R version 2.15.2 (2012-10-26) -- "Trick or Treat"
Copyright (C) 2012 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i686-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(9144
+ ,5272
+ ,719
+ ,2779
+ ,237
+ ,138
+ ,5456
+ ,2332
+ ,719
+ ,2096
+ ,162
+ ,148
+ ,5057
+ ,2436
+ ,707
+ ,1581
+ ,206
+ ,127
+ ,7779
+ ,4605
+ ,742
+ ,2062
+ ,253
+ ,117
+ ,5858
+ ,2452
+ ,722
+ ,1752
+ ,211
+ ,722
+ ,11493
+ ,5609
+ ,735
+ ,3304
+ ,949
+ ,897
+ ,6848
+ ,3887
+ ,730
+ ,1775
+ ,141
+ ,316
+ ,5772
+ ,3011
+ ,667
+ ,1423
+ ,562
+ ,109
+ ,5251
+ ,2387
+ ,728
+ ,1763
+ ,262
+ ,111
+ ,11232
+ ,7120
+ ,720
+ ,3030
+ ,205
+ ,157
+ ,5908
+ ,2823
+ ,736
+ ,1743
+ ,500
+ ,107
+ ,6812
+ ,3954
+ ,739
+ ,1812
+ ,182
+ ,125
+ ,9962
+ ,5943
+ ,798
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+ ,235
+ ,120
+ ,6155
+ ,2816
+ ,726
+ ,2262
+ ,189
+ ,163
+ ,5673
+ ,2711
+ ,727
+ ,1751
+ ,171
+ ,313
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+ ,4703
+ ,701
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+ ,136
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+ ,691
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+ ,11999
+ ,5540
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+ ,682
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+ ,44
+ ,131
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+ ,643
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+ ,547
+ ,7523
+ ,4362
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+ ,6067
+ ,3484
+ ,622
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+ ,6647
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+ ,6299
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+ ,54
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+ ,683
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+ ,83
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+ ,7241
+ ,2870
+ ,671
+ ,2003
+ ,92
+ ,1604
+ ,9331
+ ,5005
+ ,756
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+ ,81
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+ ,710
+ ,180
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+ ,218
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+ ,4736
+ ,805
+ ,2174
+ ,1090
+ ,168
+ ,5960
+ ,3389
+ ,733
+ ,1572
+ ,114
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+ ,7921
+ ,2868
+ ,857
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+ ,1250
+ ,166
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+ ,7383
+ ,866
+ ,3807
+ ,365
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+ ,3206
+ ,809
+ ,2733
+ ,161
+ ,191
+ ,5145
+ ,2426
+ ,725
+ ,1733
+ ,85
+ ,176)
+ ,dim=c(6
+ ,99)
+ ,dimnames=list(c('TO'
+ ,'DB'
+ ,'DA'
+ ,'BTW'
+ ,'NFO'
+ ,'KO')
+ ,1:99))
> y <- array(NA,dim=c(6,99),dimnames=list(c('TO','DB','DA','BTW','NFO','KO'),1:99))
> 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'
> 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
Attaching package: 'zoo'
The following object(s) are masked from 'package:base':
as.Date, 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
TO DB DA BTW NFO KO
1 9144 5272 719 2779 237 138
2 5456 2332 719 2096 162 148
3 5057 2436 707 1581 206 127
4 7779 4605 742 2062 253 117
