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.
Natural language support but running in an English locale
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Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> x <- array(list(18,15,15,0,17,3,21,2,22,3,24,12,17,3,25,0,16,12,18,15,21,0,19,10,18,20,20,20,25,2,28,3,19,16,20,4,25,2,20,4,21,0,21,0,23,15,19,9,23,1,20,15,19,5,17,4,19,15,21,4,18,12,18,2,24,4,22,2,20,4,17,8,25,30,24,6,18,6,21,7,13,4,21,17,21,5,16,0,18,3,19,4,22,15,18,0,18,8,20,10,19,4,18,0,20,6,20,11,23,10,17,0,17,0,18,0,22,0,16,0,18,0,14,0,13,7,21,4,25,12,16,6,17,12,22,10,24,9,18,0,18,16,18,2,19,0,15,0,25,1,22,10,15,14,21,12,16,12,23,12,20,5,19,0,20,4,18,3,18,0,20,3,20,0,16,12,18,12,18,15,16,0,23,8,14,6,21,14,13,5,27,10,20,16,22,4,21,0,19,8,22,12,12,6,28,4,21,20,18,0,21,13,19,0,23,0,21,0,21,0,22,10,18,6,15,16,23,6,24,0,18,4,15,9,19,17,17,12,14,3,16,8,22,3,15,0,23,10,24,3,24,0,20,8,9,0,23,4,18,13,20,12,25,16,17,20,21,20,26,14,20,12,21,15,15,9,20,4,20,8,16,0,19,13,22,0,17,21,25,0,19,1,17,16,21,12,12,2),dim=c(2,149),dimnames=list(c('Perf','Sport
'),1:149))
> y <- array(NA,dim=c(2,149),dimnames=list(c('Perf','Sport
'),1:149))
> 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
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
Perf Sport\r t
1 18 15 1
2 15 0 2
3 17 3 3
4 21 2 4
5 22 3 5
6 24 12 6
7 17 3 7
8 25 0 8
9 16 12 9
10 18 15 10
11 21 0 11
12 19 10 12
13 18 20 13
14 20 20 14
15 25 2 15
16 28 3 16
17 19 16 17
18 20 4 18
19 25 2 19
20 20 4 20
21 21 0 21
22 21 0 22
23 23 15 23
24 19 9 24
25 23 1 25
26 20 15 26
27 19 5 27
28 17 4 28
29 19 15 29
30 21 4 30
31 18 12 31
32 18 2 32
33 24 4 33
34 22 2 34
35 20 4 35
36 17 8 36
37 25 30 37
38 24 6 38
39 18 6 39
40 21 7 40
41 13 4 41
42 21 17 42
43 21 5 43
44 16 0 44
45 18 3 45
46 19 4 46
47 22 15 47
48 18 0 48
49 18 8 49
50 20 10 50
51 19 4 51
52 18 0 52
53 20 6 53
54 20 11 54
55 23 10 55
56 17 0 56
57 17 0 57
58 18 0 58
59 22 0 59
60 16 0 60
61 18 0 61
62 14 0 62
63 13 7 63
64 21 4 64
65 25 12 65
66 16 6 66
67 17 12 67
68 22 10 68
69 24 9 69
70 18 0 70
71 18 16 71
72 18 2 72
73 19 0 73
74 15 0 74
75 25 1 75
76 22 10 76
77 15 14 77
78 21 12 78
79 16 12 79
80 23 12 80
81 20 5 81
82 19 0 82
83 20 4 83
84 18 3 84
85 18 0 85
86 20 3 86
87 20 0 87
88 16 12 88
89 18 12 89
90 18 15 90
91 16 0 91
92 23 8 92
93 14 6 93
94 21 14 94
95 13 5 95
96 27 10 96
97 20 16 97
98 22 4 98
99 21 0 99
100 19 8 100
101 22 12 101
102 12 6 102
103 28 4 103
104 21 20 104
105 18 0 105
106 21 13 106
107 19 0 107
108 23 0 108
109 21 0 109
110 21 0 110
111 22 10 111
112 18 6 112
113 15 16 113
114 23 6 114
115 24 0 115
116 18 4 116
117 15 9 117
118 19 17 118
119 17 12 119
120 14 3 120
121 16 8 121
122 22 3 122
123 15 0 123
124 23 10 124
125 24 3 125
126 24 0 126
127 20 8 127
128 9 0 128
129 23 4 129
130 18 13 130
131 20 12 131
132 25 16 132
133 17 20 133
134 21 20 134
135 26 14 135
136 20 12 136
137 21 15 137
138 15 9 138
139 20 4 139
140 20 8 140
141 16 0 141
142 19 13 142
143 22 0 143
144 17 21 144
145 25 0 145
146 19 1 146
147 17 16 147
148 21 12 148
149 12 2 149
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) `Sport\r` t
19.734014 0.041207 -0.006098
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-9.9535 -2.3460 0.1150 2.1729 8.7292
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 19.734014 0.616293 32.021 <2e-16 ***
`Sport\r` 0.041207 0.044138 0.934 0.352
t -0.006098 0.006422 -0.950 0.344
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 3.362 on 146 degrees of freedom
Multiple R-squared: 0.01116, Adjusted R-squared: -0.002386
F-statistic: 0.8239 on 2 and 146 DF, p-value: 0.4408
> if (n > n25) {
+ kp3 <- k + 3
+ nmkm3 <- n - k - 3
+ gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
+ numgqtests <- 0
+ numsignificant1 <- 0
+ numsignificant5 <- 0
