R version 2.8.0 (2008-10-20)
Copyright (C) 2008 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
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Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> x <- array(list(1.3322
+ ,133.52
+ ,7.4545
+ ,0
+ ,1.4369
+ ,153.2
+ ,7.4583
+ ,0
+ ,1.4975
+ ,163.63
+ ,7.4595
+ ,0
+ ,1.577
+ ,168.45
+ ,7.4599
+ ,0
+ ,1.5553
+ ,166.26
+ ,7.4586
+ ,0
+ ,1.5557
+ ,162.31
+ ,7.4609
+ ,0
+ ,1.575
+ ,161.56
+ ,7.4603
+ ,0
+ ,1.5527
+ ,156.59
+ ,7.4561
+ ,0
+ ,1.4748
+ ,157.97
+ ,7.454
+ ,0
+ ,1.4718
+ ,158.68
+ ,7.4505
+ ,0
+ ,1.457
+ ,163.55
+ ,7.4599
+ ,0
+ ,1.4684
+ ,162.89
+ ,7.4543
+ ,0
+ ,1.4227
+ ,164.95
+ ,7.4534
+ ,0
+ ,1.3896
+ ,159.82
+ ,7.4506
+ ,0
+ ,1.3622
+ ,159.05
+ ,7.4429
+ ,0
+ ,1.3716
+ ,166.76
+ ,7.441
+ ,0
+ ,1.3419
+ ,164.55
+ ,7.4452
+ ,0
+ ,1.3511
+ ,163.22
+ ,7.4519
+ ,0
+ ,1.3516
+ ,160.68
+ ,7.453
+ ,0
+ ,1.3242
+ ,155.24
+ ,7.4494
+ ,0
+ ,1.3074
+ ,157.6
+ ,7.4541
+ ,0
+ ,1.2999
+ ,156.56
+ ,7.4539
+ ,0
+ ,1.3213
+ ,154.82
+ ,7.4549
+ ,0
+ ,1.2881
+ ,151.11
+ ,7.4564
+ ,0
+ ,1.2611
+ ,149.65
+ ,7.4555
+ ,0
+ ,1.2727
+ ,148.99
+ ,7.4601
+ ,0
+ ,1.2811
+ ,148.53
+ ,7.4609
+ ,0
+ ,1.2684
+ ,146.7
+ ,7.4602
+ ,0
+ ,1.265
+ ,145.11
+ ,7.4566
+ ,0
+ ,1.277
+ ,142.7
+ ,7.4565
+ ,0
+ ,1.2271
+ ,143.59
+ ,7.4618
+ ,0
+ ,1.202
+ ,140.96
+ ,7.4612
+ ,0
+ ,1.1938
+ ,140.77
+ ,7.4641
+ ,0
+ ,1.2103
+ ,139.81
+ ,7.4613
+ ,0
+ ,1.1856
+ ,140.58
+ ,7.4541
+ ,0
+ ,1.1786
+ ,139.59
+ ,7.4596
+ ,0
+ ,1.2015
+ ,138.05
+ ,7.462
+ ,0
+ ,1.2256
+ ,136.06
+ ,7.4584
+ ,0
+ ,1.2292
+ ,135.98
+ ,7.4596
+ ,0
+ ,1.2037
+ ,134.75
+ ,7.4584
+ ,0
+ ,1.2165
+ ,132.22
+ ,7.4448
+ ,0
+ ,1.2694
+ ,135.37
+ ,7.4443
+ ,1
+ ,1.2938
+ ,138.84
+ ,7.4499
+ ,1
+ ,1.3201
+ ,138.83
+ ,7.4466
+ ,1
+ ,1.3014
+ ,136.55
+ ,7.4427
+ ,1
+ ,1.3119
+ ,135.63
+ ,7.4405
+ ,1
+ ,1.3408
+ ,139.14
+ ,7.4338
+ ,1
+ ,1.2991
+ ,136.09
+ ,7.4313
+ ,1
+ ,1.249
+ ,135.97
+ ,7.4379
+ ,1
+ ,1.2218
+ ,134.51
+ ,7.4381
+ ,1
+ ,1.2176
+ ,134.54
+ ,7.4365
+ ,1
+ ,1.2266
+ ,134.08
+ ,7.4355
+ ,1
+ ,1.2138
+ ,132.86
+ ,7.4342
+ ,1
+ ,1.2007
+ ,134.48
+ ,7.4405
+ ,1
+ ,1.1985
+ ,129.08
+ ,7.4436
+ ,1
+ ,1.2262
+ ,133.13
+ ,7.4493
+ ,1
+ ,1.2646
+ ,134.78
+ ,7.4511
+ ,1
+ ,1.2613
+ ,134.13
+ ,7.4481
+ ,1
+ ,1.2286
+ ,132.43
+ ,7.4419
+ ,1
+ ,1.1702
+ ,127.84
+ ,7.437
+ ,1
+ ,1.1692
+ ,128.12
+ ,7.4301
+ ,1
+ ,1.1222
+ ,128.94
+ ,7.4273
+ ,1
+ ,1.1139
+ ,132.38
+ ,7.4322
+ ,1
+ ,1.1372
+ ,134.99
+ ,7.4332
+ ,1
+ ,1.1663
+ ,138.05
+ ,7.425
+ ,1
+ ,1.1582
+ ,135.83
+ ,7.4246
+ ,1
+ ,1.0848
+ ,130.12
+ ,7.4255
+ ,1
+ ,1.0807
+ ,128.16
+ ,7.4274
+ ,1
+ ,1.0773
+ ,128.6
+ ,7.4317
+ ,1
+ ,1.0622
+ ,126.12
+ ,7.4324
+ ,1
+ ,1.0183
+ ,124.2
+ ,7.4264
+ ,1
+ ,1.0014
+ ,121.65
+ ,7.428
+ ,1
+ ,0.9811
+ ,121.57
+ ,7.4297
+ ,1
+ ,0.9808
+ ,118.38
+ ,7.4271
+ ,1)
+ ,dim=c(4
+ ,74)
+ ,dimnames=list(c('Dollar'
+ ,'Yen'
+ ,'DeenseKroon'
+ ,'(Y/N)')
+ ,1:74))
> y <- array(NA,dim=c(4,74),dimnames=list(c('Dollar','Yen','DeenseKroon','(Y/N)'),1:74))
