R version 2.12.0 (2010-10-15)
Copyright (C) 2010 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-bit)
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
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> x <- array(list(20503,22885,26217,26583,27751,28158,27373,28367,26851,26733,26849,26733,27951,29781,32914,33488,35652,36488,35387,35676,34844,32447,31068,29010,29812,30951,32974,32936,34012,32946,31948,30599,27691,25073,23406,22248,22896,25317,26558,26471,27543,26198,24725,25005,23462,20780,19815,19761,21454,23899,24939,23580,24562,24696,23785,23812,21917,19713,19282,18788,21453,24482,27474,27264,27349,30632,29429,30084,26290,24379,23335,21346,21106,24514,28353,30805,31348,34556,33855,34787,32529,29998,29257,28155,30466,35704,39327,39351,42234,43630,43722,43121,37985,37135,34646,33026,35087,38846,42013,43908,42868,44423,44167,43636,44382,42142,43452,36912,42413,45344,44873,47510,49554,47369,45998,48140,48441,44928,40454,38661,37246,36843,36424,37594,38144,38737,34560,36080,33508,35462,33374,32110,35533,35532,37903,36763,40399,44164,44496,43110,43880,43930,44327),dim=c(1,143),dimnames=list(c('OPJV'),1:143))
> y <- array(NA,dim=c(1,143),dimnames=list(c('OPJV'),1:143))
> 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 = 'Do not include Seasonal 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
> 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
OPJV t
1 20503 1
2 22885 2
3 26217 3
4 26583 4
5 27751 5
6 28158 6
7 27373 7
8 28367 8
9 26851 9
10 26733 10
11 26849 11
12 26733 12
13 27951 13
14 29781 14
15 32914 15
16 33488 16
17 35652 17
18 36488 18
19 35387 19
20 35676 20
21 34844 21
22 32447 22
23 31068 23
24 29010 24
25 29812 25
26 30951 26
27 32974 27
28 32936 28
29 34012 29
30 32946 30
31 31948 31
32 30599 32
33 27691 33
34 25073 34
35 23406 35
36 22248 36
37 22896 37
38 25317 38
39 26558 39
40 26471 40
41 27543 41
42 26198 42
43 24725 43
44 25005 44
45 23462 45
46 20780 46
47 19815 47
48 19761 48
49 21454 49
50 23899 50
51 24939 51
52 23580 52
53 24562 53
54 24696 54
55 23785 55
56 23812 56
57 21917 57
58 19713 58
59 19282 59
60 18788 60
61 21453 61
62 24482 62
63 27474 63
64 27264 64
65 27349 65
66 30632 66
67 29429 67
68 30084 68
69 26290 69
70 24379 70
71 23335 71
72 21346 72
73 21106 73
74 24514 74
75 28353 75
76 30805 76
77 31348 77
78 34556 78
79 33855 79
80 34787 80
81 32529 81
82 29998 82
83 29257 83
84 28155 84
85 30466 85
86 35704 86
87 39327 87
88 39351 88
89 42234 89
90 43630 90
91 43722 91
92 43121 92
93 37985 93
94 37135 94
95 34646 95
96 33026 96
97 35087 97
98 38846 98
99 42013 99
100 43908 100
101 42868 101
102 44423 102
103 44167 103
104 43636 104
105 44382 105
106 42142 106
107 43452 107
108 36912 108
109 42413 109
110 45344 110
111 44873 111
112 47510 112
113 49554 113
114 47369 114
115 45998 115
116 48140 116
117 48441 117
118 44928 118
119 40454 119
120 38661 120
121 37246 121
122 36843 122
123 36424 123
124 37594 124
125 38144 125
126 38737 126
127 34560 127
128 36080 128
129 33508 129
130 35462 130
131 33374 131
132 32110 132
133 35533 133
134 35532 134
135 37903 135
136 36763 136
137 40399 137
138 44164 138
139 44496 139
140 43110 140
141 43880 141
