R version 2.9.0 (2009-04-17)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
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(209465
+ ,555332
+ ,213587
+ ,216234
+ ,204045
+ ,543599
+ ,209465
+ ,213587
+ ,200237
+ ,536662
+ ,204045
+ ,209465
+ ,203666
+ ,542722
+ ,200237
+ ,204045
+ ,241476
+ ,593530
+ ,203666
+ ,200237
+ ,260307
+ ,610763
+ ,241476
+ ,203666
+ ,243324
+ ,612613
+ ,260307
+ ,241476
+ ,244460
+ ,611324
+ ,243324
+ ,260307
+ ,233575
+ ,594167
+ ,244460
+ ,243324
+ ,237217
+ ,595454
+ ,233575
+ ,244460
+ ,235243
+ ,590865
+ ,237217
+ ,233575
+ ,230354
+ ,589379
+ ,235243
+ ,237217
+ ,227184
+ ,584428
+ ,230354
+ ,235243
+ ,221678
+ ,573100
+ ,227184
+ ,230354
+ ,217142
+ ,567456
+ ,221678
+ ,227184
+ ,219452
+ ,569028
+ ,217142
+ ,221678
+ ,256446
+ ,620735
+ ,219452
+ ,217142
+ ,265845
+ ,628884
+ ,256446
+ ,219452
+ ,248624
+ ,628232
+ ,265845
+ ,256446
+ ,241114
+ ,612117
+ ,248624
+ ,265845
+ ,229245
+ ,595404
+ ,241114
+ ,248624
+ ,231805
+ ,597141
+ ,229245
+ ,241114
+ ,219277
+ ,593408
+ ,231805
+ ,229245
+ ,219313
+ ,590072
+ ,219277
+ ,231805
+ ,212610
+ ,579799
+ ,219313
+ ,219277
+ ,214771
+ ,574205
+ ,212610
+ ,219313
+ ,211142
+ ,572775
+ ,214771
+ ,212610
+ ,211457
+ ,572942
+ ,211142
+ ,214771
+ ,240048
+ ,619567
+ ,211457
+ ,211142
+ ,240636
+ ,625809
+ ,240048
+ ,211457
+ ,230580
+ ,619916
+ ,240636
+ ,240048
+ ,208795
+ ,587625
+ ,230580
+ ,240636
+ ,197922
+ ,565742
+ ,208795
+ ,230580
+ ,194596
+ ,557274
+ ,197922
+ ,208795
+ ,194581
+ ,560576
+ ,194596
+ ,197922
+ ,185686
+ ,548854
+ ,194581
+ ,194596
+ ,178106
+ ,531673
+ ,185686
+ ,194581
+ ,172608
+ ,525919
+ ,178106
+ ,185686
+ ,167302
+ ,511038
+ ,172608
+ ,178106
+ ,168053
+ ,498662
+ ,167302
+ ,172608
+ ,202300
+ ,555362
+ ,168053
+ ,167302
+ ,202388
+ ,564591
+ ,202300
+ ,168053
+ ,182516
+ ,541657
+ ,202388
+ ,202300
+ ,173476
+ ,527070
+ ,182516
+ ,202388
+ ,166444
+ ,509846
+ ,173476
+ ,182516
+ ,171297
+ ,514258
+ ,166444
+ ,173476
+ ,169701
+ ,516922
+ ,171297
+ ,166444
+ ,164182
+ ,507561
+ ,169701
+ ,171297
+ ,161914
+ ,492622
+ ,164182
+ ,169701
+ ,159612
+ ,490243
+ ,161914
+ ,164182
+ ,151001
+ ,469357
+ ,159612
+ ,161914
+ ,158114
+ ,477580
+ ,151001
+ ,159612
+ ,186530
+ ,528379
+ ,158114
+ ,151001
+ ,187069
+ ,533590
+ ,186530
+ ,158114
+ ,174330
+ ,517945
+ ,187069
+ ,186530
+ ,169362
+ ,506174
+ ,174330
+ ,187069
+ ,166827
+ ,501866
+ ,169362
+ ,174330
+ ,178037
+ ,516141
+ ,166827
+ ,169362
+ ,186412
+ ,528222
+ ,178037
+ ,166827
+ ,189226
+ ,532638
+ ,186412
+ ,178037
+ ,191563
+ ,536322
+ ,189226
+ ,186412
+ ,188906
+ ,536535
+ ,191563
+ ,189226
+ ,186005
+ ,523597
+ ,188906
+ ,191563
+ ,195309
+ ,536214
+ ,186005
+ ,188906
+ ,223532
+ ,586570
+ ,195309
+ ,186005
+ ,226899
+ ,596594
+ ,223532
+ ,195309
+ ,214126
+ ,580523
+ ,226899
+ ,223532)
+ ,dim=c(4
+ ,67)
+ ,dimnames=list(c('Werkl'
+ ,'x'
+ ,'y-1'
+ ,'y-2')
+ ,1:67))
> y <- array(NA,dim=c(4,67),dimnames=list(c('Werkl','x','y-1','y-2'),1:67))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par3 = 'Linear Trend'
> par2 = 'Include Monthly Dummies'
> par1 = '1'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: Write here your technical program description (don't use hard returns!)