+ numsignificant10 <- 0
+ for (mypoint in kp3:nmkm3) {
+ j <- 0
+ numgqtests <- numgqtests + 1
+ for (myalt in c('greater', 'two.sided', 'less')) {
+ j <- j + 1
+ gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
+ }
+ if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
+ }
+ gqarr
+ }
[,1] [,2] [,3]
[1,] 0.081306668 0.16261334 0.9186933
[2,] 0.462892161 0.92578432 0.5371078
[3,] 0.441397105 0.88279421 0.5586029
[4,] 0.786501759 0.42699648 0.2134982
[5,] 0.732192663 0.53561467 0.2678073
[6,] 0.638864552 0.72227090 0.3611354
[7,] 0.553673687 0.89265263 0.4463263
[8,] 0.466892542 0.93378508 0.5331075
[9,] 0.381382242 0.76276448 0.6186178
[10,] 0.367221844 0.73444369 0.6327782
[11,] 0.455763521 0.91152704 0.5442365
[12,] 0.426499006 0.85299801 0.5735010
[13,] 0.448277328 0.89655466 0.5517227
[14,] 0.397752789 0.79550558 0.6022472
[15,] 0.411073176 0.82214635 0.5889268
[16,] 0.392278748 0.78455750 0.6077213
[17,] 0.360911685 0.72182337 0.6390883
[18,] 0.315419896 0.63083979 0.6845801
[19,] 0.310264347 0.62052869 0.6897357
[20,] 0.263544938 0.52708988 0.7364551
[21,] 0.218803418 0.43760684 0.7811966
[22,] 0.221415383 0.44283077 0.7785846
[23,] 0.283831079 0.56766216 0.7161689
[24,] 0.239653087 0.47930617 0.7603469
[25,] 0.196696719 0.39339344 0.8033033
[26,] 0.177312057 0.35462411 0.8226879
[27,] 0.175947506 0.35189501 0.8240525
[28,] 0.177928245 0.35585649 0.8220718
[29,] 0.147378207 0.29475641 0.8526218
[30,] 0.120591084 0.24118217 0.8794089
[31,] 0.125019098 0.25003820 0.8749809
[32,] 0.203509941 0.40701988 0.7964901
[33,] 0.203571030 0.40714206 0.7964290
[34,] 0.198903009 0.39780602 0.8010970
[35,] 0.165150821 0.33030164 0.8348492
[36,] 0.346964315 0.69392863 0.6530357
[37,] 0.302059136 0.60411827 0.6979409
[38,] 0.261417346 0.52283469 0.7385827
[39,] 0.284001347 0.56800269 0.7159987
[40,] 0.253336263 0.50667253 0.7466637
[41,] 0.215003757 0.43000751 0.7849962
[42,] 0.193879805 0.38775961 0.8061202
[43,] 0.167914070 0.33582814 0.8320859
[44,] 0.144359579 0.28871916 0.8556404
[45,] 0.117422202 0.23484440 0.8825778
[46,] 0.094480204 0.18896041 0.9055198
[47,] 0.077548262 0.15509652 0.9224517
[48,] 0.061229772 0.12245954 0.9387702
[49,] 0.047587341 0.09517468 0.9524127
[50,] 0.049398920 0.09879784 0.9506011
[51,] 0.043151560 0.08630312 0.9568484
[52,] 0.036903601 0.07380720 0.9630964
[53,] 0.028655042 0.05731008 0.9713450
[54,] 0.027358714 0.05471743 0.9726413
[55,] 0.026246463 0.05249293 0.9737535
[56,] 0.020024364 0.04004873 0.9799756
[57,] 0.028142902 0.05628580 0.9718571
[58,] 0.051439293 0.10287859 0.9485607
[59,] 0.045235442 0.09047088 0.9547646
[60,] 0.075097617 0.15019523 0.9249024
[61,] 0.072065262 0.14413052 0.9279347
[62,] 0.063254204 0.12650841 0.9367458
[63,] 0.059866040 0.11973208 0.9401340
[64,] 0.077554550 0.15510910 0.9224454
[65,] 0.062540035 0.12508007 0.9374600
[66,] 0.051507320 0.10301464 0.9484927
[67,] 0.040865740 0.08173148 0.9591343
[68,] 0.031639794 0.06327959 0.9683602
[69,] 0.034407389 0.06881478 0.9655926
[70,] 0.062595664 0.12519133 0.9374043
[71,] 0.057808209 0.11561642 0.9421918
[72,] 0.068176064 0.13635213 0.9318239
[73,] 0.057285108 0.11457022 0.9427149
[74,] 0.056868824 0.11373765 0.9431312
[75,] 0.059556938 0.11911388 0.9404431
[76,] 0.047706625 0.09541325 0.9522934
[77,] 0.037130767 0.07426153 0.9628692
[78,] 0.029124846 0.05824969 0.9708752
[79,] 0.022677170 0.04535434 0.9773228
[80,] 0.017438677 0.03487735 0.9825613
[81,] 0.013277569 0.02655514 0.9867224
[82,] 0.010056612 0.02011322 0.9899434
[83,] 0.010033465 0.02006693 0.9899665
[84,] 0.007705038 0.01541008 0.9922950
[85,] 0.005950944 0.01190189 0.9940491
[86,] 0.005660624 0.01132125 0.9943394
[87,] 0.006044939 0.01208988 0.9939551
[88,] 0.009957796 0.01991559 0.9900422
[89,] 0.007678267 0.01535653 0.9923217
[90,] 0.018106351 0.03621270 0.9818936
