R version 2.8.0 (2008-10-20)
Copyright (C) 2008 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
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Type 'license()' or 'licence()' for distribution details.
Natural language support but running in an English locale
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Type 'contributors()' for more information and
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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(235.1
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+ ,546
+ ,579.7
+ ,593.1)
+ ,dim=c(5
+ ,372)
+ ,dimnames=list(c('werkloosheid'
+ ,'y1'
+ ,'y2'
+ ,'y3'
+ ,'y4')
+ ,1:372))
> y <- array(NA,dim=c(5,372),dimnames=list(c('werkloosheid','y1','y2','y3','y4'),1:372))
> 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
werkloosheid y1 y2 y3 y4 M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 235.1 0.0 0.0 0.0 0.0 1 0 0 0 0 0 0 0 0 0 0 1
2 280.7 235.1 0.0 0.0 0.0 0 1 0 0 0 0 0 0 0 0 0 2
3 264.6 280.7 235.1 0.0 0.0 0 0 1 0 0 0 0 0 0 0 0 3
4 240.7 264.6 280.7 235.1 0.0 0 0 0 1 0 0 0 0 0 0 0 4
5 201.4 240.7 264.6 280.7 235.1 0 0 0 0 1 0 0 0 0 0 0 5
6 240.8 201.4 240.7 264.6 280.7 0 0 0 0 0 1 0 0 0 0 0 6
7 241.1 240.8 201.4 240.7 264.6 0 0 0 0 0 0 1 0 0 0 0 7
8 223.8 241.1 240.8 201.4 240.7 0 0 0 0 0 0 0 1 0 0 0 8
9 206.1 223.8 241.1 240.8 201.4 0 0 0 0 0 0 0 0 1 0 0 9
10 174.7 206.1 223.8 241.1 240.8 0 0 0 0 0 0 0 0 0 1 0 10
11 203.3 174.7 206.1 223.8 241.1 0 0 0 0 0 0 0 0 0 0 1 11
12 220.5 203.3 174.7 206.1 223.8 0 0 0 0 0 0 0 0 0 0 0 12
13 299.5 220.5 203.3 174.7 206.1 1 0 0 0 0 0 0 0 0 0 0 13
14 347.4 299.5 220.5 203.3 174.7 0 1 0 0 0 0 0 0 0 0 0 14
15 338.3 347.4 299.5 220.5 203.3 0 0 1 0 0 0 0 0 0 0 0 15
16 327.7 338.3 347.4 299.5 220.5 0 0 0 1 0 0 0 0 0 0 0 16
17 351.6 327.7 338.3 347.4 299.5 0 0 0 0 1 0 0 0 0 0 0 17
18 396.6 351.6 327.7 338.3 347.4 0 0 0 0 0 1 0 0 0 0 0 18
19 438.8 396.6 351.6 327.7 338.3 0 0 0 0 0 0 1 0 0 0 0 19
20 395.6 438.8 396.6 351.6 327.7 0 0 0 0 0 0 0 1 0 0 0 20
21 363.5 395.6 438.8 396.6 351.6 0 0 0 0 0 0 0 0 1 0 0 21
22 378.8 363.5 395.6 438.8 396.6 0 0 0 0 0 0 0 0 0 1 0 22
23 357.0 378.8 363.5 395.6 438.8 0 0 0 0 0 0 0 0 0 0 1 23
24 369.0 357.0 378.8 363.5 395.6 0 0 0 0 0 0 0 0 0 0 0 24
25 464.8 369.0 357.0 378.8 363.5 1 0 0 0 0 0 0 0 0 0 0 25
26 479.1 464.8 369.0 357.0 378.8 0 1 0 0 0 0 0 0 0 0 0 26
27 431.3 479.1 464.8 369.0 357.0 0 0 1 0 0 0 0 0 0 0 0 27
28 366.5 431.3 479.1 464.8 369.0 0 0 0 1 0 0 0 0 0 0 0 28
29 326.3 366.5 431.3 479.1 464.8 0 0 0 0 1 0 0 0 0 0 0 29
30 355.1 326.3 366.5 431.3 479.1 0 0 0 0 0 1 0 0 0 0 0 30
31 331.6 355.1 326.3 366.5 431.3 0 0 0 0 0 0 1 0 0 0 0 31
32 261.3 331.6 355.1 326.3 366.5 0 0 0 0 0 0 0 1 0 0 0 32
33 249.0 261.3 331.6 355.1 326.3 0 0 0 0 0 0 0 0 1 0 0 33
34 205.5 249.0 261.3 331.6 355.1 0 0 0 0 0 0 0 0 0 1 0 34
35 235.6 205.5 249.0 261.3 331.6 0 0 0 0 0 0 0 0 0 0 1 35
36 240.9 235.6 205.5 249.0 261.3 0 0 0 0 0 0 0 0 0 0 0 36
37 264.9 240.9 235.6 205.5 249.0 1 0 0 0 0 0 0 0 0 0 0 37
38 253.8 264.9 240.9 235.6 205.5 0 1 0 0 0 0 0 0 0 0 0 38
39 232.3 253.8 264.9 240.9 235.6 0 0 1 0 0 0 0 0 0 0 0 39
40 193.8 232.3 253.8 264.9 240.9 0 0 0 1 0 0 0 0 0 0 0 40
41 177.0 193.8 232.3 253.8 264.9 0 0 0 0 1 0 0 0 0 0 0 41
42 213.2 177.0 193.8 232.3 253.8 0 0 0 0 0 1 0 0 0 0 0 42
43 207.2 213.2 177.0 193.8 232.3 0 0 0 0 0 0 1 0 0 0 0 43
44 180.6 207.2 213.2 177.0 193.8 0 0 0 0 0 0 0 1 0 0 0 44
45 188.6 180.6 207.2 213.2 177.0 0 0 0 0 0 0 0 0 1 0 0 45
46 175.4 188.6 180.6 207.2 213.2 0 0 0 0 0 0 0 0 0 1 0 46
47 199.0 175.4 188.6 180.6 207.2 0 0 0 0 0 0 0 0 0 0 1 47
48 179.6 199.0 175.4 188.6 180.6 0 0 0 0 0 0 0 0 0 0 0 48
49 225.8 179.6 199.0 175.4 188.6 1 0 0 0 0 0 0 0 0 0 0 49
50 234.0 225.8 179.6 199.0 175.4 0 1 0 0 0 0 0 0 0 0 0 50
51 200.2 234.0 225.8 179.6 199.0 0 0 1 0 0 0 0 0 0 0 0 51
52 183.6 200.2 234.0 225.8 179.6 0 0 0 1 0 0 0 0 0 0 0 52
53 178.2 183.6 200.2 234.0 225.8 0 0 0 0 1 0 0 0 0 0 0 53
54 203.2 178.2 183.6 200.2 234.0 0 0 0 0 0 1 0 0 0 0 0 54
55 208.5 203.2 178.2 183.6 200.2 0 0 0 0 0 0 1 0 0 0 0 55
56 191.8 208.5 203.2 178.2 183.6 0 0 0 0 0 0 0 1 0 0 0 56
57 172.8 191.8 208.5 203.2 178.2 0 0 0 0 0 0 0 0 1 0 0 57
58 148.0 172.8 191.8 208.5 203.2 0 0 0 0 0 0 0 0 0 1 0 58
59 159.4 148.0 172.8 191.8 208.5 0 0 0 0 0 0 0 0 0 0 1 59
60 154.5 159.4 148.0 172.8 191.8 0 0 0 0 0 0 0 0 0 0 0 60
61 213.2 154.5 159.4 148.0 172.8 1 0 0 0 0 0 0 0 0 0 0 61
62 196.4 213.2 154.5 159.4 148.0 0 1 0 0 0 0 0 0 0 0 0 62
63 182.8 196.4 213.2 154.5 159.4 0 0 1 0 0 0 0 0 0 0 0 63
64 176.4 182.8 196.4 213.2 154.5 0 0 0 1 0 0 0 0 0 0 0 64
65 153.6 176.4 182.8 196.4 213.2 0 0 0 0 1 0 0 0 0 0 0 65
66 173.2 153.6 176.4 182.8 196.4 0 0 0 0 0 1 0 0 0 0 0 66
67 171.0 173.2 153.6 176.4 182.8 0 0 0 0 0 0 1 0 0 0 0 67
68 151.2 171.0 173.2 153.6 176.4 0 0 0 0 0 0 0 1 0 0 0 68
69 161.9 151.2 171.0 173.2 153.6 0 0 0 0 0 0 0 0 1 0 0 69
70 157.2 161.9 151.2 171.0 173.2 0 0 0 0 0 0 0 0 0 1 0 70
71 201.7 157.2 161.9 151.2 171.0 0 0 0 0 0 0 0 0 0 0 1 71
72 236.4 201.7 157.2 161.9 151.2 0 0 0 0 0 0 0 0 0 0 0 72
73 356.1 236.4 201.7 157.2 161.9 1 0 0 0 0 0 0 0 0 0 0 73
74 398.3 356.1 236.4 201.7 157.2 0 1 0 0 0 0 0 0 0 0 0 74
75 403.7 398.3 356.1 236.4 201.7 0 0 1 0 0 0 0 0 0 0 0 75
76 384.6 403.7 398.3 356.1 236.4 0 0 0 1 0 0 0 0 0 0 0 76
77 365.8 384.6 403.7 398.3 356.1 0 0 0 0 1 0 0 0 0 0 0 77
78 368.1 365.8 384.6 403.7 398.3 0 0 0 0 0 1 0 0 0 0 0 78
79 367.9 368.1 365.8 384.6 403.7 0 0 0 0 0 0 1 0 0 0 0 79
80 347.0 367.9 368.1 365.8 384.6 0 0 0 0 0 0 0 1 0 0 0 80
81 343.3 347.0 367.9 368.1 365.8 0 0 0 0 0 0 0 0 1 0 0 81
82 292.9 343.3 347.0 367.9 368.1 0 0 0 0 0 0 0 0 0 1 0 82
83 311.5 292.9 343.3 347.0 367.9 0 0 0 0 0 0 0 0 0 0 1 83
84 300.9 311.5 292.9 343.3 347.0 0 0 0 0 0 0 0 0 0 0 0 84
85 366.9 300.9 311.5 292.9 343.3 1 0 0 0 0 0 0 0 0 0 0 85
86 356.9 366.9 300.9 311.5 292.9 0 1 0 0 0 0 0 0 0 0 0 86
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352 656.8 755.6 810.9 784.8 702.2 0 0 0 1 0 0 0 0 0 0 0 352
353 615.1 656.8 755.6 810.9 784.8 0 0 0 0 1 0 0 0 0 0 0 353
354 745.3 615.1 656.8 755.6 810.9 0 0 0 0 0 1 0 0 0 0 0 354
355 694.1 745.3 615.1 656.8 755.6 0 0 0 0 0 0 1 0 0 0 0 355
356 675.7 694.1 745.3 615.1 656.8 0 0 0 0 0 0 0 1 0 0 0 356
357 643.7 675.7 694.1 745.3 615.1 0 0 0 0 0 0 0 0 1 0 0 357
358 622.1 643.7 675.7 694.1 745.3 0 0 0 0 0 0 0 0 0 1 0 358
359 634.6 622.1 643.7 675.7 694.1 0 0 0 0 0 0 0 0 0 0 1 359
360 588.0 634.6 622.1 643.7 675.7 0 0 0 0 0 0 0 0 0 0 0 360
361 689.7 588.0 634.6 622.1 643.7 1 0 0 0 0 0 0 0 0 0 0 361
362 673.9 689.7 588.0 634.6 622.1 0 1 0 0 0 0 0 0 0 0 0 362
363 647.9 673.9 689.7 588.0 634.6 0 0 1 0 0 0 0 0 0 0 0 363
364 568.8 647.9 673.9 689.7 588.0 0 0 0 1 0 0 0 0 0 0 0 364
365 545.7 568.8 647.9 673.9 689.7 0 0 0 0 1 0 0 0 0 0 0 365
366 632.6 545.7 568.8 647.9 673.9 0 0 0 0 0 1 0 0 0 0 0 366
367 643.8 632.6 545.7 568.8 647.9 0 0 0 0 0 0 1 0 0 0 0 367
368 593.1 643.8 632.6 545.7 568.8 0 0 0 0 0 0 0 1 0 0 0 368
369 579.7 593.1 643.8 632.6 545.7 0 0 0 0 0 0 0 0 1 0 0 369
370 546.0 579.7 593.1 643.8 632.6 0 0 0 0 0 0 0 0 0 1 0 370
371 562.9 546.0 579.7 593.1 643.8 0 0 0 0 0 0 0 0 0 0 1 371
372 572.5 562.9 546.0 579.7 593.1 0 0 0 0 0 0 0 0 0 0 0 372
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) y1 y2 y3 y4 M1
10.49529 1.04226 0.03948 -0.08985 -0.02918 73.90198
M2 M3 M4 M5 M6 M7
2.33651 -32.59597 -41.52714 -17.44357 76.48043 -25.45870
M8 M9 M10 M11 t
-38.75605 -16.59970 -12.93988 22.40501 0.03299
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-70.00 -14.32 -2.00 12.14 150.67
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 10.49529 5.73967 1.829 0.068306 .