> library(lattice)
> library(lmtest)
Loading required package: zoo
Attaching package: 'zoo'
The following object(s) are masked from package:base :
as.Date.numeric
> n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
> par1 <- as.numeric(par1)
> x <- t(y)
> k <- length(x[1,])
> n <- length(x[,1])
> x1 <- cbind(x[,par1], x[,1:k!=par1])
> mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
> colnames(x1) <- mycolnames #colnames(x)[par1]
> x <- x1
> if (par3 == 'First Differences'){
+ x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
+ for (i in 1:n-1) {
+ for (j in 1:k) {
+ x2[i,j] <- x[i+1,j] - x[i,j]
+ }
+ }
+ x <- x2
+ }
> if (par2 == 'Include Monthly Dummies'){
+ x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
+ for (i in 1:11){
+ x2[seq(i,n,12),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> if (par2 == 'Include Quarterly Dummies'){
+ x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
+ for (i in 1:3){
+ x2[seq(i,n,4),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> k <- length(x[1,])
> if (par3 == 'Linear Trend'){
+ x <- cbind(x, c(1:n))
+ colnames(x)[k+1] <- 't'
+ }
> x
Werkl x y-1 y-2 M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 209465 555332 213587 216234 1 0 0 0 0 0 0 0 0 0 0 1
2 204045 543599 209465 213587 0 1 0 0 0 0 0 0 0 0 0 2
3 200237 536662 204045 209465 0 0 1 0 0 0 0 0 0 0 0 3
4 203666 542722 200237 204045 0 0 0 1 0 0 0 0 0 0 0 4
5 241476 593530 203666 200237 0 0 0 0 1 0 0 0 0 0 0 5
6 260307 610763 241476 203666 0 0 0 0 0 1 0 0 0 0 0 6
7 243324 612613 260307 241476 0 0 0 0 0 0 1 0 0 0 0 7
8 244460 611324 243324 260307 0 0 0 0 0 0 0 1 0 0 0 8
9 233575 594167 244460 243324 0 0 0 0 0 0 0 0 1 0 0 9
10 237217 595454 233575 244460 0 0 0 0 0 0 0 0 0 1 0 10
11 235243 590865 237217 233575 0 0 0 0 0 0 0 0 0 0 1 11
12 230354 589379 235243 237217 0 0 0 0 0 0 0 0 0 0 0 12
13 227184 584428 230354 235243 1 0 0 0 0 0 0 0 0 0 0 13
14 221678 573100 227184 230354 0 1 0 0 0 0 0 0 0 0 0 14
15 217142 567456 221678 227184 0 0 1 0 0 0 0 0 0 0 0 15
16 219452 569028 217142 221678 0 0 0 1 0 0 0 0 0 0 0 16
17 256446 620735 219452 217142 0 0 0 0 1 0 0 0 0 0 0 17
18 265845 628884 256446 219452 0 0 0 0 0 1 0 0 0 0 0 18
19 248624 628232 265845 256446 0 0 0 0 0 0 1 0 0 0 0 19
20 241114 612117 248624 265845 0 0 0 0 0 0 0 1 0 0 0 20
21 229245 595404 241114 248624 0 0 0 0 0 0 0 0 1 0 0 21
22 231805 597141 229245 241114 0 0 0 0 0 0 0 0 0 1 0 22
23 219277 593408 231805 229245 0 0 0 0 0 0 0 0 0 0 1 23
24 219313 590072 219277 231805 0 0 0 0 0 0 0 0 0 0 0 24
25 212610 579799 219313 219277 1 0 0 0 0 0 0 0 0 0 0 25
26 214771 574205 212610 219313 0 1 0 0 0 0 0 0 0 0 0 26
27 211142 572775 214771 212610 0 0 1 0 0 0 0 0 0 0 0 27