[91,] 0.049150092 0.09830018 0.9508499
[92,] 0.038161651 0.07632330 0.9618383
[93,] 0.034118856 0.06823771 0.9658811
[94,] 0.027924096 0.05584819 0.9720759
[95,] 0.021245834 0.04249167 0.9787542
[96,] 0.017954850 0.03590970 0.9820451
[97,] 0.053950249 0.10790050 0.9460498
[98,] 0.158815198 0.31763040 0.8411848
[99,] 0.132282728 0.26456546 0.8677173
[100,] 0.111632355 0.22326471 0.8883676
[101,] 0.091754351 0.18350870 0.9082456
[102,] 0.073058823 0.14611765 0.9269412
[103,] 0.073967320 0.14793464 0.9260327
[104,] 0.060950350 0.12190070 0.9390497
[105,] 0.050052394 0.10010479 0.9499476
[106,] 0.044454555 0.08890911 0.9555454
[107,] 0.034283257 0.06856651 0.9657167
[108,] 0.041685850 0.08337170 0.9583141
[109,] 0.042307437 0.08461487 0.9576926
[110,] 0.059188907 0.11837781 0.9408111
[111,] 0.045092547 0.09018509 0.9549075
[112,] 0.049595919 0.09919184 0.9504041
[113,] 0.037171381 0.07434276 0.9628286
[114,] 0.032206173 0.06441235 0.9677938
[115,] 0.048284328 0.09656866 0.9517157
[116,] 0.054974865 0.10994973 0.9450251
[117,] 0.044533713 0.08906743 0.9554663
[118,] 0.061870412 0.12374082 0.9381296
[119,] 0.051909956 0.10381991 0.9480900
[120,] 0.054451737 0.10890347 0.9455483
[121,] 0.068181974 0.13636395 0.9318180
[122,] 0.049636246 0.09927249 0.9503638
[123,] 0.431921034 0.86384207 0.5680790
[124,] 0.379785112 0.75957022 0.6202149
[125,] 0.377178784 0.75435757 0.6228212
[126,] 0.328155949 0.65631190 0.6718441
[127,] 0.345407148 0.69081430 0.6545929
[128,] 0.361782785 0.72356557 0.6382172
[129,] 0.287992734 0.57598547 0.7120073
[130,] 0.410456396 0.82091279 0.5895436
[131,] 0.325556827 0.65111365 0.6744432
[132,] 0.274934258 0.54986852 0.7250657
[133,] 0.319242979 0.63848596 0.6807570
[134,] 0.232438664 0.46487733 0.7675613
[135,] 0.156246339 0.31249268 0.8437537
[136,] 0.263824020 0.52764804 0.7361760
[137,] 0.207174397 0.41434879 0.7928256
[138,] 0.131563968 0.26312794 0.8684360
> postscript(file="/var/www/html/freestat/rcomp/tmp/1vgdk1289897415.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
> points(x[,1]-mysum$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/2vgdk1289897415.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/3vgdk1289897415.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/457un1289897415.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/557un1289897415.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 = 149
Frequency = 1
1 2 3 4 5 6
-2.34601823 -4.72181860 -2.83934140 1.20796300 2.17285380 3.80809019
7 8 9 10 11 12
-2.81495099 5.31476702 -4.17361700 -2.29113980 1.33305983 -1.07291059
13 14 15 16 17 18
-2.47888100 -0.47278340 5.27503664 8.23992744 -1.28966338 0.21091585
19 20 21 22 23 24
5.29942705 0.22311105 1.39403586 1.40013347 2.78812904 -0.95853254
25 26 27 28 29 30
3.37721948 -0.19357815 -0.77541253 -2.72810812 -1.17528534 1.28408709
31 32 33 34 35 36
-2.03946973 -1.62130410 4.30237990 2.39089110 0.31457510 -2.84415450
37 38 39 40 41 42
4.25539346 4.25045431 -1.74344809 1.22144271 -6.64883928 0.82156990
43 44 45 46 47 48
1.32214913 -3.46571926 -1.58324206 -0.61835126 1.93447152 -1.44132885
49 50 51 52 53 54
-1.76488566 0.15879834 -0.58786324 -1.41693843 0.34191836 0.14198195
55 56 57 58 59 60
3.18928636 -2.39254802 -2.38645042 -1.38035281 2.62574479 -3.36815761
61 62 63 64 65 66
-1.36206000 -5.35596240 -6.63831241 1.49140560 5.16784879 -3.57881280
67 68 69 70 71 72
-2.81995600 2.26855520 4.31585961 -1.30718157 -1.96039280 -1.37739997
73 74 75 76 77 78
-0.28888876 -4.28279116 5.68209964 2.31733603 -4.84139357 1.24711763
79 80 81 82 83 84
-3.74678476 3.25931284 0.55385806 -0.23401033 0.60726006 -1.34543553
85 86 87 88 89 90
-1.21571752 0.66675968 0.79647769 -3.69190633 -1.68580873 -1.80333153
91 92 93 94 95 96
-3.17913190 3.49731129 -5.41417751 1.26226568 -6.36077550 7.43928810