y1 1.04226 0.05306 19.644 < 2e-16 ***
y2 0.03948 0.07648 0.516 0.606041
y3 -0.08985 0.07637 -1.177 0.240156
y4 -0.02918 0.05282 -0.552 0.581075
M1 73.90198 6.67053 11.079 < 2e-16 ***
M2 2.33651 7.17857 0.325 0.745007
M3 -32.59597 8.08541 -4.031 6.79e-05 ***
M4 -41.52714 8.60525 -4.826 2.07e-06 ***
M5 -17.44357 7.25760 -2.403 0.016752 *
M6 76.48043 6.74405 11.340 < 2e-16 ***
M7 -25.45870 7.00946 -3.632 0.000323 ***
M8 -38.75605 8.22538 -4.712 3.53e-06 ***
M9 -16.59970 8.49895 -1.953 0.051588 .
M10 -12.93988 6.63236 -1.951 0.051841 .
M11 22.40501 6.58973 3.400 0.000751 ***
t 0.03299 0.01753 1.882 0.060635 .
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 24.69 on 355 degrees of freedom
Multiple R-squared: 0.9757, Adjusted R-squared: 0.9746
F-statistic: 892.1 on 16 and 355 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,] 0.5075921 0.984815760 0.4924078798
[2,] 0.5836045 0.832791073 0.4163955365
[3,] 0.9319945 0.136010975 0.0680054877
[4,] 0.9169666 0.166066706 0.0830333528
[5,] 0.8912356 0.217528868 0.1087644339
[6,] 0.8413221 0.317355703 0.1586778515
[7,] 0.7772794 0.445441268 0.2227206338
[8,] 0.8022944 0.395411125 0.1977055625
[9,] 0.8966618 0.206676375 0.1033381873
[10,] 0.9707428 0.058514316 0.0292571578
[11,] 0.9787805 0.042439043 0.0212195214
[12,] 0.9917279 0.016544272 0.0082721358
[13,] 0.9951956 0.009608852 0.0048044260
[14,] 0.9923781 0.015243837 0.0076219184
[15,] 0.9917779 0.016444200 0.0082220999
[16,] 0.9888604 0.022279211 0.0111396057
[17,] 0.9853912 0.029217596 0.0146087981
[18,] 0.9989936 0.002012735 0.0010063677
[19,] 0.9991557 0.001688560 0.0008442802
[20,] 0.9987334 0.002533249 0.0012666245
[21,] 0.9983760 0.003248076 0.0016240381
[22,] 0.9978552 0.004289615 0.0021448074
[23,] 0.9972050 0.005589949 0.0027949747
[24,] 0.9959822 0.008035558 0.0040177790
[25,] 0.9950276 0.009944838 0.0049724189
[26,] 0.9949141 0.010171893 0.0050859466
[27,] 0.9930177 0.013964661 0.0069823307
[28,] 0.9905657 0.018868635 0.0094343174
[29,] 0.9902883 0.019423410 0.0097117051
[30,] 0.9927299 0.014540231 0.0072701154
[31,] 0.9899354 0.020129196 0.0100645981
[32,] 0.9863015 0.027397070 0.0136985351
[33,] 0.9868305 0.026338985 0.0131694925
[34,] 0.9845601 0.030879760 0.0154398801
[35,] 0.9839471 0.032105881 0.0160529406
[36,] 0.9807467 0.038506586 0.0192532928
[37,] 0.9795229 0.040954189 0.0204770946
[38,] 0.9734296 0.053140857 0.0265704284
[39,] 0.9659923 0.068015378 0.0340076890
[40,] 0.9569570 0.086086031 0.0430430154
[41,] 0.9459215 0.108157024 0.0540785120
[42,] 0.9393611 0.121277900 0.0606389499
[43,] 0.9359186 0.128162760 0.0640813799
[44,] 0.9288216 0.142356892 0.0711784460
[45,] 0.9353175 0.129365030 0.0646825149
[46,] 0.9214101 0.157179770 0.0785898852
[47,] 0.9285182 0.142963566 0.0714817832
[48,] 0.9173373 0.165325441 0.0826627205
[49,] 0.9098734 0.180253243 0.0901266214
[50,] 0.9131025 0.173795074 0.0868975369
[51,] 0.9055928 0.188814320 0.0944071601
[52,] 0.9159007 0.168198523 0.0840992615
[53,] 0.9277252 0.144549630 0.0722748151
[54,] 0.9488464 0.102307218 0.0511536088
[55,] 0.9570436 0.085912874 0.0429564369
[56,] 0.9632185 0.073562923 0.0367814613
[57,] 0.9587771 0.082445783 0.0412228916
[58,] 0.9508247 0.098350555 0.0491752777
[59,] 0.9654214 0.069157122 0.0345785612
[60,] 0.9662619 0.067476132 0.0337380659
[61,] 0.9675010 0.064997955 0.0324989773
[62,] 0.9658614 0.068277162 0.0341385811
[63,] 0.9648908 0.070218454 0.0351092269
[64,] 0.9599653 0.080069434 0.0400347171
[65,] 0.9516511 0.096697758 0.0483488788
[66,] 0.9417159 0.116568237 0.0582841187
[67,] 0.9322597 0.135480538 0.0677402692
[68,] 0.9216862 0.156627686 0.0783138429
[69,] 0.9271369 0.145726205 0.0728631026
[70,] 0.9233475 0.153305093 0.0766525465
[71,] 0.9391741 0.121651805 0.0608259026
[72,] 0.9350046 0.129990772 0.0649953860
[73,] 0.9427713 0.114457474 0.0572287370
[74,] 0.9327530 0.134494036 0.0672470179
[75,] 0.9305650 0.138869961 0.0694349807
[76,] 0.9180759 0.163848238 0.0819241192
[77,] 0.9045363 0.190927336 0.0954636682
[78,] 0.9205628 0.158874428 0.0794372138
[79,] 0.9067725 0.186454973 0.0932274863
[80,] 0.9120483 0.175903308 0.0879516538
[81,] 0.8977732 0.204453573 0.1022267867
[82,] 0.9129765 0.174046908 0.0870234541
[83,] 0.9213793 0.157241326 0.0786206631
[84,] 0.9109173 0.178165419 0.0890827097
[85,] 0.9031160 0.193768023 0.0968840114
[86,] 0.8875242 0.224951600 0.1124758002
[87,] 0.8720474 0.255905161 0.1279525806
[88,] 0.8889400 0.222119976 0.1110599881
[89,] 0.8719046 0.256190708 0.1280953540
[90,] 0.8738313 0.252337409 0.1261687044
[91,] 0.8662919 0.267416198 0.1337080989
[92,] 0.8472137 0.305572572 0.1527862862
[93,] 0.8419928 0.316014429 0.1580072145
[94,] 0.8394698 0.321060397 0.1605301984
[95,] 0.8610407 0.277918639 0.1389593193
[96,] 0.8563018 0.287396442 0.1436982209
[97,] 0.8384988 0.323002317 0.1615011586
[98,] 0.8228109 0.354378161 0.1771890805
[99,] 0.8132341 0.373531878 0.1867659390
[100,] 0.8604997 0.279000616 0.1395003081
[101,] 0.8473540 0.305291919 0.1526459596
[102,] 0.8656082 0.268783514 0.1343917570
[103,] 0.9249055 0.150189064 0.0750945321
[104,] 0.9229332 0.154133643 0.0770668215
[105,] 0.9252528 0.149494418 0.0747472089
[106,] 0.9134910 0.173017921 0.0865089603
[107,] 0.9320524 0.135895293 0.0679476466
[108,] 0.9287866 0.142426876 0.0712134380
[109,] 0.9170964 0.165807225 0.0829036124
[110,] 0.9251546 0.149690725 0.0748453623
[111,] 0.9156011 0.168797838 0.0843989190
[112,] 0.9032196 0.193560737 0.0967803687
[113,] 0.9281607 0.143678565 0.0718392826
[114,] 0.9214000 0.157200070 0.0786000349
[115,] 0.9095014 0.180997278 0.0904986389
[116,] 0.8989944 0.202011146 0.1010055729
[117,] 0.9071705 0.185658914 0.0928294568
[118,] 0.8965378 0.206924324 0.1034621622
[119,] 0.9125024 0.174995168 0.0874975839
[120,] 0.9032047 0.193590567 0.0967952835
[121,] 0.8941903 0.211619365 0.1058096823
[122,] 0.8790049 0.241990287 0.1209951433
[123,] 0.8800140 0.239972050 0.1199860248
[124,] 0.8725709 0.254858177 0.1274290885
[125,] 0.8652703 0.269459431 0.1347297154
[126,] 0.8573793 0.285241494 0.1426207471
[127,] 0.8647990 0.270401945 0.1352009726
[128,] 0.9433237 0.113352603 0.0566763015
[129,] 0.9434497 0.113100543 0.0565502717
[130,] 0.9350368 0.129926492 0.0649632462
[131,] 0.9446457 0.110708500 0.0553542500
[132,] 0.9409216 0.118156707 0.0590783533
[133,] 0.9392472 0.121505691 0.0607528456
[134,] 0.9421346 0.115730798 0.0578653988
[135,] 0.9629650 0.074069964 0.0370349818
[136,] 0.9631546 0.073690766 0.0368453829
[137,] 0.9784249 0.043150242 0.0215751209
[138,] 0.9744415 0.051117083 0.0255585416
[139,] 0.9743203 0.051359316 0.0256796581
[140,] 0.9704649 0.059070168 0.0295350840
[141,] 0.9659249 0.068150106 0.0340750530
[142,] 0.9610353 0.077929345 0.0389646723
[143,] 0.9678873 0.064225482 0.0321127411
[144,] 0.9642916 0.071416765 0.0357083824
[145,] 0.9585947 0.082810508 0.0414052539
[146,] 0.9548174 0.090365154 0.0451825771
[147,] 0.9490985 0.101803031 0.0509015156
[148,] 0.9413418 0.117316422 0.0586582108
[149,] 0.9363402 0.127319523 0.0636597616
[150,] 0.9307906 0.138418857 0.0692094286
[151,] 0.9266053 0.146789363 0.0733946817
[152,] 0.9227137 0.154572616 0.0772863080
[153,] 0.9121553 0.175689375 0.0878446874
[154,] 0.9263028 0.147394422 0.0736972111
[155,] 0.9656048 0.068790444 0.0343952221
[156,] 0.9632645 0.073471057 0.0367355284
[157,] 0.9807434 0.038513159 0.0192565796
[158,] 0.9819347 0.036130601 0.0180653007
[159,] 0.9785319 0.042936118 0.0214680588
[160,] 0.9851704 0.029659124 0.0148295618
[161,] 0.9824002 0.035199625 0.0175998126
[162,] 0.9790474 0.041905139 0.0209525697
[163,] 0.9782704 0.043459115 0.0217295576
[164,] 0.9771795 0.045640922 0.0228204608
[165,] 0.9731703 0.053659338 0.0268296692
[166,] 0.9762163 0.047567407 0.0237837036
[167,] 0.9838833 0.032233373 0.0161166864
[168,] 0.9831271 0.033745704 0.0168728520
[169,] 0.9809992 0.038001516 0.0190007581
[170,] 0.9783416 0.043316828 0.0216584142
[171,] 0.9760817 0.047836555 0.0239182777
[172,] 0.9808754 0.038249194 0.0191245971
