R version 2.13.0 (2011-04-13)
Copyright (C) 2011 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.
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(63031
+ ,13
+ ,5
+ ,10345
+ ,66751
+ ,26
+ ,7
+ ,17607
+ ,7176
+ ,0
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+ ,6
+ ,12
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+ ,0
+ ,14
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+ ,7131
+ ,0
+ ,0
+ ,0
+ ,4194
+ ,0
+ ,0
+ ,0
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+ ,15
+ ,4
+ ,7084
+ ,30591
+ ,0
+ ,7
+ ,14831
+ ,42419
+ ,12
+ ,10
+ ,6585)
+ ,dim=c(4
+ ,144)
+ ,dimnames=list(c('tijd'
+ ,'blogs'
+ ,'Pr'
+ ,'karakters')
+ ,1:144))
> y <- array(NA,dim=c(4,144),dimnames=list(c('tijd','blogs','Pr','karakters'),1:144))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par3 = 'No 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
tijd blogs Pr karakters
1 63031 13 5 10345
2 66751 26 7 17607
3 7176 0 0 1423
4 78306 37 12 20050
5 137944 47 15 21212
6 261308 80 16 93979
7 69266 21 12 15524
8 83529 36 15 16182
9 73226 35 15 19238
10 178519 40 13 28909
11 66476 35 6 22357
12 98606 46 16 25560
13 50001 20 7 9954
14 91093 24 12 18490
15 73884 19 9 17777
16 72961 15 10 25268
17 69388 48 16 37525
18 15629 0 5 6023
19 71693 38 20 25042
20 19920 12 7 35713
21 39403 10 13 7039
22 99933 51 13 40841
23 56088 4 11 9214
24 62006 24 9 17446
25 81665 39 10 10295
26 65223 19 7 13206
27 88794 23 13 26093
28 90642 39 15 20744
29 203699 37 13 68013
30 99340 20 7 12840
31 56695 20 14 12672
32 108143 41 11 10872
33 58313 26 3 21325
34 29101 0 8 24542
35 113060 31 12 16401
36 0 0 0 0
37 65773 8 12 12821
38 67047 35 8 14662
39 41953 3 20 22190
40 109835 47 18 37929
41 86584 42 9 18009
42 59588 11 14 11076
43 40064 10 7 24981
44 70227 26 13 30691
45 60437 27 11 29164
46 47000 0 11 13985
47 40295 15 14 7588
48 103397 32 9 20023
49 78982 13 12 25524
50 60206 24 11 14717
51 39887 10 17 6832
52 49791 14 10 9624
53 129283 24 11 24300
54 104816 29 12 21790
55 101395 40 17 16493
56 72824 22 6 9269
57 76018 27 8 20105
58 33891 8 12 11216
59 63694 27 13 15569
60 28266 0 14 21799
61 35093 0 17 3772
62 35252 17 8 6057
63 36977 7 9 20828
64 42406 18 9 9976
65 56353 7 9 14055
66 58817 24 15 17455
67 76053 18 16 39553
68 70872 39 13 14818
69 42372 17 12 17065
70 19144 0 10 1536
71 114177 39 9 11938
72 53544 20 3 24589
73 51379 29 12 21332
74 40756 27 8 13229
75 46956 23 17 11331
76 17799 0 9 853
77 71154 31 8 19821
78 58305 19 9 34666
79 27454 12 12 15051
80 34323 23 5 27969
81 44761 33 14 17897
82 113862 21 14 6031
83 35027 17 10 7153
84 62396 27 12 13365
85 29613 14 10 11197
86 65559 12 12 25291
87 110811 21 17 28994
88 27883 14 11 10461
89 40181 14 10 16415
90 53398 22 11 8495
91 56435 25 7 18318
92 77283 36 10 25143
93 71738 10 11 20471
94 48503 16 5 14561
95 25214 12 6 16902
96 119424 20 14 12994
97 79201 38 13 29697
98 19349 13 1 3895
99 78760 12 13 9807
100 54133 11 9 10711
101 21623 8 1 2325
102 25497 22 6 19000
103 69535 14 12 22418
104 30709 7 9 7872
105 37043 14 9 5650
106 24716 2 12 3979
107 54865 35 10 14956
108 27246 5 2 3738
109 0 0 0 0
110 38814 34 8 10586
111 27646 12 7 18122
112 65373 34 11 17899
113 43021 30 14 10913
114 43116 21 4 18060
115 3058 0 0 0
116 0 0 0 0
117 96347 28 13 15452
118 48626 16 17 33996
119 73073 12 13 8877
120 45266 14 12 18708
121 43410 7 1 2781
122 83842 41 12 20854
