028 1005.406028
74 808.706028 864.706028
75 346.406028 808.706028
76 297.506028 346.406028
77 346.106028 297.506028
78 5173.717398 346.106028
79 5272.817398 5173.717398
80 4908.517398 5272.817398
81 4825.217398 4908.517398
82 4239.417398 4825.217398
83 3667.288179 4239.417398
84 2586.891873 3667.288179
85 2641.191873 2586.891873
86 2439.191873 2641.191873
87 2737.891873 2439.191873
88 2804.991873 2737.891873
89 2947.591873 2804.991873
90 2971.523943 2947.591873
91 2488.623943 2971.523943
92 1966.323943 2488.623943
93 1032.023943 1966.323943
94 762.223943 1032.023943
95 -52.905276 762.223943
96 -103.301582 -52.905276
97 -245.001582 -103.301582
98 -591.001582 -245.001582
99 -607.301582 -591.001582
100 -480.201582 -607.301582
101 -391.601582 -480.201582
102 -782.669512 -391.601582
103 -1652.569512 -782.669512
104 -2776.869512 -1652.569512
105 -3003.169512 -2776.869512
106 -2815.969512 -3003.169512
107 -2683.098731 -2815.969512
108 -2933.495037 -2683.098731
109 -2848.195037 -2933.495037
110 -2427.195037 -2848.195037
111 -2566.495037 -2427.195037
112 -2675.395037 -2566.495037
113 -2370.795037 -2675.395037
114 -3429.862967 -2370.795037
115 -4231.762967 -3429.862967
116 -4929.062967 -4231.762967
117 -4676.362967 -4929.062967
118 -4191.162967 -4676.362967
> 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/7ikwd1229106254.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/88adm1229106254.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/926nl1229106254.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10bp7e1229106254.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11dlen1229106254.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/12bu751229106254.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/13utdn1229106254.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/14o1pm1229106254.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/15956c1229106254.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/16asod1229106254.tab")
+ }
>
> system("convert tmp/19vdi1229106254.ps tmp/19vdi1229106254.png")
> system("convert tmp/2hqmu1229106254.ps tmp/2hqmu1229106254.png")
> system("convert tmp/3tvcc1229106254.ps tmp/3tvcc1229106254.png")
> system("convert tmp/4ie0z1229106254.ps tmp/4ie0z1229106254.png")
> system("convert tmp/5zmqe1229106254.ps tmp/5zmqe1229106254.png")
> system("convert tmp/6alhb1229106254.ps tmp/6alhb1229106254.png")
> system("convert tmp/7ikwd1229106254.ps tmp/7ikwd1229106254.png")
> system("convert tmp/88adm1229106254.ps tmp/88adm1229106254.png")
> system("convert tmp/926nl1229106254.ps tmp/926nl1229106254.png")
> system("convert tmp/10bp7e1229106254.ps tmp/10bp7e1229106254.png")
>
>
> proc.time()
user system elapsed
3.262 1.644 4.144