142 43930 142
143 44327 143
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) t
23615.9 126.7
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-12432.5 -4638.3 -392.3 4633.0 11616.0
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 23615.90 999.99 23.62 <2e-16 ***
t 126.74 12.05 10.52 <2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 5948 on 141 degrees of freedom
Multiple R-squared: 0.4397, Adjusted R-squared: 0.4357
F-statistic: 110.7 on 1 and 141 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,] 5.936203e-03 1.187241e-02 9.940638e-01
[2,] 2.262666e-03 4.525332e-03 9.977373e-01
[3,] 2.312440e-03 4.624881e-03 9.976876e-01
[4,] 8.352344e-04 1.670469e-03 9.991648e-01
[5,] 9.231536e-04 1.846307e-03 9.990768e-01
[6,] 6.414566e-04 1.282913e-03 9.993585e-01
[7,] 3.273192e-04 6.546384e-04 9.996727e-01
[8,] 1.547802e-04 3.095604e-04 9.998452e-01
[9,] 4.749295e-05 9.498591e-05 9.999525e-01
[10,] 1.464897e-05 2.929794e-05 9.999854e-01
[11,] 1.522360e-05 3.044720e-05 9.999848e-01
[12,] 1.013541e-05 2.027083e-05 9.999899e-01
[13,] 1.311633e-05 2.623267e-05 9.999869e-01
[14,] 1.243119e-05 2.486238e-05 9.999876e-01
[15,] 5.466925e-06 1.093385e-05 9.999945e-01
[16,] 2.383256e-06 4.766512e-06 9.999976e-01
[17,] 1.207666e-06 2.415332e-06 9.999988e-01
[18,] 2.298153e-06 4.596305e-06 9.999977e-01
[19,] 8.733894e-06 1.746779e-05 9.999913e-01
[20,] 6.793609e-05 1.358722e-04 9.999321e-01
[21,] 1.441051e-04 2.882101e-04 9.998559e-01
[22,] 1.589465e-04 3.178931e-04 9.998411e-01
[23,] 1.162597e-04 2.325193e-04 9.998837e-01
[24,] 8.967233e-05 1.793447e-04 9.999103e-01
[25,] 6.796947e-05 1.359389e-04 9.999320e-01
[26,] 6.015969e-05 1.203194e-04 9.999398e-01
[27,] 6.659174e-05 1.331835e-04 9.999334e-01
[28,] 1.031920e-04 2.063840e-04 9.998968e-01
[29,] 3.863339e-04 7.726678e-04 9.996137e-01
[30,] 2.287253e-03 4.574506e-03 9.977127e-01
[31,] 1.035238e-02 2.070476e-02 9.896476e-01
[32,] 3.125652e-02 6.251305e-02 9.687435e-01
[33,] 5.156795e-02 1.031359e-01 9.484320e-01
[34,] 5.212025e-02 1.042405e-01 9.478798e-01
[35,] 4.597468e-02 9.194936e-02 9.540253e-01
[36,] 3.970248e-02 7.940496e-02 9.602975e-01
[37,] 3.241184e-02 6.482369e-02 9.675882e-01
[38,] 2.724181e-02 5.448362e-02 9.727582e-01
[39,] 2.454309e-02 4.908618e-02 9.754569e-01
[40,] 2.080650e-02 4.161300e-02 9.791935e-01
[41,] 1.942535e-02 3.885071e-02 9.805746e-01
[42,] 2.428239e-02 4.856478e-02 9.757176e-01
[43,] 3.157319e-02 6.314638e-02 9.684268e-01
[44,] 3.731171e-02 7.462341e-02 9.626883e-01
[45,] 3.399801e-02 6.799603e-02 9.660020e-01
[46,] 2.585148e-02 5.170296e-02 9.741485e-01
[47,] 1.895032e-02 3.790064e-02 9.810497e-01
[48,] 1.415634e-02 2.831269e-02 9.858437e-01
[49,] 1.015107e-02 2.030214e-02 9.898489e-01
[50,] 7.181864e-03 1.436373e-02 9.928181e-01
[51,] 5.140383e-03 1.028077e-02 9.948596e-01
[52,] 3.647886e-03 7.295771e-03 9.963521e-01
[53,] 2.936634e-03 5.873269e-03 9.970634e-01
[54,] 3.188471e-03 6.376941e-03 9.968115e-01
[55,] 3.752332e-03 7.504663e-03 9.962477e-01
[56,] 4.925622e-03 9.851244e-03 9.950744e-01
[57,] 4.586692e-03 9.173383e-03 9.954133e-01
[58,] 3.772059e-03 7.544118e-03 9.962279e-01
[59,] 3.550162e-03 7.100324e-03 9.964498e-01
