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.
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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(63047
+ ,13
+ ,6
+ ,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
+ ,39000
+ ,1
+ ,7
+ ,14831
+ ,42419
+ ,12
+ ,10
+ ,6585)
+ ,dim=c(4
+ ,144)
+ ,dimnames=list(c('y'
+ ,'X1'
+ ,'X2'
+ ,'X3')
+ ,1:144))
> y <- array(NA,dim=c(4,144),dimnames=list(c('y','X1','X2','X3'),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
y X1 X2 X3
1 63047 13 6 10345
2 66751 26 7 17607
3 7176 0 0 1423
4 78306 37 12 20050
5 144655 47 15 21212
6 269638 84 16 93979
7 69266 21 12 15524
8 83529 36 15 16182
9 73226 35 15 19238
10 178519 40 13 28909
11 67250 35 6 22357
12 102982 46 16 25560
13 50001 20 7 9954
14 91093 24 12 18490
15 80112 19 9 17777
16 72961 15 10 25268
17 77159 52 16 37525
18 15629 0 5 6023
19 71693 38 20 25042
20 19920 12 7 35713
21 39403 10 13 7039
22 104383 53 13 40841
23 56088 4 11 9214
24 62006 24 9 17446
25 81665 39 10 10295
26 69451 19 7 13206
27 88794 23 13 26093
28 90642 39 15 20744
29 207069 38 13 68013
30 99340 20 7 12840
31 56695 20 14 12672
32 108143 41 11 10872
33 64204 29 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 113787 47 18 37929
41 86584 42 9 18009
42 59588 11 14 11076
43 40064 10 7 24981
44 74471 26 13 30691
45 60437 27 11 29164
46 55118 1 11 13985
47 40295 15 14 7588
48 103397 32 9 20023
49 78982 13 12 25524
50 67317 25 12 14717
51 39887 10 17 6832
52 59682 24 10 9624
53 132740 26 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 33239 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 81051 19 16 39553
68 70872 39 13 14818
69 42372 17 12 17065
70 19144 0 10 1536
71 114177 39 9 11938
72 59414 21 3 24589
73 51379 29 12 21332
74 40756 27 8 13229
75 53398 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 120064 22 17 28994
88 36149 15 13 10461
89 40181 14 10 16415
90 53398 22 11 8495
91 56435 25 7 18318
92 86791 45 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 60734 35 12 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 55195 18 17 33996
119 73321 13 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 66463 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 35414 18 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 39000 1 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) X1 X2 X3
3928.173 1215.067 1316.065 1.149
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-54142 -13467 -2799 8383 75650
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 3928.1727 4156.5571 0.945 0.3463
X1 1215.0666 164.6612 7.379 1.29e-11 ***
X2 1316.0649 438.7492 3.000 0.0032 **
X3 1.1494 0.1978 5.811 4.00e-08 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 21530 on 140 degrees of freedom
Multiple R-squared: 0.6962, Adjusted R-squared: 0.6897
F-statistic: 107 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,] 0.6227732 0.7544536748 3.772268e-01
[2,] 0.5313867 0.9372266460 4.686133e-01
[3,] 0.5127741 0.9744518548 4.872259e-01
[4,] 0.9670791 0.0658418341 3.292092e-02