97 98 99 100 101 102
0.19814489 2.69872412 1.86964893 -0.45390789 2.38736251 -7.35929908
103 104 105 106 107 108
8.72921213 1.07600091 -1.09376545 1.37664373 -0.08157025 3.92452736
109 110 111 112 113 114
1.93062496 1.93672256 2.53075215 -1.29832304 -4.70429346 3.71387217
115 116 117 118 119 120
4.96721058 -1.19151902 -4.39145543 -0.71501224 -2.50288063 -5.12592181
121 122 123 124 125 126
-3.32585822 2.88627340 -3.98400859 3.61002099 4.90456621 5.03428422
127 128 129 130 131 132
0.71072740 -9.95352058 3.88774982 -1.47701379 0.57029061 5.41156101
133 134 135 136 137 138
-2.74716860 1.25892901 6.51226742 0.60077863 1.48325583 -4.26340576
139 140 141 142 143 144
0.94872585 0.78999625 -2.87425173 -0.40384255 3.13794347 -2.72130176
145 146 147 148 149
6.15013868 0.11502948 -2.49697494 1.67394987 -6.90788451
> postscript(file="/var/www/html/freestat/rcomp/tmp/657un1289897415.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 = 149
Frequency = 1
lag(myerror, k = 1) myerror
0 -2.34601823 NA
1 -4.72181860 -2.34601823
2 -2.83934140 -4.72181860
3 1.20796300 -2.83934140
4 2.17285380 1.20796300
5 3.80809019 2.17285380
6 -2.81495099 3.80809019
7 5.31476702 -2.81495099
8 -4.17361700 5.31476702
9 -2.29113980 -4.17361700
10 1.33305983 -2.29113980
11 -1.07291059 1.33305983
12 -2.47888100 -1.07291059
13 -0.47278340 -2.47888100
14 5.27503664 -0.47278340
15 8.23992744 5.27503664
16 -1.28966338 8.23992744
17 0.21091585 -1.28966338
18 5.29942705 0.21091585
19 0.22311105 5.29942705
20 1.39403586 0.22311105
21 1.40013347 1.39403586
22 2.78812904 1.40013347
23 -0.95853254 2.78812904
24 3.37721948 -0.95853254
25 -0.19357815 3.37721948
26 -0.77541253 -0.19357815
27 -2.72810812 -0.77541253
28 -1.17528534 -2.72810812
29 1.28408709 -1.17528534
30 -2.03946973 1.28408709
31 -1.62130410 -2.03946973
32 4.30237990 -1.62130410
33 2.39089110 4.30237990
34 0.31457510 2.39089110
35 -2.84415450 0.31457510
36 4.25539346 -2.84415450
37 4.25045431 4.25539346
38 -1.74344809 4.25045431
39 1.22144271 -1.74344809
40 -6.64883928 1.22144271
41 0.82156990 -6.64883928
42 1.32214913 0.82156990
43 -3.46571926 1.32214913
44 -1.58324206 -3.46571926
45 -0.61835126 -1.58324206
46 1.93447152 -0.61835126
47 -1.44132885 1.93447152
48 -1.76488566 -1.44132885
49 0.15879834 -1.76488566
50 -0.58786324 0.15879834
51 -1.41693843 -0.58786324
52 0.34191836 -1.41693843
53 0.14198195 0.34191836
54 3.18928636 0.14198195
55 -2.39254802 3.18928636
56 -2.38645042 -2.39254802
57 -1.38035281 -2.38645042
58 2.62574479 -1.38035281
59 -3.36815761 2.62574479
60 -1.36206000 -3.36815761
61 -5.35596240 -1.36206000
62 -6.63831241 -5.35596240
63 1.49140560 -6.63831241
64 5.16784879 1.49140560
65 -3.57881280 5.16784879
66 -2.81995600 -3.57881280
67 2.26855520 -2.81995600
68 4.31585961 2.26855520
69 -1.30718157 4.31585961
70 -1.96039280 -1.30718157
71 -1.37739997 -1.96039280
72 -0.28888876 -1.37739997
73 -4.28279116 -0.28888876
74 5.68209964 -4.28279116
75 2.31733603 5.68209964
76 -4.84139357 2.31733603
77 1.24711763 -4.84139357
78 -3.74678476 1.24711763
79 3.25931284 -3.74678476
80 0.55385806 3.25931284
81 -0.23401033 0.55385806
82 0.60726006 -0.23401033
83 -1.34543553 0.60726006
84 -1.21571752 -1.34543553
85 0.66675968 -1.21571752
86 0.79647769 0.66675968
87 -3.69190633 0.79647769
88 -1.68580873 -3.69190633
89 -1.80333153 -1.68580873
90 -3.17913190 -1.80333153
91 3.49731129 -3.17913190
92 -5.41417751 3.49731129
93 1.26226568 -5.41417751
94 -6.36077550 1.26226568
95 7.43928810 -6.36077550
96 0.19814489 7.43928810
97 2.69872412 0.19814489
98 1.86964893 2.69872412
99 -0.45390789 1.86964893
100 2.38736251 -0.45390789
101 -7.35929908 2.38736251
102 8.72921213 -7.35929908
103 1.07600091 8.72921213
104 -1.09376545 1.07600091
105 1.37664373 -1.09376545
106 -0.08157025 1.37664373