28 211457 572942 211142 214771 0 0 0 1 0 0 0 0 0 0 0 28
29 240048 619567 211457 211142 0 0 0 0 1 0 0 0 0 0 0 29
30 240636 625809 240048 211457 0 0 0 0 0 1 0 0 0 0 0 30
31 230580 619916 240636 240048 0 0 0 0 0 0 1 0 0 0 0 31
32 208795 587625 230580 240636 0 0 0 0 0 0 0 1 0 0 0 32
33 197922 565742 208795 230580 0 0 0 0 0 0 0 0 1 0 0 33
34 194596 557274 197922 208795 0 0 0 0 0 0 0 0 0 1 0 34
35 194581 560576 194596 197922 0 0 0 0 0 0 0 0 0 0 1 35
36 185686 548854 194581 194596 0 0 0 0 0 0 0 0 0 0 0 36
37 178106 531673 185686 194581 1 0 0 0 0 0 0 0 0 0 0 37
38 172608 525919 178106 185686 0 1 0 0 0 0 0 0 0 0 0 38
39 167302 511038 172608 178106 0 0 1 0 0 0 0 0 0 0 0 39
40 168053 498662 167302 172608 0 0 0 1 0 0 0 0 0 0 0 40
41 202300 555362 168053 167302 0 0 0 0 1 0 0 0 0 0 0 41
42 202388 564591 202300 168053 0 0 0 0 0 1 0 0 0 0 0 42
43 182516 541657 202388 202300 0 0 0 0 0 0 1 0 0 0 0 43
44 173476 527070 182516 202388 0 0 0 0 0 0 0 1 0 0 0 44
45 166444 509846 173476 182516 0 0 0 0 0 0 0 0 1 0 0 45
46 171297 514258 166444 173476 0 0 0 0 0 0 0 0 0 1 0 46
47 169701 516922 171297 166444 0 0 0 0 0 0 0 0 0 0 1 47
48 164182 507561 169701 171297 0 0 0 0 0 0 0 0 0 0 0 48
49 161914 492622 164182 169701 1 0 0 0 0 0 0 0 0 0 0 49
50 159612 490243 161914 164182 0 1 0 0 0 0 0 0 0 0 0 50
51 151001 469357 159612 161914 0 0 1 0 0 0 0 0 0 0 0 51
52 158114 477580 151001 159612 0 0 0 1 0 0 0 0 0 0 0 52
53 186530 528379 158114 151001 0 0 0 0 1 0 0 0 0 0 0 53
54 187069 533590 186530 158114 0 0 0 0 0 1 0 0 0 0 0 54
55 174330 517945 187069 186530 0 0 0 0 0 0 1 0 0 0 0 55
56 169362 506174 174330 187069 0 0 0 0 0 0 0 1 0 0 0 56
57 166827 501866 169362 174330 0 0 0 0 0 0 0 0 1 0 0 57
58 178037 516141 166827 169362 0 0 0 0 0 0 0 0 0 1 0 58
59 186412 528222 178037 166827 0 0 0 0 0 0 0 0 0 0 1 59
60 189226 532638 186412 178037 0 0 0 0 0 0 0 0 0 0 0 60
61 191563 536322 189226 186412 1 0 0 0 0 0 0 0 0 0 0 61
62 188906 536535 191563 189226 0 1 0 0 0 0 0 0 0 0 0 62
63 186005 523597 188906 191563 0 0 1 0 0 0 0 0 0 0 0 63
64 195309 536214 186005 188906 0 0 0 1 0 0 0 0 0 0 0 64
65 223532 586570 195309 186005 0 0 0 0 1 0 0 0 0 0 0 65
66 226899 596594 223532 195309 0 0 0 0 0 1 0 0 0 0 0 66
67 214126 580523 226899 223532 0 0 0 0 0 0 1 0 0 0 0 67
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) x `y-1` `y-2` M1 M2
-3.791e+04 1.679e-01 9.837e-01 -2.621e-01 8.562e+02 1.422e+03
M3 M4 M5 M6 M7 M8
6.456e+02 7.996e+03 2.677e+04 -1.099e+02 -1.023e+04 -1.533e+02
M9 M10 M11 t
-1.876e+03 7.809e+03 -1.116e+00 -5.474e+01
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-13802 -2754 -141 3118 11949
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -3.791e+04 2.460e+04 -1.541 0.12949
x 1.679e-01 9.346e-02 1.797 0.07831 .