[60,] 3.244340e-03 6.488681e-03 9.967557e-01
[61,] 2.961530e-03 5.923060e-03 9.970385e-01
[62,] 3.819048e-03 7.638096e-03 9.961810e-01
[63,] 3.935891e-03 7.871781e-03 9.960641e-01
[64,] 4.194845e-03 8.389689e-03 9.958052e-01
[65,] 3.613785e-03 7.227570e-03 9.963862e-01
[66,] 3.506715e-03 7.013430e-03 9.964933e-01
[67,] 4.046934e-03 8.093869e-03 9.959531e-01
[68,] 7.040106e-03 1.408021e-02 9.929599e-01
[69,] 1.483067e-02 2.966135e-02 9.851693e-01
[70,] 2.180540e-02 4.361079e-02 9.781946e-01
[71,] 2.820292e-02 5.640583e-02 9.717971e-01
[72,] 3.833853e-02 7.667707e-02 9.616615e-01
[73,] 5.156624e-02 1.031325e-01 9.484338e-01
[74,] 7.956318e-02 1.591264e-01 9.204368e-01
[75,] 1.050352e-01 2.100703e-01 8.949648e-01
[76,] 1.361023e-01 2.722046e-01 8.638977e-01
[77,] 1.571317e-01 3.142634e-01 8.428683e-01
[78,] 1.912281e-01 3.824561e-01 8.087719e-01
[79,] 2.516187e-01 5.032374e-01 7.483813e-01
[80,] 3.721577e-01 7.443155e-01 6.278423e-01
[81,] 4.904271e-01 9.808542e-01 5.095729e-01
[82,] 5.703847e-01 8.592306e-01 4.296153e-01
[83,] 6.598090e-01 6.803820e-01 3.401910e-01
[84,] 7.239356e-01 5.521288e-01 2.760644e-01
[85,] 7.988709e-01 4.022583e-01 2.011291e-01
[86,] 8.620587e-01 2.758825e-01 1.379413e-01
[87,] 9.005329e-01 1.989343e-01 9.946714e-02
[88,] 9.195514e-01 1.608972e-01 8.044862e-02
[89,] 9.175893e-01 1.648214e-01 8.241072e-02
[90,] 9.171179e-01 1.657642e-01 8.288209e-02
[91,] 9.307007e-01 1.385986e-01 6.929929e-02
[92,] 9.583912e-01 8.321764e-02 4.160882e-02
[93,] 9.724169e-01 5.516628e-02 2.758314e-02
[94,] 9.750525e-01 4.989494e-02 2.494747e-02
[95,] 9.748597e-01 5.028056e-02 2.514028e-02
[96,] 9.749491e-01 5.010178e-02 2.505089e-02
[97,] 9.729696e-01 5.406085e-02 2.703043e-02
[98,] 9.715643e-01 5.687148e-02 2.843574e-02
[99,] 9.686259e-01 6.274828e-02 3.137414e-02
[100,] 9.636711e-01 7.265770e-02 3.632885e-02
[101,] 9.585108e-01 8.297842e-02 4.148921e-02
[102,] 9.489306e-01 1.021388e-01 5.106939e-02
[103,] 9.380762e-01 1.238477e-01 6.192383e-02
[104,] 9.424744e-01 1.150512e-01 5.752562e-02
[105,] 9.285662e-01 1.428676e-01 7.143379e-02
[106,] 9.175726e-01 1.648549e-01 8.242744e-02
[107,] 9.026153e-01 1.947694e-01 9.738468e-02
[108,] 9.070865e-01 1.858270e-01 9.291348e-02
[109,] 9.387724e-01 1.224551e-01 6.122756e-02
[110,] 9.513084e-01 9.738327e-02 4.869163e-02
[111,] 9.581386e-01 8.372280e-02 4.186140e-02
[112,] 9.828499e-01 3.430029e-02 1.715015e-02
[113,] 9.977276e-01 4.544878e-03 2.272439e-03
[114,] 9.996427e-01 7.146018e-04 3.573009e-04
[115,] 9.997845e-01 4.309686e-04 2.154843e-04
[116,] 9.998030e-01 3.939731e-04 1.969865e-04
[117,] 9.997491e-01 5.017344e-04 2.508672e-04
[118,] 9.996630e-01 6.739831e-04 3.369916e-04
[119,] 9.995136e-01 9.728929e-04 4.864465e-04
[120,] 9.995504e-01 8.991621e-04 4.495811e-04
[121,] 9.997661e-01 4.677972e-04 2.338986e-04
[122,] 9.999742e-01 5.156756e-05 2.578378e-05
[123,] 9.999641e-01 7.171993e-05 3.585997e-05
[124,] 9.999857e-01 2.869590e-05 1.434795e-05
[125,] 9.999653e-01 6.949183e-05 3.474591e-05
[126,] 9.999682e-01 6.351982e-05 3.175991e-05
[127,] 9.998930e-01 2.139943e-04 1.069971e-04
[128,] 9.998250e-01 3.500670e-04 1.750335e-04