123 39296 21 6 8179
124 38490 28 11 7139
125 39841 1 8 13798
126 19764 10 2 5619
127 59975 31 12 13050
128 64589 7 12 11297
129 63339 26 14 16170
130 11796 1 2 0
131 7627 0 0 0
132 68998 12 9 20539
133 6836 0 1 0
134 33365 17 3 10056
135 5118 5 0 0
136 20898 4 2 2418
137 0 0 0 0
138 42690 6 12 11806
139 14507 0 14 15924
140 7131 0 0 0
141 4194 0 0 0
142 21416 15 4 7084
143 30591 0 7 14831
144 42419 12 10 6585
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) blogs Pr karakters
4097.466 1227.945 1280.586 1.099
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-55375 -12758 -3192 9300 76889
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 4097.4657 4145.6026 0.988 0.32467
blogs 1227.9449 166.2266 7.387 1.23e-11 ***
Pr 1280.5860 440.2353 2.909 0.00422 **
karakters 1.0989 0.1957 5.615 1.02e-07 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 21500 on 140 degrees of freedom
Multiple R-squared: 0.6847, Adjusted R-squared: 0.678
F-statistic: 101.3 on 3 and 140 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,] 0.5504273 0.8991453602 4.495727e-01
[2,] 0.4304936 0.8609872683 5.695064e-01
[3,] 0.3980569 0.7961138587 6.019431e-01
[4,] 0.9604216 0.0791567733 3.957839e-02
[5,] 0.9624037 0.0751925277 3.759626e-02
[6,] 0.9567661 0.0864678624 4.323393e-02
[7,] 0.9312424 0.1375152044 6.875760e-02
[8,] 0.9039767 0.1920466744 9.602334e-02
[9,] 0.8644422 0.2711155629 1.355578e-01
[10,] 0.8279743 0.3440513037 1.720257e-01
[11,] 0.9870330 0.0259340592 1.296703e-02
[12,] 0.9807578 0.0384844935 1.924225e-02
[13,] 0.9835964 0.0328072312 1.640362e-02
[14,] 0.9959435 0.0081129497 4.056475e-03
[15,] 0.9940623 0.0118754976 5.937749e-03
[16,] 0.9962562 0.0074876047 3.743802e-03
[17,] 0.9968164 0.0063672234 3.183612e-03
[18,] 0.9949737 0.0100525261 5.026263e-03
[19,] 0.9922320 0.0155359090 7.767955e-03
[20,] 0.9892873 0.0214253404 1.071267e-02
[21,] 0.9857024 0.0285952822 1.429764e-02
[22,] 0.9793484 0.0413031007 2.065155e-02
[23,] 0.9980616 0.0038768013 1.938401e-03
[24,] 0.9995029 0.0009941218 4.970609e-04
[25,] 0.9991955 0.0016090818 8.045409e-04
[26,] 0.9993310 0.0013380403 6.690202e-04
[27,] 0.9991381 0.0017238801 8.619401e-04
[28,] 0.9988960 0.0022079481 1.103974e-03
[29,] 0.9994884 0.0010232532 5.116266e-04
[30,] 0.9992431 0.0015138133 7.569067e-04
[31,] 0.9992048 0.0015903517 7.951759e-04
[32,] 0.9988519 0.0022961509 1.148075e-03
[33,] 0.9985624 0.0028752218 1.437611e-03
[34,] 0.9982463 0.0035073461 1.753673e-03
[35,] 0.9974731 0.0050538412 2.526921e-03
[36,] 0.9966036 0.0067927146 3.396357e-03
[37,] 0.9958391 0.0083217695 4.160885e-03
[38,] 0.9949990 0.0100019064 5.000953e-03
[39,] 0.9950649 0.0098702614 4.935131e-03
[40,] 0.9937273 0.0125454147 6.272707e-03
[41,] 0.9916527 0.0166946073 8.347304e-03
[42,] 0.9932147 0.0135705415 6.785271e-03
[43,] 0.9922979 0.0154041108 7.702055e-03
[44,] 0.9893558 0.0212884932 1.064425e-02
[45,] 0.9861078 0.0277843967 1.389220e-02
[46,] 0.9811739 0.0376522079 1.882610e-02
[47,] 0.9978535 0.0042929816 2.146491e-03
[48,] 0.9985186 0.0029627252 1.481363e-03
[49,] 0.9980108 0.0039783591 1.989180e-03
[50,] 0.9982515 0.0034970488 1.748524e-03
[51,] 0.9978373 0.0043254667 2.162733e-03
[52,] 0.9970861 0.0058277986 2.913899e-03
[53,] 0.9959643 0.0080713630 4.035681e-03
[54,] 0.9955267 0.0089465527 4.473276e-03
[55,] 0.9942682 0.0114636198 5.731810e-03
[56,] 0.9924356 0.0151288119 7.564406e-03