`y-1` 9.837e-01 1.552e-01 6.339 6.02e-08 ***
`y-2` -2.621e-01 1.500e-01 -1.748 0.08651 .
M1 8.562e+02 3.092e+03 0.277 0.78294
M2 1.422e+03 3.124e+03 0.455 0.65078
M3 6.456e+02 3.282e+03 0.197 0.84481
M4 7.996e+03 3.116e+03 2.566 0.01326 *
M5 2.677e+04 5.381e+03 4.976 7.78e-06 ***
M6 -1.099e+02 5.996e+03 -0.018 0.98544
M7 -1.023e+04 3.436e+03 -2.976 0.00445 **
M8 -1.533e+02 4.000e+03 -0.038 0.96958
M9 -1.876e+03 3.545e+03 -0.529 0.59895
M10 7.809e+03 3.303e+03 2.364 0.02190 *
M11 -1.116e+00 3.288e+03 -0.000339 0.99973
t -5.474e+01 5.502e+01 -0.995 0.32452
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 4997 on 51 degrees of freedom
Multiple R-squared: 0.977, Adjusted R-squared: 0.9702
F-statistic: 144.5 on 15 and 51 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,] 0.01830029 0.0366005734 0.9816997133
[2,] 0.01807828 0.0361565567 0.9819217216
[3,] 0.00626334 0.0125266795 0.9937366603
[4,] 0.00660126 0.0132025202 0.9933987399
[5,] 0.17377174 0.3475434740 0.8262282630
[6,] 0.18147055 0.3629411003 0.8185294499
[7,] 0.16111988 0.3222397531 0.8388801234
[8,] 0.51340214 0.9731957231 0.4865978616
[9,] 0.44979118 0.8995823603 0.5502088198
[10,] 0.35767384 0.7153476721 0.6423261639
[11,] 0.59611523 0.8077695384 0.4038847692
[12,] 0.96124738 0.0775052420 0.0387526210
[13,] 0.98273119 0.0345376135 0.0172688068
[14,] 0.97109955 0.0578009092 0.0289004546
[15,] 0.98756070 0.0248786045 0.0124393022
[16,] 0.98894913 0.0221017446 0.0110508723
[17,] 0.99550683 0.0089863380 0.0044931690
[18,] 0.99214927 0.0157014635 0.0078507317
[19,] 0.99135716 0.0172856791 0.0086428396
[20,] 0.98353140 0.0329372074 0.0164686037
[21,] 0.99157575 0.0168484929 0.0084242464
[22,] 0.99679438 0.0064112429 0.0032056214
[23,] 0.99964069 0.0007186131 0.0003593066
[24,] 0.99894598 0.0021080397 0.0010540198
[25,] 0.99682094 0.0063581217 0.0031790609
[26,] 0.99155936 0.0168812706 0.0084406353
[27,] 0.98935398 0.0212920330 0.0106460165
[28,] 0.99463604 0.0107279264 0.0053639632
[29,] 0.98195061 0.0360987850 0.0180493925
[30,] 0.99857916 0.0028416717 0.0014208359
> postscript(file="/var/www/html/rcomp/tmp/1kxek1259925883.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
> points(x[,1]-mysum$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2k7ve1259925883.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/36w6z1259925883.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4prnq1259925883.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5sfpo1259925883.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
> qqline(mysum$resid)
> grid()
> dev.off()
null device
1
> (myerror <- as.ts(mysum$resid))
Time Series:
Start = 1
End = 67
Frequency = 1
1 2 3 4 5 6
-96.2286 -696.4670 1742.9236 -816.1947 5367.5098 11948.8038
7 8 9 10 11 12
-3786.1363 9190.2675 -2605.5376 2195.3704 2420.7815 731.4457
13 14 15 16 17 18
1883.1375 -395.2960 1433.1238 -797.7770 5328.8817 4512.9392
19 20 21 22 23 24
-1975.5778 2606.0760 -1805.6707 539.1875 -9126.7303 4517.8463
25 26 27 28 29 30
-4581.0628 4611.0508 -1829.2524 -4701.6261 -3924.3638 -5488.0760
31 32 33 34 35 36
2533.0603 -13801.8290 -428.9978 -6978.2634 738.5906 -6991.5226
37 38 39 40 41 42
-3741.9481 -3660.4161 -2214.7968 -2902.9835 969.9722 -7044.7948
43 44 45 46 47 48
-4003.6082 -1041.5300 279.6550 -690.8677 -1486.6306 -2537.9694
49 50 51 52 53 54
1911.7399 282.1368 -2320.2813 3983.4038 -4108.3481 -3593.7780
55 56 57 58 59 60
3384.2590 3047.0154 4560.5511 4934.5732 7453.9887 4280.2000
61 62 63 64 65 66
