R version 2.10.0 (2009-10-26)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
R is free software and comes with ABSOLUTELY NO WARRANTY.
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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(277
+ ,7.7
+ ,0
+ ,260.6
+ ,7.5
+ ,0
+ ,291.6
+ ,8.3
+ ,0
+ ,275.4
+ ,7.8
+ ,0
+ ,275.3
+ ,7.9
+ ,0
+ ,231.7
+ ,6.6
+ ,0
+ ,238.8
+ ,7
+ ,0
+ ,274.2
+ ,8.2
+ ,0
+ ,277.8
+ ,8.2
+ ,0
+ ,299.1
+ ,9.1
+ ,0
+ ,286.6
+ ,9
+ ,0
+ ,232.3
+ ,7.1
+ ,0
+ ,294.1
+ ,8.9
+ ,0
+ ,267.5
+ ,8.5
+ ,0
+ ,309.7
+ ,9.8
+ ,0
+ ,280.7
+ ,8.8
+ ,0
+ ,287.3
+ ,9.2
+ ,0
+ ,235.7
+ ,7.4
+ ,0
+ ,256.4
+ ,8.3
+ ,0
+ ,289
+ ,9.7
+ ,0
+ ,290.8
+ ,9.7
+ ,0
+ ,321.9
+ ,10.8
+ ,0
+ ,291.8
+ ,9.8
+ ,0
+ ,241.4
+ ,7.9
+ ,0
+ ,295.5
+ ,9.8
+ ,0
+ ,258.2
+ ,9
+ ,0
+ ,306.1
+ ,10.5
+ ,0
+ ,281.5
+ ,9.5
+ ,0
+ ,283.1
+ ,9.7
+ ,0
+ ,237.4
+ ,8.1
+ ,0
+ ,274.8
+ ,10.1
+ ,0
+ ,299.3
+ ,11.1
+ ,0
+ ,300.4
+ ,11.2
+ ,0
+ ,340.9
+ ,12.6
+ ,0
+ ,318.8
+ ,12.2
+ ,0
+ ,265.7
+ ,9.9
+ ,0
+ ,322.7
+ ,11.8
+ ,0
+ ,281.6
+ ,11.1
+ ,0
+ ,323.5
+ ,12.6
+ ,0
+ ,312.6
+ ,11.9
+ ,0
+ ,310.8
+ ,11.9
+ ,0
+ ,262.8
+ ,10
+ ,0
+ ,273.8
+ ,10.8
+ ,0
+ ,320
+ ,12.9
+ ,0
+ ,310.3
+ ,12.5
+ ,0
+ ,342.2
+ ,13.8
+ ,0
+ ,320.1
+ ,13.1
+ ,0
+ ,265.6
+ ,10.5
+ ,0
+ ,327
+ ,12.9
+ ,0
+ ,300.7
+ ,12.9
+ ,0
+ ,346.4
+ ,14.4
+ ,0
+ ,317.3
+ ,12.7
+ ,0
+ ,326.2
+ ,13.3
+ ,0
+ ,270.7
+ ,11
+ ,0
+ ,278.2
+ ,11.9
+ ,0
+ ,324.6
+ ,14.1
+ ,0
+ ,321.8
+ ,14.4
+ ,0
+ ,343.5
+ ,14.9
+ ,0
+ ,354
+ ,15.7
+ ,0
+ ,278.2
+ ,12
+ ,0
+ ,330.2
+ ,14.3
+ ,0
+ ,307.3
+ ,14.2
+ ,0
+ ,375.9
+ ,17.4
+ ,0
+ ,335.3
+ ,15.1
+ ,0
+ ,339.3
+ ,15.3
+ ,0
+ ,280.3
+ ,12.6
+ ,0
+ ,293.7
+ ,14
+ ,0
+ ,341.2
+ ,16.6
+ ,0
+ ,345.1
+ ,16.7
+ ,0
+ ,368.7
+ ,17.6
+ ,0
+ ,369.4
+ ,18.3
+ ,0
+ ,288.4
+ ,13.6
+ ,0
+ ,341
+ ,15.8
+ ,0
+ ,319.1
+ ,16.1
+ ,0
+ ,374.2
+ ,18.6
+ ,0
+ ,344.5
+ ,17.3
+ ,0
+ ,337.3
+ ,17
+ ,0
+ ,281
+ ,13.9
+ ,0
+ ,282.2
+ ,15.2
+ ,0
+ ,321
+ ,17.8
+ ,0
+ ,325.4
+ ,18
+ ,0
+ ,366.3
+ ,19.4
+ ,0
+ ,380.3
+ ,21.8
+ ,0
+ ,300.7
+ ,16.2
+ ,0
+ ,359.3
+ ,19.2
+ ,0
+ ,327.6
+ ,19.5
+ ,0
+ ,383.6
+ ,22
+ ,0
+ ,352.4
+ ,20
+ ,0
+ ,329.4
+ ,19.2
+ ,0
+ ,294.5
+ ,16.9
+ ,0
+ ,333.5
+ ,20
+ ,0
+ ,334.3
+ ,20.4
+ ,0
+ ,358
+ ,21.8
+ ,0
+ ,396.1
+ ,25
+ ,0
+ ,387
+ ,25.8
+ ,0
+ ,307.2
+ ,19.4
+ ,0
+ ,363.9
+ ,22.6
+ ,0
+ ,344.7
+ ,24.1
+ ,0
+ ,397.6
+ ,26.9
+ ,0
+ ,376.8
+ ,24.9
+ ,0
+ ,337.1
+ ,23.3
+ ,0
+ ,299.3
+ ,20.3
+ ,0
+ ,323.1
+ ,22.3
+ ,0
+ ,329.1
+ ,23.7
+ ,0
+ ,347
+ ,24.3
+ ,0
+ ,462
+ ,31.7
+ ,1
+ ,436.5
+ ,32.2
+ ,0
+ ,360.4
+ ,25.4
+ ,0
+ ,415.5
+ ,28.6
+ ,0
+ ,382.1
+ ,28.7
+ ,0
+ ,432.2
+ ,30.9
+ ,0
+ ,424.3
+ ,31.4
+ ,0
+ ,386.7
+ ,29.1
+ ,0
+ ,354.5
+ ,26.3
+ ,0
+ ,375.8
+ ,28.9
+ ,0
+ ,368
+ ,28.9
+ ,0
+ ,402.4
+ ,31
+ ,0
+ ,426.5
+ ,33.4
+ ,0
+ ,433.3
+ ,35.9
+ ,0
+ ,338.5
+ ,25.8
+ ,0
+ ,416.8
+ ,31.2
+ ,0
+ ,381.1
+ ,31.7
+ ,0
+ ,445.7
+ ,36.2
+ ,0
+ ,412.4
+ ,32
+ ,0
+ ,394
+ ,32.1
+ ,0
+ ,348.2
+ ,28.1
+ ,0
+ ,380.1
+ ,31.1
+ ,0
+ ,373.7
+ ,31.9
+ ,0
+ ,393.6
+ ,32
+ ,0
+ ,434.2
+ ,36.6
+ ,0
+ ,430.7
+ ,38.1
+ ,0
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+ ,28.1
+ ,0
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+ ,32.9
+ ,0
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+ ,30.7
+ ,0
+ ,437.3
+ ,35.4
+ ,0
+ ,411.3
+ ,33.7
+ ,0
+ ,385.5
+ ,31.6
+ ,0
+ ,341.3
+ ,27.9
+ ,0
+ ,384.2
+ ,32.2
+ ,0
+ ,373.2
+ ,32.3
+ ,0
+ ,415.8
+ ,35.3
+ ,0
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+ ,37.2
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+ ,39.6
+ ,0
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+ ,28.4
+ ,0
+ ,419.1
+ ,33.9
+ ,0