107 3.92452736 -0.08157025
108 1.93062496 3.92452736
109 1.93672256 1.93062496
110 2.53075215 1.93672256
111 -1.29832304 2.53075215
112 -4.70429346 -1.29832304
113 3.71387217 -4.70429346
114 4.96721058 3.71387217
115 -1.19151902 4.96721058
116 -4.39145543 -1.19151902
117 -0.71501224 -4.39145543
118 -2.50288063 -0.71501224
119 -5.12592181 -2.50288063
120 -3.32585822 -5.12592181
121 2.88627340 -3.32585822
122 -3.98400859 2.88627340
123 3.61002099 -3.98400859
124 4.90456621 3.61002099
125 5.03428422 4.90456621
126 0.71072740 5.03428422
127 -9.95352058 0.71072740
128 3.88774982 -9.95352058
129 -1.47701379 3.88774982
130 0.57029061 -1.47701379
131 5.41156101 0.57029061
132 -2.74716860 5.41156101
133 1.25892901 -2.74716860
134 6.51226742 1.25892901
135 0.60077863 6.51226742
136 1.48325583 0.60077863
137 -4.26340576 1.48325583
138 0.94872585 -4.26340576
139 0.78999625 0.94872585
140 -2.87425173 0.78999625
141 -0.40384255 -2.87425173
142 3.13794347 -0.40384255
143 -2.72130176 3.13794347
144 6.15013868 -2.72130176
145 0.11502948 6.15013868
146 -2.49697494 0.11502948
147 1.67394987 -2.49697494
148 -6.90788451 1.67394987
149 NA -6.90788451
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -4.72181860 -2.34601823
[2,] -2.83934140 -4.72181860
[3,] 1.20796300 -2.83934140
[4,] 2.17285380 1.20796300
[5,] 3.80809019 2.17285380
[6,] -2.81495099 3.80809019
[7,] 5.31476702 -2.81495099
[8,] -4.17361700 5.31476702
[9,] -2.29113980 -4.17361700
[10,] 1.33305983 -2.29113980
[11,] -1.07291059 1.33305983
[12,] -2.47888100 -1.07291059
[13,] -0.47278340 -2.47888100
[14,] 5.27503664 -0.47278340
[15,] 8.23992744 5.27503664
[16,] -1.28966338 8.23992744
[17,] 0.21091585 -1.28966338
[18,] 5.29942705 0.21091585
[19,] 0.22311105 5.29942705
[20,] 1.39403586 0.22311105
[21,] 1.40013347 1.39403586
[22,] 2.78812904 1.40013347
[23,] -0.95853254 2.78812904
[24,] 3.37721948 -0.95853254
[25,] -0.19357815 3.37721948
[26,] -0.77541253 -0.19357815
[27,] -2.72810812 -0.77541253
[28,] -1.17528534 -2.72810812
[29,] 1.28408709 -1.17528534
[30,] -2.03946973 1.28408709
[31,] -1.62130410 -2.03946973
[32,] 4.30237990 -1.62130410
[33,] 2.39089110 4.30237990
[34,] 0.31457510 2.39089110
[35,] -2.84415450 0.31457510
[36,] 4.25539346 -2.84415450
[37,] 4.25045431 4.25539346
[38,] -1.74344809 4.25045431
[39,] 1.22144271 -1.74344809
[40,] -6.64883928 1.22144271
[41,] 0.82156990 -6.64883928
[42,] 1.32214913 0.82156990
[43,] -3.46571926 1.32214913
[44,] -1.58324206 -3.46571926
[45,] -0.61835126 -1.58324206
[46,] 1.93447152 -0.61835126
[47,] -1.44132885 1.93447152
[48,] -1.76488566 -1.44132885
[49,] 0.15879834 -1.76488566
[50,] -0.58786324 0.15879834
[51,] -1.41693843 -0.58786324
[52,] 0.34191836 -1.41693843
[53,] 0.14198195 0.34191836
[54,] 3.18928636 0.14198195
[55,] -2.39254802 3.18928636
[56,] -2.38645042 -2.39254802
[57,] -1.38035281 -2.38645042
[58,] 2.62574479 -1.38035281
[59,] -3.36815761 2.62574479
[60,] -1.36206000 -3.36815761
[61,] -5.35596240 -1.36206000
[62,] -6.63831241 -5.35596240
[63,] 1.49140560 -6.63831241
[64,] 5.16784879 1.49140560
[65,] -3.57881280 5.16784879
[66,] -2.81995600 -3.57881280
[67,] 2.26855520 -2.81995600
[68,] 4.31585961 2.26855520
[69,] -1.30718157 4.31585961
[70,] -1.96039280 -1.30718157
[71,] -1.37739997 -1.96039280
[72,] -0.28888876 -1.37739997
[73,] -4.28279116 -0.28888876
[74,] 5.68209964 -4.28279116
[75,] 2.31733603 5.68209964
[76,] -4.84139357 2.31733603
[77,] 1.24711763 -4.84139357
[78,] -3.74678476 1.24711763
[79,] 3.25931284 -3.74678476
[80,] 0.55385806 3.25931284
[81,] -0.23401033 0.55385806
[82,] 0.60726006 -0.23401033
[83,] -1.34543553 0.60726006
[84,] -1.21571752 -1.34543553
[85,] 0.66675968 -1.21571752
[86,] 0.79647769 0.66675968
[87,] -3.69190633 0.79647769
[88,] -1.68580873 -3.69190633
[89,] -1.80333153 -1.68580873
[90,] -3.17913190 -1.80333153