[129,] 9.993859e-01 1.228116e-03 6.140580e-04
[130,] 9.985718e-01 2.856326e-03 1.428163e-03
[131,] 9.955077e-01 8.984533e-03 4.492266e-03
[132,] 9.988519e-01 2.296256e-03 1.148128e-03
[133,] 9.998674e-01 2.651820e-04 1.325910e-04
[134,] 9.985557e-01 2.888501e-03 1.444251e-03
> postscript(file="/var/www/rcomp/tmp/1mfe91293462005.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
> points(x[,1]-mysum$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/2xodu1293462005.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/3xodu1293462005.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/4xodu1293462005.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/5pfuf1293462005.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
> qqline(mysum$resid)
> grid()
> dev.off()
null device
1
> (myerror <- as.ts(mysum$resid))
Time Series:
Start = 1
End = 143
Frequency = 1
1 2 3 4 5 6
-3239.6413 -984.3854 2220.8706 2460.1265 3501.3825 3781.6385
7 8 9 10 11 12
2869.8944 3737.1504 2094.4063 1849.6623 1838.9182 1596.1742
13 14 15 16 17 18
2687.4301 4390.6861 7396.9420 7844.1980 9881.4540 10590.7099
19 20 21 22 23 24
9362.9659 9525.2218 8566.4778 6042.7337 4536.9897 2352.2456
25 26 27 28 29 30
3027.5016 4039.7576 5936.0135 5771.2695 6720.5254 5527.7814
31 32 33 34 35 36
4403.0373 2927.2933 -107.4508 -2852.1948 -4645.9389 -5930.6829
37 38 39 40 41 42
-5409.4269 -3115.1710 -2000.9150 -2214.6591 -1269.4031 -2741.1472
43 44 45 46 47 48
-4340.8912 -4187.6353 -5857.3793 -8666.1234 -9757.8674 -9938.6114
49 50 51 52 53 54
-8372.3555 -6054.0995 -5140.8436 -6626.5876 -5771.3317 -5764.0757
55 56 57 58 59 60
-6801.8198 -6901.5638 -8923.3079 -11254.0519 -11811.7959 -12432.5400
61 62 63 64 65 66
-9894.2840 -6992.0281 -4126.7721 -4463.5162 -4505.2602 -1349.0043
67 68 69 70 71 72
-2678.7483 -2150.4924 -6071.2364 -8108.9804 -9279.7245 -11395.4685
73 74 75 76 77 78
-11762.2126 -8480.9566 -4768.7007 -2443.4447 -2027.1888 1054.0672
79 80 81 82 83 84
226.3232 1031.5791 -1353.1649 -4010.9090 -4878.6530 -6107.3971
85 86 87 88 89 90
-3923.1411 1188.1148 4684.3708 4581.6267 7337.8827 8607.1387
91 92 93 94 95 96
8572.3946 7844.6506 2581.9065 1605.1625 -1010.5816 -2757.3256
97 98 99 100 101 102
-823.0697 2809.1863 5849.4422 7617.6982 6450.9542 7879.2101
103 104 105 106 107 108
7496.4661 6838.7220 7457.9780 5091.2339 6274.4899 -392.2542
109 110 111 112 113 114
4982.0018 7786.2577 7188.5137 9698.7697 11616.0256 9304.2816
115 116 117 118 119 120
7806.5375 9821.7935 9996.0494 6356.3054 1755.5613 -164.1827
121 122 123 124 125 126
-1705.9267 -2235.6708 -2781.4148 -1738.1589 -1314.9029 -848.6470
127 128 129 130 131 132
-5152.3910 -3759.1351 -6457.8791 -4630.6232 -6845.3672 -8236.1112
133 134 135 136 137 138
-4939.8553 -5067.5993 -2823.3434 -4090.0874 -580.8315 3057.4245
139 140 141 142 143
3262.6804 1749.9364 2393.1923 2316.4483 2586.7043
> postscript(file="/var/www/rcomp/tmp/6pfuf1293462005.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> dum <- cbind(lag(myerror,k=1),myerror)
> dum
Time Series:
Start = 0
End = 143
Frequency = 1
lag(myerror, k = 1) myerror
0 -3239.6413 NA
1 -984.3854 -3239.6413
2 2220.8706 -984.3854
3 2460.1265 2220.8706