[5,] 0.9667556 0.0664888575 3.324443e-02
[6,] 0.9589241 0.0821517680 4.107588e-02
[7,] 0.9343056 0.1313888044 6.569440e-02
[8,] 0.9069699 0.1860601636 9.303008e-02
[9,] 0.8731308 0.2537383483 1.268692e-01
[10,] 0.8412605 0.3174789841 1.587395e-01
[11,] 0.9862286 0.0275427991 1.377140e-02
[12,] 0.9803013 0.0393974957 1.969875e-02
[13,] 0.9861135 0.0277729243 1.388646e-02
[14,] 0.9972681 0.0054638236 2.731912e-03
[15,] 0.9957770 0.0084460340 4.223017e-03
[16,] 0.9972950 0.0054100644 2.705032e-03
[17,] 0.9975205 0.0049589111 2.479456e-03
[18,] 0.9960602 0.0078796886 3.939844e-03
[19,] 0.9938430 0.0123139795 6.156990e-03
[20,] 0.9920531 0.0158938325 7.946916e-03
[21,] 0.9889847 0.0220306142 1.101531e-02
[22,] 0.9839952 0.0320096433 1.600482e-02
[23,] 0.9983953 0.0032093083 1.604654e-03
[24,] 0.9995779 0.0008441513 4.220756e-04
[25,] 0.9993182 0.0013636023 6.818012e-04
[26,] 0.9994293 0.0011414190 5.707095e-04
[27,] 0.9992311 0.0015378976 7.689488e-04
[28,] 0.9990581 0.0018837338 9.418669e-04
[29,] 0.9995427 0.0009146473 4.573236e-04
[30,] 0.9993180 0.0013640344 6.820172e-04
[31,] 0.9992518 0.0014963365 7.481683e-04
[32,] 0.9989199 0.0021602856 1.080143e-03
[33,] 0.9987149 0.0025701227 1.285061e-03
[34,] 0.9983468 0.0033063754 1.653188e-03
[35,] 0.9976148 0.0047703548 2.385177e-03
[36,] 0.9967432 0.0065136723 3.256836e-03
[37,] 0.9960909 0.0078181648 3.909082e-03
[38,] 0.9950194 0.0099611306 4.980565e-03
[39,] 0.9952875 0.0094250172 4.712509e-03
[40,] 0.9947860 0.0104279960 5.213998e-03
[41,] 0.9930750 0.0138499966 6.924998e-03
[42,] 0.9942088 0.0115824576 5.791229e-03
[43,] 0.9931699 0.0136601056 6.830053e-03
[44,] 0.9904034 0.0191931396 9.596570e-03
[45,] 0.9874753 0.0250494761 1.252474e-02
[46,] 0.9828613 0.0342774644 1.713873e-02
[47,] 0.9980727 0.0038545226 1.927261e-03
[48,] 0.9986019 0.0027962360 1.398118e-03
[49,] 0.9980981 0.0038038806 1.901940e-03
[50,] 0.9983115 0.0033770828 1.688541e-03
[51,] 0.9978733 0.0042534264 2.126713e-03
[52,] 0.9971669 0.0056661003 2.833050e-03
[53,] 0.9961028 0.0077944682 3.897234e-03
[54,] 0.9952548 0.0094904889 4.745244e-03
[55,] 0.9938780 0.0122439006 6.121950e-03
[56,] 0.9919535 0.0160930303 8.046515e-03
[57,] 0.9897885 0.0204229568 1.021148e-02
[58,] 0.9865893 0.0268213794 1.341069e-02
[59,] 0.9845789 0.0308421809 1.542109e-02
[60,] 0.9814799 0.0370401855 1.852009e-02
[61,] 0.9764331 0.0471338540 2.356693e-02
[62,] 0.9720958 0.0558083892 2.790419e-02
[63,] 0.9692450 0.0615100736 3.075504e-02
[64,] 0.9616016 0.0767967172 3.839836e-02
[65,] 0.9856817 0.0286365453 1.431827e-02
[66,] 0.9843893 0.0312213575 1.561068e-02
[67,] 0.9859835 0.0280329501 1.401648e-02
[68,] 0.9854882 0.0290236234 1.451181e-02
[69,] 0.9842871 0.0314257853 1.571289e-02
[70,] 0.9805201 0.0389597096 1.947985e-02
[71,] 0.9766948 0.0466103072 2.330515e-02
[72,] 0.9731668 0.0536664402 2.683322e-02
[73,] 0.9779291 0.0441417704 2.207089e-02
[74,] 0.9820858 0.0358283013 1.791415e-02
[75,] 0.9903763 0.0192473512 9.623676e-03
[76,] 0.9992157 0.0015686257 7.843128e-04