5 5858 2452 722 1752 211 722
6 11493 5609 735 3304 949 897
7 6848 3887 730 1775 141 316
8 5772 3011 667 1423 562 109
9 5251 2387 728 1763 262 111
10 11232 7120 720 3030 205 157
11 5908 2823 736 1743 500 107
12 6812 3954 739 1812 182 125
13 9962 5943 798 2866 235 120
14 6155 2816 726 2262 189 163
15 5673 2711 727 1751 171 313
16 7985 4703 701 2261 184 136
17 5780 2633 691 2079 230 146
18 11999 5540 743 3592 1441 682
19 6973 3949 786 2063 44 131
20 5817 3281 643 1624 138 132
21 5844 2792 766 1878 278 131
22 11178 6790 730 3229 304 125
23 5533 2712 739 1896 68 117
24 6870 3979 724 1917 71 179
25 9521 5475 770 3086 45 146
26 5363 2038 740 2350 70 166
27 6031 3268 708 1775 120 160
28 9245 5150 790 2374 765 166
29 5621 2625 725 2048 76 146
30 11802 6146 726 3829 789 312
31 8364 4808 822 2112 64 559
32 6286 3563 742 1691 72 219
33 5071 2014 698 2051 167 141
34 10773 6212 817 3378 305 61
35 5821 2749 768 2106 60 138
36 7794 4694 446 2208 289 157
37 10636 6031 1071 3277 76 182
38 6405 2914 656 2641 41 152
39 5811 3079 896 1582 113 140
40 8981 5397 851 2497 65 170
41 6228 2987 768 2236 70 168
42 11950 5949 713 3969 772 547
43 7523 4362 828 2096 73 164
44 6067 3484 622 1718 93 149
45 4825 1572 747 2123 235 148
46 12162 7402 750 3491 384 134
47 6989 3614 779 2321 63 212
48 8012 4942 857 1995 58 160
49 10893 6538 738 3396 42 179
50 6647 2941 712 2789 55 151
51 5938 3120 782 1772 109 155
52 9005 5415 774 2528 84 204
53 6262 3070 744 2144 134 170
54 12022 6299 786 3547 1068 320
55 7683 4693 710 2089 54 137
56 6004 3369 773 1485 236 140
57 4724 1431 785 1857 502 149
58 10343 4827 683 3237 462 1135
59 6604 1721 717 1740 83 2343
60 7241 2870 671 2003 92 1604
61 9331 5005 756 3271 81 219
62 6418 2869 683 2530 139 197
63 7094 3930 954 1915 107 189
64 10340 6646 740 2611 169 175
65 6814 3220 671 2119 633 171
66 12003 6173 439 4026 1113 252
67 7481 4133 1000 2093 127 129
68 5452 2866 697 1673 67 148
69 6380 2642 665 2097 818 157
70 11425 6530 830 3411 502 153
71 5905 2914 759 1960 104 168
72 8536 4656 830 2401 475 174
73 10785 6098 835 3540 121 191
74 6672 3003 786 2646 43 194
75 7293 3074 710 1932 364 1213
76 9809 4618 844 2795 196 1355
77 5658 2354 801 2083 245 175
78 12364 5709 820 4436 1087 311
79 8078 4356 856 2304 418 144
80 5269 2772 635 1618 84 160
81 7787 2987 704 2535 1376 186
82 11729 6665 794 3614 499 157
83 6236 3377 728 1887 63 182
84 8576 4511 754 2789 335 188
85 11216 6668 827 3351 103 268
86 6814 3075 743 2748 35 213
87 6019 3197 786 1654 200 182
88 9317 4508 801 3119 710 180
89 5419 2292 772 2075 118 162
90 12525 5482 890 4812 1122 218
91 8973 4736 805 2174 1090 168
92 5960 3389 733 1572 114 152
93 7921 2868 857 2781 1250 166
94 12581 7383 866 3807 365 159
95 7180 3761 765 1978 489 187
96 9062 4980 825 2697 369 192
97 13064 6926 790 3757 1399 192
98 7100 3206 809 2733 161 191
99 5145 2426 725 1733 85 176
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) DB DA BTW NFO KO
0.2970 1.0000 0.9992 1.0000 1.0002 1.0001
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-1.1392 -0.8212 0.1295 0.1841 1.9297
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 2.970e-01 6.742e-01 0.441 0.661