4 3501.3825 2460.1265
5 3781.6385 3501.3825
6 2869.8944 3781.6385
7 3737.1504 2869.8944
8 2094.4063 3737.1504
9 1849.6623 2094.4063
10 1838.9182 1849.6623
11 1596.1742 1838.9182
12 2687.4301 1596.1742
13 4390.6861 2687.4301
14 7396.9420 4390.6861
15 7844.1980 7396.9420
16 9881.4540 7844.1980
17 10590.7099 9881.4540
18 9362.9659 10590.7099
19 9525.2218 9362.9659
20 8566.4778 9525.2218
21 6042.7337 8566.4778
22 4536.9897 6042.7337
23 2352.2456 4536.9897
24 3027.5016 2352.2456
25 4039.7576 3027.5016
26 5936.0135 4039.7576
27 5771.2695 5936.0135
28 6720.5254 5771.2695
29 5527.7814 6720.5254
30 4403.0373 5527.7814
31 2927.2933 4403.0373
32 -107.4508 2927.2933
33 -2852.1948 -107.4508
34 -4645.9389 -2852.1948
35 -5930.6829 -4645.9389
36 -5409.4269 -5930.6829
37 -3115.1710 -5409.4269
38 -2000.9150 -3115.1710
39 -2214.6591 -2000.9150
40 -1269.4031 -2214.6591
41 -2741.1472 -1269.4031
42 -4340.8912 -2741.1472
43 -4187.6353 -4340.8912
44 -5857.3793 -4187.6353
45 -8666.1234 -5857.3793
46 -9757.8674 -8666.1234
47 -9938.6114 -9757.8674
48 -8372.3555 -9938.6114
49 -6054.0995 -8372.3555
50 -5140.8436 -6054.0995
51 -6626.5876 -5140.8436
52 -5771.3317 -6626.5876
53 -5764.0757 -5771.3317
54 -6801.8198 -5764.0757
55 -6901.5638 -6801.8198
56 -8923.3079 -6901.5638
57 -11254.0519 -8923.3079
58 -11811.7959 -11254.0519
59 -12432.5400 -11811.7959
60 -9894.2840 -12432.5400
61 -6992.0281 -9894.2840
62 -4126.7721 -6992.0281
63 -4463.5162 -4126.7721
64 -4505.2602 -4463.5162
65 -1349.0043 -4505.2602
66 -2678.7483 -1349.0043
67 -2150.4924 -2678.7483
68 -6071.2364 -2150.4924
69 -8108.9804 -6071.2364
70 -9279.7245 -8108.9804
71 -11395.4685 -9279.7245
72 -11762.2126 -11395.4685
73 -8480.9566 -11762.2126
74 -4768.7007 -8480.9566
75 -2443.4447 -4768.7007
76 -2027.1888 -2443.4447
77 1054.0672 -2027.1888
78 226.3232 1054.0672
79 1031.5791 226.3232
80 -1353.1649 1031.5791
81 -4010.9090 -1353.1649
82 -4878.6530 -4010.9090
83 -6107.3971 -4878.6530
84 -3923.1411 -6107.3971
85 1188.1148 -3923.1411
86 4684.3708 1188.1148
87 4581.6267 4684.3708
88 7337.8827 4581.6267
89 8607.1387 7337.8827
90 8572.3946 8607.1387
91 7844.6506 8572.3946
92 2581.9065 7844.6506
93 1605.1625 2581.9065
94 -1010.5816 1605.1625
95 -2757.3256 -1010.5816
96 -823.0697 -2757.3256
97 2809.1863 -823.0697
98 5849.4422 2809.1863
99 7617.6982 5849.4422
100 6450.9542 7617.6982
101 7879.2101 6450.9542
102 7496.4661 7879.2101
103 6838.7220 7496.4661
104 7457.9780 6838.7220
105 5091.2339 7457.9780
106 6274.4899 5091.2339
107 -392.2542 6274.4899
108 4982.0018 -392.2542
109 7786.2577 4982.0018
110 7188.5137 7786.2577
111 9698.7697 7188.5137
112 11616.0256 9698.7697
113 9304.2816 11616.0256
114 7806.5375 9304.2816
115 9821.7935 7806.5375
116 9996.0494 9821.7935
117 6356.3054 9996.0494
118 1755.5613 6356.3054
119 -164.1827 1755.5613
120 -1705.9267 -164.1827
121 -2235.6708 -1705.9267
122 -2781.4148 -2235.6708
123 -1738.1589 -2781.4148
124 -1314.9029 -1738.1589
125 -848.6470 -1314.9029
126 -5152.3910 -848.6470
127 -3759.1351 -5152.3910
128 -6457.8791 -3759.1351
129 -4630.6232 -6457.8791
130 -6845.3672 -4630.6232
131 -8236.1112 -6845.3672
132 -4939.8553 -8236.1112
133 -5067.5993 -4939.8553