[77,] 0.9989713 0.0020574472 1.028724e-03
[78,] 0.9984553 0.0030894745 1.544737e-03
[79,] 0.9983755 0.0032489172 1.624459e-03
[80,] 0.9975909 0.0048182540 2.409127e-03
[81,] 0.9992492 0.0015015969 7.507985e-04
[82,] 0.9992369 0.0015261286 7.630643e-04
[83,] 0.9989676 0.0020648818 1.032441e-03
[84,] 0.9984148 0.0031703091 1.585155e-03
[85,] 0.9977117 0.0045766823 2.288341e-03
[86,] 0.9971768 0.0056464318 2.823216e-03
[87,] 0.9972835 0.0054329539 2.716477e-03
[88,] 0.9964556 0.0070888105 3.544405e-03
[89,] 0.9956795 0.0086409586 4.320479e-03
[90,] 0.9999277 0.0001445241 7.226204e-05
[91,] 0.9998913 0.0002174632 1.087316e-04
[92,] 0.9998139 0.0003721245 1.860622e-04
[93,] 0.9999306 0.0001388369 6.941845e-05
[94,] 0.9999148 0.0001704405 8.522024e-05
[95,] 0.9998548 0.0002904609 1.452304e-04
[96,] 0.9999135 0.0001729144 8.645720e-05
[97,] 0.9998907 0.0002186954 1.093477e-04
[98,] 0.9998068 0.0003864937 1.932468e-04
[99,] 0.9996591 0.0006817726 3.408863e-04
[100,] 0.9994783 0.0010433723 5.216862e-04
[101,] 0.9992104 0.0015791064 7.895532e-04
[102,] 0.9988596 0.0022807599 1.140380e-03
[103,] 0.9982299 0.0035402175 1.770109e-03
[104,] 0.9984067 0.0031865792 1.593290e-03
[105,] 0.9980930 0.0038140214 1.907011e-03
[106,] 0.9969702 0.0060596982 3.029849e-03
[107,] 0.9982962 0.0034076913 1.703846e-03
[108,] 0.9971337 0.0057326404 2.866320e-03
[109,] 0.9953224 0.0093551751 4.677588e-03
[110,] 0.9929640 0.0140720166 7.036008e-03
[111,] 0.9970480 0.0059039000 2.951950e-03
[112,] 0.9981657 0.0036686251 1.834313e-03
[113,] 0.9995481 0.0009037968 4.518984e-04
[114,] 0.9993973 0.0012054554 6.027277e-04
[115,] 0.9998512 0.0002976572 1.488286e-04
[116,] 0.9996702 0.0006595587 3.297793e-04
[117,] 0.9992858 0.0014283274 7.141637e-04
[118,] 0.9990450 0.0019100524 9.550262e-04
[119,] 0.9981133 0.0037733146 1.886657e-03
[120,] 0.9963595 0.0072810132 3.640507e-03
[121,] 0.9926662 0.0146676238 7.333812e-03
[122,] 0.9984152 0.0031696878 1.584844e-03
[123,] 0.9963140 0.0073719571 3.685979e-03
[124,] 0.9925411 0.0149177242 7.458862e-03
[125,] 0.9843469 0.0313062164 1.565311e-02
[126,] 0.9868677 0.0262646340 1.313232e-02
[127,] 0.9704530 0.0590939822 2.954699e-02
[128,] 0.9379055 0.1241890407 6.209452e-02
[129,] 0.8863672 0.2272656954 1.136328e-01
[130,] 0.8038964 0.3922072098 1.961036e-01
[131,] 0.6657293 0.6685413208 3.342707e-01
> postscript(file="/var/wessaorg/rcomp/tmp/140jf1322157014.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/2q0vs1322157014.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3uvy61322157014.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/4z2st1322157014.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/5ogpf1322157014.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
23535.7359 1780.6565 1612.1909 -9418.4546 39496.0486 34565.0708
7 8 9 10 11 12
6184.9241 -2482.5942 -15083.1803 75650.4955 -12799.6627 -7275.6639
13 14 15 16 17 18
1117.6309 20957.5199 20819.5903 8602.4248 -54141.9730 -1802.5038
19 20 21 22 23 24