[173,] 0.9782683 0.043463398 0.0217316992
[174,] 0.9742684 0.051463224 0.0257316119
[175,] 0.9706689 0.058662242 0.0293311208
[176,] 0.9665931 0.066813737 0.0334068684
[177,] 0.9624763 0.075047369 0.0375236844
[178,] 0.9566789 0.086642244 0.0433211222
[179,] 0.9666168 0.066766426 0.0333832130
[180,] 0.9854584 0.029083263 0.0145416313
[181,] 0.9881320 0.023735941 0.0118679704
[182,] 0.9859121 0.028175787 0.0140878935
[183,] 0.9833015 0.033397038 0.0166985192
[184,] 0.9815008 0.036998312 0.0184991561
[185,] 0.9788164 0.042367175 0.0211835877
[186,] 0.9795165 0.040966984 0.0204834918
[187,] 0.9782635 0.043472999 0.0217364995
[188,] 0.9772850 0.045430092 0.0227150460
[189,] 0.9774884 0.045023256 0.0225116279
[190,] 0.9741442 0.051711672 0.0258558362
[191,] 0.9802562 0.039487698 0.0197438488
[192,] 0.9850393 0.029921398 0.0149606990
[193,] 0.9844677 0.031064578 0.0155322892
[194,] 0.9822846 0.035430806 0.0177154029
[195,] 0.9785768 0.042846363 0.0214231814
[196,] 0.9758590 0.048281938 0.0241409692
[197,] 0.9730923 0.053815443 0.0269077215
[198,] 0.9796941 0.040611701 0.0203058507
[199,] 0.9783853 0.043229489 0.0216147443
[200,] 0.9794340 0.041132069 0.0205660345
[201,] 0.9780557 0.043888544 0.0219442719
[202,] 0.9780804 0.043839118 0.0219195590
[203,] 0.9850552 0.029889593 0.0149447964
[204,] 0.9894876 0.021024798 0.0105123989
[205,] 0.9908948 0.018210360 0.0091051802
[206,] 0.9900746 0.019850836 0.0099254180
[207,] 0.9881755 0.023648950 0.0118244750
[208,] 0.9862988 0.027402477 0.0137012385
[209,] 0.9834764 0.033047270 0.0165236350
[210,] 0.9878598 0.024280315 0.0121401577
[211,] 0.9854438 0.029112361 0.0145561803
[212,] 0.9842834 0.031433135 0.0157165674
[213,] 0.9822727 0.035454607 0.0177273037
[214,] 0.9786560 0.042687996 0.0213439980
[215,] 0.9842672 0.031465561 0.0157327805
[216,] 0.9831258 0.033748378 0.0168741890
[217,] 0.9800894 0.039821203 0.0199106014
[218,] 0.9768616 0.046276727 0.0231383636
[219,] 0.9764225 0.047155038 0.0235775191
[220,] 0.9795793 0.040841440 0.0204207202
[221,] 0.9794447 0.041110634 0.0205553170
[222,] 0.9882114 0.023577289 0.0117886444
[223,] 0.9878269 0.024346168 0.0121730842
[224,] 0.9853808 0.029238483 0.0146192413
[225,] 0.9824973 0.035005486 0.0175027432
[226,] 0.9795629 0.040874255 0.0204371274
[227,] 0.9872872 0.025425690 0.0127128452
[228,] 0.9883897 0.023220595 0.0116102977
[229,] 0.9875470 0.024905946 0.0124529729
[230,] 0.9845273 0.030945317 0.0154726584
[231,] 0.9817758 0.036448447 0.0182242233
[232,] 0.9798548 0.040290416 0.0201452080
[233,] 0.9791362 0.041727512 0.0208637562
[234,] 0.9890852 0.021829653 0.0109148263
[235,] 0.9863705 0.027259012 0.0136295059
[236,] 0.9854766 0.029046828 0.0145234141
[237,] 0.9849972 0.030005510 0.0150027551
[238,] 0.9821011 0.035797721 0.0178988606
[239,] 0.9854529 0.029094178 0.0145470892
[240,] 0.9820963 0.035807367 0.0179036837
[241,] 0.9780256 0.043948802 0.0219744012
[242,] 0.9758036 0.048392865 0.0241964324
[243,] 0.9703524 0.059295297 0.0296476484
[244,] 0.9855003 0.028999312 0.0144996560
[245,] 0.9828437 0.034312532 0.0171562660
[246,] 0.9801538 0.039692367 0.0198461836
[247,] 0.9826810 0.034637909 0.0173189546
[248,] 0.9818134 0.036373288 0.0181866442
[249,] 0.9799455 0.040109084 0.0200545418
[250,] 0.9751461 0.049707708 0.0248538538
[251,] 0.9800569 0.039886135 0.0199430673
[252,] 0.9755126 0.048974842 0.0244874211
[253,] 0.9698689 0.060262217 0.0301311086
[254,] 0.9677778 0.064444397 0.0322221985
[255,] 0.9643292 0.071341602 0.0356708009
[256,] 0.9575407 0.084918613 0.0424593066
[257,] 0.9484822 0.103035589 0.0515177944
[258,] 0.9534476 0.093104827 0.0465524136
[259,] 0.9436930 0.112614019 0.0563070097
[260,] 0.9361514 0.127697295 0.0638486474
[261,] 0.9272370 0.145525925 0.0727629623
[262,] 0.9131299 0.173740245 0.0868701226
[263,] 0.9180213 0.163957415 0.0819787074
[264,] 0.9042713 0.191457367 0.0957286837
[265,] 0.8898587 0.220282681 0.1101413403
[266,] 0.8746457 0.250708653 0.1253543264
[267,] 0.8540674 0.291865147 0.1459325733
[268,] 0.8364091 0.327181814 0.1635909068
[269,] 0.8136292 0.372741512 0.1863707559
[270,] 0.8309239 0.338152284 0.1690761420
[271,] 0.8060208 0.387958415 0.1939792077
[272,] 0.8074972 0.385005552 0.1925027759
[273,] 0.7871155 0.425768955 0.2128844775
[274,] 0.7624251 0.475149795 0.2375748976
[275,] 0.7642363 0.471527473 0.2357637365
[276,] 0.7325960 0.534807979 0.2674039897
[277,] 0.6993797 0.601240645 0.3006203224
[278,] 0.6666035 0.666792908 0.3333964542
[279,] 0.6292278 0.741544404 0.3707722022
[280,] 0.7090340 0.581932049 0.2909660246
[281,] 0.6912259 0.617548185 0.3087740926
[282,] 0.7717080 0.456584081 0.2282920403
[283,] 0.7477795 0.504440966 0.2522204831
[284,] 0.7238238 0.552352337 0.2761761683
[285,] 0.7189473 0.562105427 0.2810527137
[286,] 0.6986502 0.602699677 0.3013498384
[287,] 0.7357042 0.528591531 0.2642957656
[288,] 0.7244295 0.551141019 0.2755705097
[289,] 0.6868462 0.626307683 0.3131538413
[290,] 0.6477277 0.704544671 0.3522723356
[291,] 0.6648658 0.670268445 0.3351342226
[292,] 0.6336726 0.732654862 0.3663274311
[293,] 0.5948032 0.810393521 0.4051967603
[294,] 0.6935759 0.612848279 0.3064241395
[295,] 0.6666703 0.666659306 0.3333296529
[296,] 0.6622761 0.675447788 0.3377238938
[297,] 0.6188175 0.762364949 0.3811824743
[298,] 0.5763332 0.847333696 0.4236668482
[299,] 0.6255916 0.748816857 0.3744084283
[300,] 0.6780485 0.643902908 0.3219514538
[301,] 0.8281470 0.343706099 0.1718530493
[302,] 0.8136514 0.372697215 0.1863486076
[303,] 0.8959047 0.208190573 0.1040952864
[304,] 0.9516433 0.096713442 0.0483567209
[305,] 0.9783108 0.043378398 0.0216891990
[306,] 0.9937205 0.012559048 0.0062795238
[307,] 0.9913346 0.017330751 0.0086653757
[308,] 0.9872862 0.025427500 0.0127137500
[309,] 0.9846249 0.030750218 0.0153751092
[310,] 0.9882535 0.023492946 0.0117464731
[311,] 0.9833754 0.033249106 0.0166245529
[312,] 0.9812653 0.037469331 0.0187346657
[313,] 0.9820735 0.035853051 0.0179265256
[314,] 0.9730858 0.053828495 0.0269142475
[315,] 0.9602307 0.079538594 0.0397692968
[316,] 0.9587769 0.082446192 0.0412230958
[317,] 0.9422994 0.115401155 0.0577005774
[318,] 0.9248880 0.150224007 0.0751120035
[319,] 0.9147862 0.170427544 0.0852137721
[320,] 0.9372001 0.125599733 0.0627998663
[321,] 0.9089091 0.182181743 0.0910908713
[322,] 0.9034683 0.193063463 0.0965317317
[323,] 0.8825436 0.234912812 0.1174564058
[324,] 0.8373011 0.325397816 0.1626989078
[325,] 0.7760318 0.447936453 0.2239682265
[326,] 0.7221511 0.555697752 0.2778488758
[327,] 0.6459920 0.708016002 0.3540080012
[328,] 0.5476098 0.904780387 0.4523901934
[329,] 0.4708626 0.941725133 0.5291374336
[330,] 0.3845252 0.769050483 0.6154747584
[331,] 0.5347667 0.930466571 0.4652332854
[332,] 0.6250801 0.749839774 0.3749198872
[333,] 0.5572869 0.885426214 0.4427131070
> postscript(file="/var/www/html/freestat/rcomp/tmp/1m7gq1291149891.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/2m7gq1291149891.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/3fzgt1291149891.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/4fzgt1291149891.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/5fzgt1291149891.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 = 372
Frequency = 1
1 2 3 4 5 6
150.66972823 22.76759948 -15.24175343 5.86131346 -21.05291426 -33.82184406
7 8 9 10 11 12
26.25369060 16.12121498 -3.35527967 -18.14062111 6.96143149 15.86941535
13 14 15 16 17 18
-1.45939424 36.60942716 11.74577346 25.23773102 43.03734743 -29.83122574
19 20 21 22 23 24
65.21179232 -8.64546976 -14.83461488 37.03940006 -37.46817261 14.87623275
25 26 27 28 29 30
25.53306814 9.53112786 -21.61370529 -19.30200751 -10.11311874 -34.69087578
31 32 33 34 35 36
8.06815996 -31.11428953 10.00975551 -22.85911006 10.68435072 5.54553169
37 38 39 40 41 42
-55.36933208 -18.72481017 6.65062831 2.20671968 1.96872768 -39.01408413
43 44 45 46 47 48
15.73892318 4.59476266 21.12892026 -2.53470406 -3.43584406 -24.59719617
49 50 51 52 53 54