[91,] 3.49731129 -3.17913190
[92,] -5.41417751 3.49731129
[93,] 1.26226568 -5.41417751
[94,] -6.36077550 1.26226568
[95,] 7.43928810 -6.36077550
[96,] 0.19814489 7.43928810
[97,] 2.69872412 0.19814489
[98,] 1.86964893 2.69872412
[99,] -0.45390789 1.86964893
[100,] 2.38736251 -0.45390789
[101,] -7.35929908 2.38736251
[102,] 8.72921213 -7.35929908
[103,] 1.07600091 8.72921213
[104,] -1.09376545 1.07600091
[105,] 1.37664373 -1.09376545
[106,] -0.08157025 1.37664373
[107,] 3.92452736 -0.08157025
[108,] 1.93062496 3.92452736
[109,] 1.93672256 1.93062496
[110,] 2.53075215 1.93672256
[111,] -1.29832304 2.53075215
[112,] -4.70429346 -1.29832304
[113,] 3.71387217 -4.70429346
[114,] 4.96721058 3.71387217
[115,] -1.19151902 4.96721058
[116,] -4.39145543 -1.19151902
[117,] -0.71501224 -4.39145543
[118,] -2.50288063 -0.71501224
[119,] -5.12592181 -2.50288063
[120,] -3.32585822 -5.12592181
[121,] 2.88627340 -3.32585822
[122,] -3.98400859 2.88627340
[123,] 3.61002099 -3.98400859
[124,] 4.90456621 3.61002099
[125,] 5.03428422 4.90456621
[126,] 0.71072740 5.03428422
[127,] -9.95352058 0.71072740
[128,] 3.88774982 -9.95352058
[129,] -1.47701379 3.88774982
[130,] 0.57029061 -1.47701379
[131,] 5.41156101 0.57029061
[132,] -2.74716860 5.41156101
[133,] 1.25892901 -2.74716860
[134,] 6.51226742 1.25892901
[135,] 0.60077863 6.51226742
[136,] 1.48325583 0.60077863
[137,] -4.26340576 1.48325583
[138,] 0.94872585 -4.26340576
[139,] 0.78999625 0.94872585
[140,] -2.87425173 0.78999625
[141,] -0.40384255 -2.87425173
[142,] 3.13794347 -0.40384255
[143,] -2.72130176 3.13794347
[144,] 6.15013868 -2.72130176
[145,] 0.11502948 6.15013868
[146,] -2.49697494 0.11502948
[147,] 1.67394987 -2.49697494
[148,] -6.90788451 1.67394987
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -4.72181860 -2.34601823
2 -2.83934140 -4.72181860
3 1.20796300 -2.83934140
4 2.17285380 1.20796300
5 3.80809019 2.17285380
6 -2.81495099 3.80809019
7 5.31476702 -2.81495099
8 -4.17361700 5.31476702
9 -2.29113980 -4.17361700
10 1.33305983 -2.29113980
11 -1.07291059 1.33305983
12 -2.47888100 -1.07291059
13 -0.47278340 -2.47888100
14 5.27503664 -0.47278340
15 8.23992744 5.27503664
16 -1.28966338 8.23992744
17 0.21091585 -1.28966338
18 5.29942705 0.21091585
19 0.22311105 5.29942705
20 1.39403586 0.22311105
21 1.40013347 1.39403586
22 2.78812904 1.40013347
23 -0.95853254 2.78812904
24 3.37721948 -0.95853254
25 -0.19357815 3.37721948
26 -0.77541253 -0.19357815
27 -2.72810812 -0.77541253
28 -1.17528534 -2.72810812
29 1.28408709 -1.17528534
30 -2.03946973 1.28408709
31 -1.62130410 -2.03946973
32 4.30237990 -1.62130410
33 2.39089110 4.30237990
34 0.31457510 2.39089110
35 -2.84415450 0.31457510
36 4.25539346 -2.84415450
37 4.25045431 4.25539346
38 -1.74344809 4.25045431
39 1.22144271 -1.74344809
40 -6.64883928 1.22144271
41 0.82156990 -6.64883928
42 1.32214913 0.82156990
43 -3.46571926 1.32214913
44 -1.58324206 -3.46571926
45 -0.61835126 -1.58324206
46 1.93447152 -0.61835126
47 -1.44132885 1.93447152
48 -1.76488566 -1.44132885
49 0.15879834 -1.76488566
50 -0.58786324 0.15879834
51 -1.41693843 -0.58786324
52 0.34191836 -1.41693843
53 0.14198195 0.34191836
54 3.18928636 0.14198195
55 -2.39254802 3.18928636
56 -2.38645042 -2.39254802
57 -1.38035281 -2.38645042
58 2.62574479 -1.38035281
59 -3.36815761 2.62574479
60 -1.36206000 -3.36815761
61 -5.35596240 -1.36206000
62 -6.63831241 -5.35596240
63 1.49140560 -6.63831241
64 5.16784879 1.49140560
65 -3.57881280 5.16784879
66 -2.81995600 -3.57881280
67 2.26855520 -2.81995600
68 4.31585961 2.26855520
69 -1.30718157 4.31585961
70 -1.96039280 -1.30718157
71 -1.37739997 -1.96039280
72 -0.28888876 -1.37739997
73 -4.28279116 -0.28888876
74 5.68209964 -4.28279116
75 2.31733603 5.68209964
76 -4.84139357 2.31733603
77 1.24711763 -4.84139357
78 -3.74678476 1.24711763