[57,] 0.9902269 0.0195461240 9.773062e-03
[58,] 0.9870944 0.0258112489 1.290562e-02
[59,] 0.9854217 0.0291566185 1.457831e-02
[60,] 0.9821828 0.0356343704 1.781719e-02
[61,] 0.9775324 0.0449351868 2.246759e-02
[62,] 0.9731566 0.0536867390 2.684337e-02
[63,] 0.9698628 0.0602743468 3.013717e-02
[64,] 0.9623761 0.0752478255 3.762391e-02
[65,] 0.9865537 0.0268926628 1.344633e-02
[66,] 0.9848918 0.0302164931 1.510825e-02
[67,] 0.9859845 0.0280309130 1.401546e-02
[68,] 0.9853155 0.0293690320 1.468452e-02
[69,] 0.9867237 0.0265525205 1.327626e-02
[70,] 0.9835574 0.0328851624 1.644258e-02
[71,] 0.9805071 0.0389858833 1.949294e-02
[72,] 0.9771849 0.0456301873 2.281509e-02
[73,] 0.9809300 0.0381400179 1.907001e-02
[74,] 0.9839194 0.0321611968 1.608060e-02
[75,] 0.9911075 0.0177850321 8.892516e-03
[76,] 0.9992905 0.0014190444 7.095222e-04
[77,] 0.9990678 0.0018644751 9.322376e-04
[78,] 0.9985912 0.0028176426 1.408821e-03
[79,] 0.9984964 0.0030071422 1.503571e-03
[80,] 0.9978039 0.0043921392 2.196070e-03
[81,] 0.9988467 0.0023066321 1.153316e-03
[82,] 0.9989582 0.0020835180 1.041759e-03
[83,] 0.9985752 0.0028496345 1.424817e-03
[84,] 0.9978376 0.0043248857 2.162443e-03
[85,] 0.9969377 0.0061245329 3.062266e-03
[86,] 0.9959935 0.0080129719 4.006486e-03
[87,] 0.9963390 0.0073219842 3.660992e-03
[88,] 0.9953389 0.0093222649 4.661132e-03
[89,] 0.9942161 0.0115677104 5.783855e-03
[90,] 0.9998951 0.0002097814 1.048907e-04
[91,] 0.9998440 0.0003120424 1.560212e-04
[92,] 0.9997371 0.0005258048 2.629024e-04
[93,] 0.9999020 0.0001960733 9.803666e-05
[94,] 0.9998832 0.0002335263 1.167632e-04
[95,] 0.9998032 0.0003935691 1.967846e-04
[96,] 0.9998672 0.0002656501 1.328250e-04
[97,] 0.9998472 0.0003055775 1.527888e-04
[98,] 0.9997326 0.0005348380 2.674190e-04
[99,] 0.9995348 0.0009304594 4.652297e-04
[100,] 0.9992999 0.0014001615 7.000808e-04
[101,] 0.9989985 0.0020029060 1.001453e-03
[102,] 0.9985710 0.0028579443 1.428972e-03
[103,] 0.9978037 0.0043926013 2.196301e-03
[104,] 0.9979961 0.0040078641 2.003932e-03
[105,] 0.9974514 0.0050972033 2.548602e-03
[106,] 0.9959676 0.0080648905 4.032445e-03
[107,] 0.9976275 0.0047449113 2.372456e-03
[108,] 0.9960792 0.0078416020 3.920801e-03
[109,] 0.9937076 0.0125847370 6.292368e-03
[110,] 0.9906595 0.0186810748 9.340537e-03
[111,] 0.9962041 0.0075918942 3.795947e-03
[112,] 0.9979483 0.0041033140 2.051657e-03
[113,] 0.9995391 0.0009217856 4.608928e-04
[114,] 0.9993258 0.0013483214 6.741607e-04
[115,] 0.9998386 0.0003227078 1.613539e-04
[116,] 0.9996547 0.0006905904 3.452952e-04
[117,] 0.9992517 0.0014966793 7.483396e-04
[118,] 0.9989375 0.0021249119 1.062456e-03
[119,] 0.9979994 0.0040012073 2.000604e-03
[120,] 0.9960492 0.0079016766 3.950838e-03
[121,] 0.9928658 0.0142683901 7.134195e-03
[122,] 0.9985573 0.0028853387 1.442669e-03
[123,] 0.9966514 0.0066972796 3.348640e-03
[124,] 0.9931489 0.0137022252 6.851113e-03
[125,] 0.9856798 0.0286403993 1.432020e-02
[126,] 0.9935733 0.0128534557 6.426728e-03
[127,] 0.9839768 0.0320463546 1.602318e-02
[128,] 0.9624576 0.0750847164 3.754236e-02
[129,] 0.9263085 0.1473829541 7.369148e-02
[130,] 0.8650180 0.2699640233 1.349820e-01
[131,] 0.7479214 0.5041572587 2.520786e-01