+ ,398
+ ,33.7
+ ,0
+ ,456.1
+ ,38.3
+ ,0
+ ,430.1
+ ,34.6
+ ,0
+ ,399.8
+ ,32.7
+ ,0
+ ,362.7
+ ,29.5
+ ,0
+ ,384.9
+ ,32
+ ,0
+ ,385.3
+ ,33.2
+ ,0
+ ,432.3
+ ,36.7
+ ,0
+ ,468.9
+ ,38.6
+ ,0
+ ,442.7
+ ,38.1
+ ,0
+ ,370.2
+ ,29.8
+ ,0
+ ,439.4
+ ,35.6
+ ,0
+ ,393.9
+ ,33.2
+ ,0
+ ,468.7
+ ,38.9
+ ,0
+ ,438.8
+ ,34.8
+ ,0
+ ,430.1
+ ,37.2
+ ,0
+ ,366.3
+ ,29.7
+ ,0
+ ,391
+ ,32.2
+ ,0
+ ,380.9
+ ,32.1
+ ,0
+ ,431.4
+ ,36.3
+ ,0
+ ,465.4
+ ,38.4
+ ,0
+ ,471.5
+ ,40.8
+ ,0
+ ,387.5
+ ,31.3
+ ,0
+ ,446.4
+ ,36.2
+ ,0
+ ,421.5
+ ,35.1
+ ,0
+ ,504.8
+ ,44.1
+ ,0
+ ,492.1
+ ,39.3
+ ,0
+ ,421.3
+ ,34.1
+ ,0
+ ,396.7
+ ,32.4
+ ,0
+ ,428
+ ,36.3
+ ,0
+ ,421.9
+ ,36.8
+ ,0
+ ,465.6
+ ,40.5
+ ,0
+ ,525.8
+ ,46
+ ,0
+ ,499.9
+ ,43.9
+ ,0
+ ,435.3
+ ,37.2
+ ,0
+ ,479.5
+ ,40.7
+ ,0
+ ,473
+ ,42
+ ,0
+ ,554.4
+ ,49.2
+ ,0
+ ,489.6
+ ,42.3
+ ,0
+ ,462.2
+ ,40.8
+ ,0
+ ,420.3
+ ,37.6
+ ,0)
+ ,dim=c(3
+ ,186)
+ ,dimnames=list(c('Y[t]'
+ ,'X[t]'
+ ,'D[t]')
+ ,1:186))
> y <- array(NA,dim=c(3,186),dimnames=list(c('Y[t]','X[t]','D[t]'),1:186))
> 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
Warning messages:
1: package 'lmtest' was built under R version 2.8.1 and help may not work correctly
2: package 'zoo' was built under R version 2.8.1 and help may not work correctly
> n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
> par1 <- as.numeric(par1)
> x <- t(y)
> k <- length(x[1,])
> n <- length(x[,1])
> x1 <- cbind(x[,par1], x[,1:k!=par1])
> mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
> colnames(x1) <- mycolnames #colnames(x)[par1]
> x <- x1
> if (par3 == 'First Differences'){
+ x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
+ for (i in 1:n-1) {
+ for (j in 1:k) {
+ x2[i,j] <- x[i+1,j] - x[i,j]
+ }
+ }
+ x <- x2
+ }
> if (par2 == 'Include Monthly Dummies'){
+ x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
+ for (i in 1:11){
+ x2[seq(i,n,12),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> if (par2 == 'Include Quarterly Dummies'){
+ x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
+ for (i in 1:3){
+ x2[seq(i,n,4),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> k <- length(x[1,])
> if (par3 == 'Linear Trend'){
+ x <- cbind(x, c(1:n))
+ colnames(x)[k+1] <- 't'
+ }
> x
Y[t] X[t] D[t] M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 277.0 7.7 0 1 0 0 0 0 0 0 0 0 0 0 1
2 260.6 7.5 0 0 1 0 0 0 0 0 0 0 0 0 2
3 291.6 8.3 0 0 0 1 0 0 0 0 0 0 0 0 3
4 275.4 7.8 0 0 0 0 1 0 0 0 0 0 0 0 4
5 275.3 7.9 0 0 0 0 0 1 0 0 0 0 0 0 5
6 231.7 6.6 0 0 0 0 0 0 1 0 0 0 0 0 6
7 238.8 7.0 0 0 0 0 0 0 0 1 0 0 0 0 7
8 274.2 8.2 0 0 0 0 0 0 0 0 1 0 0 0 8
9 277.8 8.2 0 0 0 0 0 0 0 0 0 1 0 0 9
10 299.1 9.1 0 0 0 0 0 0 0 0 0 0 1 0 10
11 286.6 9.0 0 0 0 0 0 0 0 0 0 0 0 1 11
12 232.3 7.1 0 0 0 0 0 0 0 0 0 0 0 0 12
13 294.1 8.9 0 1 0 0 0 0 0 0 0 0 0 0 13
14 267.5 8.5 0 0 1 0 0 0 0 0 0 0 0 0 14
15 309.7 9.8 0 0 0 1 0 0 0 0 0 0 0 0 15
16 280.7 8.8 0 0 0 0 1 0 0 0 0 0 0 0 16
17 287.3 9.2 0 0 0 0 0 1 0 0 0 0 0 0 17
18 235.7 7.4 0 0 0 0 0 0 1 0 0 0 0 0 18
19 256.4 8.3 0 0 0 0 0 0 0 1 0 0 0 0 19
20 289.0 9.7 0 0 0 0 0 0 0 0 1 0 0 0 20
21 290.8 9.7 0 0 0 0 0 0 0 0 0 1 0 0 21
22 321.9 10.8 0 0 0 0 0 0 0 0 0 0 1 0 22
23 291.8 9.8 0 0 0 0 0 0 0 0 0 0 0 1 23
24 241.4 7.9 0 0 0 0 0 0 0 0 0 0 0 0 24
25 295.5 9.8 0 1 0 0 0 0 0 0 0 0 0 0 25
26 258.2 9.0 0 0 1 0 0 0 0 0 0 0 0 0 26
27 306.1 10.5 0 0 0 1 0 0 0 0 0 0 0 0 27
28 281.5 9.5 0 0 0 0 1 0 0 0 0 0 0 0 28
29 283.1 9.7 0 0 0 0 0 1 0 0 0 0 0 0 29
30 237.4 8.1 0 0 0 0 0 0 1 0 0 0 0 0 30
31 274.8 10.1 0 0 0 0 0 0 0 1 0 0 0 0 31
32 299.3 11.1 0 0 0 0 0 0 0 0 1 0 0 0 32
33 300.4 11.2 0 0 0 0 0 0 0 0 0 1 0 0 33