> 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
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
Dollar Yen DeenseKroon (Y/N)
1 1.3322 133.52 7.4545 0
2 1.4369 153.20 7.4583 0
3 1.4975 163.63 7.4595 0
4 1.5770 168.45 7.4599 0
5 1.5553 166.26 7.4586 0
6 1.5557 162.31 7.4609 0
7 1.5750 161.56 7.4603 0
8 1.5527 156.59 7.4561 0
9 1.4748 157.97 7.4540 0
10 1.4718 158.68 7.4505 0
11 1.4570 163.55 7.4599 0
12 1.4684 162.89 7.4543 0
13 1.4227 164.95 7.4534 0
14 1.3896 159.82 7.4506 0
15 1.3622 159.05 7.4429 0
16 1.3716 166.76 7.4410 0
17 1.3419 164.55 7.4452 0
18 1.3511 163.22 7.4519 0
19 1.3516 160.68 7.4530 0
20 1.3242 155.24 7.4494 0
21 1.3074 157.60 7.4541 0
22 1.2999 156.56 7.4539 0
23 1.3213 154.82 7.4549 0
24 1.2881 151.11 7.4564 0
25 1.2611 149.65 7.4555 0
26 1.2727 148.99 7.4601 0
27 1.2811 148.53 7.4609 0
28 1.2684 146.70 7.4602 0
29 1.2650 145.11 7.4566 0
30 1.2770 142.70 7.4565 0
31 1.2271 143.59 7.4618 0
32 1.2020 140.96 7.4612 0
33 1.1938 140.77 7.4641 0
34 1.2103 139.81 7.4613 0
35 1.1856 140.58 7.4541 0
36 1.1786 139.59 7.4596 0
37 1.2015 138.05 7.4620 0
38 1.2256 136.06 7.4584 0
39 1.2292 135.98 7.4596 0
40 1.2037 134.75 7.4584 0
41 1.2165 132.22 7.4448 0
42 1.2694 135.37 7.4443 1
43 1.2938 138.84 7.4499 1
44 1.3201 138.83 7.4466 1
45 1.3014 136.55 7.4427 1
46 1.3119 135.63 7.4405 1
47 1.3408 139.14 7.4338 1
48 1.2991 136.09 7.4313 1
49 1.2490 135.97 7.4379 1
50 1.2218 134.51 7.4381 1
51 1.2176 134.54 7.4365 1
52 1.2266 134.08 7.4355 1
53 1.2138 132.86 7.4342 1
54 1.2007 134.48 7.4405 1
55 1.1985 129.08 7.4436 1
56 1.2262 133.13 7.4493 1
57 1.2646 134.78 7.4511 1
58 1.2613 134.13 7.4481 1
59 1.2286 132.43 7.4419 1
60 1.1702 127.84 7.4370 1
61 1.1692 128.12 7.4301 1
62 1.1222 128.94 7.4273 1
63 1.1139 132.38 7.4322 1
64 1.1372 134.99 7.4332 1
65 1.1663 138.05 7.4250 1
66 1.1582 135.83 7.4246 1
67 1.0848 130.12 7.4255 1
68 1.0807 128.16 7.4274 1
69 1.0773 128.60 7.4317 1
70 1.0622 126.12 7.4324 1
71 1.0183 124.20 7.4264 1
72 1.0014 121.65 7.4280 1
73 0.9811 121.57 7.4297 1
74 0.9808 118.38 7.4271 1
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Yen DeenseKroon `(Y/N)`
-38.70200 0.01032 5.16050 0.14811
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-0.08682 -0.04453 -0.01239 0.02688 0.18736
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -3.870e+01 7.880e+00 -4.912 5.71e-06 ***
Yen 1.032e-02 7.938e-04 13.000 < 2e-16 ***
DeenseKroon 5.160e+00 1.056e+00 4.885 6.31e-06 ***
`(Y/N)` 1.481e-01 3.006e-02 4.927 5.38e-06 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.05971 on 70 degrees of freedom
Multiple R-squared: 0.8213, Adjusted R-squared: 0.8137
F-statistic: 107.3 on 3 and 70 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,] 0.3474966 6.949932e-01 6.525034e-01
[2,] 0.5691301 8.617397e-01 4.308699e-01
[3,] 0.5273558 9.452884e-01 4.726442e-01
[4,] 0.4675150 9.350299e-01 5.324850e-01
[5,] 0.7030259 5.939483e-01 2.969741e-01
[6,] 0.6970867 6.058266e-01 3.029133e-01
[7,] 0.7953592 4.092816e-01 2.046408e-01