> postscript(file="/var/wessaorg/rcomp/tmp/16fla1322147097.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/2547l1322147097.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/3ttaf1322147097.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/4p5mr1322147097.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/5kvsh1322147097.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 = 144
Frequency = 1
1 2 3 4 5 6
25199.57059 2415.16318 1514.85056 -8624.68575 33615.22725 35215.40740
7 8 9 10 11 12
6955.89183 -1765.09202 -14198.27619 76889.05549 -12850.35983 -10553.27549
13 14 15 16 17 18
1442.44035 21839.82591 15395.79846 9872.40013 -55375.07565 -1489.85478
19 20 21 22 23 24
-32195.84870 -47120.64405 -1356.43753 -28315.98610 22867.37405 -2258.20189
25 26 27 28 29 30
5559.01693 14318.87879 11133.52013 -3348.94524 62782.90365 47610.11821
31 32 33 34 35 36
-3814.37450 27666.49653 -4986.07005 -12209.47924 37506.73909 -4097.46565
37 38 39 40 41 42
22396.40529 -6384.77162 -15823.81706 -16705.24388 -401.87033 11883.91674
43 44 45 46 47 48
-12727.74347 -16169.89220 -22948.69945 13448.47238 -8488.02439 26477.46595
49 50 51 52 53 54
15506.80869 -3620.57340 -5767.31658 5120.97688 54926.01077 25796.84957
55 56 57 58 59 60
8286.20971 23842.85856 6428.66949 -7721.91763 -7313.81234 -17713.81059
61 62 63 64 65 66
5080.65676 -6621.03712 -10128.49768 -6282.01687 16690.10968 -13140.60758
67 68 69 70 71 72
-14100.22582 -14045.90390 -16719.67840 552.81905 37546.16900 -5974.09358
73 74 75 76 77 78
-27136.87062 -21277.54013 -19605.39018 1238.92930 -3035.03260 -18741.91936
79 80 81 82 83 84
-23284.84145 -35154.26126 -37453.22352 59422.23791 -10611.56428 -4909.32961
85 86 87 88 89 90
-16785.53654 3567.78893 27296.26085 -18987.35846 -11951.41004 -1135.55046
91 92 93 94 95 96
-7454.18440 -11455.08437 18779.79022 2354.92439 -19875.32321 58560.79122
97 98 99 100 101 102
-20838.95975 -6272.41125 32503.01654 13232.93211 3866.52999 -34177.18917
103 104 105 106 107 108
8244.93607 -2159.61284 -1979.55072 -1576.76798 -21451.00967 10340.08351
109 110 111 112 113 114
-4097.46565 -28910.85617 -20064.52354 -14229.60818 -27834.92116 -11736.13995
115 116 117 118 119 120
-1039.46565 -4097.46565 24239.80989 -34245.53357 27837.96026 -11947.27767
121 122 123 124 125 126
26380.39279 -8883.95211 -7259.43455 -21921.15987 9108.77307 -5348.60450
127 128 129 130 131 132
-11895.96691 24115.01925 -8381.87084 3909.41750 3529.53435 16070.34966
133 134 135 136 137 138
1457.94836 -6499.46521 -5119.19006 6670.52916 -4097.46565 2884.64224
139 140 141 142 143 144
-25016.98330 3033.53435 96.53435 -14007.33697 1232.17719 3544.31501
> postscript(file="/var/wessaorg/rcomp/tmp/6afr41322147097.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 = 144
Frequency = 1
lag(myerror, k = 1) myerror
0 25199.57059 NA
1 2415.16318 25199.57059
2 1514.85056 2415.16318
3 -8624.68575 1514.85056
4 33615.22725 -8624.68575
5 35215.40740 33615.22725
6 6955.89183 35215.40740
7 -1765.09202 6955.89183
8 -14198.27619 -1765.09202
9 76889.05549 -14198.27619
10 -12850.35983 76889.05549
11 -10553.27549 -12850.35983
12 1442.44035 -10553.27549
13 21839.82591 1442.44035
14 15395.79846 21839.82591
15 9872.40013 15395.79846
16 -55375.07565 9872.40013
17 -1489.85478 -55375.07565
18 -32195.84870 -1489.85478
19 -47120.64405 -32195.84870
20 -1356.43753 -47120.64405
21 -28315.98610 -1356.43753
22 22867.37405 -28315.98610
23 -2258.20189 22867.37405
24 5559.01693 -2258.20189
25 14318.87879 5559.01693
26 11133.52013 14318.87879
27 -3348.94524 11133.52013
28 62782.90365 -3348.94524