34 340.9 12.6 0 0 0 0 0 0 0 0 0 0 1 0 34
35 318.8 12.2 0 0 0 0 0 0 0 0 0 0 0 1 35
36 265.7 9.9 0 0 0 0 0 0 0 0 0 0 0 0 36
37 322.7 11.8 0 1 0 0 0 0 0 0 0 0 0 0 37
38 281.6 11.1 0 0 1 0 0 0 0 0 0 0 0 0 38
39 323.5 12.6 0 0 0 1 0 0 0 0 0 0 0 0 39
40 312.6 11.9 0 0 0 0 1 0 0 0 0 0 0 0 40
41 310.8 11.9 0 0 0 0 0 1 0 0 0 0 0 0 41
42 262.8 10.0 0 0 0 0 0 0 1 0 0 0 0 0 42
43 273.8 10.8 0 0 0 0 0 0 0 1 0 0 0 0 43
44 320.0 12.9 0 0 0 0 0 0 0 0 1 0 0 0 44
45 310.3 12.5 0 0 0 0 0 0 0 0 0 1 0 0 45
46 342.2 13.8 0 0 0 0 0 0 0 0 0 0 1 0 46
47 320.1 13.1 0 0 0 0 0 0 0 0 0 0 0 1 47
48 265.6 10.5 0 0 0 0 0 0 0 0 0 0 0 0 48
49 327.0 12.9 0 1 0 0 0 0 0 0 0 0 0 0 49
50 300.7 12.9 0 0 1 0 0 0 0 0 0 0 0 0 50
51 346.4 14.4 0 0 0 1 0 0 0 0 0 0 0 0 51
52 317.3 12.7 0 0 0 0 1 0 0 0 0 0 0 0 52
53 326.2 13.3 0 0 0 0 0 1 0 0 0 0 0 0 53
54 270.7 11.0 0 0 0 0 0 0 1 0 0 0 0 0 54
55 278.2 11.9 0 0 0 0 0 0 0 1 0 0 0 0 55
56 324.6 14.1 0 0 0 0 0 0 0 0 1 0 0 0 56
57 321.8 14.4 0 0 0 0 0 0 0 0 0 1 0 0 57
58 343.5 14.9 0 0 0 0 0 0 0 0 0 0 1 0 58
59 354.0 15.7 0 0 0 0 0 0 0 0 0 0 0 1 59
60 278.2 12.0 0 0 0 0 0 0 0 0 0 0 0 0 60
61 330.2 14.3 0 1 0 0 0 0 0 0 0 0 0 0 61
62 307.3 14.2 0 0 1 0 0 0 0 0 0 0 0 0 62
63 375.9 17.4 0 0 0 1 0 0 0 0 0 0 0 0 63
64 335.3 15.1 0 0 0 0 1 0 0 0 0 0 0 0 64
65 339.3 15.3 0 0 0 0 0 1 0 0 0 0 0 0 65
66 280.3 12.6 0 0 0 0 0 0 1 0 0 0 0 0 66
67 293.7 14.0 0 0 0 0 0 0 0 1 0 0 0 0 67
68 341.2 16.6 0 0 0 0 0 0 0 0 1 0 0 0 68
69 345.1 16.7 0 0 0 0 0 0 0 0 0 1 0 0 69
70 368.7 17.6 0 0 0 0 0 0 0 0 0 0 1 0 70
71 369.4 18.3 0 0 0 0 0 0 0 0 0 0 0 1 71
72 288.4 13.6 0 0 0 0 0 0 0 0 0 0 0 0 72
73 341.0 15.8 0 1 0 0 0 0 0 0 0 0 0 0 73
74 319.1 16.1 0 0 1 0 0 0 0 0 0 0 0 0 74
75 374.2 18.6 0 0 0 1 0 0 0 0 0 0 0 0 75
76 344.5 17.3 0 0 0 0 1 0 0 0 0 0 0 0 76
77 337.3 17.0 0 0 0 0 0 1 0 0 0 0 0 0 77
78 281.0 13.9 0 0 0 0 0 0 1 0 0 0 0 0 78
79 282.2 15.2 0 0 0 0 0 0 0 1 0 0 0 0 79
80 321.0 17.8 0 0 0 0 0 0 0 0 1 0 0 0 80
81 325.4 18.0 0 0 0 0 0 0 0 0 0 1 0 0 81
82 366.3 19.4 0 0 0 0 0 0 0 0 0 0 1 0 82
83 380.3 21.8 0 0 0 0 0 0 0 0 0 0 0 1 83
84 300.7 16.2 0 0 0 0 0 0 0 0 0 0 0 0 84
85 359.3 19.2 0 1 0 0 0 0 0 0 0 0 0 0 85
86 327.6 19.5 0 0 1 0 0 0 0 0 0 0 0 0 86
87 383.6 22.0 0 0 0 1 0 0 0 0 0 0 0 0 87
88 352.4 20.0 0 0 0 0 1 0 0 0 0 0 0 0 88
89 329.4 19.2 0 0 0 0 0 1 0 0 0 0 0 0 89
90 294.5 16.9 0 0 0 0 0 0 1 0 0 0 0 0 90
91 333.5 20.0 0 0 0 0 0 0 0 1 0 0 0 0 91
92 334.3 20.4 0 0 0 0 0 0 0 0 1 0 0 0 92
93 358.0 21.8 0 0 0 0 0 0 0 0 0 1 0 0 93
94 396.1 25.0 0 0 0 0 0 0 0 0 0 0 1 0 94
95 387.0 25.8 0 0 0 0 0 0 0 0 0 0 0 1 95
96 307.2 19.4 0 0 0 0 0 0 0 0 0 0 0 0 96
97 363.9 22.6 0 1 0 0 0 0 0 0 0 0 0 0 97
98 344.7 24.1 0 0 1 0 0 0 0 0 0 0 0 0 98
99 397.6 26.9 0 0 0 1 0 0 0 0 0 0 0 0 99
100 376.8 24.9 0 0 0 0 1 0 0 0 0 0 0 0 100
101 337.1 23.3 0 0 0 0 0 1 0 0 0 0 0 0 101
102 299.3 20.3 0 0 0 0 0 0 1 0 0 0 0 0 102
103 323.1 22.3 0 0 0 0 0 0 0 1 0 0 0 0 103
104 329.1 23.7 0 0 0 0 0 0 0 0 1 0 0 0 104
105 347.0 24.3 0 0 0 0 0 0 0 0 0 1 0 0 105
106 462.0 31.7 1 0 0 0 0 0 0 0 0 0 1 0 106
107 436.5 32.2 0 0 0 0 0 0 0 0 0 0 0 1 107
108 360.4 25.4 0 0 0 0 0 0 0 0 0 0 0 0 108
109 415.5 28.6 0 1 0 0 0 0 0 0 0 0 0 0 109
110 382.1 28.7 0 0 1 0 0 0 0 0 0 0 0 0 110
111 432.2 30.9 0 0 0 1 0 0 0 0 0 0 0 0 111
112 424.3 31.4 0 0 0 0 1 0 0 0 0 0 0 0 112
113 386.7 29.1 0 0 0 0 0 1 0 0 0 0 0 0 113
114 354.5 26.3 0 0 0 0 0 0 1 0 0 0 0 0 114
115 375.8 28.9 0 0 0 0 0 0 0 1 0 0 0 0 115
116 368.0 28.9 0 0 0 0 0 0 0 0 1 0 0 0 116
117 402.4 31.0 0 0 0 0 0 0 0 0 0 1 0 0 117
118 426.5 33.4 0 0 0 0 0 0 0 0 0 0 1 0 118
119 433.3 35.9 0 0 0 0 0 0 0 0 0 0 0 1 119