DB 1.000e+00 7.472e-05 13383.735 <2e-16 ***
DA 9.992e-01 8.860e-04 1127.822 <2e-16 ***
BTW 1.000e+00 1.699e-04 5886.472 <2e-16 ***
NFO 1.000e+00 2.457e-04 4071.388 <2e-16 ***
KO 1.000e+00 2.201e-04 4543.879 <2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.7161 on 93 degrees of freedom
Multiple R-squared: 1, Adjusted R-squared: 1
F-statistic: 2.068e+08 on 5 and 93 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,] 0.14935381 0.2987076 0.8506462
[2,] 0.26662345 0.5332469 0.7333765
[3,] 0.32230930 0.6446186 0.6776907
[4,] 0.23405231 0.4681046 0.7659477
[5,] 0.17222268 0.3444454 0.8277773
[6,] 0.11443190 0.2288638 0.8855681
[7,] 0.11280933 0.2256187 0.8871907
[8,] 0.07651279 0.1530256 0.9234872
[9,] 0.33460641 0.6692128 0.6653936
[10,] 0.46179859 0.9235972 0.5382014
[11,] 0.41422833 0.8284567 0.5857717
[12,] 0.39758286 0.7951657 0.6024171
[13,] 0.42409879 0.8481976 0.5759012
[14,] 0.34592146 0.6918429 0.6540785
[15,] 0.54422974 0.9115405 0.4557703
[16,] 0.48961985 0.9792397 0.5103801
[17,] 0.49369360 0.9873872 0.5063064
[18,] 0.46768304 0.9353661 0.5323170
[19,] 0.41115878 0.8223176 0.5888412
[20,] 0.35359139 0.7071828 0.6464086
[21,] 0.51800101 0.9639980 0.4819990
[22,] 0.44967047 0.8993409 0.5503295
[23,] 0.41300867 0.8260173 0.5869913
[24,] 0.40679000 0.8135800 0.5932100
[25,] 0.34699825 0.6939965 0.6530018
[26,] 0.28846864 0.5769373 0.7115314
[27,] 0.24331592 0.4866318 0.7566841
[28,] 0.19809718 0.3961944 0.8019028
[29,] 0.17229693 0.3445939 0.8277031
[30,] 0.23355684 0.4671137 0.7664432
[31,] 0.39573476 0.7914695 0.6042652
[32,] 0.53605326 0.9278935 0.4639467
[33,] 0.54885281 0.9022944 0.4511472
[34,] 0.49128966 0.9825793 0.5087103
[35,] 0.43749673 0.8749935 0.5625033
[36,] 0.51872477 0.9625505 0.4812752
[37,] 0.45936577 0.9187315 0.5406342
[38,] 0.50719930 0.9856014 0.4928007
[39,] 0.45293162 0.9058632 0.5470684
[40,] 0.40106338 0.8021268 0.5989366
[41,] 0.34546612 0.6909322 0.6545339
[42,] 0.36773260 0.7354652 0.6322674
[43,] 0.31605351 0.6321070 0.6839465
[44,] 0.26784620 0.5356924 0.7321538
[45,] 0.22240237 0.4448047 0.7775976
[46,] 0.52897811 0.9420438 0.4710219
[47,] 0.47330911 0.9466182 0.5266909
[48,] 0.59070398 0.8185920 0.4092960
[49,] 0.53077782 0.9384444 0.4692222
[50,] 0.60108364 0.7978327 0.3989164
[51,] 0.75024383 0.4995123 0.2497562
[52,] 0.76731723 0.4653655 0.2326828
[53,] 0.80108155 0.3978369 0.1989185
[54,] 0.75738336 0.4852333 0.2426166
[55,] 0.74239748 0.5152050 0.2576025
[56,] 0.74607195 0.5078561 0.2539280
[57,] 0.69319242 0.6136152 0.3068076
[58,] 0.66688065 0.6662387 0.3331193
[59,] 0.63021251 0.7395750 0.3697875
[60,] 0.73993969 0.5201206 0.2600603
[61,] 0.84828439 0.3034312 0.1517156
[62,] 0.88207100 0.2358580 0.1179290
[63,] 0.84903160 0.3019368 0.1509684
[64,] 0.80625082 0.3874984 0.1937492
[65,] 0.75977040 0.4804592 0.2402296
[66,] 0.70030791 0.5993842 0.2996921
[67,] 0.64184416 0.7163117 0.3581558
[68,] 0.63166203 0.7366759 0.3683380
[69,] 0.56319451 0.8736110 0.4368055
[70,] 0.75412476 0.4917505 0.2458752
[71,] 0.68339829 0.6332034 0.3166017
[72,] 0.63224446 0.7355111 0.3677555
[73,] 0.59750841 0.8049832 0.4024916
[74,] 0.53228599 0.9354280 0.4677140
[75,] 0.51486891 0.9702622 0.4851311