-33.99680571 0.08477499 -10.24087893 20.54711459 11.75122314 -53.72005533
55 56 57 58 59 60
25.16510042 14.24892922 -7.65515212 -14.48011427 -13.20583760 -8.83091240
61 62 63 64 65 66
-22.19166233 -28.14543951 8.23876400 30.70642881 -8.79965978 -60.85271362
67 68 69 70 71 72
18.35347732 11.10155459 21.43168940 3.04262212 14.79758335 26.05848251
73 74 75 76 77 78
33.79016714 25.25592024 21.26263028 15.53458128 -0.40378094 -69.99580664
79 80 81 82 83 84
28.49670228 18.73216099 14.29203407 -35.07014674 -1.05600786 -7.62238813
85 86 87 88 89 90
-9.88041915 -16.51759353 -1.41104890 28.35247618 -26.79264943 -53.45794657
91 92 93 94 95 96
4.04722558 23.35122609 -4.14674827 6.41121772 0.83708855 1.51068119
97 98 99 100 101 102
-34.75678938 -7.23909275 24.73397049 -0.91528018 25.57352869 -38.03673442
103 104 105 106 107 108
0.96160171 -18.97388606 -2.23451644 -2.50985676 27.43282190 0.42513373
109 110 111 112 113 114
-29.47461195 -23.15657881 -2.07115781 20.30014669 18.85172378 -28.28542380
115 116 117 118 119 120
-9.42632541 -0.30027210 13.86711631 8.88236414 40.06717822 12.96025663
121 122 123 124 125 126
27.83683407 51.61399232 21.76260693 25.69152504 -3.13317117 -31.19779810
127 128 129 130 131 132
17.66815391 -9.03311466 -31.61770102 -6.93449157 -9.31995202 32.55458288
133 134 135 136 137 138
-14.38376264 -6.13040263 -13.07874874 -30.26241477 3.18673436 -22.00839616
139 140 141 142 143 144
8.27919110 7.95986248 1.54811040 18.06543761 17.20668871 -16.39337307
145 146 147 148 149 150
-20.26136860 -30.15766960 54.61376727 -15.20510505 -5.41439037 7.50507326
151 152 153 154 155 156
-5.23313757 13.95651119 -22.21054336 37.97598838 21.62866242 44.54415841
157 158 159 160 161 162
3.82537669 19.62822472 0.53891224 -12.10619045 4.34435087 -1.92865020
163 164 165 166 167 168
-6.77282029 -14.96040534 -16.91996977 5.37003093 -8.49079341 11.25854549
169 170 171 172 173 174
-18.12803089 -21.23930998 11.28801247 -3.29007316 30.49524115 -46.04990793
175 176 177 178 179 180
-15.91771989 37.69811193 -20.34762231 -8.58174479 28.78107993 0.70712980
181 182 183 184 185 186
4.87110826 13.98173545 -20.92761821 -5.39060866 19.29300604 -10.94217792
187 188 189 190 191 192
-18.60210425 -4.78227952 -8.40238641 9.57431458 24.97546433 -11.39733916
193 194 195 196 197 198
-8.38284780 -14.41123624 0.67182035 1.34747223 -9.45471822 19.93732899
199 200 201 202 203 204
-55.39788008 19.02994457 -8.63628496 7.58980142 -11.36077549 4.89824593
205 206 207 208 209 210
-27.21330739 12.50335755 -24.90587377 16.72483762 -8.12173856 8.43709810
211 212 213 214 215 216
-42.46150160 3.42644691 -14.30426478 0.22680124 -6.31828958 -15.75014349
217 218 219 220 221 222
-36.50672352 -24.38599766 10.50734252 10.14698604 20.01632629 -1.04354718
223 224 225 226 227 228
-39.54589435 3.96177435 -16.65681620 7.35931412 -15.04154896 0.67324531
229 230 231 232 233 234
-34.54448017 -11.42555265 -2.97669729 5.48443658 -6.43266852 37.23204627
235 236 237 238 239 240
-23.16942502 -8.41990385 8.09634254 16.22233817 -33.67518564 -26.03918009
241 242 243 244 245 246
-44.93235579 11.45274282 -14.83277302 -10.61580125 -3.42134922 52.34576698
247 248 249 250 251 252
-26.42985043 -24.31780616 -3.82101212 1.98911294 -21.18721316 -23.89208101
253 254 255 256 257 258
-37.27297365 -7.63780977 1.62742853 11.82520162 -12.66557013 26.96800537
259 260 261 262 263 264
-6.93196094 -10.26466563 18.77371503 -3.34791154 -43.18493912 -15.21728751
265 266 267 268 269 270
-2.89181673 25.06414266 9.22341862 11.60504086 -4.44663082 48.90481843
271 272 273 274 275 276
-0.16013535 -6.43482410 20.48521048 9.45356634 8.96116894 -2.10622749
277 278 279 280 281 282
-2.72412948 -6.56306792 -3.07758656 -7.48637453 -7.89472634 38.59757571
283 284 285 286 287 288
6.35574460 0.97009083 -5.67805123 -10.51489608 4.73675905 -12.13117370
289 290 291 292 293 294
-2.39722433 -10.85501786 4.65997803 -11.16423128 -13.93454161 37.27297335
295 296 297 298 299 300
-2.72867810 -3.65025259 -3.11304803 -2.73379570 -41.70916360 -15.04294975
301 302 303 304 305 306
-18.90854716 9.57242530 -10.69645413 3.02294866 -18.89212977 29.87378832
307 308 309 310 311 312
-9.67674424 -8.15065871 10.50043456 -27.17143276 4.87959993 -2.88359244
313 314 315 316 317 318
13.07857115 0.24859956 -19.98753824 -8.34156695 4.63818476 49.36276221
319 320 321 322 323 324
5.86308567 -13.48062563 46.23642358 -2.28746030 37.93109836 37.97252616
325 326 327 328 329 330
124.53300333 -3.56203912 20.35712351 -10.50106303 8.87293453 33.00205827
331 332 333 334 335 336
-3.60883551 -11.20085783 12.02437889 0.21751311 -12.45857198 5.70572221
337 338 339 340 341 342
30.46856125 -14.92169901 -20.35296302 -12.75969878 -25.69790865 74.05236238
343 344 345 346 347 348
22.47521161 5.91712718 -8.55706399 3.54855367 13.13597915 -1.74085627
349 350 351 352 353 354
10.90042725 24.52178453 -26.23426508 -52.32070148 -8.22381266 71.17453095
355 356 357 358 359 360
-22.66595455 13.79198725 -8.71597190 -0.73191494 -2.98083212 -42.79644064
361 362 363 364 365 366
30.16973747 -17.76253744 -0.23311460 -34.93384329 2.86615045 20.21099900
367 368 369 370 371 372
35.79090734 -21.13239374 2.81291647 -15.07017588 -2.12382785 10.88125130
> postscript(file="/var/www/html/freestat/rcomp/tmp/67qfw1291149891.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 = 372
Frequency = 1
lag(myerror, k = 1) myerror
0 150.66972823 NA
1 22.76759948 150.66972823
2 -15.24175343 22.76759948
3 5.86131346 -15.24175343
4 -21.05291426 5.86131346
5 -33.82184406 -21.05291426
6 26.25369060 -33.82184406
7 16.12121498 26.25369060
8 -3.35527967 16.12121498
9 -18.14062111 -3.35527967
10 6.96143149 -18.14062111
11 15.86941535 6.96143149
12 -1.45939424 15.86941535
13 36.60942716 -1.45939424
14 11.74577346 36.60942716
15 25.23773102 11.74577346
16 43.03734743 25.23773102
17 -29.83122574 43.03734743
18 65.21179232 -29.83122574
19 -8.64546976 65.21179232
20 -14.83461488 -8.64546976
21 37.03940006 -14.83461488
22 -37.46817261 37.03940006
23 14.87623275 -37.46817261
24 25.53306814 14.87623275
25 9.53112786 25.53306814
26 -21.61370529 9.53112786
27 -19.30200751 -21.61370529
28 -10.11311874 -19.30200751
29 -34.69087578 -10.11311874
30 8.06815996 -34.69087578
31 -31.11428953 8.06815996
32 10.00975551 -31.11428953
33 -22.85911006 10.00975551
34 10.68435072 -22.85911006
35 5.54553169 10.68435072
36 -55.36933208 5.54553169
37 -18.72481017 -55.36933208
38 6.65062831 -18.72481017
39 2.20671968 6.65062831
40 1.96872768 2.20671968
41 -39.01408413 1.96872768
42 15.73892318 -39.01408413
43 4.59476266 15.73892318
44 21.12892026 4.59476266
45 -2.53470406 21.12892026
46 -3.43584406 -2.53470406
47 -24.59719617 -3.43584406
48 -33.99680571 -24.59719617
49 0.08477499 -33.99680571
50 -10.24087893 0.08477499
51 20.54711459 -10.24087893
52 11.75122314 20.54711459
53 -53.72005533 11.75122314
54 25.16510042 -53.72005533
55 14.24892922 25.16510042
56 -7.65515212 14.24892922
57 -14.48011427 -7.65515212
58 -13.20583760 -14.48011427
59 -8.83091240 -13.20583760
60 -22.19166233 -8.83091240
61 -28.14543951 -22.19166233
62 8.23876400 -28.14543951
63 30.70642881 8.23876400
64 -8.79965978 30.70642881
65 -60.85271362 -8.79965978
66 18.35347732 -60.85271362
67 11.10155459 18.35347732
68 21.43168940 11.10155459
69 3.04262212 21.43168940
70 14.79758335 3.04262212
71 26.05848251 14.79758335
72 33.79016714 26.05848251
73 25.25592024 33.79016714
74 21.26263028 25.25592024
75 15.53458128 21.26263028
76 -0.40378094 15.53458128
77 -69.99580664 -0.40378094
78 28.49670228 -69.99580664
79 18.73216099 28.49670228
80 14.29203407 18.73216099
81 -35.07014674 14.29203407
82 -1.05600786 -35.07014674
83 -7.62238813 -1.05600786
84 -9.88041915 -7.62238813
85 -16.51759353 -9.88041915
86 -1.41104890 -16.51759353
87 28.35247618 -1.41104890
88 -26.79264943 28.35247618
89 -53.45794657 -26.79264943
90 4.04722558 -53.45794657
91 23.35122609 4.04722558
92 -4.14674827 23.35122609
93 6.41121772 -4.14674827
94 0.83708855 6.41121772
95 1.51068119 0.83708855