120 338.5 25.8 0 0 0 0 0 0 0 0 0 0 0 0 120
121 416.8 31.2 0 1 0 0 0 0 0 0 0 0 0 0 121
122 381.1 31.7 0 0 1 0 0 0 0 0 0 0 0 0 122
123 445.7 36.2 0 0 0 1 0 0 0 0 0 0 0 0 123
124 412.4 32.0 0 0 0 0 1 0 0 0 0 0 0 0 124
125 394.0 32.1 0 0 0 0 0 1 0 0 0 0 0 0 125
126 348.2 28.1 0 0 0 0 0 0 1 0 0 0 0 0 126
127 380.1 31.1 0 0 0 0 0 0 0 1 0 0 0 0 127
128 373.7 31.9 0 0 0 0 0 0 0 0 1 0 0 0 128
129 393.6 32.0 0 0 0 0 0 0 0 0 0 1 0 0 129
130 434.2 36.6 0 0 0 0 0 0 0 0 0 0 1 0 130
131 430.7 38.1 0 0 0 0 0 0 0 0 0 0 0 1 131
132 344.5 28.1 0 0 0 0 0 0 0 0 0 0 0 0 132
133 411.9 32.9 0 1 0 0 0 0 0 0 0 0 0 0 133
134 370.5 30.7 0 0 1 0 0 0 0 0 0 0 0 0 134
135 437.3 35.4 0 0 0 1 0 0 0 0 0 0 0 0 135
136 411.3 33.7 0 0 0 0 1 0 0 0 0 0 0 0 136
137 385.5 31.6 0 0 0 0 0 1 0 0 0 0 0 0 137
138 341.3 27.9 0 0 0 0 0 0 1 0 0 0 0 0 138
139 384.2 32.2 0 0 0 0 0 0 0 1 0 0 0 0 139
140 373.2 32.3 0 0 0 0 0 0 0 0 1 0 0 0 140
141 415.8 35.3 0 0 0 0 0 0 0 0 0 1 0 0 141
142 448.6 37.2 0 0 0 0 0 0 0 0 0 0 1 0 142
143 454.3 39.6 0 0 0 0 0 0 0 0 0 0 0 1 143
144 350.3 28.4 0 0 0 0 0 0 0 0 0 0 0 0 144
145 419.1 33.9 0 1 0 0 0 0 0 0 0 0 0 0 145
146 398.0 33.7 0 0 1 0 0 0 0 0 0 0 0 0 146
147 456.1 38.3 0 0 0 1 0 0 0 0 0 0 0 0 147
148 430.1 34.6 0 0 0 0 1 0 0 0 0 0 0 0 148
149 399.8 32.7 0 0 0 0 0 1 0 0 0 0 0 0 149
150 362.7 29.5 0 0 0 0 0 0 1 0 0 0 0 0 150
151 384.9 32.0 0 0 0 0 0 0 0 1 0 0 0 0 151
152 385.3 33.2 0 0 0 0 0 0 0 0 1 0 0 0 152
153 432.3 36.7 0 0 0 0 0 0 0 0 0 1 0 0 153
154 468.9 38.6 0 0 0 0 0 0 0 0 0 0 1 0 154
155 442.7 38.1 0 0 0 0 0 0 0 0 0 0 0 1 155
156 370.2 29.8 0 0 0 0 0 0 0 0 0 0 0 0 156
157 439.4 35.6 0 1 0 0 0 0 0 0 0 0 0 0 157
158 393.9 33.2 0 0 1 0 0 0 0 0 0 0 0 0 158
159 468.7 38.9 0 0 0 1 0 0 0 0 0 0 0 0 159
160 438.8 34.8 0 0 0 0 1 0 0 0 0 0 0 0 160
161 430.1 37.2 0 0 0 0 0 1 0 0 0 0 0 0 161
162 366.3 29.7 0 0 0 0 0 0 1 0 0 0 0 0 162
163 391.0 32.2 0 0 0 0 0 0 0 1 0 0 0 0 163
164 380.9 32.1 0 0 0 0 0 0 0 0 1 0 0 0 164
165 431.4 36.3 0 0 0 0 0 0 0 0 0 1 0 0 165
166 465.4 38.4 0 0 0 0 0 0 0 0 0 0 1 0 166
167 471.5 40.8 0 0 0 0 0 0 0 0 0 0 0 1 167
168 387.5 31.3 0 0 0 0 0 0 0 0 0 0 0 0 168
169 446.4 36.2 0 1 0 0 0 0 0 0 0 0 0 0 169
170 421.5 35.1 0 0 1 0 0 0 0 0 0 0 0 0 170
171 504.8 44.1 0 0 0 1 0 0 0 0 0 0 0 0 171
172 492.1 39.3 0 0 0 0 1 0 0 0 0 0 0 0 172
173 421.3 34.1 0 0 0 0 0 1 0 0 0 0 0 0 173
174 396.7 32.4 0 0 0 0 0 0 1 0 0 0 0 0 174
175 428.0 36.3 0 0 0 0 0 0 0 1 0 0 0 0 175
176 421.9 36.8 0 0 0 0 0 0 0 0 1 0 0 0 176
177 465.6 40.5 0 0 0 0 0 0 0 0 0 1 0 0 177
178 525.8 46.0 0 0 0 0 0 0 0 0 0 0 1 0 178
179 499.9 43.9 0 0 0 0 0 0 0 0 0 0 0 1 179
180 435.3 37.2 0 0 0 0 0 0 0 0 0 0 0 0 180
181 479.5 40.7 0 1 0 0 0 0 0 0 0 0 0 0 181
182 473.0 42.0 0 0 1 0 0 0 0 0 0 0 0 0 182
183 554.4 49.2 0 0 0 1 0 0 0 0 0 0 0 0 183
184 489.6 42.3 0 0 0 0 1 0 0 0 0 0 0 0 184
185 462.2 40.8 0 0 0 0 0 1 0 0 0 0 0 0 185
186 420.3 37.6 0 0 0 0 0 0 1 0 0 0 0 0 186
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) `X[t]` `D[t]` M1 M2 M3
209.716 4.161 35.614 44.488 17.060 59.901
M4 M5 M6 M7 M8 M9
42.332 28.267 -5.121 7.384 18.120 31.427
M10 M11 t
58.171 48.862 0.251
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-24.1664 -8.6177 -0.7808 6.7515 34.1444
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 209.71551 3.46008 60.610 < 2e-16 ***
`X[t]` 4.16065 0.40193 10.352 < 2e-16 ***
`D[t]` 35.61396 12.39356 2.874 0.004573 **
M1 44.48811 4.48990 9.908 < 2e-16 ***
M2 17.05951 4.43623 3.846 0.000170 ***
M3 59.90125 4.95736 12.083 < 2e-16 ***
M4 42.33201 4.52459 9.356 < 2e-16 ***
M5 28.26722 4.41446 6.403 1.41e-09 ***
M6 -5.12092 4.26983 -1.199 0.232060
M7 7.38450 4.38773 1.683 0.094202 .