134 -2823.3434 -5067.5993
135 -4090.0874 -2823.3434
136 -580.8315 -4090.0874
137 3057.4245 -580.8315
138 3262.6804 3057.4245
139 1749.9364 3262.6804
140 2393.1923 1749.9364
141 2316.4483 2393.1923
142 2586.7043 2316.4483
143 NA 2586.7043
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -984.3854 -3239.6413
[2,] 2220.8706 -984.3854
[3,] 2460.1265 2220.8706
[4,] 3501.3825 2460.1265
[5,] 3781.6385 3501.3825
[6,] 2869.8944 3781.6385
[7,] 3737.1504 2869.8944
[8,] 2094.4063 3737.1504
[9,] 1849.6623 2094.4063
[10,] 1838.9182 1849.6623
[11,] 1596.1742 1838.9182
[12,] 2687.4301 1596.1742
[13,] 4390.6861 2687.4301
[14,] 7396.9420 4390.6861
[15,] 7844.1980 7396.9420
[16,] 9881.4540 7844.1980
[17,] 10590.7099 9881.4540
[18,] 9362.9659 10590.7099
[19,] 9525.2218 9362.9659
[20,] 8566.4778 9525.2218
[21,] 6042.7337 8566.4778
[22,] 4536.9897 6042.7337
[23,] 2352.2456 4536.9897
[24,] 3027.5016 2352.2456
[25,] 4039.7576 3027.5016
[26,] 5936.0135 4039.7576
[27,] 5771.2695 5936.0135
[28,] 6720.5254 5771.2695
[29,] 5527.7814 6720.5254
[30,] 4403.0373 5527.7814
[31,] 2927.2933 4403.0373
[32,] -107.4508 2927.2933
[33,] -2852.1948 -107.4508
[34,] -4645.9389 -2852.1948
[35,] -5930.6829 -4645.9389
[36,] -5409.4269 -5930.6829
[37,] -3115.1710 -5409.4269
[38,] -2000.9150 -3115.1710
[39,] -2214.6591 -2000.9150
[40,] -1269.4031 -2214.6591
[41,] -2741.1472 -1269.4031
[42,] -4340.8912 -2741.1472
[43,] -4187.6353 -4340.8912
[44,] -5857.3793 -4187.6353
[45,] -8666.1234 -5857.3793
[46,] -9757.8674 -8666.1234
[47,] -9938.6114 -9757.8674
[48,] -8372.3555 -9938.6114
[49,] -6054.0995 -8372.3555
[50,] -5140.8436 -6054.0995
[51,] -6626.5876 -5140.8436
[52,] -5771.3317 -6626.5876
[53,] -5764.0757 -5771.3317
[54,] -6801.8198 -5764.0757
[55,] -6901.5638 -6801.8198
[56,] -8923.3079 -6901.5638
[57,] -11254.0519 -8923.3079
[58,] -11811.7959 -11254.0519
[59,] -12432.5400 -11811.7959
[60,] -9894.2840 -12432.5400
[61,] -6992.0281 -9894.2840
[62,] -4126.7721 -6992.0281
[63,] -4463.5162 -4126.7721
[64,] -4505.2602 -4463.5162
[65,] -1349.0043 -4505.2602
[66,] -2678.7483 -1349.0043
[67,] -2150.4924 -2678.7483
[68,] -6071.2364 -2150.4924
[69,] -8108.9804 -6071.2364
[70,] -9279.7245 -8108.9804
[71,] -11395.4685 -9279.7245
[72,] -11762.2126 -11395.4685
[73,] -8480.9566 -11762.2126
[74,] -4768.7007 -8480.9566
[75,] -2443.4447 -4768.7007
[76,] -2027.1888 -2443.4447
[77,] 1054.0672 -2027.1888
[78,] 226.3232 1054.0672
[79,] 1031.5791 226.3232
[80,] -1353.1649 1031.5791
[81,] -4010.9090 -1353.1649
[82,] -4878.6530 -4010.9090
[83,] -6107.3971 -4878.6530
[84,] -3923.1411 -6107.3971
[85,] 1188.1148 -3923.1411
[86,] 4684.3708 1188.1148
[87,] 4581.6267 4684.3708
[88,] 7337.8827 4581.6267
[89,] 8607.1387 7337.8827
[90,] 8572.3946 8607.1387
[91,] 7844.6506 8572.3946
[92,] 2581.9065 7844.6506
[93,] 1605.1625 2581.9065
[94,] -1010.5816 1605.1625
[95,] -2757.3256 -1010.5816
[96,] -823.0697 -2757.3256
[97,] 2809.1863 -823.0697
[98,] 5849.4422 2809.1863
[99,] 7617.6982 5849.4422
[100,] 6450.9542 7617.6982
[101,] 7879.2101 6450.9542
[102,] 7496.4661 7879.2101
[103,] 6838.7220 7496.4661
[104,] 7457.9780 6838.7220
[105,] 5091.2339 7457.9780
[106,] 6274.4899 5091.2339