[8,] 0.7825455 4.349090e-01 2.174545e-01
[9,] 0.7317655 5.364690e-01 2.682345e-01
[10,] 0.6527097 6.945806e-01 3.472903e-01
[11,] 0.6576920 6.846160e-01 3.423080e-01
[12,] 0.8090424 3.819151e-01 1.909576e-01
[13,] 0.8785267 2.429466e-01 1.214733e-01
[14,] 0.8704575 2.590850e-01 1.295425e-01
[15,] 0.9563128 8.737446e-02 4.368723e-02
[16,] 0.9831855 3.362897e-02 1.681448e-02
[17,] 0.9875372 2.492558e-02 1.246279e-02
[18,] 0.9931086 1.378288e-02 6.891439e-03
[19,] 0.9959957 8.008700e-03 4.004350e-03
[20,] 0.9981524 3.695148e-03 1.847574e-03
[21,] 0.9986899 2.620133e-03 1.310067e-03
[22,] 0.9986977 2.604550e-03 1.302275e-03
[23,] 0.9978966 4.206886e-03 2.103443e-03
[24,] 0.9965756 6.848824e-03 3.424412e-03
[25,] 0.9972889 5.422272e-03 2.711136e-03
[26,] 0.9974071 5.185843e-03 2.592922e-03
[27,] 0.9985033 2.993475e-03 1.496738e-03
[28,] 0.9981280 3.744001e-03 1.872000e-03
[29,] 0.9980825 3.834980e-03 1.917490e-03
[30,] 0.9991237 1.752637e-03 8.763185e-04
[31,] 0.9994192 1.161665e-03 5.808323e-04
[32,] 0.9991573 1.685493e-03 8.427467e-04
[33,] 0.9988943 2.211386e-03 1.105693e-03
[34,] 0.9992878 1.424309e-03 7.121543e-04
[35,] 0.9993852 1.229689e-03 6.148447e-04
[36,] 0.9988395 2.321014e-03 1.160507e-03
[37,] 0.9985840 2.831978e-03 1.415989e-03
[38,] 0.9974803 5.039393e-03 2.519696e-03
[39,] 0.9960215 7.957092e-03 3.978546e-03
[40,] 0.9965106 6.978875e-03 3.489438e-03
[41,] 0.9983753 3.249476e-03 1.624738e-03
[42,] 0.9998031 3.938716e-04 1.969358e-04
[43,] 0.9996524 6.951049e-04 3.475525e-04
[44,] 0.9993336 1.332749e-03 6.663747e-04
[45,] 0.9987853 2.429471e-03 1.214736e-03
[46,] 0.9984326 3.134897e-03 1.567449e-03
[47,] 0.9985081 2.983767e-03 1.491884e-03
[48,] 0.9973546 5.290838e-03 2.645419e-03
[49,] 0.9955617 8.876589e-03 4.438294e-03
[50,] 0.9926208 1.475833e-02 7.379165e-03
[51,] 0.9870698 2.586044e-02 1.293022e-02
[52,] 0.9758000 4.840000e-02 2.420000e-02
[53,] 0.9624993 7.500134e-02 3.750067e-02
[54,] 0.9777492 4.450157e-02 2.225079e-02
[55,] 0.9997411 5.178882e-04 2.589441e-04
[56,] 0.9999744 5.118115e-05 2.559058e-05
[57,] 0.9998798 2.404451e-04 1.202225e-04
[58,] 0.9995188 9.623584e-04 4.811792e-04
[59,] 0.9981628 3.674452e-03 1.837226e-03
[60,] 0.9921997 1.560054e-02 7.800271e-03
[61,] 0.9689981 6.200380e-02 3.100190e-02
> postscript(file="/var/www/html/rcomp/tmp/177hq1227535224.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2246f1227535224.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3qp9x1227535224.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4ipnv1227535224.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5xcec1227535224.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 = 74
Frequency = 1
1 2 3 4 5 6
0.187363086 0.069359702 0.016131682 0.043826090 0.051435081 0.080729108
7 8 9 10 11 12
0.110865250 0.161528708 0.080224444 0.087959139 -0.025606934 0.021502923
13 14 15 16 17 18
-0.040811398 -0.006521472 0.013760609 -0.046600031 -0.075167389 -0.086817411
19 20 21 22 23 24