M8 18.12047 4.46203 4.061 7.43e-05 ***
M9 31.42704 4.58063 6.861 1.20e-10 ***
M10 58.17085 4.96215 11.723 < 2e-16 ***
M11 48.86224 5.02460 9.725 < 2e-16 ***
t 0.25101 0.08216 3.055 0.002611 **
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 11.88 on 171 degrees of freedom
Multiple R-squared: 0.9711, Adjusted R-squared: 0.9687
F-statistic: 410.4 on 14 and 171 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,] 1.154177e-02 2.308354e-02 9.884582e-01
[2,] 2.939459e-03 5.878918e-03 9.970605e-01
[3,] 9.886685e-04 1.977337e-03 9.990113e-01
[4,] 3.759150e-04 7.518300e-04 9.996241e-01
[5,] 8.413804e-05 1.682761e-04 9.999159e-01
[6,] 1.648069e-05 3.296138e-05 9.999835e-01
[7,] 6.376027e-06 1.275205e-05 9.999936e-01
[8,] 1.859701e-06 3.719403e-06 9.999981e-01
[9,] 3.917427e-06 7.834854e-06 9.999961e-01
[10,] 1.490040e-06 2.980080e-06 9.999985e-01
[11,] 3.753704e-07 7.507408e-07 9.999996e-01
[12,] 8.025422e-08 1.605084e-07 9.999999e-01
[13,] 2.391961e-08 4.783921e-08 1.000000e+00
[14,] 6.840236e-09 1.368047e-08 1.000000e+00
[15,] 4.731557e-09 9.463114e-09 1.000000e+00
[16,] 8.304497e-09 1.660899e-08 1.000000e+00
[17,] 2.010327e-09 4.020655e-09 1.000000e+00
[18,] 6.071447e-10 1.214289e-09 1.000000e+00
[19,] 2.347643e-10 4.695286e-10 1.000000e+00
[20,] 8.801330e-11 1.760266e-10 1.000000e+00
[21,] 1.190562e-10 2.381125e-10 1.000000e+00
[22,] 6.445710e-10 1.289142e-09 1.000000e+00
[23,] 1.809555e-10 3.619110e-10 1.000000e+00
[24,] 5.148529e-11 1.029706e-10 1.000000e+00
[25,] 3.137878e-11 6.275755e-11 1.000000e+00
[26,] 8.173356e-12 1.634671e-11 1.000000e+00
[27,] 3.986650e-12 7.973301e-12 1.000000e+00
[28,] 2.305318e-12 4.610635e-12 1.000000e+00
[29,] 2.278090e-12 4.556181e-12 1.000000e+00
[30,] 8.886941e-13 1.777388e-12 1.000000e+00
[31,] 4.167401e-13 8.334801e-13 1.000000e+00
[32,] 1.148150e-13 2.296300e-13 1.000000e+00
[33,] 4.728812e-14 9.457623e-14 1.000000e+00
[34,] 1.390308e-14 2.780617e-14 1.000000e+00
[35,] 5.724172e-15 1.144834e-14 1.000000e+00
[36,] 3.702575e-15 7.405151e-15 1.000000e+00
[37,] 2.969622e-15 5.939243e-15 1.000000e+00
[38,] 1.283948e-15 2.567895e-15 1.000000e+00
[39,] 1.753294e-15 3.506589e-15 1.000000e+00
[40,] 2.653147e-14 5.306293e-14 1.000000e+00
[41,] 1.012458e-13 2.024916e-13 1.000000e+00
[42,] 3.982757e-14 7.965513e-14 1.000000e+00
[43,] 1.365153e-14 2.730305e-14 1.000000e+00
[44,] 1.521850e-14 3.043700e-14 1.000000e+00
[45,] 9.288631e-15 1.857726e-14 1.000000e+00
[46,] 8.089567e-15 1.617913e-14 1.000000e+00
[47,] 3.729122e-15 7.458245e-15 1.000000e+00
[48,] 3.495025e-15 6.990050e-15 1.000000e+00
[49,] 1.227187e-15 2.454375e-15 1.000000e+00
[50,] 1.748143e-15 3.496285e-15 1.000000e+00
[51,] 8.835505e-14 1.767101e-13 1.000000e+00
[52,] 1.566515e-13 3.133030e-13 1.000000e+00
[53,] 4.318597e-13 8.637193e-13 1.000000e+00
[54,] 4.831824e-13 9.663648e-13 1.000000e+00
[55,] 2.048521e-13 4.097043e-13 1.000000e+00
[56,] 1.681622e-13 3.363243e-13 1.000000e+00
[57,] 2.153496e-13 4.306992e-13 1.000000e+00
[58,] 3.503461e-13 7.006923e-13 1.000000e+00
[59,] 8.721875e-13 1.744375e-12 1.000000e+00
[60,] 1.847015e-11 3.694030e-11 1.000000e+00
[61,] 1.571674e-11 3.143348e-11 1.000000e+00
[62,] 4.633131e-09 9.266261e-09 1.000000e+00
[63,] 6.731919e-06 1.346384e-05 9.999933e-01
[64,] 1.358170e-04 2.716341e-04 9.998642e-01
[65,] 3.132714e-04 6.265429e-04 9.996867e-01
[66,] 6.041391e-04 1.208278e-03 9.993959e-01
[67,] 5.040468e-04 1.008094e-03 9.994960e-01
[68,] 5.807275e-04 1.161455e-03 9.994193e-01
[69,] 9.762848e-04 1.952570e-03 9.990237e-01
[70,] 1.194772e-03 2.389545e-03 9.988052e-01
[71,] 1.095446e-03 2.190893e-03 9.989046e-01
[72,] 5.478201e-03 1.095640e-02 9.945218e-01
[73,] 5.134455e-03 1.026891e-02 9.948655e-01
[74,] 5.957358e-03 1.191472e-02 9.940426e-01
[75,] 3.003071e-02 6.006141e-02 9.699693e-01
[76,] 4.226388e-02 8.452776e-02 9.577361e-01
[77,] 6.201264e-02 1.240253e-01 9.379874e-01
[78,] 7.918016e-02 1.583603e-01 9.208198e-01
[79,] 7.654054e-02 1.530811e-01 9.234595e-01
[80,] 8.476465e-02 1.695293e-01 9.152354e-01
[81,] 8.091629e-02 1.618326e-01 9.190837e-01
[82,] 7.792828e-02 1.558566e-01 9.220717e-01
[83,] 6.782851e-02 1.356570e-01 9.321715e-01
[84,] 1.458241e-01 2.916483e-01 8.541759e-01
[85,] 1.496016e-01 2.992031e-01 8.503984e-01
[86,] 1.369535e-01 2.739070e-01 8.630465e-01
[87,] 3.002088e-01 6.004175e-01 6.997912e-01
[88,] 3.341314e-01 6.682628e-01 6.658686e-01
[89,] 2.933677e-01 5.867354e-01 7.066323e-01
[90,] 6.034997e-01 7.930006e-01 3.965003e-01
[91,] 7.559773e-01 4.880454e-01 2.440227e-01