4624.3621 -141.0085 3188.2832 5235.1774 -3633.6517 -335.0942
67
3848.0029
> postscript(file="/var/www/html/rcomp/tmp/6yldu1259925883.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> dum <- cbind(lag(myerror,k=1),myerror)
> dum
Time Series:
Start = 0
End = 67
Frequency = 1
lag(myerror, k = 1) myerror
0 -96.2286 NA
1 -696.4670 -96.2286
2 1742.9236 -696.4670
3 -816.1947 1742.9236
4 5367.5098 -816.1947
5 11948.8038 5367.5098
6 -3786.1363 11948.8038
7 9190.2675 -3786.1363
8 -2605.5376 9190.2675
9 2195.3704 -2605.5376
10 2420.7815 2195.3704
11 731.4457 2420.7815
12 1883.1375 731.4457
13 -395.2960 1883.1375
14 1433.1238 -395.2960
15 -797.7770 1433.1238
16 5328.8817 -797.7770
17 4512.9392 5328.8817
18 -1975.5778 4512.9392
19 2606.0760 -1975.5778
20 -1805.6707 2606.0760
21 539.1875 -1805.6707
22 -9126.7303 539.1875
23 4517.8463 -9126.7303
24 -4581.0628 4517.8463
25 4611.0508 -4581.0628
26 -1829.2524 4611.0508
27 -4701.6261 -1829.2524
28 -3924.3638 -4701.6261
29 -5488.0760 -3924.3638
30 2533.0603 -5488.0760
31 -13801.8290 2533.0603
32 -428.9978 -13801.8290
33 -6978.2634 -428.9978
34 738.5906 -6978.2634
35 -6991.5226 738.5906
36 -3741.9481 -6991.5226
37 -3660.4161 -3741.9481
38 -2214.7968 -3660.4161
39 -2902.9835 -2214.7968
40 969.9722 -2902.9835
41 -7044.7948 969.9722
42 -4003.6082 -7044.7948
43 -1041.5300 -4003.6082
44 279.6550 -1041.5300
45 -690.8677 279.6550
46 -1486.6306 -690.8677
47 -2537.9694 -1486.6306
48 1911.7399 -2537.9694
49 282.1368 1911.7399
50 -2320.2813 282.1368
51 3983.4038 -2320.2813
52 -4108.3481 3983.4038
53 -3593.7780 -4108.3481
54 3384.2590 -3593.7780
55 3047.0154 3384.2590
56 4560.5511 3047.0154
57 4934.5732 4560.5511
58 7453.9887 4934.5732
59 4280.2000 7453.9887
60 4624.3621 4280.2000
61 -141.0085 4624.3621
62 3188.2832 -141.0085
63 5235.1774 3188.2832
64 -3633.6517 5235.1774
65 -335.0942 -3633.6517
66 3848.0029 -335.0942
67 NA 3848.0029
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -696.4670 -96.2286
[2,] 1742.9236 -696.4670
[3,] -816.1947 1742.9236
[4,] 5367.5098 -816.1947
[5,] 11948.8038 5367.5098
[6,] -3786.1363 11948.8038
[7,] 9190.2675 -3786.1363
[8,] -2605.5376 9190.2675
[9,] 2195.3704 -2605.5376
[10,] 2420.7815 2195.3704
[11,] 731.4457 2420.7815
[12,] 1883.1375 731.4457
[13,] -395.2960 1883.1375
[14,] 1433.1238 -395.2960
[15,] -797.7770 1433.1238
[16,] 5328.8817 -797.7770
[17,] 4512.9392 5328.8817
[18,] -1975.5778 4512.9392
[19,] 2606.0760 -1975.5778
[20,] -1805.6707 2606.0760
[21,] 539.1875 -1805.6707
[22,] -9126.7303 539.1875
[23,] 4517.8463 -9126.7303
[24,] -4581.0628 4517.8463
[25,] 4611.0508 -4581.0628
[26,] -1829.2524 4611.0508
[27,] -4701.6261 -1829.2524
[28,] -3924.3638 -4701.6261
[29,] -5488.0760 -3924.3638
[30,] 2533.0603 -5488.0760
[31,] -13801.8290 2533.0603
[32,] -428.9978 -13801.8290
[33,] -6978.2634 -428.9978
[34,] 738.5906 -6978.2634
[35,] -6991.5226 738.5906
[36,] -3741.9481 -6991.5226
[37,] -3660.4161 -3741.9481
[38,] -2214.7968 -3660.4161
[39,] -2902.9835 -2214.7968
[40,] 969.9722 -2902.9835
[41,] -7044.7948 969.9722
[42,] -4003.6082 -7044.7948
[43,] -1041.5300 -4003.6082
[44,] 279.6550 -1041.5300
[45,] -690.8677 279.6550
[46,] -1486.6306 -690.8677
[47,] -2537.9694 -1486.6306
[48,] 1911.7399 -2537.9694
[49,] 282.1368 1911.7399
[50,] -2320.2813 282.1368
[51,] 3983.4038 -2320.2813
[52,] -4108.3481 3983.4038
[53,] -3593.7780 -4108.3481
[54,] 3384.2590 -3593.7780
[55,] 3047.0154 3384.2590
[56,] 4560.5511 3047.0154
[57,] 4934.5732 4560.5511
[58,] 7453.9887 4934.5732
[59,] 4280.2000 7453.9887
[60,] 4624.3621 4280.2000