79 3.25931284 -3.74678476
80 0.55385806 3.25931284
81 -0.23401033 0.55385806
82 0.60726006 -0.23401033
83 -1.34543553 0.60726006
84 -1.21571752 -1.34543553
85 0.66675968 -1.21571752
86 0.79647769 0.66675968
87 -3.69190633 0.79647769
88 -1.68580873 -3.69190633
89 -1.80333153 -1.68580873
90 -3.17913190 -1.80333153
91 3.49731129 -3.17913190
92 -5.41417751 3.49731129
93 1.26226568 -5.41417751
94 -6.36077550 1.26226568
95 7.43928810 -6.36077550
96 0.19814489 7.43928810
97 2.69872412 0.19814489
98 1.86964893 2.69872412
99 -0.45390789 1.86964893
100 2.38736251 -0.45390789
101 -7.35929908 2.38736251
102 8.72921213 -7.35929908
103 1.07600091 8.72921213
104 -1.09376545 1.07600091
105 1.37664373 -1.09376545
106 -0.08157025 1.37664373
107 3.92452736 -0.08157025
108 1.93062496 3.92452736
109 1.93672256 1.93062496
110 2.53075215 1.93672256
111 -1.29832304 2.53075215
112 -4.70429346 -1.29832304
113 3.71387217 -4.70429346
114 4.96721058 3.71387217
115 -1.19151902 4.96721058
116 -4.39145543 -1.19151902
117 -0.71501224 -4.39145543
118 -2.50288063 -0.71501224
119 -5.12592181 -2.50288063
120 -3.32585822 -5.12592181
121 2.88627340 -3.32585822
122 -3.98400859 2.88627340
123 3.61002099 -3.98400859
124 4.90456621 3.61002099
125 5.03428422 4.90456621
126 0.71072740 5.03428422
127 -9.95352058 0.71072740
128 3.88774982 -9.95352058
129 -1.47701379 3.88774982
130 0.57029061 -1.47701379
131 5.41156101 0.57029061
132 -2.74716860 5.41156101
133 1.25892901 -2.74716860
134 6.51226742 1.25892901
135 0.60077863 6.51226742
136 1.48325583 0.60077863
137 -4.26340576 1.48325583
138 0.94872585 -4.26340576
139 0.78999625 0.94872585
140 -2.87425173 0.78999625
141 -0.40384255 -2.87425173
142 3.13794347 -0.40384255
143 -2.72130176 3.13794347
144 6.15013868 -2.72130176
145 0.11502948 6.15013868
146 -2.49697494 0.11502948
147 1.67394987 -2.49697494
148 -6.90788451 1.67394987
> plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
> lines(lowess(z))
> abline(lm(z))
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/7q9e31289897416.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/810d51289897416.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/910d51289897416.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/freestat/rcomp/tmp/10c9u81289897416.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/freestat/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
+ myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ')
+ if (rownames(mysum$coefficients)[i] != '(Intercept)') {
+ myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
+ if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
+ }
+ }
> myeq <- paste(myeq, ' + e[t]')
> a<-table.row.start(a)
> a<-table.element(a, myeq)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/freestat/rcomp/tmp/11xste1289897416.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Variable',header=TRUE)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
> a<-table.element(a,'2-tail p-value',header=TRUE)
> a<-table.element(a,'1-tail p-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:k){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
+ a<-table.element(a,mysum$coefficients[i,1])
+ a<-table.element(a, round(mysum$coefficients[i,2],6))
+ a<-table.element(a, round(mysum$coefficients[i,3],4))
+ a<-table.element(a, round(mysum$coefficients[i,4],6))
+ a<-table.element(a, round(mysum$coefficients[i,4]/2,6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/html/freestat/rcomp/tmp/120sr21289897416.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple R',1,TRUE)
> a<-table.element(a, sqrt(mysum$r.squared))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'R-squared',1,TRUE)
> a<-table.element(a, mysum$r.squared)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Adjusted R-squared',1,TRUE)