[76,] 0.61383970 0.7723206 0.3861603
[77,] 0.59951018 0.8009796 0.4004898
[78,] 0.49195157 0.9839031 0.5080484
[79,] 0.40818012 0.8163602 0.5918199
[80,] 0.61442600 0.7711480 0.3855740
[81,] 0.46652560 0.9330512 0.5334744
[82,] 0.54781299 0.9043740 0.4521870
> postscript(file="/var/wessaorg/rcomp/tmp/1s9se1353159948.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/26l7u1353159948.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/365371353159948.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/4unv11353159948.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/50aou1353159948.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 = 99
Frequency = 1
1 2 3 4 5 6
-0.914561305 -0.864572537 0.136460802 0.129448822 -0.923617896 -1.139163105
7 8 9 10 11 12
-0.867464779 0.042124939 0.138189656 0.072908782 -0.901779047 0.151117263
13 14 15 16 17 18
0.143142541 -0.873715501 0.131382445 0.101520045 1.100031894 0.788107191
19 20 21 22 23 24
0.205004206 -0.906558337 -0.843216330 0.060482979 1.176940928 0.151016828
25 26 27 28 29 30
-0.850393216 -0.839651078 0.139493174 0.051381433 1.156778602 -0.071692580
31 32 33 34 35 36
-0.823414139 -0.830068721 0.121933041 0.132954886 0.191650505 -0.117428083
37 38 39 40 41 42
-0.634891736 1.088132417 1.296637519 1.225993717 -0.818969536 -0.107940748
43 44 45 46 47 48
0.225480381 1.079686528 0.146207226 1.048277381 0.180242758 0.251822029
49 50 51 52 53 54
0.106255448 -0.875818010 0.200558806 0.157617194 0.152603628 1.929728797
55 56 57 58 59 60
0.138787757 1.179315610 0.134457840 -1.107253302 -0.076623339 0.952447736
61 62 63 64 65 66
-0.879892841 0.089503764 -0.677549755 -0.890561791 0.001073373 -0.356638730
67 68 69 70 71 72
-0.645815756 1.147621100 0.966386113 -0.907011765 0.177006196 0.138200031
73 74 75 76 77 78
0.162885502 0.183760690 -0.024679782 1.060038411 0.180880783 0.927232357
79 80 81 82 83 84
0.177196820 0.097084957 -1.128391320 0.057757903 -0.840745872 -0.907982724
85 86 87 88 89 90
-0.844928208 0.146017943 0.186955562 -0.952506626 0.184390301 0.974009198
91 92 93 94 95 96
0.009778839 0.167052148 -0.990693875 1.129153460 0.101810748 -0.858869553
97 98 99
-0.125929376 0.175750540 0.163120822
> postscript(file="/var/wessaorg/rcomp/tmp/6oq511353159948.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 = 99
Frequency = 1
lag(myerror, k = 1) myerror
0 -0.914561305 NA
1 -0.864572537 -0.914561305
2 0.136460802 -0.864572537
3 0.129448822 0.136460802
4 -0.923617896 0.129448822
5 -1.139163105 -0.923617896
6 -0.867464779 -1.139163105
7 0.042124939 -0.867464779
8 0.138189656 0.042124939
9 0.072908782 0.138189656
10 -0.901779047 0.072908782
11 0.151117263 -0.901779047
12 0.143142541 0.151117263
13 -0.873715501 0.143142541
14 0.131382445 -0.873715501
15 0.101520045 0.131382445
16 1.100031894 0.101520045
17 0.788107191 1.100031894
18 0.205004206 0.788107191
19 -0.906558337 0.205004206
20 -0.843216330 -0.906558337
21 0.060482979 -0.843216330
22 1.176940928 0.060482979
23 0.151016828 1.176940928
24 -0.850393216 0.151016828
25 -0.839651078 -0.850393216
26 0.139493174 -0.839651078
27 0.051381433 0.139493174
28 1.156778602 0.051381433
29 -0.071692580 1.156778602