-33512.9866 -48850.9588 -1875.5089 -27996.3490 22232.0144 -2981.2822
25 26 27 28 29 30
5355.2148 18044.7568 9818.4185 -4258.4859 61683.3857 47139.3809
31 32 33 34 35 36
-4524.9697 27423.7965 -3420.8580 -13564.9608 36820.2091 -3928.1727
37 38 39 40 41 42
21594.6951 -6789.9420 -17447.4846 -14535.1386 -921.6099 11138.1176
43 44 45 46 47 48
-13941.1613 -13434.8526 -24296.6124 19423.2920 -9005.9431 25727.1080
49 50 51 52 53 54
14127.1746 303.2462 -6417.8369 2369.4808 54812.2733 24812.0734
55 56 57 58 59 60
7533.5372 23613.9209 5645.2531 -8442.4725 -8045.2650 -14170.4686
61 62 63 64 65 66
4456.0800 -6822.9121 -11241.5156 -6704.6531 15919.5621 -14077.0166
67 68 69 70 71 72
-12483.8143 -14584.8441 -17620.0783 289.6562 37294.7691 -2242.0588
73 74 75 76 77 78
-28098.4884 -21713.2781 -13873.9811 1045.7806 -3752.5759 -20400.1038
79 80 81 82 83 84
-24147.7965 -36280.3895 -38260.5988 59060.3168 -10939.8154 -5493.8601
85 86 87 88 89 90
-17356.9034 2187.0580 33704.7340 -15138.1856 -12786.6201 -1502.7463
91 92 93 94 95 96
-8137.5204 -13875.8960 17652.5005 1816.6113 -20618.9986 57833.9144
97 98 99 100 101 102
-22143.1207 -6168.1271 31869.7404 12682.9836 3985.8085 -34898.1656
103 104 105 106 107 108
7035.2321 -2617.5229 -2234.9598 -2008.6603 -18705.1336 10313.8014
109 110 111 112 113 114
-3928.1727 -29122.8057 -20905.3661 -14917.7695 -28327.7918 -12351.5065
115 116 117 118 119 120
-870.1727 -3928.1727 23527.1515 -32053.4396 26284.6421 -12969.3890
121 122 123 124 125 126
26463.7359 -9666.8615 -7446.1356 -22142.5214 8309.4299 -5405.6064
127 128 129 130 131 132
-5925.0568 23377.4904 -9192.0696 4020.6308 3698.8273 15036.3359
133 134 135 136 137 138
1591.7624 -5892.2178 -4885.5059 6698.1133 -3928.1727 2108.4981
139 140 141 142 143 144
-26149.5775 3202.8273 265.8273 -14144.9820 7597.1355 3180.3931
> postscript(file="/var/wessaorg/rcomp/tmp/6c0at1322157014.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 23535.7359 NA
1 1780.6565 23535.7359
2 1612.1909 1780.6565
3 -9418.4546 1612.1909
4 39496.0486 -9418.4546
5 34565.0708 39496.0486
6 6184.9241 34565.0708
7 -2482.5942 6184.9241
8 -15083.1803 -2482.5942
9 75650.4955 -15083.1803
10 -12799.6627 75650.4955
11 -7275.6639 -12799.6627
12 1117.6309 -7275.6639
13 20957.5199 1117.6309
14 20819.5903 20957.5199
15 8602.4248 20819.5903
16 -54141.9730 8602.4248
17 -1802.5038 -54141.9730
18 -33512.9866 -1802.5038
19 -48850.9588 -33512.9866
20 -1875.5089 -48850.9588
21 -27996.3490 -1875.5089
22 22232.0144 -27996.3490
23 -2981.2822 22232.0144
24 5355.2148 -2981.2822
25 18044.7568 5355.2148
26 9818.4185 18044.7568
27 -4258.4859 9818.4185
28 61683.3857 -4258.4859
29 47139.3809 61683.3857
30 -4524.9697 47139.3809
31 27423.7965 -4524.9697
32 -3420.8580 27423.7965
33 -13564.9608 -3420.8580
34 36820.2091 -13564.9608
35 -3928.1727 36820.2091
36 21594.6951 -3928.1727
37 -6789.9420 21594.6951
38 -17447.4846 -6789.9420
39 -14535.1386 -17447.4846
40 -921.6099 -14535.1386
41 11138.1176 -921.6099
42 -13941.1613 11138.1176
43 -13434.8526 -13941.1613
44 -24296.6124 -13434.8526
45 19423.2920 -24296.6124