29 47610.11821 62782.90365
30 -3814.37450 47610.11821
31 27666.49653 -3814.37450
32 -4986.07005 27666.49653
33 -12209.47924 -4986.07005
34 37506.73909 -12209.47924
35 -4097.46565 37506.73909
36 22396.40529 -4097.46565
37 -6384.77162 22396.40529
38 -15823.81706 -6384.77162
39 -16705.24388 -15823.81706
40 -401.87033 -16705.24388
41 11883.91674 -401.87033
42 -12727.74347 11883.91674
43 -16169.89220 -12727.74347
44 -22948.69945 -16169.89220
45 13448.47238 -22948.69945
46 -8488.02439 13448.47238
47 26477.46595 -8488.02439
48 15506.80869 26477.46595
49 -3620.57340 15506.80869
50 -5767.31658 -3620.57340
51 5120.97688 -5767.31658
52 54926.01077 5120.97688
53 25796.84957 54926.01077
54 8286.20971 25796.84957
55 23842.85856 8286.20971
56 6428.66949 23842.85856
57 -7721.91763 6428.66949
58 -7313.81234 -7721.91763
59 -17713.81059 -7313.81234
60 5080.65676 -17713.81059
61 -6621.03712 5080.65676
62 -10128.49768 -6621.03712
63 -6282.01687 -10128.49768
64 16690.10968 -6282.01687
65 -13140.60758 16690.10968
66 -14100.22582 -13140.60758
67 -14045.90390 -14100.22582
68 -16719.67840 -14045.90390
69 552.81905 -16719.67840
70 37546.16900 552.81905
71 -5974.09358 37546.16900
72 -27136.87062 -5974.09358
73 -21277.54013 -27136.87062
74 -19605.39018 -21277.54013
75 1238.92930 -19605.39018
76 -3035.03260 1238.92930
77 -18741.91936 -3035.03260
78 -23284.84145 -18741.91936
79 -35154.26126 -23284.84145
80 -37453.22352 -35154.26126
81 59422.23791 -37453.22352
82 -10611.56428 59422.23791
83 -4909.32961 -10611.56428
84 -16785.53654 -4909.32961
85 3567.78893 -16785.53654
86 27296.26085 3567.78893
87 -18987.35846 27296.26085
88 -11951.41004 -18987.35846
89 -1135.55046 -11951.41004
90 -7454.18440 -1135.55046
91 -11455.08437 -7454.18440
92 18779.79022 -11455.08437
93 2354.92439 18779.79022
94 -19875.32321 2354.92439
95 58560.79122 -19875.32321
96 -20838.95975 58560.79122
97 -6272.41125 -20838.95975
98 32503.01654 -6272.41125
99 13232.93211 32503.01654
100 3866.52999 13232.93211
101 -34177.18917 3866.52999
102 8244.93607 -34177.18917
103 -2159.61284 8244.93607
104 -1979.55072 -2159.61284
105 -1576.76798 -1979.55072
106 -21451.00967 -1576.76798
107 10340.08351 -21451.00967
108 -4097.46565 10340.08351
109 -28910.85617 -4097.46565
110 -20064.52354 -28910.85617
111 -14229.60818 -20064.52354
112 -27834.92116 -14229.60818
113 -11736.13995 -27834.92116
114 -1039.46565 -11736.13995
115 -4097.46565 -1039.46565
116 24239.80989 -4097.46565
117 -34245.53357 24239.80989
118 27837.96026 -34245.53357
119 -11947.27767 27837.96026
120 26380.39279 -11947.27767
121 -8883.95211 26380.39279
122 -7259.43455 -8883.95211
123 -21921.15987 -7259.43455
124 9108.77307 -21921.15987
125 -5348.60450 9108.77307
126 -11895.96691 -5348.60450
127 24115.01925 -11895.96691
128 -8381.87084 24115.01925
129 3909.41750 -8381.87084
130 3529.53435 3909.41750
131 16070.34966 3529.53435
132 1457.94836 16070.34966
133 -6499.46521 1457.94836
134 -5119.19006 -6499.46521
135 6670.52916 -5119.19006
136 -4097.46565 6670.52916
137 2884.64224 -4097.46565
138 -25016.98330 2884.64224
139 3033.53435 -25016.98330
140 96.53435 3033.53435
141 -14007.33697 96.53435
142 1232.17719 -14007.33697
143 3544.31501 1232.17719
144 NA 3544.31501
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 2415.16318 25199.57059
[2,] 1514.85056 2415.16318
[3,] -8624.68575 1514.85056
[4,] 33615.22725 -8624.68575