96 -34.75678938 1.51068119
97 -7.23909275 -34.75678938
98 24.73397049 -7.23909275
99 -0.91528018 24.73397049
100 25.57352869 -0.91528018
101 -38.03673442 25.57352869
102 0.96160171 -38.03673442
103 -18.97388606 0.96160171
104 -2.23451644 -18.97388606
105 -2.50985676 -2.23451644
106 27.43282190 -2.50985676
107 0.42513373 27.43282190
108 -29.47461195 0.42513373
109 -23.15657881 -29.47461195
110 -2.07115781 -23.15657881
111 20.30014669 -2.07115781
112 18.85172378 20.30014669
113 -28.28542380 18.85172378
114 -9.42632541 -28.28542380
115 -0.30027210 -9.42632541
116 13.86711631 -0.30027210
117 8.88236414 13.86711631
118 40.06717822 8.88236414
119 12.96025663 40.06717822
120 27.83683407 12.96025663
121 51.61399232 27.83683407
122 21.76260693 51.61399232
123 25.69152504 21.76260693
124 -3.13317117 25.69152504
125 -31.19779810 -3.13317117
126 17.66815391 -31.19779810
127 -9.03311466 17.66815391
128 -31.61770102 -9.03311466
129 -6.93449157 -31.61770102
130 -9.31995202 -6.93449157
131 32.55458288 -9.31995202
132 -14.38376264 32.55458288
133 -6.13040263 -14.38376264
134 -13.07874874 -6.13040263
135 -30.26241477 -13.07874874
136 3.18673436 -30.26241477
137 -22.00839616 3.18673436
138 8.27919110 -22.00839616
139 7.95986248 8.27919110
140 1.54811040 7.95986248
141 18.06543761 1.54811040
142 17.20668871 18.06543761
143 -16.39337307 17.20668871
144 -20.26136860 -16.39337307
145 -30.15766960 -20.26136860
146 54.61376727 -30.15766960
147 -15.20510505 54.61376727
148 -5.41439037 -15.20510505
149 7.50507326 -5.41439037
150 -5.23313757 7.50507326
151 13.95651119 -5.23313757
152 -22.21054336 13.95651119
153 37.97598838 -22.21054336
154 21.62866242 37.97598838
155 44.54415841 21.62866242
156 3.82537669 44.54415841
157 19.62822472 3.82537669
158 0.53891224 19.62822472
159 -12.10619045 0.53891224
160 4.34435087 -12.10619045
161 -1.92865020 4.34435087
162 -6.77282029 -1.92865020
163 -14.96040534 -6.77282029
164 -16.91996977 -14.96040534
165 5.37003093 -16.91996977
166 -8.49079341 5.37003093
167 11.25854549 -8.49079341
168 -18.12803089 11.25854549
169 -21.23930998 -18.12803089
170 11.28801247 -21.23930998
171 -3.29007316 11.28801247
172 30.49524115 -3.29007316
173 -46.04990793 30.49524115
174 -15.91771989 -46.04990793
175 37.69811193 -15.91771989
176 -20.34762231 37.69811193
177 -8.58174479 -20.34762231
178 28.78107993 -8.58174479
179 0.70712980 28.78107993
180 4.87110826 0.70712980
181 13.98173545 4.87110826
182 -20.92761821 13.98173545
183 -5.39060866 -20.92761821
184 19.29300604 -5.39060866
185 -10.94217792 19.29300604
186 -18.60210425 -10.94217792
187 -4.78227952 -18.60210425
188 -8.40238641 -4.78227952
189 9.57431458 -8.40238641
190 24.97546433 9.57431458
191 -11.39733916 24.97546433
192 -8.38284780 -11.39733916
193 -14.41123624 -8.38284780
194 0.67182035 -14.41123624
195 1.34747223 0.67182035
196 -9.45471822 1.34747223
197 19.93732899 -9.45471822
198 -55.39788008 19.93732899
199 19.02994457 -55.39788008
200 -8.63628496 19.02994457
201 7.58980142 -8.63628496
202 -11.36077549 7.58980142
203 4.89824593 -11.36077549
204 -27.21330739 4.89824593
205 12.50335755 -27.21330739
206 -24.90587377 12.50335755
207 16.72483762 -24.90587377
208 -8.12173856 16.72483762
209 8.43709810 -8.12173856
210 -42.46150160 8.43709810
211 3.42644691 -42.46150160
212 -14.30426478 3.42644691
213 0.22680124 -14.30426478
214 -6.31828958 0.22680124
215 -15.75014349 -6.31828958
216 -36.50672352 -15.75014349
217 -24.38599766 -36.50672352
218 10.50734252 -24.38599766
219 10.14698604 10.50734252
220 20.01632629 10.14698604
221 -1.04354718 20.01632629
222 -39.54589435 -1.04354718
223 3.96177435 -39.54589435
224 -16.65681620 3.96177435
225 7.35931412 -16.65681620
226 -15.04154896 7.35931412
227 0.67324531 -15.04154896
228 -34.54448017 0.67324531
229 -11.42555265 -34.54448017
230 -2.97669729 -11.42555265
231 5.48443658 -2.97669729
232 -6.43266852 5.48443658
233 37.23204627 -6.43266852
234 -23.16942502 37.23204627
235 -8.41990385 -23.16942502
236 8.09634254 -8.41990385
237 16.22233817 8.09634254
238 -33.67518564 16.22233817
239 -26.03918009 -33.67518564
240 -44.93235579 -26.03918009
241 11.45274282 -44.93235579
242 -14.83277302 11.45274282
243 -10.61580125 -14.83277302
244 -3.42134922 -10.61580125
245 52.34576698 -3.42134922
246 -26.42985043 52.34576698
247 -24.31780616 -26.42985043
248 -3.82101212 -24.31780616
249 1.98911294 -3.82101212
250 -21.18721316 1.98911294
251 -23.89208101 -21.18721316
252 -37.27297365 -23.89208101
253 -7.63780977 -37.27297365
254 1.62742853 -7.63780977
255 11.82520162 1.62742853
256 -12.66557013 11.82520162
257 26.96800537 -12.66557013
258 -6.93196094 26.96800537
259 -10.26466563 -6.93196094
260 18.77371503 -10.26466563
261 -3.34791154 18.77371503
262 -43.18493912 -3.34791154
263 -15.21728751 -43.18493912
264 -2.89181673 -15.21728751
265 25.06414266 -2.89181673
266 9.22341862 25.06414266
267 11.60504086 9.22341862
268 -4.44663082 11.60504086
269 48.90481843 -4.44663082
270 -0.16013535 48.90481843
271 -6.43482410 -0.16013535
272 20.48521048 -6.43482410
273 9.45356634 20.48521048
274 8.96116894 9.45356634
275 -2.10622749 8.96116894
276 -2.72412948 -2.10622749
277 -6.56306792 -2.72412948
278 -3.07758656 -6.56306792
279 -7.48637453 -3.07758656
280 -7.89472634 -7.48637453
281 38.59757571 -7.89472634
282 6.35574460 38.59757571
283 0.97009083 6.35574460
284 -5.67805123 0.97009083
285 -10.51489608 -5.67805123
286 4.73675905 -10.51489608
287 -12.13117370 4.73675905
288 -2.39722433 -12.13117370
289 -10.85501786 -2.39722433
290 4.65997803 -10.85501786
291 -11.16423128 4.65997803
292 -13.93454161 -11.16423128
293 37.27297335 -13.93454161
294 -2.72867810 37.27297335
295 -3.65025259 -2.72867810
296 -3.11304803 -3.65025259
297 -2.73379570 -3.11304803
298 -41.70916360 -2.73379570
299 -15.04294975 -41.70916360
300 -18.90854716 -15.04294975
301 9.57242530 -18.90854716
302 -10.69645413 9.57242530
303 3.02294866 -10.69645413
304 -18.89212977 3.02294866
305 29.87378832 -18.89212977
306 -9.67674424 29.87378832
307 -8.15065871 -9.67674424
308 10.50043456 -8.15065871
309 -27.17143276 10.50043456
310 4.87959993 -27.17143276
311 -2.88359244 4.87959993
312 13.07857115 -2.88359244
313 0.24859956 13.07857115
314 -19.98753824 0.24859956
315 -8.34156695 -19.98753824
316 4.63818476 -8.34156695
317 49.36276221 4.63818476
318 5.86308567 49.36276221
319 -13.48062563 5.86308567
320 46.23642358 -13.48062563
321 -2.28746030 46.23642358
322 37.93109836 -2.28746030
323 37.97252616 37.93109836
324 124.53300333 37.97252616
325 -3.56203912 124.53300333
326 20.35712351 -3.56203912
327 -10.50106303 20.35712351
328 8.87293453 -10.50106303
329 33.00205827 8.87293453
330 -3.60883551 33.00205827
331 -11.20085783 -3.60883551
332 12.02437889 -11.20085783
333 0.21751311 12.02437889
334 -12.45857198 0.21751311
335 5.70572221 -12.45857198
336 30.46856125 5.70572221
337 -14.92169901 30.46856125
338 -20.35296302 -14.92169901
339 -12.75969878 -20.35296302
340 -25.69790865 -12.75969878
341 74.05236238 -25.69790865
342 22.47521161 74.05236238
343 5.91712718 22.47521161
344 -8.55706399 5.91712718
345 3.54855367 -8.55706399
346 13.13597915 3.54855367
347 -1.74085627 13.13597915
348 10.90042725 -1.74085627
349 24.52178453 10.90042725
350 -26.23426508 24.52178453
351 -52.32070148 -26.23426508
352 -8.22381266 -52.32070148
353 71.17453095 -8.22381266
354 -22.66595455 71.17453095
355 13.79198725 -22.66595455
356 -8.71597190 13.79198725
357 -0.73191494 -8.71597190
358 -2.98083212 -0.73191494
359 -42.79644064 -2.98083212
360 30.16973747 -42.79644064
361 -17.76253744 30.16973747
362 -0.23311460 -17.76253744
363 -34.93384329 -0.23311460
364 2.86615045 -34.93384329
365 20.21099900 2.86615045
366 35.79090734 20.21099900
367 -21.13239374 35.79090734
368 2.81291647 -21.13239374
369 -15.07017588 2.81291647
370 -2.12382785 -15.07017588
371 10.88125130 -2.12382785
372 NA 10.88125130
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 22.76759948 150.66972823
[2,] -15.24175343 22.76759948