[61,] -141.0085 4624.3621
[62,] 3188.2832 -141.0085
[63,] 5235.1774 3188.2832
[64,] -3633.6517 5235.1774
[65,] -335.0942 -3633.6517
[66,] 3848.0029 -335.0942
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -696.4670 -96.2286
2 1742.9236 -696.4670
3 -816.1947 1742.9236
4 5367.5098 -816.1947
5 11948.8038 5367.5098
6 -3786.1363 11948.8038
7 9190.2675 -3786.1363
8 -2605.5376 9190.2675
9 2195.3704 -2605.5376
10 2420.7815 2195.3704
11 731.4457 2420.7815
12 1883.1375 731.4457
13 -395.2960 1883.1375
14 1433.1238 -395.2960
15 -797.7770 1433.1238
16 5328.8817 -797.7770
17 4512.9392 5328.8817
18 -1975.5778 4512.9392
19 2606.0760 -1975.5778
20 -1805.6707 2606.0760
21 539.1875 -1805.6707
22 -9126.7303 539.1875
23 4517.8463 -9126.7303
24 -4581.0628 4517.8463
25 4611.0508 -4581.0628
26 -1829.2524 4611.0508
27 -4701.6261 -1829.2524
28 -3924.3638 -4701.6261
29 -5488.0760 -3924.3638
30 2533.0603 -5488.0760
31 -13801.8290 2533.0603
32 -428.9978 -13801.8290
33 -6978.2634 -428.9978
34 738.5906 -6978.2634
35 -6991.5226 738.5906
36 -3741.9481 -6991.5226
37 -3660.4161 -3741.9481
38 -2214.7968 -3660.4161
39 -2902.9835 -2214.7968
40 969.9722 -2902.9835
41 -7044.7948 969.9722
42 -4003.6082 -7044.7948
43 -1041.5300 -4003.6082
44 279.6550 -1041.5300
45 -690.8677 279.6550
46 -1486.6306 -690.8677
47 -2537.9694 -1486.6306
48 1911.7399 -2537.9694
49 282.1368 1911.7399
50 -2320.2813 282.1368
51 3983.4038 -2320.2813
52 -4108.3481 3983.4038
53 -3593.7780 -4108.3481
54 3384.2590 -3593.7780
55 3047.0154 3384.2590
56 4560.5511 3047.0154
57 4934.5732 4560.5511
58 7453.9887 4934.5732
59 4280.2000 7453.9887
60 4624.3621 4280.2000
61 -141.0085 4624.3621
62 3188.2832 -141.0085
63 5235.1774 3188.2832
64 -3633.6517 5235.1774
65 -335.0942 -3633.6517
66 3848.0029 -335.0942
> plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
> lines(lowess(z))
> abline(lm(z))
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/7k6fk1259925883.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8cbmr1259925883.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/92dvm1259925883.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/109xzc1259925883.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
+ myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ')
+ if (rownames(mysum$coefficients)[i] != '(Intercept)') {
+ myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
+ if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
+ }
+ }
> myeq <- paste(myeq, ' + e[t]')
> a<-table.row.start(a)
> a<-table.element(a, myeq)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/112vrk1259925884.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Variable',header=TRUE)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
> a<-table.element(a,'2-tail p-value',header=TRUE)
> a<-table.element(a,'1-tail p-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:k){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
+ a<-table.element(a,mysum$coefficients[i,1])
+ a<-table.element(a, round(mysum$coefficients[i,2],6))
+ a<-table.element(a, round(mysum$coefficients[i,3],4))
+ a<-table.element(a, round(mysum$coefficients[i,4],6))
+ a<-table.element(a, round(mysum$coefficients[i,4]/2,6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/12p3cj1259925884.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple R',1,TRUE)
> a<-table.element(a, sqrt(mysum$r.squared))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'R-squared',1,TRUE)
> a<-table.element(a, mysum$r.squared)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Adjusted R-squared',1,TRUE)