[5,] 35215.40740 33615.22725
[6,] 6955.89183 35215.40740
[7,] -1765.09202 6955.89183
[8,] -14198.27619 -1765.09202
[9,] 76889.05549 -14198.27619
[10,] -12850.35983 76889.05549
[11,] -10553.27549 -12850.35983
[12,] 1442.44035 -10553.27549
[13,] 21839.82591 1442.44035
[14,] 15395.79846 21839.82591
[15,] 9872.40013 15395.79846
[16,] -55375.07565 9872.40013
[17,] -1489.85478 -55375.07565
[18,] -32195.84870 -1489.85478
[19,] -47120.64405 -32195.84870
[20,] -1356.43753 -47120.64405
[21,] -28315.98610 -1356.43753
[22,] 22867.37405 -28315.98610
[23,] -2258.20189 22867.37405
[24,] 5559.01693 -2258.20189
[25,] 14318.87879 5559.01693
[26,] 11133.52013 14318.87879
[27,] -3348.94524 11133.52013
[28,] 62782.90365 -3348.94524
[29,] 47610.11821 62782.90365
[30,] -3814.37450 47610.11821
[31,] 27666.49653 -3814.37450
[32,] -4986.07005 27666.49653
[33,] -12209.47924 -4986.07005
[34,] 37506.73909 -12209.47924
[35,] -4097.46565 37506.73909
[36,] 22396.40529 -4097.46565
[37,] -6384.77162 22396.40529
[38,] -15823.81706 -6384.77162
[39,] -16705.24388 -15823.81706
[40,] -401.87033 -16705.24388
[41,] 11883.91674 -401.87033
[42,] -12727.74347 11883.91674
[43,] -16169.89220 -12727.74347
[44,] -22948.69945 -16169.89220
[45,] 13448.47238 -22948.69945
[46,] -8488.02439 13448.47238
[47,] 26477.46595 -8488.02439
[48,] 15506.80869 26477.46595
[49,] -3620.57340 15506.80869
[50,] -5767.31658 -3620.57340
[51,] 5120.97688 -5767.31658
[52,] 54926.01077 5120.97688
[53,] 25796.84957 54926.01077
[54,] 8286.20971 25796.84957
[55,] 23842.85856 8286.20971
[56,] 6428.66949 23842.85856
[57,] -7721.91763 6428.66949
[58,] -7313.81234 -7721.91763
[59,] -17713.81059 -7313.81234
[60,] 5080.65676 -17713.81059
[61,] -6621.03712 5080.65676
[62,] -10128.49768 -6621.03712
[63,] -6282.01687 -10128.49768
[64,] 16690.10968 -6282.01687
[65,] -13140.60758 16690.10968
[66,] -14100.22582 -13140.60758
[67,] -14045.90390 -14100.22582
[68,] -16719.67840 -14045.90390
[69,] 552.81905 -16719.67840
[70,] 37546.16900 552.81905
[71,] -5974.09358 37546.16900
[72,] -27136.87062 -5974.09358
[73,] -21277.54013 -27136.87062
[74,] -19605.39018 -21277.54013
[75,] 1238.92930 -19605.39018
[76,] -3035.03260 1238.92930
[77,] -18741.91936 -3035.03260
[78,] -23284.84145 -18741.91936
[79,] -35154.26126 -23284.84145
[80,] -37453.22352 -35154.26126
[81,] 59422.23791 -37453.22352
[82,] -10611.56428 59422.23791
[83,] -4909.32961 -10611.56428
[84,] -16785.53654 -4909.32961
[85,] 3567.78893 -16785.53654
[86,] 27296.26085 3567.78893
[87,] -18987.35846 27296.26085
[88,] -11951.41004 -18987.35846
[89,] -1135.55046 -11951.41004
[90,] -7454.18440 -1135.55046
[91,] -11455.08437 -7454.18440
[92,] 18779.79022 -11455.08437
[93,] 2354.92439 18779.79022
[94,] -19875.32321 2354.92439
[95,] 58560.79122 -19875.32321
[96,] -20838.95975 58560.79122
[97,] -6272.41125 -20838.95975
[98,] 32503.01654 -6272.41125
[99,] 13232.93211 32503.01654
[100,] 3866.52999 13232.93211
[101,] -34177.18917 3866.52999
[102,] 8244.93607 -34177.18917
[103,] -2159.61284 8244.93607
[104,] -1979.55072 -2159.61284
[105,] -1576.76798 -1979.55072
[106,] -21451.00967 -1576.76798
[107,] 10340.08351 -21451.00967
[108,] -4097.46565 10340.08351
[109,] -28910.85617 -4097.46565
[110,] -20064.52354 -28910.85617
[111,] -14229.60818 -20064.52354
[112,] -27834.92116 -14229.60818
[113,] -11736.13995 -27834.92116
[114,] -1039.46565 -11736.13995
[115,] -4097.46565 -1039.46565