-0.065781690 -0.018464231 -0.083873283 -0.079608600 -0.045412663 -0.048066987
25 26 27 28 29 30
-0.055355643 -0.060682876 -0.051664172 -0.041866605 -0.010280340 0.027106406
31 32 33 34 35 36
-0.059328853 -0.054191503 -0.075396190 -0.034539793 -0.030030439 -0.055196591
37 38 39 40 41 42
-0.028789310 0.034424870 0.032657855 0.026043797 0.135135655 0.010001272
43 44 45 46 47 48
-0.030307197 0.013125647 0.038080717 0.069428023 0.096680900 0.099357510
49 50 51 52 53 54
0.016436591 0.003271387 0.007018591 0.025926194 0.032424988 -0.029904217
55 56 57 58 59 60
0.007625107 -0.035884891 -0.023801445 -0.004912083 0.011926656 0.026180942
61 62 63 64 65 66
0.057898844 0.016886012 -0.052200514 -0.060995668 -0.021158136 -0.004284001
67 68 69 70 71 72
-0.023402443 -0.017080601 -0.047211455 -0.040330722 -0.033453729 -0.032295060
73 74
-0.060542325 -0.014504894
> postscript(file="/var/www/html/rcomp/tmp/63a5l1227535224.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 = 74
Frequency = 1
lag(myerror, k = 1) myerror
0 0.187363086 NA
1 0.069359702 0.187363086
2 0.016131682 0.069359702
3 0.043826090 0.016131682
4 0.051435081 0.043826090
5 0.080729108 0.051435081
6 0.110865250 0.080729108
7 0.161528708 0.110865250
8 0.080224444 0.161528708
9 0.087959139 0.080224444
10 -0.025606934 0.087959139
11 0.021502923 -0.025606934
12 -0.040811398 0.021502923
13 -0.006521472 -0.040811398
14 0.013760609 -0.006521472
15 -0.046600031 0.013760609
16 -0.075167389 -0.046600031
17 -0.086817411 -0.075167389
18 -0.065781690 -0.086817411
19 -0.018464231 -0.065781690
20 -0.083873283 -0.018464231
21 -0.079608600 -0.083873283
22 -0.045412663 -0.079608600
23 -0.048066987 -0.045412663
24 -0.055355643 -0.048066987
25 -0.060682876 -0.055355643
26 -0.051664172 -0.060682876
27 -0.041866605 -0.051664172
28 -0.010280340 -0.041866605
29 0.027106406 -0.010280340
30 -0.059328853 0.027106406
31 -0.054191503 -0.059328853
32 -0.075396190 -0.054191503
33 -0.034539793 -0.075396190
34 -0.030030439 -0.034539793
35 -0.055196591 -0.030030439
36 -0.028789310 -0.055196591
37 0.034424870 -0.028789310
38 0.032657855 0.034424870
39 0.026043797 0.032657855
40 0.135135655 0.026043797
41 0.010001272 0.135135655
42 -0.030307197 0.010001272
43 0.013125647 -0.030307197
44 0.038080717 0.013125647
45 0.069428023 0.038080717
46 0.096680900 0.069428023
47 0.099357510 0.096680900
48 0.016436591 0.099357510
49 0.003271387 0.016436591
50 0.007018591 0.003271387
51 0.025926194 0.007018591
52 0.032424988 0.025926194
53 -0.029904217 0.032424988
54 0.007625107 -0.029904217
55 -0.035884891 0.007625107
56 -0.023801445 -0.035884891
57 -0.004912083 -0.023801445
58 0.011926656 -0.004912083
59 0.026180942 0.011926656
60 0.057898844 0.026180942
61 0.016886012 0.057898844
62 -0.052200514 0.016886012
63 -0.060995668 -0.052200514
64 -0.021158136 -0.060995668
65 -0.004284001 -0.021158136
66 -0.023402443 -0.004284001
67 -0.017080601 -0.023402443
68 -0.047211455 -0.017080601
69 -0.040330722 -0.047211455
70 -0.033453729 -0.040330722