46 -9005.9431 19423.2920
47 25727.1080 -9005.9431
48 14127.1746 25727.1080
49 303.2462 14127.1746
50 -6417.8369 303.2462
51 2369.4808 -6417.8369
52 54812.2733 2369.4808
53 24812.0734 54812.2733
54 7533.5372 24812.0734
55 23613.9209 7533.5372
56 5645.2531 23613.9209
57 -8442.4725 5645.2531
58 -8045.2650 -8442.4725
59 -14170.4686 -8045.2650
60 4456.0800 -14170.4686
61 -6822.9121 4456.0800
62 -11241.5156 -6822.9121
63 -6704.6531 -11241.5156
64 15919.5621 -6704.6531
65 -14077.0166 15919.5621
66 -12483.8143 -14077.0166
67 -14584.8441 -12483.8143
68 -17620.0783 -14584.8441
69 289.6562 -17620.0783
70 37294.7691 289.6562
71 -2242.0588 37294.7691
72 -28098.4884 -2242.0588
73 -21713.2781 -28098.4884
74 -13873.9811 -21713.2781
75 1045.7806 -13873.9811
76 -3752.5759 1045.7806
77 -20400.1038 -3752.5759
78 -24147.7965 -20400.1038
79 -36280.3895 -24147.7965
80 -38260.5988 -36280.3895
81 59060.3168 -38260.5988
82 -10939.8154 59060.3168
83 -5493.8601 -10939.8154
84 -17356.9034 -5493.8601
85 2187.0580 -17356.9034
86 33704.7340 2187.0580
87 -15138.1856 33704.7340
88 -12786.6201 -15138.1856
89 -1502.7463 -12786.6201
90 -8137.5204 -1502.7463
91 -13875.8960 -8137.5204
92 17652.5005 -13875.8960
93 1816.6113 17652.5005
94 -20618.9986 1816.6113
95 57833.9144 -20618.9986
96 -22143.1207 57833.9144
97 -6168.1271 -22143.1207
98 31869.7404 -6168.1271
99 12682.9836 31869.7404
100 3985.8085 12682.9836
101 -34898.1656 3985.8085
102 7035.2321 -34898.1656
103 -2617.5229 7035.2321
104 -2234.9598 -2617.5229
105 -2008.6603 -2234.9598
106 -18705.1336 -2008.6603
107 10313.8014 -18705.1336
108 -3928.1727 10313.8014
109 -29122.8057 -3928.1727
110 -20905.3661 -29122.8057
111 -14917.7695 -20905.3661
112 -28327.7918 -14917.7695
113 -12351.5065 -28327.7918
114 -870.1727 -12351.5065
115 -3928.1727 -870.1727
116 23527.1515 -3928.1727
117 -32053.4396 23527.1515
118 26284.6421 -32053.4396
119 -12969.3890 26284.6421
120 26463.7359 -12969.3890
121 -9666.8615 26463.7359
122 -7446.1356 -9666.8615
123 -22142.5214 -7446.1356
124 8309.4299 -22142.5214
125 -5405.6064 8309.4299
126 -5925.0568 -5405.6064
127 23377.4904 -5925.0568
128 -9192.0696 23377.4904
129 4020.6308 -9192.0696
130 3698.8273 4020.6308
131 15036.3359 3698.8273
132 1591.7624 15036.3359
133 -5892.2178 1591.7624
134 -4885.5059 -5892.2178
135 6698.1133 -4885.5059
136 -3928.1727 6698.1133
137 2108.4981 -3928.1727
138 -26149.5775 2108.4981
139 3202.8273 -26149.5775
140 265.8273 3202.8273
141 -14144.9820 265.8273
142 7597.1355 -14144.9820
143 3180.3931 7597.1355
144 NA 3180.3931
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 1780.6565 23535.7359
[2,] 1612.1909 1780.6565
[3,] -9418.4546 1612.1909
[4,] 39496.0486 -9418.4546
[5,] 34565.0708 39496.0486
[6,] 6184.9241 34565.0708
[7,] -2482.5942 6184.9241
[8,] -15083.1803 -2482.5942
[9,] 75650.4955 -15083.1803
[10,] -12799.6627 75650.4955
[11,] -7275.6639 -12799.6627
[12,] 1117.6309 -7275.6639
[13,] 20957.5199 1117.6309
[14,] 20819.5903 20957.5199
[15,] 8602.4248 20819.5903
[16,] -54141.9730 8602.4248