30 -0.823414139 -0.071692580
31 -0.830068721 -0.823414139
32 0.121933041 -0.830068721
33 0.132954886 0.121933041
34 0.191650505 0.132954886
35 -0.117428083 0.191650505
36 -0.634891736 -0.117428083
37 1.088132417 -0.634891736
38 1.296637519 1.088132417
39 1.225993717 1.296637519
40 -0.818969536 1.225993717
41 -0.107940748 -0.818969536
42 0.225480381 -0.107940748
43 1.079686528 0.225480381
44 0.146207226 1.079686528
45 1.048277381 0.146207226
46 0.180242758 1.048277381
47 0.251822029 0.180242758
48 0.106255448 0.251822029
49 -0.875818010 0.106255448
50 0.200558806 -0.875818010
51 0.157617194 0.200558806
52 0.152603628 0.157617194
53 1.929728797 0.152603628
54 0.138787757 1.929728797
55 1.179315610 0.138787757
56 0.134457840 1.179315610
57 -1.107253302 0.134457840
58 -0.076623339 -1.107253302
59 0.952447736 -0.076623339
60 -0.879892841 0.952447736
61 0.089503764 -0.879892841
62 -0.677549755 0.089503764
63 -0.890561791 -0.677549755
64 0.001073373 -0.890561791
65 -0.356638730 0.001073373
66 -0.645815756 -0.356638730
67 1.147621100 -0.645815756
68 0.966386113 1.147621100
69 -0.907011765 0.966386113
70 0.177006196 -0.907011765
71 0.138200031 0.177006196
72 0.162885502 0.138200031
73 0.183760690 0.162885502
74 -0.024679782 0.183760690
75 1.060038411 -0.024679782
76 0.180880783 1.060038411
77 0.927232357 0.180880783
78 0.177196820 0.927232357
79 0.097084957 0.177196820
80 -1.128391320 0.097084957
81 0.057757903 -1.128391320
82 -0.840745872 0.057757903
83 -0.907982724 -0.840745872
84 -0.844928208 -0.907982724
85 0.146017943 -0.844928208
86 0.186955562 0.146017943
87 -0.952506626 0.186955562
88 0.184390301 -0.952506626
89 0.974009198 0.184390301
90 0.009778839 0.974009198
91 0.167052148 0.009778839
92 -0.990693875 0.167052148
93 1.129153460 -0.990693875
94 0.101810748 1.129153460
95 -0.858869553 0.101810748
96 -0.125929376 -0.858869553
97 0.175750540 -0.125929376
98 0.163120822 0.175750540
99 NA 0.163120822
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -0.864572537 -0.914561305
[2,] 0.136460802 -0.864572537
[3,] 0.129448822 0.136460802
[4,] -0.923617896 0.129448822
[5,] -1.139163105 -0.923617896
[6,] -0.867464779 -1.139163105
[7,] 0.042124939 -0.867464779
[8,] 0.138189656 0.042124939
[9,] 0.072908782 0.138189656
[10,] -0.901779047 0.072908782
[11,] 0.151117263 -0.901779047
[12,] 0.143142541 0.151117263
[13,] -0.873715501 0.143142541
[14,] 0.131382445 -0.873715501
[15,] 0.101520045 0.131382445
[16,] 1.100031894 0.101520045
[17,] 0.788107191 1.100031894
[18,] 0.205004206 0.788107191
[19,] -0.906558337 0.205004206
[20,] -0.843216330 -0.906558337
[21,] 0.060482979 -0.843216330
[22,] 1.176940928 0.060482979
[23,] 0.151016828 1.176940928
[24,] -0.850393216 0.151016828
[25,] -0.839651078 -0.850393216
[26,] 0.139493174 -0.839651078
[27,] 0.051381433 0.139493174
[28,] 1.156778602 0.051381433
[29,] -0.071692580 1.156778602
[30,] -0.823414139 -0.071692580
[31,] -0.830068721 -0.823414139
[32,] 0.121933041 -0.830068721
[33,] 0.132954886 0.121933041
[34,] 0.191650505 0.132954886
[35,] -0.117428083 0.191650505
[36,] -0.634891736 -0.117428083
[37,] 1.088132417 -0.634891736
[38,] 1.296637519 1.088132417
[39,] 1.225993717 1.296637519