[116,] 24239.80989 -4097.46565
[117,] -34245.53357 24239.80989
[118,] 27837.96026 -34245.53357
[119,] -11947.27767 27837.96026
[120,] 26380.39279 -11947.27767
[121,] -8883.95211 26380.39279
[122,] -7259.43455 -8883.95211
[123,] -21921.15987 -7259.43455
[124,] 9108.77307 -21921.15987
[125,] -5348.60450 9108.77307
[126,] -11895.96691 -5348.60450
[127,] 24115.01925 -11895.96691
[128,] -8381.87084 24115.01925
[129,] 3909.41750 -8381.87084
[130,] 3529.53435 3909.41750
[131,] 16070.34966 3529.53435
[132,] 1457.94836 16070.34966
[133,] -6499.46521 1457.94836
[134,] -5119.19006 -6499.46521
[135,] 6670.52916 -5119.19006
[136,] -4097.46565 6670.52916
[137,] 2884.64224 -4097.46565
[138,] -25016.98330 2884.64224
[139,] 3033.53435 -25016.98330
[140,] 96.53435 3033.53435
[141,] -14007.33697 96.53435
[142,] 1232.17719 -14007.33697
[143,] 3544.31501 1232.17719
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 2415.16318 25199.57059
2 1514.85056 2415.16318
3 -8624.68575 1514.85056
4 33615.22725 -8624.68575
5 35215.40740 33615.22725
6 6955.89183 35215.40740
7 -1765.09202 6955.89183
8 -14198.27619 -1765.09202
9 76889.05549 -14198.27619
10 -12850.35983 76889.05549
11 -10553.27549 -12850.35983
12 1442.44035 -10553.27549
13 21839.82591 1442.44035
14 15395.79846 21839.82591
15 9872.40013 15395.79846
16 -55375.07565 9872.40013
17 -1489.85478 -55375.07565
18 -32195.84870 -1489.85478
19 -47120.64405 -32195.84870
20 -1356.43753 -47120.64405
21 -28315.98610 -1356.43753
22 22867.37405 -28315.98610
23 -2258.20189 22867.37405
24 5559.01693 -2258.20189
25 14318.87879 5559.01693
26 11133.52013 14318.87879
27 -3348.94524 11133.52013
28 62782.90365 -3348.94524
29 47610.11821 62782.90365
30 -3814.37450 47610.11821
31 27666.49653 -3814.37450
32 -4986.07005 27666.49653
33 -12209.47924 -4986.07005
34 37506.73909 -12209.47924
35 -4097.46565 37506.73909
36 22396.40529 -4097.46565
37 -6384.77162 22396.40529
38 -15823.81706 -6384.77162
39 -16705.24388 -15823.81706
40 -401.87033 -16705.24388
41 11883.91674 -401.87033
42 -12727.74347 11883.91674
43 -16169.89220 -12727.74347
44 -22948.69945 -16169.89220
45 13448.47238 -22948.69945
46 -8488.02439 13448.47238
47 26477.46595 -8488.02439
48 15506.80869 26477.46595
49 -3620.57340 15506.80869
50 -5767.31658 -3620.57340
51 5120.97688 -5767.31658
52 54926.01077 5120.97688
53 25796.84957 54926.01077
54 8286.20971 25796.84957
55 23842.85856 8286.20971
56 6428.66949 23842.85856
57 -7721.91763 6428.66949
58 -7313.81234 -7721.91763
59 -17713.81059 -7313.81234
60 5080.65676 -17713.81059
61 -6621.03712 5080.65676
62 -10128.49768 -6621.03712
63 -6282.01687 -10128.49768
64 16690.10968 -6282.01687
65 -13140.60758 16690.10968
66 -14100.22582 -13140.60758
67 -14045.90390 -14100.22582
68 -16719.67840 -14045.90390
69 552.81905 -16719.67840
70 37546.16900 552.81905
71 -5974.09358 37546.16900
72 -27136.87062 -5974.09358
73 -21277.54013 -27136.87062
74 -19605.39018 -21277.54013
75 1238.92930 -19605.39018
76 -3035.03260 1238.92930
77 -18741.91936 -3035.03260
78 -23284.84145 -18741.91936
79 -35154.26126 -23284.84145
80 -37453.22352 -35154.26126
81 59422.23791 -37453.22352
82 -10611.56428 59422.23791
83 -4909.32961 -10611.56428
84 -16785.53654 -4909.32961
85 3567.78893 -16785.53654
86 27296.26085 3567.78893
87 -18987.35846 27296.26085
88 -11951.41004 -18987.35846
89 -1135.55046 -11951.41004
90 -7454.18440 -1135.55046