[107,] -392.2542 6274.4899
[108,] 4982.0018 -392.2542
[109,] 7786.2577 4982.0018
[110,] 7188.5137 7786.2577
[111,] 9698.7697 7188.5137
[112,] 11616.0256 9698.7697
[113,] 9304.2816 11616.0256
[114,] 7806.5375 9304.2816
[115,] 9821.7935 7806.5375
[116,] 9996.0494 9821.7935
[117,] 6356.3054 9996.0494
[118,] 1755.5613 6356.3054
[119,] -164.1827 1755.5613
[120,] -1705.9267 -164.1827
[121,] -2235.6708 -1705.9267
[122,] -2781.4148 -2235.6708
[123,] -1738.1589 -2781.4148
[124,] -1314.9029 -1738.1589
[125,] -848.6470 -1314.9029
[126,] -5152.3910 -848.6470
[127,] -3759.1351 -5152.3910
[128,] -6457.8791 -3759.1351
[129,] -4630.6232 -6457.8791
[130,] -6845.3672 -4630.6232
[131,] -8236.1112 -6845.3672
[132,] -4939.8553 -8236.1112
[133,] -5067.5993 -4939.8553
[134,] -2823.3434 -5067.5993
[135,] -4090.0874 -2823.3434
[136,] -580.8315 -4090.0874
[137,] 3057.4245 -580.8315
[138,] 3262.6804 3057.4245
[139,] 1749.9364 3262.6804
[140,] 2393.1923 1749.9364
[141,] 2316.4483 2393.1923
[142,] 2586.7043 2316.4483
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -984.3854 -3239.6413
2 2220.8706 -984.3854
3 2460.1265 2220.8706
4 3501.3825 2460.1265
5 3781.6385 3501.3825
6 2869.8944 3781.6385
7 3737.1504 2869.8944
8 2094.4063 3737.1504
9 1849.6623 2094.4063
10 1838.9182 1849.6623
11 1596.1742 1838.9182
12 2687.4301 1596.1742
13 4390.6861 2687.4301
14 7396.9420 4390.6861
15 7844.1980 7396.9420
16 9881.4540 7844.1980
17 10590.7099 9881.4540
18 9362.9659 10590.7099
19 9525.2218 9362.9659
20 8566.4778 9525.2218
21 6042.7337 8566.4778
22 4536.9897 6042.7337
23 2352.2456 4536.9897
24 3027.5016 2352.2456
25 4039.7576 3027.5016
26 5936.0135 4039.7576
27 5771.2695 5936.0135
28 6720.5254 5771.2695
29 5527.7814 6720.5254
30 4403.0373 5527.7814
31 2927.2933 4403.0373
32 -107.4508 2927.2933
33 -2852.1948 -107.4508
34 -4645.9389 -2852.1948
35 -5930.6829 -4645.9389
36 -5409.4269 -5930.6829
37 -3115.1710 -5409.4269
38 -2000.9150 -3115.1710
39 -2214.6591 -2000.9150
40 -1269.4031 -2214.6591
41 -2741.1472 -1269.4031
42 -4340.8912 -2741.1472
43 -4187.6353 -4340.8912
44 -5857.3793 -4187.6353
45 -8666.1234 -5857.3793
46 -9757.8674 -8666.1234
47 -9938.6114 -9757.8674
48 -8372.3555 -9938.6114
49 -6054.0995 -8372.3555
50 -5140.8436 -6054.0995
51 -6626.5876 -5140.8436
52 -5771.3317 -6626.5876
53 -5764.0757 -5771.3317
54 -6801.8198 -5764.0757
55 -6901.5638 -6801.8198
56 -8923.3079 -6901.5638
57 -11254.0519 -8923.3079
58 -11811.7959 -11254.0519
59 -12432.5400 -11811.7959
60 -9894.2840 -12432.5400
61 -6992.0281 -9894.2840
62 -4126.7721 -6992.0281
63 -4463.5162 -4126.7721
64 -4505.2602 -4463.5162
65 -1349.0043 -4505.2602
66 -2678.7483 -1349.0043
67 -2150.4924 -2678.7483
68 -6071.2364 -2150.4924
69 -8108.9804 -6071.2364
70 -9279.7245 -8108.9804
71 -11395.4685 -9279.7245
72 -11762.2126 -11395.4685
73 -8480.9566 -11762.2126
74 -4768.7007 -8480.9566
75 -2443.4447 -4768.7007
76 -2027.1888 -2443.4447
77 1054.0672 -2027.1888
78 226.3232 1054.0672
79 1031.5791 226.3232
80 -1353.1649 1031.5791
81 -4010.9090 -1353.1649
82 -4878.6530 -4010.9090
83 -6107.3971 -4878.6530
84 -3923.1411 -6107.3971
85 1188.1148 -3923.1411
86 4684.3708 1188.1148
87 4581.6267 4684.3708