[92,] 8.929934e-01 2.140131e-01 1.070066e-01
[93,] 9.259594e-01 1.480813e-01 7.404064e-02
[94,] 9.766668e-01 4.666641e-02 2.333320e-02
[95,] 9.865757e-01 2.684860e-02 1.342430e-02
[96,] 9.922157e-01 1.556870e-02 7.784348e-03
[97,] 9.974654e-01 5.069163e-03 2.534582e-03
[98,] 9.986222e-01 2.755551e-03 1.377776e-03
[99,] 9.997548e-01 4.903824e-04 2.451912e-04
[100,] 9.999493e-01 1.014076e-04 5.070380e-05
[101,] 9.999626e-01 7.470968e-05 3.735484e-05
[102,] 9.999795e-01 4.092752e-05 2.046376e-05
[103,] 9.999792e-01 4.160616e-05 2.080308e-05
[104,] 9.999989e-01 2.108152e-06 1.054076e-06
[105,] 9.999985e-01 3.064867e-06 1.532434e-06
[106,] 9.999986e-01 2.819940e-06 1.409970e-06
[107,] 9.999984e-01 3.162645e-06 1.581322e-06
[108,] 9.999990e-01 2.004665e-06 1.002333e-06
[109,] 9.999990e-01 1.958071e-06 9.790356e-07
[110,] 9.999993e-01 1.321222e-06 6.606109e-07
[111,] 9.999997e-01 5.082892e-07 2.541446e-07
[112,] 9.999997e-01 5.468547e-07 2.734273e-07
[113,] 9.999997e-01 6.547445e-07 3.273722e-07
[114,] 9.999996e-01 7.554262e-07 3.777131e-07
[115,] 9.999994e-01 1.204038e-06 6.020189e-07
[116,] 9.999991e-01 1.813959e-06 9.069793e-07
[117,] 9.999985e-01 3.054879e-06 1.527439e-06
[118,] 9.999975e-01 5.089879e-06 2.544939e-06
[119,] 9.999984e-01 3.246865e-06 1.623432e-06
[120,] 9.999974e-01 5.279351e-06 2.639676e-06
[121,] 9.999951e-01 9.890755e-06 4.945378e-06
[122,] 9.999902e-01 1.958685e-05 9.793427e-06
[123,] 9.999876e-01 2.486228e-05 1.243114e-05
[124,] 9.999744e-01 5.124316e-05 2.562158e-05
[125,] 9.999494e-01 1.012316e-04 5.061582e-05
[126,] 9.999051e-01 1.897561e-04 9.487804e-05
[127,] 9.998830e-01 2.340208e-04 1.170104e-04
[128,] 9.997808e-01 4.384317e-04 2.192159e-04
[129,] 9.995785e-01 8.430923e-04 4.215461e-04
[130,] 9.992924e-01 1.415119e-03 7.075595e-04
[131,] 9.989514e-01 2.097162e-03 1.048581e-03
[132,] 9.982345e-01 3.531013e-03 1.765507e-03
[133,] 9.970534e-01 5.893245e-03 2.946622e-03
[134,] 9.948871e-01 1.022585e-02 5.112925e-03
[135,] 9.921305e-01 1.573906e-02 7.869528e-03
[136,] 9.873036e-01 2.539272e-02 1.269636e-02
[137,] 9.823792e-01 3.524158e-02 1.762079e-02
[138,] 9.758141e-01 4.837188e-02 2.418594e-02
[139,] 9.628008e-01 7.439830e-02 3.719915e-02
[140,] 9.437894e-01 1.124213e-01 5.621063e-02
[141,] 9.396766e-01 1.206469e-01 6.032345e-02
[142,] 9.082086e-01 1.835829e-01 9.179145e-02
[143,] 8.769107e-01 2.461786e-01 1.230893e-01
[144,] 8.478950e-01 3.042100e-01 1.521050e-01
[145,] 7.939675e-01 4.120650e-01 2.060325e-01
[146,] 7.478941e-01 5.042117e-01 2.521059e-01
[147,] 7.020256e-01 5.959487e-01 2.979744e-01
[148,] 6.206784e-01 7.586431e-01 3.793216e-01
[149,] 4.924807e-01 9.849613e-01 5.075193e-01
[150,] 5.129600e-01 9.740800e-01 4.870400e-01
[151,] 3.841050e-01 7.682100e-01 6.158950e-01
> postscript(file="/var/www/rcomp/tmp/1vi191261082312.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/2zlbw1261082312.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/rcomp/tmp/3vge31261082312.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/45qcd1261082312.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/5i7561261082312.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 = 186
Frequency = 1
1 2 3 4 5
-9.491620e+00 2.118094e+00 -1.330317e+01 -1.010462e+01 3.193094e+00
6 7 8 9 10
-1.860932e+00 -9.181620e+00 1.023862e+01 2.810381e-01 -9.158370e+00
11 12 13 14 15
-1.218470e+01 -9.968238e+00 -3.965239e-01 1.845319e+00 -4.456273e+00
16 17 18 19 20
-1.197739e+01 6.772125e+00 -4.201577e+00 -2.589310e-03 1.578552e+01
21 22 23 24 25
4.027939e+00 3.556402e+00 -1.332535e+01 -7.208883e+00 -5.753233e+00
26 27 28 29 30
-1.254713e+01 -1.398085e+01 -1.710197e+01 -2.520325e+00 -8.426157e+00
31 32 33 34 35
7.896117e+00 1.724849e+01 4.374840e+00 1.205511e+01 6.769683e-01
36 37 38 39 40
5.757694e+00 1.011334e+01 -8.966189e-01 -8.330341e+00 1.000346e+00
41 42 43 44 45
1.301412e+01 6.056485e+00 9.715373e-01 2.744719e+01 5.853871e+00
46 47 48 49 50
5.350204e+00 -4.779741e+00 1.491791e-01 6.824504e+00 7.702088e+00
51 52 53 54 55
4.068365e+00 -6.402986e-01 1.957709e+01 6.783710e+00 -2.217302e+00
56 57 58 59 60
2.404229e+01 6.436513e+00 -9.386353e-01 1.529045e+01 3.496080e+00
61 62 63 64 65
1.187470e+00 5.881118e+00 1.807429e+01 4.362019e+00 2.134366e+01
66 67 68 69 70
6.714547e+00 1.533210e+00 2.722854e+01 1.715489e+01 1.001549e+01
71 72 73 74 75
1.686063e+01 4.026916e+00 2.734371e+00 6.763760e+00 8.369389e+00
76 77 78 79 80
1.396465e+00 9.258436e+00 -1.006422e+00 -1.797169e+01 -9.763621e-01
81 82 83 84 85