[17,] -1802.5038 -54141.9730
[18,] -33512.9866 -1802.5038
[19,] -48850.9588 -33512.9866
[20,] -1875.5089 -48850.9588
[21,] -27996.3490 -1875.5089
[22,] 22232.0144 -27996.3490
[23,] -2981.2822 22232.0144
[24,] 5355.2148 -2981.2822
[25,] 18044.7568 5355.2148
[26,] 9818.4185 18044.7568
[27,] -4258.4859 9818.4185
[28,] 61683.3857 -4258.4859
[29,] 47139.3809 61683.3857
[30,] -4524.9697 47139.3809
[31,] 27423.7965 -4524.9697
[32,] -3420.8580 27423.7965
[33,] -13564.9608 -3420.8580
[34,] 36820.2091 -13564.9608
[35,] -3928.1727 36820.2091
[36,] 21594.6951 -3928.1727
[37,] -6789.9420 21594.6951
[38,] -17447.4846 -6789.9420
[39,] -14535.1386 -17447.4846
[40,] -921.6099 -14535.1386
[41,] 11138.1176 -921.6099
[42,] -13941.1613 11138.1176
[43,] -13434.8526 -13941.1613
[44,] -24296.6124 -13434.8526
[45,] 19423.2920 -24296.6124
[46,] -9005.9431 19423.2920
[47,] 25727.1080 -9005.9431
[48,] 14127.1746 25727.1080
[49,] 303.2462 14127.1746
[50,] -6417.8369 303.2462
[51,] 2369.4808 -6417.8369
[52,] 54812.2733 2369.4808
[53,] 24812.0734 54812.2733
[54,] 7533.5372 24812.0734
[55,] 23613.9209 7533.5372
[56,] 5645.2531 23613.9209
[57,] -8442.4725 5645.2531
[58,] -8045.2650 -8442.4725
[59,] -14170.4686 -8045.2650
[60,] 4456.0800 -14170.4686
[61,] -6822.9121 4456.0800
[62,] -11241.5156 -6822.9121
[63,] -6704.6531 -11241.5156
[64,] 15919.5621 -6704.6531
[65,] -14077.0166 15919.5621
[66,] -12483.8143 -14077.0166
[67,] -14584.8441 -12483.8143
[68,] -17620.0783 -14584.8441
[69,] 289.6562 -17620.0783
[70,] 37294.7691 289.6562
[71,] -2242.0588 37294.7691
[72,] -28098.4884 -2242.0588
[73,] -21713.2781 -28098.4884
[74,] -13873.9811 -21713.2781
[75,] 1045.7806 -13873.9811
[76,] -3752.5759 1045.7806
[77,] -20400.1038 -3752.5759
[78,] -24147.7965 -20400.1038
[79,] -36280.3895 -24147.7965
[80,] -38260.5988 -36280.3895
[81,] 59060.3168 -38260.5988
[82,] -10939.8154 59060.3168
[83,] -5493.8601 -10939.8154
[84,] -17356.9034 -5493.8601
[85,] 2187.0580 -17356.9034
[86,] 33704.7340 2187.0580
[87,] -15138.1856 33704.7340
[88,] -12786.6201 -15138.1856
[89,] -1502.7463 -12786.6201
[90,] -8137.5204 -1502.7463
[91,] -13875.8960 -8137.5204
[92,] 17652.5005 -13875.8960
[93,] 1816.6113 17652.5005
[94,] -20618.9986 1816.6113
[95,] 57833.9144 -20618.9986
[96,] -22143.1207 57833.9144
[97,] -6168.1271 -22143.1207
[98,] 31869.7404 -6168.1271
[99,] 12682.9836 31869.7404
[100,] 3985.8085 12682.9836
[101,] -34898.1656 3985.8085
[102,] 7035.2321 -34898.1656
[103,] -2617.5229 7035.2321
[104,] -2234.9598 -2617.5229
[105,] -2008.6603 -2234.9598
[106,] -18705.1336 -2008.6603
[107,] 10313.8014 -18705.1336
[108,] -3928.1727 10313.8014
[109,] -29122.8057 -3928.1727
[110,] -20905.3661 -29122.8057
[111,] -14917.7695 -20905.3661
[112,] -28327.7918 -14917.7695
[113,] -12351.5065 -28327.7918
[114,] -870.1727 -12351.5065
[115,] -3928.1727 -870.1727
[116,] 23527.1515 -3928.1727
[117,] -32053.4396 23527.1515
[118,] 26284.6421 -32053.4396
[119,] -12969.3890 26284.6421
[120,] 26463.7359 -12969.3890
[121,] -9666.8615 26463.7359
[122,] -7446.1356 -9666.8615