88 7337.8827 4581.6267
89 8607.1387 7337.8827
90 8572.3946 8607.1387
91 7844.6506 8572.3946
92 2581.9065 7844.6506
93 1605.1625 2581.9065
94 -1010.5816 1605.1625
95 -2757.3256 -1010.5816
96 -823.0697 -2757.3256
97 2809.1863 -823.0697
98 5849.4422 2809.1863
99 7617.6982 5849.4422
100 6450.9542 7617.6982
101 7879.2101 6450.9542
102 7496.4661 7879.2101
103 6838.7220 7496.4661
104 7457.9780 6838.7220
105 5091.2339 7457.9780
106 6274.4899 5091.2339
107 -392.2542 6274.4899
108 4982.0018 -392.2542
109 7786.2577 4982.0018
110 7188.5137 7786.2577
111 9698.7697 7188.5137
112 11616.0256 9698.7697
113 9304.2816 11616.0256
114 7806.5375 9304.2816
115 9821.7935 7806.5375
116 9996.0494 9821.7935
117 6356.3054 9996.0494
118 1755.5613 6356.3054
119 -164.1827 1755.5613
120 -1705.9267 -164.1827
121 -2235.6708 -1705.9267
122 -2781.4148 -2235.6708
123 -1738.1589 -2781.4148
124 -1314.9029 -1738.1589
125 -848.6470 -1314.9029
126 -5152.3910 -848.6470
127 -3759.1351 -5152.3910
128 -6457.8791 -3759.1351
129 -4630.6232 -6457.8791
130 -6845.3672 -4630.6232
131 -8236.1112 -6845.3672
132 -4939.8553 -8236.1112
133 -5067.5993 -4939.8553
134 -2823.3434 -5067.5993
135 -4090.0874 -2823.3434
136 -580.8315 -4090.0874
137 3057.4245 -580.8315
138 3262.6804 3057.4245
139 1749.9364 3262.6804
140 2393.1923 1749.9364
141 2316.4483 2393.1923
142 2586.7043 2316.4483
> 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/rcomp/tmp/7na0o1293462005.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/8tgbl1293462005.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/9tgbl1293462005.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/rcomp/tmp/10tgbl1293462005.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/rcomp/tmp/11p8qt1293462005.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/rcomp/tmp/12s87h1293462005.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/rcomp/tmp/13z9mt1293462005.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/rcomp/tmp/14s1le1293462005.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/rcomp/tmp/15v12k1293462005.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/rcomp/tmp/169tit1293462005.tab")
+ }
>
> try(system("convert tmp/1mfe91293462005.ps tmp/1mfe91293462005.png",intern=TRUE))
character(0)
> try(system("convert tmp/2xodu1293462005.ps tmp/2xodu1293462005.png",intern=TRUE))
character(0)
> try(system("convert tmp/3xodu1293462005.ps tmp/3xodu1293462005.png",intern=TRUE))
character(0)
> try(system("convert tmp/4xodu1293462005.ps tmp/4xodu1293462005.png",intern=TRUE))
character(0)
> try(system("convert tmp/5pfuf1293462005.ps tmp/5pfuf1293462005.png",intern=TRUE))
character(0)
> try(system("convert tmp/6pfuf1293462005.ps tmp/6pfuf1293462005.png",intern=TRUE))
character(0)
> try(system("convert tmp/7na0o1293462005.ps tmp/7na0o1293462005.png",intern=TRUE))
character(0)
> try(system("convert tmp/8tgbl1293462005.ps tmp/8tgbl1293462005.png",intern=TRUE))
character(0)
> try(system("convert tmp/9tgbl1293462005.ps tmp/9tgbl1293462005.png",intern=TRUE))
character(0)
> try(system("convert tmp/10tgbl1293462005.ps tmp/10tgbl1293462005.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
4.160 1.640 5.782