[3,] 5.86131346 -15.24175343
[4,] -21.05291426 5.86131346
[5,] -33.82184406 -21.05291426
[6,] 26.25369060 -33.82184406
[7,] 16.12121498 26.25369060
[8,] -3.35527967 16.12121498
[9,] -18.14062111 -3.35527967
[10,] 6.96143149 -18.14062111
[11,] 15.86941535 6.96143149
[12,] -1.45939424 15.86941535
[13,] 36.60942716 -1.45939424
[14,] 11.74577346 36.60942716
[15,] 25.23773102 11.74577346
[16,] 43.03734743 25.23773102
[17,] -29.83122574 43.03734743
[18,] 65.21179232 -29.83122574
[19,] -8.64546976 65.21179232
[20,] -14.83461488 -8.64546976
[21,] 37.03940006 -14.83461488
[22,] -37.46817261 37.03940006
[23,] 14.87623275 -37.46817261
[24,] 25.53306814 14.87623275
[25,] 9.53112786 25.53306814
[26,] -21.61370529 9.53112786
[27,] -19.30200751 -21.61370529
[28,] -10.11311874 -19.30200751
[29,] -34.69087578 -10.11311874
[30,] 8.06815996 -34.69087578
[31,] -31.11428953 8.06815996
[32,] 10.00975551 -31.11428953
[33,] -22.85911006 10.00975551
[34,] 10.68435072 -22.85911006
[35,] 5.54553169 10.68435072
[36,] -55.36933208 5.54553169
[37,] -18.72481017 -55.36933208
[38,] 6.65062831 -18.72481017
[39,] 2.20671968 6.65062831
[40,] 1.96872768 2.20671968
[41,] -39.01408413 1.96872768
[42,] 15.73892318 -39.01408413
[43,] 4.59476266 15.73892318
[44,] 21.12892026 4.59476266
[45,] -2.53470406 21.12892026
[46,] -3.43584406 -2.53470406
[47,] -24.59719617 -3.43584406
[48,] -33.99680571 -24.59719617
[49,] 0.08477499 -33.99680571
[50,] -10.24087893 0.08477499
[51,] 20.54711459 -10.24087893
[52,] 11.75122314 20.54711459
[53,] -53.72005533 11.75122314
[54,] 25.16510042 -53.72005533
[55,] 14.24892922 25.16510042
[56,] -7.65515212 14.24892922
[57,] -14.48011427 -7.65515212
[58,] -13.20583760 -14.48011427
[59,] -8.83091240 -13.20583760
[60,] -22.19166233 -8.83091240
[61,] -28.14543951 -22.19166233
[62,] 8.23876400 -28.14543951
[63,] 30.70642881 8.23876400
[64,] -8.79965978 30.70642881
[65,] -60.85271362 -8.79965978
[66,] 18.35347732 -60.85271362
[67,] 11.10155459 18.35347732
[68,] 21.43168940 11.10155459
[69,] 3.04262212 21.43168940
[70,] 14.79758335 3.04262212
[71,] 26.05848251 14.79758335
[72,] 33.79016714 26.05848251
[73,] 25.25592024 33.79016714
[74,] 21.26263028 25.25592024
[75,] 15.53458128 21.26263028
[76,] -0.40378094 15.53458128
[77,] -69.99580664 -0.40378094
[78,] 28.49670228 -69.99580664
[79,] 18.73216099 28.49670228
[80,] 14.29203407 18.73216099
[81,] -35.07014674 14.29203407
[82,] -1.05600786 -35.07014674
[83,] -7.62238813 -1.05600786
[84,] -9.88041915 -7.62238813
[85,] -16.51759353 -9.88041915
[86,] -1.41104890 -16.51759353
[87,] 28.35247618 -1.41104890
[88,] -26.79264943 28.35247618
[89,] -53.45794657 -26.79264943
[90,] 4.04722558 -53.45794657
[91,] 23.35122609 4.04722558
[92,] -4.14674827 23.35122609
[93,] 6.41121772 -4.14674827
[94,] 0.83708855 6.41121772
[95,] 1.51068119 0.83708855
[96,] -34.75678938 1.51068119
[97,] -7.23909275 -34.75678938
[98,] 24.73397049 -7.23909275
[99,] -0.91528018 24.73397049
[100,] 25.57352869 -0.91528018
[101,] -38.03673442 25.57352869
[102,] 0.96160171 -38.03673442
[103,] -18.97388606 0.96160171
[104,] -2.23451644 -18.97388606
[105,] -2.50985676 -2.23451644
[106,] 27.43282190 -2.50985676
[107,] 0.42513373 27.43282190
[108,] -29.47461195 0.42513373
[109,] -23.15657881 -29.47461195
[110,] -2.07115781 -23.15657881
[111,] 20.30014669 -2.07115781
[112,] 18.85172378 20.30014669
[113,] -28.28542380 18.85172378
[114,] -9.42632541 -28.28542380
[115,] -0.30027210 -9.42632541
[116,] 13.86711631 -0.30027210
[117,] 8.88236414 13.86711631
[118,] 40.06717822 8.88236414
[119,] 12.96025663 40.06717822
[120,] 27.83683407 12.96025663
[121,] 51.61399232 27.83683407
[122,] 21.76260693 51.61399232
[123,] 25.69152504 21.76260693
[124,] -3.13317117 25.69152504
[125,] -31.19779810 -3.13317117
[126,] 17.66815391 -31.19779810
[127,] -9.03311466 17.66815391
[128,] -31.61770102 -9.03311466
[129,] -6.93449157 -31.61770102
[130,] -9.31995202 -6.93449157
[131,] 32.55458288 -9.31995202
[132,] -14.38376264 32.55458288
[133,] -6.13040263 -14.38376264
[134,] -13.07874874 -6.13040263
[135,] -30.26241477 -13.07874874
[136,] 3.18673436 -30.26241477
[137,] -22.00839616 3.18673436
[138,] 8.27919110 -22.00839616
[139,] 7.95986248 8.27919110
[140,] 1.54811040 7.95986248
[141,] 18.06543761 1.54811040
[142,] 17.20668871 18.06543761
[143,] -16.39337307 17.20668871
[144,] -20.26136860 -16.39337307
[145,] -30.15766960 -20.26136860
[146,] 54.61376727 -30.15766960
[147,] -15.20510505 54.61376727
[148,] -5.41439037 -15.20510505
[149,] 7.50507326 -5.41439037
[150,] -5.23313757 7.50507326
[151,] 13.95651119 -5.23313757
[152,] -22.21054336 13.95651119
[153,] 37.97598838 -22.21054336
[154,] 21.62866242 37.97598838
[155,] 44.54415841 21.62866242
[156,] 3.82537669 44.54415841
[157,] 19.62822472 3.82537669
[158,] 0.53891224 19.62822472
[159,] -12.10619045 0.53891224
[160,] 4.34435087 -12.10619045
[161,] -1.92865020 4.34435087
[162,] -6.77282029 -1.92865020
[163,] -14.96040534 -6.77282029
[164,] -16.91996977 -14.96040534
[165,] 5.37003093 -16.91996977
[166,] -8.49079341 5.37003093
[167,] 11.25854549 -8.49079341
[168,] -18.12803089 11.25854549
[169,] -21.23930998 -18.12803089
[170,] 11.28801247 -21.23930998
[171,] -3.29007316 11.28801247
[172,] 30.49524115 -3.29007316
[173,] -46.04990793 30.49524115
[174,] -15.91771989 -46.04990793
[175,] 37.69811193 -15.91771989
[176,] -20.34762231 37.69811193
[177,] -8.58174479 -20.34762231
[178,] 28.78107993 -8.58174479
[179,] 0.70712980 28.78107993
[180,] 4.87110826 0.70712980
[181,] 13.98173545 4.87110826
[182,] -20.92761821 13.98173545
[183,] -5.39060866 -20.92761821
[184,] 19.29300604 -5.39060866
[185,] -10.94217792 19.29300604
[186,] -18.60210425 -10.94217792
[187,] -4.78227952 -18.60210425
[188,] -8.40238641 -4.78227952
[189,] 9.57431458 -8.40238641
[190,] 24.97546433 9.57431458
[191,] -11.39733916 24.97546433
[192,] -8.38284780 -11.39733916
[193,] -14.41123624 -8.38284780
[194,] 0.67182035 -14.41123624
[195,] 1.34747223 0.67182035
[196,] -9.45471822 1.34747223
[197,] 19.93732899 -9.45471822
[198,] -55.39788008 19.93732899
[199,] 19.02994457 -55.39788008
[200,] -8.63628496 19.02994457
[201,] 7.58980142 -8.63628496
[202,] -11.36077549 7.58980142
[203,] 4.89824593 -11.36077549
[204,] -27.21330739 4.89824593
[205,] 12.50335755 -27.21330739
[206,] -24.90587377 12.50335755
[207,] 16.72483762 -24.90587377
[208,] -8.12173856 16.72483762
[209,] 8.43709810 -8.12173856
[210,] -42.46150160 8.43709810
[211,] 3.42644691 -42.46150160
[212,] -14.30426478 3.42644691
[213,] 0.22680124 -14.30426478
[214,] -6.31828958 0.22680124
[215,] -15.75014349 -6.31828958
[216,] -36.50672352 -15.75014349
[217,] -24.38599766 -36.50672352
[218,] 10.50734252 -24.38599766
[219,] 10.14698604 10.50734252
[220,] 20.01632629 10.14698604
[221,] -1.04354718 20.01632629
[222,] -39.54589435 -1.04354718
[223,] 3.96177435 -39.54589435
[224,] -16.65681620 3.96177435
[225,] 7.35931412 -16.65681620
[226,] -15.04154896 7.35931412
[227,] 0.67324531 -15.04154896
[228,] -34.54448017 0.67324531
[229,] -11.42555265 -34.54448017
[230,] -2.97669729 -11.42555265
[231,] 5.48443658 -2.97669729
[232,] -6.43266852 5.48443658
[233,] 37.23204627 -6.43266852
[234,] -23.16942502 37.23204627
[235,] -8.41990385 -23.16942502
[236,] 8.09634254 -8.41990385
[237,] 16.22233817 8.09634254
[238,] -33.67518564 16.22233817
[239,] -26.03918009 -33.67518564
[240,] -44.93235579 -26.03918009
[241,] 11.45274282 -44.93235579
[242,] -14.83277302 11.45274282
[243,] -10.61580125 -14.83277302
[244,] -3.42134922 -10.61580125
[245,] 52.34576698 -3.42134922
[246,] -26.42985043 52.34576698
[247,] -24.31780616 -26.42985043
[248,] -3.82101212 -24.31780616
[249,] 1.98911294 -3.82101212
[250,] -21.18721316 1.98911294
[251,] -23.89208101 -21.18721316
[252,] -37.27297365 -23.89208101
[253,] -7.63780977 -37.27297365
[254,] 1.62742853 -7.63780977
[255,] 11.82520162 1.62742853
[256,] -12.66557013 11.82520162
[257,] 26.96800537 -12.66557013
[258,] -6.93196094 26.96800537
[259,] -10.26466563 -6.93196094