[123,] -22142.5214 -7446.1356
[124,] 8309.4299 -22142.5214
[125,] -5405.6064 8309.4299
[126,] -5925.0568 -5405.6064
[127,] 23377.4904 -5925.0568
[128,] -9192.0696 23377.4904
[129,] 4020.6308 -9192.0696
[130,] 3698.8273 4020.6308
[131,] 15036.3359 3698.8273
[132,] 1591.7624 15036.3359
[133,] -5892.2178 1591.7624
[134,] -4885.5059 -5892.2178
[135,] 6698.1133 -4885.5059
[136,] -3928.1727 6698.1133
[137,] 2108.4981 -3928.1727
[138,] -26149.5775 2108.4981
[139,] 3202.8273 -26149.5775
[140,] 265.8273 3202.8273
[141,] -14144.9820 265.8273
[142,] 7597.1355 -14144.9820
[143,] 3180.3931 7597.1355
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 1780.6565 23535.7359
2 1612.1909 1780.6565
3 -9418.4546 1612.1909
4 39496.0486 -9418.4546
5 34565.0708 39496.0486
6 6184.9241 34565.0708
7 -2482.5942 6184.9241
8 -15083.1803 -2482.5942
9 75650.4955 -15083.1803
10 -12799.6627 75650.4955
11 -7275.6639 -12799.6627
12 1117.6309 -7275.6639
13 20957.5199 1117.6309
14 20819.5903 20957.5199
15 8602.4248 20819.5903
16 -54141.9730 8602.4248
17 -1802.5038 -54141.9730
18 -33512.9866 -1802.5038
19 -48850.9588 -33512.9866
20 -1875.5089 -48850.9588
21 -27996.3490 -1875.5089
22 22232.0144 -27996.3490
23 -2981.2822 22232.0144
24 5355.2148 -2981.2822
25 18044.7568 5355.2148
26 9818.4185 18044.7568
27 -4258.4859 9818.4185
28 61683.3857 -4258.4859
29 47139.3809 61683.3857
30 -4524.9697 47139.3809
31 27423.7965 -4524.9697
32 -3420.8580 27423.7965
33 -13564.9608 -3420.8580
34 36820.2091 -13564.9608
35 -3928.1727 36820.2091
36 21594.6951 -3928.1727
37 -6789.9420 21594.6951
38 -17447.4846 -6789.9420
39 -14535.1386 -17447.4846
40 -921.6099 -14535.1386
41 11138.1176 -921.6099
42 -13941.1613 11138.1176
43 -13434.8526 -13941.1613
44 -24296.6124 -13434.8526
45 19423.2920 -24296.6124
46 -9005.9431 19423.2920
47 25727.1080 -9005.9431
48 14127.1746 25727.1080
49 303.2462 14127.1746
50 -6417.8369 303.2462
51 2369.4808 -6417.8369
52 54812.2733 2369.4808
53 24812.0734 54812.2733
54 7533.5372 24812.0734
55 23613.9209 7533.5372
56 5645.2531 23613.9209
57 -8442.4725 5645.2531
58 -8045.2650 -8442.4725
59 -14170.4686 -8045.2650
60 4456.0800 -14170.4686
61 -6822.9121 4456.0800
62 -11241.5156 -6822.9121
63 -6704.6531 -11241.5156
64 15919.5621 -6704.6531
65 -14077.0166 15919.5621
66 -12483.8143 -14077.0166
67 -14584.8441 -12483.8143
68 -17620.0783 -14584.8441
69 289.6562 -17620.0783
70 37294.7691 289.6562
71 -2242.0588 37294.7691
72 -28098.4884 -2242.0588
73 -21713.2781 -28098.4884
74 -13873.9811 -21713.2781
75 1045.7806 -13873.9811
76 -3752.5759 1045.7806
77 -20400.1038 -3752.5759
78 -24147.7965 -20400.1038
79 -36280.3895 -24147.7965
80 -38260.5988 -36280.3895
81 59060.3168 -38260.5988
82 -10939.8154 59060.3168
83 -5493.8601 -10939.8154
84 -17356.9034 -5493.8601
85 2187.0580 -17356.9034
86 33704.7340 2187.0580
87 -15138.1856 33704.7340
88 -12786.6201 -15138.1856
89 -1502.7463 -12786.6201
90 -8137.5204 -1502.7463
91 -13875.8960 -8137.5204
92 17652.5005 -13875.8960
93 1816.6113 17652.5005
94 -20618.9986 1816.6113