71 -0.032295060 -0.033453729
72 -0.060542325 -0.032295060
73 -0.014504894 -0.060542325
74 NA -0.014504894
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 0.069359702 0.187363086
[2,] 0.016131682 0.069359702
[3,] 0.043826090 0.016131682
[4,] 0.051435081 0.043826090
[5,] 0.080729108 0.051435081
[6,] 0.110865250 0.080729108
[7,] 0.161528708 0.110865250
[8,] 0.080224444 0.161528708
[9,] 0.087959139 0.080224444
[10,] -0.025606934 0.087959139
[11,] 0.021502923 -0.025606934
[12,] -0.040811398 0.021502923
[13,] -0.006521472 -0.040811398
[14,] 0.013760609 -0.006521472
[15,] -0.046600031 0.013760609
[16,] -0.075167389 -0.046600031
[17,] -0.086817411 -0.075167389
[18,] -0.065781690 -0.086817411
[19,] -0.018464231 -0.065781690
[20,] -0.083873283 -0.018464231
[21,] -0.079608600 -0.083873283
[22,] -0.045412663 -0.079608600
[23,] -0.048066987 -0.045412663
[24,] -0.055355643 -0.048066987
[25,] -0.060682876 -0.055355643
[26,] -0.051664172 -0.060682876
[27,] -0.041866605 -0.051664172
[28,] -0.010280340 -0.041866605
[29,] 0.027106406 -0.010280340
[30,] -0.059328853 0.027106406
[31,] -0.054191503 -0.059328853
[32,] -0.075396190 -0.054191503
[33,] -0.034539793 -0.075396190
[34,] -0.030030439 -0.034539793
[35,] -0.055196591 -0.030030439
[36,] -0.028789310 -0.055196591
[37,] 0.034424870 -0.028789310
[38,] 0.032657855 0.034424870
[39,] 0.026043797 0.032657855
[40,] 0.135135655 0.026043797
[41,] 0.010001272 0.135135655
[42,] -0.030307197 0.010001272
[43,] 0.013125647 -0.030307197
[44,] 0.038080717 0.013125647
[45,] 0.069428023 0.038080717
[46,] 0.096680900 0.069428023
[47,] 0.099357510 0.096680900
[48,] 0.016436591 0.099357510
[49,] 0.003271387 0.016436591
[50,] 0.007018591 0.003271387
[51,] 0.025926194 0.007018591
[52,] 0.032424988 0.025926194
[53,] -0.029904217 0.032424988
[54,] 0.007625107 -0.029904217
[55,] -0.035884891 0.007625107
[56,] -0.023801445 -0.035884891
[57,] -0.004912083 -0.023801445
[58,] 0.011926656 -0.004912083
[59,] 0.026180942 0.011926656
[60,] 0.057898844 0.026180942
[61,] 0.016886012 0.057898844
[62,] -0.052200514 0.016886012
[63,] -0.060995668 -0.052200514
[64,] -0.021158136 -0.060995668
[65,] -0.004284001 -0.021158136
[66,] -0.023402443 -0.004284001
[67,] -0.017080601 -0.023402443
[68,] -0.047211455 -0.017080601
[69,] -0.040330722 -0.047211455
[70,] -0.033453729 -0.040330722
[71,] -0.032295060 -0.033453729
[72,] -0.060542325 -0.032295060
[73,] -0.014504894 -0.060542325
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 0.069359702 0.187363086
2 0.016131682 0.069359702
3 0.043826090 0.016131682
4 0.051435081 0.043826090
5 0.080729108 0.051435081
6 0.110865250 0.080729108
7 0.161528708 0.110865250
8 0.080224444 0.161528708
9 0.087959139 0.080224444
10 -0.025606934 0.087959139
11 0.021502923 -0.025606934
12 -0.040811398 0.021502923
13 -0.006521472 -0.040811398
14 0.013760609 -0.006521472
15 -0.046600031 0.013760609
16 -0.075167389 -0.046600031
17 -0.086817411 -0.075167389
18 -0.065781690 -0.086817411
19 -0.018464231 -0.065781690