91 -11455.08437 -7454.18440
92 18779.79022 -11455.08437
93 2354.92439 18779.79022
94 -19875.32321 2354.92439
95 58560.79122 -19875.32321
96 -20838.95975 58560.79122
97 -6272.41125 -20838.95975
98 32503.01654 -6272.41125
99 13232.93211 32503.01654
100 3866.52999 13232.93211
101 -34177.18917 3866.52999
102 8244.93607 -34177.18917
103 -2159.61284 8244.93607
104 -1979.55072 -2159.61284
105 -1576.76798 -1979.55072
106 -21451.00967 -1576.76798
107 10340.08351 -21451.00967
108 -4097.46565 10340.08351
109 -28910.85617 -4097.46565
110 -20064.52354 -28910.85617
111 -14229.60818 -20064.52354
112 -27834.92116 -14229.60818
113 -11736.13995 -27834.92116
114 -1039.46565 -11736.13995
115 -4097.46565 -1039.46565
116 24239.80989 -4097.46565
117 -34245.53357 24239.80989
118 27837.96026 -34245.53357
119 -11947.27767 27837.96026
120 26380.39279 -11947.27767
121 -8883.95211 26380.39279
122 -7259.43455 -8883.95211
123 -21921.15987 -7259.43455
124 9108.77307 -21921.15987
125 -5348.60450 9108.77307
126 -11895.96691 -5348.60450
127 24115.01925 -11895.96691
128 -8381.87084 24115.01925
129 3909.41750 -8381.87084
130 3529.53435 3909.41750
131 16070.34966 3529.53435
132 1457.94836 16070.34966
133 -6499.46521 1457.94836
134 -5119.19006 -6499.46521
135 6670.52916 -5119.19006
136 -4097.46565 6670.52916
137 2884.64224 -4097.46565
138 -25016.98330 2884.64224
139 3033.53435 -25016.98330
140 96.53435 3033.53435
141 -14007.33697 96.53435
142 1232.17719 -14007.33697
143 3544.31501 1232.17719
> 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/wessaorg/rcomp/tmp/74cog1322147097.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/8j64q1322147097.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/9mq0r1322147097.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/wessaorg/rcomp/tmp/10u8do1322147097.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/wessaorg/rcomp/tmp/112n3r1322147097.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/wessaorg/rcomp/tmp/12tpie1322147097.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/wessaorg/rcomp/tmp/13lbvv1322147097.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/wessaorg/rcomp/tmp/14qmzu1322147097.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/wessaorg/rcomp/tmp/15zobj1322147097.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/wessaorg/rcomp/tmp/16vg9h1322147097.tab")
+ }
>
> try(system("convert tmp/16fla1322147097.ps tmp/16fla1322147097.png",intern=TRUE))
character(0)
> try(system("convert tmp/2547l1322147097.ps tmp/2547l1322147097.png",intern=TRUE))
character(0)
> try(system("convert tmp/3ttaf1322147097.ps tmp/3ttaf1322147097.png",intern=TRUE))
character(0)
> try(system("convert tmp/4p5mr1322147097.ps tmp/4p5mr1322147097.png",intern=TRUE))
character(0)
> try(system("convert tmp/5kvsh1322147097.ps tmp/5kvsh1322147097.png",intern=TRUE))
character(0)
> try(system("convert tmp/6afr41322147097.ps tmp/6afr41322147097.png",intern=TRUE))
character(0)
> try(system("convert tmp/74cog1322147097.ps tmp/74cog1322147097.png",intern=TRUE))
character(0)
> try(system("convert tmp/8j64q1322147097.ps tmp/8j64q1322147097.png",intern=TRUE))
character(0)
> try(system("convert tmp/9mq0r1322147097.ps tmp/9mq0r1322147097.png",intern=TRUE))
character(0)
> try(system("convert tmp/10u8do1322147097.ps tmp/10u8do1322147097.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
4.769 0.526 5.327