-1.096607e+01 -2.885806e+00 1.018624e+01 2.497104e+00 3.876039e+00
86 87 88 89 90
-1.894572e+00 6.110569e-01 -4.949412e+00 -1.080712e+01 -3.000495e+00
91 92 93 94 95
1.034507e+01 -1.506175e+00 2.811334e+00 6.024343e-01 -2.768484e+00
96 97 98 99 100
-7.329098e+00 -8.682293e+00 -6.945682e+00 -8.788248e+00 -3.948717e+00
101 102 103 104 105
-2.317790e+01 -1.535883e+01 -1.263655e+01 -2.344844e+01 -2.160241e+01
106 107 108 109 110
3.883883e-15 1.709124e+01 1.789488e+01 1.494169e+01 8.303208e+00
111 112 113 114 115
6.157031e+00 1.349494e+01 -7.217925e-01 1.186515e+01 9.591039e+00
116 117 118 119 120
-9.195941e+00 2.909114e+00 -9.971267e+00 -4.515289e+00 -8.681502e+00
121 122 123 124 125
2.411876e+00 -8.190865e+00 -5.406534e+00 -3.913575e+00 -8.915865e+00
126 127 128 129 130
-4.936139e+00 1.725486e+00 -1.899001e+01 -1.306366e+01 -1.859747e+01
131 132 133 134 135
-1.928084e+01 -1.526312e+01 -1.257335e+01 -1.764234e+01 -1.349014e+01
136 137 138 139 140
-1.509880e+01 -1.834767e+01 -1.401613e+01 -1.763353e+00 -2.416640e+01
141 142 143 144 145
-7.605928e+00 -9.705984e+00 -4.933941e+00 -1.372344e+01 -1.254613e+01
146 147 148 149 150
-5.636414e+00 -9.768148e+00 -3.055514e+00 -1.163651e+01 -2.285298e+00
151 152 153 154 155
-3.243349e+00 -1.882311e+01 5.703829e-02 1.756982e+00 -1.330509e+01
156 157 158 159 160
-2.660474e+00 -2.331356e+00 -1.066821e+01 -2.676663e+00 1.800231e+00
161 162 163 164 165
-3.071551e+00 -2.529554e+00 -9.876043e-01 -2.165852e+01 -2.190828e+00
166 167 168 169 170
-3.923014e+00 1.249029e+00 5.386427e+00 -8.398707e-01 6.014427e+00
171 172 173 174 175
8.775838e+00 3.336519e+01 -1.985665e+00 1.362457e+01 1.594161e+01
176 177 178 179 180
-3.225695e+00 1.152232e+01 2.184393e+01 1.373889e+01 2.562647e+01
181 182 183 184 185
1.052508e+01 2.579382e+01 3.414440e+01 1.537111e+01 8.025862e+00
186
1.257707e+01
> postscript(file="/var/www/rcomp/tmp/6x8sm1261082312.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 = 186
Frequency = 1
lag(myerror, k = 1) myerror
0 -9.491620e+00 NA
1 2.118094e+00 -9.491620e+00
2 -1.330317e+01 2.118094e+00
3 -1.010462e+01 -1.330317e+01
4 3.193094e+00 -1.010462e+01
5 -1.860932e+00 3.193094e+00
6 -9.181620e+00 -1.860932e+00
7 1.023862e+01 -9.181620e+00
8 2.810381e-01 1.023862e+01
9 -9.158370e+00 2.810381e-01
10 -1.218470e+01 -9.158370e+00
11 -9.968238e+00 -1.218470e+01
12 -3.965239e-01 -9.968238e+00
13 1.845319e+00 -3.965239e-01
14 -4.456273e+00 1.845319e+00
15 -1.197739e+01 -4.456273e+00
16 6.772125e+00 -1.197739e+01
17 -4.201577e+00 6.772125e+00
18 -2.589310e-03 -4.201577e+00
19 1.578552e+01 -2.589310e-03
20 4.027939e+00 1.578552e+01
21 3.556402e+00 4.027939e+00
22 -1.332535e+01 3.556402e+00
23 -7.208883e+00 -1.332535e+01
24 -5.753233e+00 -7.208883e+00
25 -1.254713e+01 -5.753233e+00
26 -1.398085e+01 -1.254713e+01
27 -1.710197e+01 -1.398085e+01
28 -2.520325e+00 -1.710197e+01
29 -8.426157e+00 -2.520325e+00
30 7.896117e+00 -8.426157e+00
31 1.724849e+01 7.896117e+00
32 4.374840e+00 1.724849e+01
33 1.205511e+01 4.374840e+00
34 6.769683e-01 1.205511e+01
35 5.757694e+00 6.769683e-01
36 1.011334e+01 5.757694e+00
37 -8.966189e-01 1.011334e+01
38 -8.330341e+00 -8.966189e-01
39 1.000346e+00 -8.330341e+00
40 1.301412e+01 1.000346e+00
41 6.056485e+00 1.301412e+01
42 9.715373e-01 6.056485e+00
43 2.744719e+01 9.715373e-01
44 5.853871e+00 2.744719e+01
45 5.350204e+00 5.853871e+00
46 -4.779741e+00 5.350204e+00
47 1.491791e-01 -4.779741e+00
48 6.824504e+00 1.491791e-01
49 7.702088e+00 6.824504e+00
50 4.068365e+00 7.702088e+00
51 -6.402986e-01 4.068365e+00
52 1.957709e+01 -6.402986e-01
53 6.783710e+00 1.957709e+01
54 -2.217302e+00 6.783710e+00
55 2.404229e+01 -2.217302e+00
56 6.436513e+00 2.404229e+01
57 -9.386353e-01 6.436513e+00
58 1.529045e+01 -9.386353e-01
59 3.496080e+00 1.529045e+01
60 1.187470e+00 3.496080e+00
61 5.881118e+00 1.187470e+00
62 1.807429e+01 5.881118e+00
63 4.362019e+00 1.807429e+01
64 2.134366e+01 4.362019e+00
65 6.714547e+00 2.134366e+01
66 1.533210e+00 6.714547e+00
67 2.722854e+01 1.533210e+00
68 1.715489e+01 2.722854e+01
69 1.001549e+01 1.715489e+01
70 1.686063e+01 1.001549e+01
71 4.026916e+00 1.686063e+01
72 2.734371e+00 4.026916e+00
73 6.763760e+00 2.734371e+00
74 8.369389e+00 6.763760e+00
75 1.396465e+00 8.369389e+00
76 9.258436e+00 1.396465e+00
77 -1.006422e+00 9.258436e+00
78 -1.797169e+01 -1.006422e+00
79 -9.763621e-01 -1.797169e+01
80 -1.096607e+01 -9.763621e-01
81 -2.885806e+00 -1.096607e+01
82 1.018624e+01 -2.885806e+00
83 2.497104e+00 1.018624e+01
84 3.876039e+00 2.497104e+00