> a<-table.element(a, mysum$adj.r.squared)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (value)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[1])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[2])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[3])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'p-value',1,TRUE)
> a<-table.element(a, 1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
> a<-table.element(a, mysum$sigma)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a, sum(myerror*myerror))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/13g2qm1259925884.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Time or Index', 1, TRUE)
> a<-table.element(a, 'Actuals', 1, TRUE)
> a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
> a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
> a<-table.row.end(a)
> for (i in 1:n) {
+ a<-table.row.start(a)
+ a<-table.element(a,i, 1, TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]-mysum$resid[i])
+ a<-table.element(a,mysum$resid[i])
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/142euf1259925884.tab")
> if (n > n25) {
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'p-values',header=TRUE)
+ a<-table.element(a,'Alternative Hypothesis',3,header=TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'breakpoint index',header=TRUE)
+ a<-table.element(a,'greater',header=TRUE)
+ a<-table.element(a,'2-sided',header=TRUE)
+ a<-table.element(a,'less',header=TRUE)
+ a<-table.row.end(a)
+ for (mypoint in kp3:nmkm3) {
+ a<-table.row.start(a)
+ a<-table.element(a,mypoint,header=TRUE)
+ a<-table.element(a,gqarr[mypoint-kp3+1,1])
+ a<-table.element(a,gqarr[mypoint-kp3+1,2])
+ a<-table.element(a,gqarr[mypoint-kp3+1,3])
+ a<-table.row.end(a)
+ }
+ a<-table.end(a)
+ table.save(a,file="/var/www/html/rcomp/tmp/15jueq1259925884.tab")
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'Description',header=TRUE)
+ a<-table.element(a,'# significant tests',header=TRUE)
+ a<-table.element(a,'% significant tests',header=TRUE)
+ a<-table.element(a,'OK/NOK',header=TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'1% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant1)
+ a<-table.element(a,numsignificant1/numgqtests)
+ if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'5% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant5)
+ a<-table.element(a,numsignificant5/numgqtests)
+ if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'10% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant10)
+ a<-table.element(a,numsignificant10/numgqtests)
+ if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.end(a)
+ table.save(a,file="/var/www/html/rcomp/tmp/16ya5e1259925884.tab")
+ }
>
> system("convert tmp/1kxek1259925883.ps tmp/1kxek1259925883.png")
> system("convert tmp/2k7ve1259925883.ps tmp/2k7ve1259925883.png")
> system("convert tmp/36w6z1259925883.ps tmp/36w6z1259925883.png")
> system("convert tmp/4prnq1259925883.ps tmp/4prnq1259925883.png")
> system("convert tmp/5sfpo1259925883.ps tmp/5sfpo1259925883.png")
> system("convert tmp/6yldu1259925883.ps tmp/6yldu1259925883.png")
> system("convert tmp/7k6fk1259925883.ps tmp/7k6fk1259925883.png")
> system("convert tmp/8cbmr1259925883.ps tmp/8cbmr1259925883.png")
> system("convert tmp/92dvm1259925883.ps tmp/92dvm1259925883.png")
> system("convert tmp/109xzc1259925883.ps tmp/109xzc1259925883.png")
>
>
> proc.time()
user system elapsed
2.460 1.594 3.358