20 -0.083873283 -0.018464231
21 -0.079608600 -0.083873283
22 -0.045412663 -0.079608600
23 -0.048066987 -0.045412663
24 -0.055355643 -0.048066987
25 -0.060682876 -0.055355643
26 -0.051664172 -0.060682876
27 -0.041866605 -0.051664172
28 -0.010280340 -0.041866605
29 0.027106406 -0.010280340
30 -0.059328853 0.027106406
31 -0.054191503 -0.059328853
32 -0.075396190 -0.054191503
33 -0.034539793 -0.075396190
34 -0.030030439 -0.034539793
35 -0.055196591 -0.030030439
36 -0.028789310 -0.055196591
37 0.034424870 -0.028789310
38 0.032657855 0.034424870
39 0.026043797 0.032657855
40 0.135135655 0.026043797
41 0.010001272 0.135135655
42 -0.030307197 0.010001272
43 0.013125647 -0.030307197
44 0.038080717 0.013125647
45 0.069428023 0.038080717
46 0.096680900 0.069428023
47 0.099357510 0.096680900
48 0.016436591 0.099357510
49 0.003271387 0.016436591
50 0.007018591 0.003271387
51 0.025926194 0.007018591
52 0.032424988 0.025926194
53 -0.029904217 0.032424988
54 0.007625107 -0.029904217
55 -0.035884891 0.007625107
56 -0.023801445 -0.035884891
57 -0.004912083 -0.023801445
58 0.011926656 -0.004912083
59 0.026180942 0.011926656
60 0.057898844 0.026180942
61 0.016886012 0.057898844
62 -0.052200514 0.016886012
63 -0.060995668 -0.052200514
64 -0.021158136 -0.060995668
65 -0.004284001 -0.021158136
66 -0.023402443 -0.004284001
67 -0.017080601 -0.023402443
68 -0.047211455 -0.017080601
69 -0.040330722 -0.047211455
70 -0.033453729 -0.040330722
71 -0.032295060 -0.033453729
72 -0.060542325 -0.032295060
73 -0.014504894 -0.060542325
> 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/7m28j1227535224.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8udfr1227535224.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9ptq01227535224.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/108yga1227535224.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11ytub1227535224.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/127wqx1227535224.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/135fvm1227535224.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/14wgc01227535224.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/15tew51227535224.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/162iie1227535224.tab")
+ }
>
> system("convert tmp/177hq1227535224.ps tmp/177hq1227535224.png")
> system("convert tmp/2246f1227535224.ps tmp/2246f1227535224.png")
> system("convert tmp/3qp9x1227535224.ps tmp/3qp9x1227535224.png")
> system("convert tmp/4ipnv1227535224.ps tmp/4ipnv1227535224.png")
> system("convert tmp/5xcec1227535224.ps tmp/5xcec1227535224.png")
> system("convert tmp/63a5l1227535224.ps tmp/63a5l1227535224.png")
> system("convert tmp/7m28j1227535224.ps tmp/7m28j1227535224.png")
> system("convert tmp/8udfr1227535224.ps tmp/8udfr1227535224.png")
> system("convert tmp/9ptq01227535224.ps tmp/9ptq01227535224.png")
> system("convert tmp/108yga1227535224.ps tmp/108yga1227535224.png")
>
>
> proc.time()
user system elapsed
2.655 1.593 6.653