[40,] -0.818969536 1.225993717
[41,] -0.107940748 -0.818969536
[42,] 0.225480381 -0.107940748
[43,] 1.079686528 0.225480381
[44,] 0.146207226 1.079686528
[45,] 1.048277381 0.146207226
[46,] 0.180242758 1.048277381
[47,] 0.251822029 0.180242758
[48,] 0.106255448 0.251822029
[49,] -0.875818010 0.106255448
[50,] 0.200558806 -0.875818010
[51,] 0.157617194 0.200558806
[52,] 0.152603628 0.157617194
[53,] 1.929728797 0.152603628
[54,] 0.138787757 1.929728797
[55,] 1.179315610 0.138787757
[56,] 0.134457840 1.179315610
[57,] -1.107253302 0.134457840
[58,] -0.076623339 -1.107253302
[59,] 0.952447736 -0.076623339
[60,] -0.879892841 0.952447736
[61,] 0.089503764 -0.879892841
[62,] -0.677549755 0.089503764
[63,] -0.890561791 -0.677549755
[64,] 0.001073373 -0.890561791
[65,] -0.356638730 0.001073373
[66,] -0.645815756 -0.356638730
[67,] 1.147621100 -0.645815756
[68,] 0.966386113 1.147621100
[69,] -0.907011765 0.966386113
[70,] 0.177006196 -0.907011765
[71,] 0.138200031 0.177006196
[72,] 0.162885502 0.138200031
[73,] 0.183760690 0.162885502
[74,] -0.024679782 0.183760690
[75,] 1.060038411 -0.024679782
[76,] 0.180880783 1.060038411
[77,] 0.927232357 0.180880783
[78,] 0.177196820 0.927232357
[79,] 0.097084957 0.177196820
[80,] -1.128391320 0.097084957
[81,] 0.057757903 -1.128391320
[82,] -0.840745872 0.057757903
[83,] -0.907982724 -0.840745872
[84,] -0.844928208 -0.907982724
[85,] 0.146017943 -0.844928208
[86,] 0.186955562 0.146017943
[87,] -0.952506626 0.186955562
[88,] 0.184390301 -0.952506626
[89,] 0.974009198 0.184390301
[90,] 0.009778839 0.974009198
[91,] 0.167052148 0.009778839
[92,] -0.990693875 0.167052148
[93,] 1.129153460 -0.990693875
[94,] 0.101810748 1.129153460
[95,] -0.858869553 0.101810748
[96,] -0.125929376 -0.858869553
[97,] 0.175750540 -0.125929376
[98,] 0.163120822 0.175750540
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -0.864572537 -0.914561305
2 0.136460802 -0.864572537
3 0.129448822 0.136460802
4 -0.923617896 0.129448822
5 -1.139163105 -0.923617896
6 -0.867464779 -1.139163105
7 0.042124939 -0.867464779
8 0.138189656 0.042124939
9 0.072908782 0.138189656
10 -0.901779047 0.072908782
11 0.151117263 -0.901779047
12 0.143142541 0.151117263
13 -0.873715501 0.143142541
14 0.131382445 -0.873715501
15 0.101520045 0.131382445
16 1.100031894 0.101520045
17 0.788107191 1.100031894
18 0.205004206 0.788107191
19 -0.906558337 0.205004206
20 -0.843216330 -0.906558337
21 0.060482979 -0.843216330
22 1.176940928 0.060482979
23 0.151016828 1.176940928
24 -0.850393216 0.151016828
25 -0.839651078 -0.850393216
26 0.139493174 -0.839651078
27 0.051381433 0.139493174
28 1.156778602 0.051381433
29 -0.071692580 1.156778602
30 -0.823414139 -0.071692580
31 -0.830068721 -0.823414139
32 0.121933041 -0.830068721
33 0.132954886 0.121933041
34 0.191650505 0.132954886
35 -0.117428083 0.191650505
36 -0.634891736 -0.117428083
37 1.088132417 -0.634891736
38 1.296637519 1.088132417
39 1.225993717 1.296637519
40 -0.818969536 1.225993717
41 -0.107940748 -0.818969536
42 0.225480381 -0.107940748
43 1.079686528 0.225480381
44 0.146207226 1.079686528
45 1.048277381 0.146207226
46 0.180242758 1.048277381
47 0.251822029 0.180242758