[260,] 18.77371503 -10.26466563
[261,] -3.34791154 18.77371503
[262,] -43.18493912 -3.34791154
[263,] -15.21728751 -43.18493912
[264,] -2.89181673 -15.21728751
[265,] 25.06414266 -2.89181673
[266,] 9.22341862 25.06414266
[267,] 11.60504086 9.22341862
[268,] -4.44663082 11.60504086
[269,] 48.90481843 -4.44663082
[270,] -0.16013535 48.90481843
[271,] -6.43482410 -0.16013535
[272,] 20.48521048 -6.43482410
[273,] 9.45356634 20.48521048
[274,] 8.96116894 9.45356634
[275,] -2.10622749 8.96116894
[276,] -2.72412948 -2.10622749
[277,] -6.56306792 -2.72412948
[278,] -3.07758656 -6.56306792
[279,] -7.48637453 -3.07758656
[280,] -7.89472634 -7.48637453
[281,] 38.59757571 -7.89472634
[282,] 6.35574460 38.59757571
[283,] 0.97009083 6.35574460
[284,] -5.67805123 0.97009083
[285,] -10.51489608 -5.67805123
[286,] 4.73675905 -10.51489608
[287,] -12.13117370 4.73675905
[288,] -2.39722433 -12.13117370
[289,] -10.85501786 -2.39722433
[290,] 4.65997803 -10.85501786
[291,] -11.16423128 4.65997803
[292,] -13.93454161 -11.16423128
[293,] 37.27297335 -13.93454161
[294,] -2.72867810 37.27297335
[295,] -3.65025259 -2.72867810
[296,] -3.11304803 -3.65025259
[297,] -2.73379570 -3.11304803
[298,] -41.70916360 -2.73379570
[299,] -15.04294975 -41.70916360
[300,] -18.90854716 -15.04294975
[301,] 9.57242530 -18.90854716
[302,] -10.69645413 9.57242530
[303,] 3.02294866 -10.69645413
[304,] -18.89212977 3.02294866
[305,] 29.87378832 -18.89212977
[306,] -9.67674424 29.87378832
[307,] -8.15065871 -9.67674424
[308,] 10.50043456 -8.15065871
[309,] -27.17143276 10.50043456
[310,] 4.87959993 -27.17143276
[311,] -2.88359244 4.87959993
[312,] 13.07857115 -2.88359244
[313,] 0.24859956 13.07857115
[314,] -19.98753824 0.24859956
[315,] -8.34156695 -19.98753824
[316,] 4.63818476 -8.34156695
[317,] 49.36276221 4.63818476
[318,] 5.86308567 49.36276221
[319,] -13.48062563 5.86308567
[320,] 46.23642358 -13.48062563
[321,] -2.28746030 46.23642358
[322,] 37.93109836 -2.28746030
[323,] 37.97252616 37.93109836
[324,] 124.53300333 37.97252616
[325,] -3.56203912 124.53300333
[326,] 20.35712351 -3.56203912
[327,] -10.50106303 20.35712351
[328,] 8.87293453 -10.50106303
[329,] 33.00205827 8.87293453
[330,] -3.60883551 33.00205827
[331,] -11.20085783 -3.60883551
[332,] 12.02437889 -11.20085783
[333,] 0.21751311 12.02437889
[334,] -12.45857198 0.21751311
[335,] 5.70572221 -12.45857198
[336,] 30.46856125 5.70572221
[337,] -14.92169901 30.46856125
[338,] -20.35296302 -14.92169901
[339,] -12.75969878 -20.35296302
[340,] -25.69790865 -12.75969878
[341,] 74.05236238 -25.69790865
[342,] 22.47521161 74.05236238
[343,] 5.91712718 22.47521161
[344,] -8.55706399 5.91712718
[345,] 3.54855367 -8.55706399
[346,] 13.13597915 3.54855367
[347,] -1.74085627 13.13597915
[348,] 10.90042725 -1.74085627
[349,] 24.52178453 10.90042725
[350,] -26.23426508 24.52178453
[351,] -52.32070148 -26.23426508
[352,] -8.22381266 -52.32070148
[353,] 71.17453095 -8.22381266
[354,] -22.66595455 71.17453095
[355,] 13.79198725 -22.66595455
[356,] -8.71597190 13.79198725
[357,] -0.73191494 -8.71597190
[358,] -2.98083212 -0.73191494
[359,] -42.79644064 -2.98083212
[360,] 30.16973747 -42.79644064
[361,] -17.76253744 30.16973747
[362,] -0.23311460 -17.76253744
[363,] -34.93384329 -0.23311460
[364,] 2.86615045 -34.93384329
[365,] 20.21099900 2.86615045
[366,] 35.79090734 20.21099900
[367,] -21.13239374 35.79090734
[368,] 2.81291647 -21.13239374
[369,] -15.07017588 2.81291647
[370,] -2.12382785 -15.07017588
[371,] 10.88125130 -2.12382785
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 22.76759948 150.66972823
2 -15.24175343 22.76759948
3 5.86131346 -15.24175343
4 -21.05291426 5.86131346
5 -33.82184406 -21.05291426
6 26.25369060 -33.82184406
7 16.12121498 26.25369060
8 -3.35527967 16.12121498
9 -18.14062111 -3.35527967
10 6.96143149 -18.14062111
11 15.86941535 6.96143149
12 -1.45939424 15.86941535
13 36.60942716 -1.45939424
14 11.74577346 36.60942716
15 25.23773102 11.74577346
16 43.03734743 25.23773102
17 -29.83122574 43.03734743
18 65.21179232 -29.83122574
19 -8.64546976 65.21179232
20 -14.83461488 -8.64546976
21 37.03940006 -14.83461488
22 -37.46817261 37.03940006
23 14.87623275 -37.46817261
24 25.53306814 14.87623275
25 9.53112786 25.53306814
26 -21.61370529 9.53112786
27 -19.30200751 -21.61370529
28 -10.11311874 -19.30200751
29 -34.69087578 -10.11311874
30 8.06815996 -34.69087578
31 -31.11428953 8.06815996
32 10.00975551 -31.11428953
33 -22.85911006 10.00975551
34 10.68435072 -22.85911006
35 5.54553169 10.68435072
36 -55.36933208 5.54553169
37 -18.72481017 -55.36933208
38 6.65062831 -18.72481017
39 2.20671968 6.65062831
40 1.96872768 2.20671968
41 -39.01408413 1.96872768
42 15.73892318 -39.01408413
43 4.59476266 15.73892318
44 21.12892026 4.59476266
45 -2.53470406 21.12892026
46 -3.43584406 -2.53470406
47 -24.59719617 -3.43584406
48 -33.99680571 -24.59719617
49 0.08477499 -33.99680571
50 -10.24087893 0.08477499
51 20.54711459 -10.24087893
52 11.75122314 20.54711459
53 -53.72005533 11.75122314
54 25.16510042 -53.72005533
55 14.24892922 25.16510042
56 -7.65515212 14.24892922
57 -14.48011427 -7.65515212
58 -13.20583760 -14.48011427
59 -8.83091240 -13.20583760
60 -22.19166233 -8.83091240
61 -28.14543951 -22.19166233
62 8.23876400 -28.14543951
63 30.70642881 8.23876400
64 -8.79965978 30.70642881
65 -60.85271362 -8.79965978
66 18.35347732 -60.85271362
67 11.10155459 18.35347732
68 21.43168940 11.10155459
69 3.04262212 21.43168940
70 14.79758335 3.04262212
71 26.05848251 14.79758335
72 33.79016714 26.05848251
73 25.25592024 33.79016714
74 21.26263028 25.25592024
75 15.53458128 21.26263028
76 -0.40378094 15.53458128
77 -69.99580664 -0.40378094
78 28.49670228 -69.99580664
79 18.73216099 28.49670228
80 14.29203407 18.73216099
81 -35.07014674 14.29203407
82 -1.05600786 -35.07014674
83 -7.62238813 -1.05600786
84 -9.88041915 -7.62238813
85 -16.51759353 -9.88041915
86 -1.41104890 -16.51759353
87 28.35247618 -1.41104890
88 -26.79264943 28.35247618
89 -53.45794657 -26.79264943
90 4.04722558 -53.45794657
91 23.35122609 4.04722558
92 -4.14674827 23.35122609
93 6.41121772 -4.14674827
94 0.83708855 6.41121772
95 1.51068119 0.83708855
96 -34.75678938 1.51068119
97 -7.23909275 -34.75678938
98 24.73397049 -7.23909275
99 -0.91528018 24.73397049
100 25.57352869 -0.91528018
101 -38.03673442 25.57352869
102 0.96160171 -38.03673442
103 -18.97388606 0.96160171
104 -2.23451644 -18.97388606
105 -2.50985676 -2.23451644
106 27.43282190 -2.50985676
107 0.42513373 27.43282190
108 -29.47461195 0.42513373
109 -23.15657881 -29.47461195
110 -2.07115781 -23.15657881
111 20.30014669 -2.07115781
112 18.85172378 20.30014669
113 -28.28542380 18.85172378
114 -9.42632541 -28.28542380
115 -0.30027210 -9.42632541
116 13.86711631 -0.30027210
117 8.88236414 13.86711631
118 40.06717822 8.88236414
119 12.96025663 40.06717822
120 27.83683407 12.96025663
121 51.61399232 27.83683407
122 21.76260693 51.61399232
123 25.69152504 21.76260693
124 -3.13317117 25.69152504
125 -31.19779810 -3.13317117
126 17.66815391 -31.19779810
127 -9.03311466 17.66815391
128 -31.61770102 -9.03311466
129 -6.93449157 -31.61770102
130 -9.31995202 -6.93449157
131 32.55458288 -9.31995202
132 -14.38376264 32.55458288
133 -6.13040263 -14.38376264
134 -13.07874874 -6.13040263
135 -30.26241477 -13.07874874
136 3.18673436 -30.26241477
137 -22.00839616 3.18673436
138 8.27919110 -22.00839616
139 7.95986248 8.27919110
140 1.54811040 7.95986248
141 18.06543761 1.54811040
142 17.20668871 18.06543761
143 -16.39337307 17.20668871
144 -20.26136860 -16.39337307
145 -30.15766960 -20.26136860
146 54.61376727 -30.15766960
147 -15.20510505 54.61376727
148 -5.41439037 -15.20510505
149 7.50507326 -5.41439037
150 -5.23313757 7.50507326
151 13.95651119 -5.23313757
152 -22.21054336 13.95651119
153 37.97598838 -22.21054336
154 21.62866242 37.97598838
155 44.54415841 21.62866242
156 3.82537669 44.54415841
157 19.62822472 3.82537669
158 0.53891224 19.62822472
159 -12.10619045 0.53891224