95 57833.9144 -20618.9986
96 -22143.1207 57833.9144
97 -6168.1271 -22143.1207
98 31869.7404 -6168.1271
99 12682.9836 31869.7404
100 3985.8085 12682.9836
101 -34898.1656 3985.8085
102 7035.2321 -34898.1656
103 -2617.5229 7035.2321
104 -2234.9598 -2617.5229
105 -2008.6603 -2234.9598
106 -18705.1336 -2008.6603
107 10313.8014 -18705.1336
108 -3928.1727 10313.8014
109 -29122.8057 -3928.1727
110 -20905.3661 -29122.8057
111 -14917.7695 -20905.3661
112 -28327.7918 -14917.7695
113 -12351.5065 -28327.7918
114 -870.1727 -12351.5065
115 -3928.1727 -870.1727
116 23527.1515 -3928.1727
117 -32053.4396 23527.1515
118 26284.6421 -32053.4396
119 -12969.3890 26284.6421
120 26463.7359 -12969.3890
121 -9666.8615 26463.7359
122 -7446.1356 -9666.8615
123 -22142.5214 -7446.1356
124 8309.4299 -22142.5214
125 -5405.6064 8309.4299
126 -5925.0568 -5405.6064
127 23377.4904 -5925.0568
128 -9192.0696 23377.4904
129 4020.6308 -9192.0696
130 3698.8273 4020.6308
131 15036.3359 3698.8273
132 1591.7624 15036.3359
133 -5892.2178 1591.7624
134 -4885.5059 -5892.2178
135 6698.1133 -4885.5059
136 -3928.1727 6698.1133
137 2108.4981 -3928.1727
138 -26149.5775 2108.4981
139 3202.8273 -26149.5775
140 265.8273 3202.8273
141 -14144.9820 265.8273
142 7597.1355 -14144.9820
143 3180.3931 7597.1355
> 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/7x8pq1322157014.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/8zpv31322157014.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/9qejg1322157014.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/wessaorg/rcomp/tmp/10ee991322157014.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11a7f91322157014.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/12a83y1322157014.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/13ote01322157014.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/14totq1322157014.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/15xjgw1322157014.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/169bz01322157014.tab")
+ }
>
> try(system("convert tmp/140jf1322157014.ps tmp/140jf1322157014.png",intern=TRUE))
character(0)
> try(system("convert tmp/2q0vs1322157014.ps tmp/2q0vs1322157014.png",intern=TRUE))
character(0)
> try(system("convert tmp/3uvy61322157014.ps tmp/3uvy61322157014.png",intern=TRUE))
character(0)
> try(system("convert tmp/4z2st1322157014.ps tmp/4z2st1322157014.png",intern=TRUE))
character(0)
> try(system("convert tmp/5ogpf1322157014.ps tmp/5ogpf1322157014.png",intern=TRUE))
character(0)
> try(system("convert tmp/6c0at1322157014.ps tmp/6c0at1322157014.png",intern=TRUE))
character(0)
> try(system("convert tmp/7x8pq1322157014.ps tmp/7x8pq1322157014.png",intern=TRUE))
character(0)
> try(system("convert tmp/8zpv31322157014.ps tmp/8zpv31322157014.png",intern=TRUE))
character(0)
> try(system("convert tmp/9qejg1322157014.ps tmp/9qejg1322157014.png",intern=TRUE))
character(0)
> try(system("convert tmp/10ee991322157014.ps tmp/10ee991322157014.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
4.951 0.520 5.575