> a<-table.element(a, mysum$adj.r.squared)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (value)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[1])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[2])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[3])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'p-value',1,TRUE)
> a<-table.element(a, 1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
> a<-table.element(a, mysum$sigma)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a, sum(myerror*myerror))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/freestat/rcomp/tmp/13fkpb1289897416.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Time or Index', 1, TRUE)
> a<-table.element(a, 'Actuals', 1, TRUE)
> a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
> a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
> a<-table.row.end(a)
> for (i in 1:n) {
+ a<-table.row.start(a)
+ a<-table.element(a,i, 1, TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]-mysum$resid[i])
+ a<-table.element(a,mysum$resid[i])
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/html/freestat/rcomp/tmp/14i3oz1289897416.tab")
> if (n > n25) {
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'p-values',header=TRUE)
+ a<-table.element(a,'Alternative Hypothesis',3,header=TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'breakpoint index',header=TRUE)
+ a<-table.element(a,'greater',header=TRUE)
+ a<-table.element(a,'2-sided',header=TRUE)
+ a<-table.element(a,'less',header=TRUE)
+ a<-table.row.end(a)
+ for (mypoint in kp3:nmkm3) {
+ a<-table.row.start(a)
+ a<-table.element(a,mypoint,header=TRUE)
+ a<-table.element(a,gqarr[mypoint-kp3+1,1])
+ a<-table.element(a,gqarr[mypoint-kp3+1,2])
+ a<-table.element(a,gqarr[mypoint-kp3+1,3])
+ a<-table.row.end(a)
+ }
+ a<-table.end(a)
+ table.save(a,file="/var/www/html/freestat/rcomp/tmp/153lmn1289897416.tab")
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'Description',header=TRUE)
+ a<-table.element(a,'# significant tests',header=TRUE)
+ a<-table.element(a,'% significant tests',header=TRUE)
+ a<-table.element(a,'OK/NOK',header=TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'1% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant1)
+ a<-table.element(a,numsignificant1/numgqtests)
+ if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'5% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant5)
+ a<-table.element(a,numsignificant5/numgqtests)
+ if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'10% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant10)
+ a<-table.element(a,numsignificant10/numgqtests)
+ if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.end(a)
+ table.save(a,file="/var/www/html/freestat/rcomp/tmp/16zd2v1289897416.tab")
+ }
>
> try(system("convert tmp/1vgdk1289897415.ps tmp/1vgdk1289897415.png",intern=TRUE))
character(0)
> try(system("convert tmp/2vgdk1289897415.ps tmp/2vgdk1289897415.png",intern=TRUE))
character(0)
> try(system("convert tmp/3vgdk1289897415.ps tmp/3vgdk1289897415.png",intern=TRUE))
character(0)
> try(system("convert tmp/457un1289897415.ps tmp/457un1289897415.png",intern=TRUE))
character(0)
> try(system("convert tmp/557un1289897415.ps tmp/557un1289897415.png",intern=TRUE))
character(0)
> try(system("convert tmp/657un1289897415.ps tmp/657un1289897415.png",intern=TRUE))
character(0)
> try(system("convert tmp/7q9e31289897416.ps tmp/7q9e31289897416.png",intern=TRUE))
character(0)
> try(system("convert tmp/810d51289897416.ps tmp/810d51289897416.png",intern=TRUE))
character(0)
> try(system("convert tmp/910d51289897416.ps tmp/910d51289897416.png",intern=TRUE))
character(0)
> try(system("convert tmp/10c9u81289897416.ps tmp/10c9u81289897416.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
5.127 2.612 5.449