160 4.34435087 -12.10619045
161 -1.92865020 4.34435087
162 -6.77282029 -1.92865020
163 -14.96040534 -6.77282029
164 -16.91996977 -14.96040534
165 5.37003093 -16.91996977
166 -8.49079341 5.37003093
167 11.25854549 -8.49079341
168 -18.12803089 11.25854549
169 -21.23930998 -18.12803089
170 11.28801247 -21.23930998
171 -3.29007316 11.28801247
172 30.49524115 -3.29007316
173 -46.04990793 30.49524115
174 -15.91771989 -46.04990793
175 37.69811193 -15.91771989
176 -20.34762231 37.69811193
177 -8.58174479 -20.34762231
178 28.78107993 -8.58174479
179 0.70712980 28.78107993
180 4.87110826 0.70712980
181 13.98173545 4.87110826
182 -20.92761821 13.98173545
183 -5.39060866 -20.92761821
184 19.29300604 -5.39060866
185 -10.94217792 19.29300604
186 -18.60210425 -10.94217792
187 -4.78227952 -18.60210425
188 -8.40238641 -4.78227952
189 9.57431458 -8.40238641
190 24.97546433 9.57431458
191 -11.39733916 24.97546433
192 -8.38284780 -11.39733916
193 -14.41123624 -8.38284780
194 0.67182035 -14.41123624
195 1.34747223 0.67182035
196 -9.45471822 1.34747223
197 19.93732899 -9.45471822
198 -55.39788008 19.93732899
199 19.02994457 -55.39788008
200 -8.63628496 19.02994457
201 7.58980142 -8.63628496
202 -11.36077549 7.58980142
203 4.89824593 -11.36077549
204 -27.21330739 4.89824593
205 12.50335755 -27.21330739
206 -24.90587377 12.50335755
207 16.72483762 -24.90587377
208 -8.12173856 16.72483762
209 8.43709810 -8.12173856
210 -42.46150160 8.43709810
211 3.42644691 -42.46150160
212 -14.30426478 3.42644691
213 0.22680124 -14.30426478
214 -6.31828958 0.22680124
215 -15.75014349 -6.31828958
216 -36.50672352 -15.75014349
217 -24.38599766 -36.50672352
218 10.50734252 -24.38599766
219 10.14698604 10.50734252
220 20.01632629 10.14698604
221 -1.04354718 20.01632629
222 -39.54589435 -1.04354718
223 3.96177435 -39.54589435
224 -16.65681620 3.96177435
225 7.35931412 -16.65681620
226 -15.04154896 7.35931412
227 0.67324531 -15.04154896
228 -34.54448017 0.67324531
229 -11.42555265 -34.54448017
230 -2.97669729 -11.42555265
231 5.48443658 -2.97669729
232 -6.43266852 5.48443658
233 37.23204627 -6.43266852
234 -23.16942502 37.23204627
235 -8.41990385 -23.16942502
236 8.09634254 -8.41990385
237 16.22233817 8.09634254
238 -33.67518564 16.22233817
239 -26.03918009 -33.67518564
240 -44.93235579 -26.03918009
241 11.45274282 -44.93235579
242 -14.83277302 11.45274282
243 -10.61580125 -14.83277302
244 -3.42134922 -10.61580125
245 52.34576698 -3.42134922
246 -26.42985043 52.34576698
247 -24.31780616 -26.42985043
248 -3.82101212 -24.31780616
249 1.98911294 -3.82101212
250 -21.18721316 1.98911294
251 -23.89208101 -21.18721316
252 -37.27297365 -23.89208101
253 -7.63780977 -37.27297365
254 1.62742853 -7.63780977
255 11.82520162 1.62742853
256 -12.66557013 11.82520162
257 26.96800537 -12.66557013
258 -6.93196094 26.96800537
259 -10.26466563 -6.93196094
260 18.77371503 -10.26466563
261 -3.34791154 18.77371503
262 -43.18493912 -3.34791154
263 -15.21728751 -43.18493912
264 -2.89181673 -15.21728751
265 25.06414266 -2.89181673
266 9.22341862 25.06414266
267 11.60504086 9.22341862
268 -4.44663082 11.60504086
269 48.90481843 -4.44663082
270 -0.16013535 48.90481843
271 -6.43482410 -0.16013535
272 20.48521048 -6.43482410
273 9.45356634 20.48521048
274 8.96116894 9.45356634
275 -2.10622749 8.96116894
276 -2.72412948 -2.10622749
277 -6.56306792 -2.72412948
278 -3.07758656 -6.56306792
279 -7.48637453 -3.07758656
280 -7.89472634 -7.48637453
281 38.59757571 -7.89472634
282 6.35574460 38.59757571
283 0.97009083 6.35574460
284 -5.67805123 0.97009083
285 -10.51489608 -5.67805123
286 4.73675905 -10.51489608
287 -12.13117370 4.73675905
288 -2.39722433 -12.13117370
289 -10.85501786 -2.39722433
290 4.65997803 -10.85501786
291 -11.16423128 4.65997803
292 -13.93454161 -11.16423128
293 37.27297335 -13.93454161
294 -2.72867810 37.27297335
295 -3.65025259 -2.72867810
296 -3.11304803 -3.65025259
297 -2.73379570 -3.11304803
298 -41.70916360 -2.73379570
299 -15.04294975 -41.70916360
300 -18.90854716 -15.04294975
301 9.57242530 -18.90854716
302 -10.69645413 9.57242530
303 3.02294866 -10.69645413
304 -18.89212977 3.02294866
305 29.87378832 -18.89212977
306 -9.67674424 29.87378832
307 -8.15065871 -9.67674424
308 10.50043456 -8.15065871
309 -27.17143276 10.50043456
310 4.87959993 -27.17143276
311 -2.88359244 4.87959993
312 13.07857115 -2.88359244
313 0.24859956 13.07857115
314 -19.98753824 0.24859956
315 -8.34156695 -19.98753824
316 4.63818476 -8.34156695
317 49.36276221 4.63818476
318 5.86308567 49.36276221
319 -13.48062563 5.86308567
320 46.23642358 -13.48062563
321 -2.28746030 46.23642358
322 37.93109836 -2.28746030
323 37.97252616 37.93109836
324 124.53300333 37.97252616
325 -3.56203912 124.53300333
326 20.35712351 -3.56203912
327 -10.50106303 20.35712351
328 8.87293453 -10.50106303
329 33.00205827 8.87293453
330 -3.60883551 33.00205827
331 -11.20085783 -3.60883551
332 12.02437889 -11.20085783
333 0.21751311 12.02437889
334 -12.45857198 0.21751311
335 5.70572221 -12.45857198
336 30.46856125 5.70572221
337 -14.92169901 30.46856125
338 -20.35296302 -14.92169901
339 -12.75969878 -20.35296302
340 -25.69790865 -12.75969878
341 74.05236238 -25.69790865
342 22.47521161 74.05236238
343 5.91712718 22.47521161
344 -8.55706399 5.91712718
345 3.54855367 -8.55706399
346 13.13597915 3.54855367
347 -1.74085627 13.13597915
348 10.90042725 -1.74085627
349 24.52178453 10.90042725
350 -26.23426508 24.52178453
351 -52.32070148 -26.23426508
352 -8.22381266 -52.32070148
353 71.17453095 -8.22381266
354 -22.66595455 71.17453095
355 13.79198725 -22.66595455
356 -8.71597190 13.79198725
357 -0.73191494 -8.71597190
358 -2.98083212 -0.73191494
359 -42.79644064 -2.98083212
360 30.16973747 -42.79644064
361 -17.76253744 30.16973747
362 -0.23311460 -17.76253744
363 -34.93384329 -0.23311460
364 2.86615045 -34.93384329
365 20.21099900 2.86615045
366 35.79090734 20.21099900
367 -21.13239374 35.79090734
368 2.81291647 -21.13239374
369 -15.07017588 2.81291647
370 -2.12382785 -15.07017588
371 10.88125130 -2.12382785
> 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/freestat/rcomp/tmp/70zwy1291149891.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/80zwy1291149891.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/90zwy1291149891.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/freestat/rcomp/tmp/10t8e11291149891.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/freestat/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/freestat/rcomp/tmp/11wrup1291149891.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/freestat/rcomp/tmp/12zrsd1291149891.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/freestat/rcomp/tmp/13osp71291149891.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/freestat/rcomp/tmp/14z2ps1291149891.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/freestat/rcomp/tmp/1522ng1291149891.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/freestat/rcomp/tmp/16yu361291149891.tab")
+ }
>
> try(system("convert tmp/1m7gq1291149891.ps tmp/1m7gq1291149891.png",intern=TRUE))
character(0)
> try(system("convert tmp/2m7gq1291149891.ps tmp/2m7gq1291149891.png",intern=TRUE))
character(0)
> try(system("convert tmp/3fzgt1291149891.ps tmp/3fzgt1291149891.png",intern=TRUE))
character(0)
> try(system("convert tmp/4fzgt1291149891.ps tmp/4fzgt1291149891.png",intern=TRUE))
character(0)
> try(system("convert tmp/5fzgt1291149891.ps tmp/5fzgt1291149891.png",intern=TRUE))
character(0)
> try(system("convert tmp/67qfw1291149891.ps tmp/67qfw1291149891.png",intern=TRUE))
character(0)
> try(system("convert tmp/70zwy1291149891.ps tmp/70zwy1291149891.png",intern=TRUE))
character(0)
> try(system("convert tmp/80zwy1291149891.ps tmp/80zwy1291149891.png",intern=TRUE))
character(0)
> try(system("convert tmp/90zwy1291149891.ps tmp/90zwy1291149891.png",intern=TRUE))
character(0)
> try(system("convert tmp/10t8e11291149891.ps tmp/10t8e11291149891.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
13.570 3.139 14.327