48 0.106255448 0.251822029
49 -0.875818010 0.106255448
50 0.200558806 -0.875818010
51 0.157617194 0.200558806
52 0.152603628 0.157617194
53 1.929728797 0.152603628
54 0.138787757 1.929728797
55 1.179315610 0.138787757
56 0.134457840 1.179315610
57 -1.107253302 0.134457840
58 -0.076623339 -1.107253302
59 0.952447736 -0.076623339
60 -0.879892841 0.952447736
61 0.089503764 -0.879892841
62 -0.677549755 0.089503764
63 -0.890561791 -0.677549755
64 0.001073373 -0.890561791
65 -0.356638730 0.001073373
66 -0.645815756 -0.356638730
67 1.147621100 -0.645815756
68 0.966386113 1.147621100
69 -0.907011765 0.966386113
70 0.177006196 -0.907011765
71 0.138200031 0.177006196
72 0.162885502 0.138200031
73 0.183760690 0.162885502
74 -0.024679782 0.183760690
75 1.060038411 -0.024679782
76 0.180880783 1.060038411
77 0.927232357 0.180880783
78 0.177196820 0.927232357
79 0.097084957 0.177196820
80 -1.128391320 0.097084957
81 0.057757903 -1.128391320
82 -0.840745872 0.057757903
83 -0.907982724 -0.840745872
84 -0.844928208 -0.907982724
85 0.146017943 -0.844928208
86 0.186955562 0.146017943
87 -0.952506626 0.186955562
88 0.184390301 -0.952506626
89 0.974009198 0.184390301
90 0.009778839 0.974009198
91 0.167052148 0.009778839
92 -0.990693875 0.167052148
93 1.129153460 -0.990693875
94 0.101810748 1.129153460
95 -0.858869553 0.101810748
96 -0.125929376 -0.858869553
97 0.175750540 -0.125929376
98 0.163120822 0.175750540
> 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/7b0in1353159948.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/8nfsh1353159948.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/925bc1353159948.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/wessaorg/rcomp/tmp/10i26t1353159948.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/111ijg1353159948.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/126orv1353159948.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/13uyq01353159948.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/14qj3f1353159948.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/15qggf1353159948.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/16yiqm1353159948.tab")
+ }
>
> try(system("convert tmp/1s9se1353159948.ps tmp/1s9se1353159948.png",intern=TRUE))
character(0)
> try(system("convert tmp/26l7u1353159948.ps tmp/26l7u1353159948.png",intern=TRUE))
character(0)
> try(system("convert tmp/365371353159948.ps tmp/365371353159948.png",intern=TRUE))
character(0)
> try(system("convert tmp/4unv11353159948.ps tmp/4unv11353159948.png",intern=TRUE))
character(0)
> try(system("convert tmp/50aou1353159948.ps tmp/50aou1353159948.png",intern=TRUE))
character(0)
> try(system("convert tmp/6oq511353159948.ps tmp/6oq511353159948.png",intern=TRUE))
character(0)
> try(system("convert tmp/7b0in1353159948.ps tmp/7b0in1353159948.png",intern=TRUE))
character(0)
> try(system("convert tmp/8nfsh1353159948.ps tmp/8nfsh1353159948.png",intern=TRUE))
character(0)
> try(system("convert tmp/925bc1353159948.ps tmp/925bc1353159948.png",intern=TRUE))
character(0)
> try(system("convert tmp/10i26t1353159948.ps tmp/10i26t1353159948.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
7.523 0.998 8.583