85 -1.894572e+00 3.876039e+00
86 6.110569e-01 -1.894572e+00
87 -4.949412e+00 6.110569e-01
88 -1.080712e+01 -4.949412e+00
89 -3.000495e+00 -1.080712e+01
90 1.034507e+01 -3.000495e+00
91 -1.506175e+00 1.034507e+01
92 2.811334e+00 -1.506175e+00
93 6.024343e-01 2.811334e+00
94 -2.768484e+00 6.024343e-01
95 -7.329098e+00 -2.768484e+00
96 -8.682293e+00 -7.329098e+00
97 -6.945682e+00 -8.682293e+00
98 -8.788248e+00 -6.945682e+00
99 -3.948717e+00 -8.788248e+00
100 -2.317790e+01 -3.948717e+00
101 -1.535883e+01 -2.317790e+01
102 -1.263655e+01 -1.535883e+01
103 -2.344844e+01 -1.263655e+01
104 -2.160241e+01 -2.344844e+01
105 3.883883e-15 -2.160241e+01
106 1.709124e+01 3.883883e-15
107 1.789488e+01 1.709124e+01
108 1.494169e+01 1.789488e+01
109 8.303208e+00 1.494169e+01
110 6.157031e+00 8.303208e+00
111 1.349494e+01 6.157031e+00
112 -7.217925e-01 1.349494e+01
113 1.186515e+01 -7.217925e-01
114 9.591039e+00 1.186515e+01
115 -9.195941e+00 9.591039e+00
116 2.909114e+00 -9.195941e+00
117 -9.971267e+00 2.909114e+00
118 -4.515289e+00 -9.971267e+00
119 -8.681502e+00 -4.515289e+00
120 2.411876e+00 -8.681502e+00
121 -8.190865e+00 2.411876e+00
122 -5.406534e+00 -8.190865e+00
123 -3.913575e+00 -5.406534e+00
124 -8.915865e+00 -3.913575e+00
125 -4.936139e+00 -8.915865e+00
126 1.725486e+00 -4.936139e+00
127 -1.899001e+01 1.725486e+00
128 -1.306366e+01 -1.899001e+01
129 -1.859747e+01 -1.306366e+01
130 -1.928084e+01 -1.859747e+01
131 -1.526312e+01 -1.928084e+01
132 -1.257335e+01 -1.526312e+01
133 -1.764234e+01 -1.257335e+01
134 -1.349014e+01 -1.764234e+01
135 -1.509880e+01 -1.349014e+01
136 -1.834767e+01 -1.509880e+01
137 -1.401613e+01 -1.834767e+01
138 -1.763353e+00 -1.401613e+01
139 -2.416640e+01 -1.763353e+00
140 -7.605928e+00 -2.416640e+01
141 -9.705984e+00 -7.605928e+00
142 -4.933941e+00 -9.705984e+00
143 -1.372344e+01 -4.933941e+00
144 -1.254613e+01 -1.372344e+01
145 -5.636414e+00 -1.254613e+01
146 -9.768148e+00 -5.636414e+00
147 -3.055514e+00 -9.768148e+00
148 -1.163651e+01 -3.055514e+00
149 -2.285298e+00 -1.163651e+01
150 -3.243349e+00 -2.285298e+00
151 -1.882311e+01 -3.243349e+00
152 5.703829e-02 -1.882311e+01
153 1.756982e+00 5.703829e-02
154 -1.330509e+01 1.756982e+00
155 -2.660474e+00 -1.330509e+01
156 -2.331356e+00 -2.660474e+00
157 -1.066821e+01 -2.331356e+00
158 -2.676663e+00 -1.066821e+01
159 1.800231e+00 -2.676663e+00
160 -3.071551e+00 1.800231e+00
161 -2.529554e+00 -3.071551e+00
162 -9.876043e-01 -2.529554e+00
163 -2.165852e+01 -9.876043e-01
164 -2.190828e+00 -2.165852e+01
165 -3.923014e+00 -2.190828e+00
166 1.249029e+00 -3.923014e+00
167 5.386427e+00 1.249029e+00
168 -8.398707e-01 5.386427e+00
169 6.014427e+00 -8.398707e-01
170 8.775838e+00 6.014427e+00
171 3.336519e+01 8.775838e+00
172 -1.985665e+00 3.336519e+01
173 1.362457e+01 -1.985665e+00
174 1.594161e+01 1.362457e+01
175 -3.225695e+00 1.594161e+01
176 1.152232e+01 -3.225695e+00
177 2.184393e+01 1.152232e+01
178 1.373889e+01 2.184393e+01
179 2.562647e+01 1.373889e+01
180 1.052508e+01 2.562647e+01
181 2.579382e+01 1.052508e+01
182 3.414440e+01 2.579382e+01
183 1.537111e+01 3.414440e+01
184 8.025862e+00 1.537111e+01
185 1.257707e+01 8.025862e+00
186 NA 1.257707e+01
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 2.118094e+00 -9.491620e+00
[2,] -1.330317e+01 2.118094e+00
[3,] -1.010462e+01 -1.330317e+01
[4,] 3.193094e+00 -1.010462e+01
[5,] -1.860932e+00 3.193094e+00
[6,] -9.181620e+00 -1.860932e+00
[7,] 1.023862e+01 -9.181620e+00
[8,] 2.810381e-01 1.023862e+01
[9,] -9.158370e+00 2.810381e-01
[10,] -1.218470e+01 -9.158370e+00
[11,] -9.968238e+00 -1.218470e+01
[12,] -3.965239e-01 -9.968238e+00
[13,] 1.845319e+00 -3.965239e-01
[14,] -4.456273e+00 1.845319e+00
[15,] -1.197739e+01 -4.456273e+00
[16,] 6.772125e+00 -1.197739e+01
[17,] -4.201577e+00 6.772125e+00
[18,] -2.589310e-03 -4.201577e+00
[19,] 1.578552e+01 -2.589310e-03
[20,] 4.027939e+00 1.578552e+01
[21,] 3.556402e+00 4.027939e+00
[22,] -1.332535e+01 3.556402e+00
[23,] -7.208883e+00 -1.332535e+01
[24,] -5.753233e+00 -7.208883e+00
[25,] -1.254713e+01 -5.753233e+00
[26,] -1.398085e+01 -1.254713e+01
[27,] -1.710197e+01 -1.398085e+01
[28,] -2.520325e+00 -1.710197e+01
[29,] -8.426157e+00 -2.520325e+00
[30,] 7.896117e+00 -8.426157e+00
[31,] 1.724849e+01 7.896117e+00
[32,] 4.374840e+00 1.724849e+01
[33,] 1.205511e+01 4.374840e+00
[34,] 6.769683e-01 1.205511e+01
[35,] 5.757694e+00 6.769683e-01
[36,] 1.011334e+01 5.757694e+00
[37,] -8.966189e-01 1.011334e+01
[38,] -8.330341e+00 -8.966189e-01
[39,] 1.000346e+00 -8.330341e+00
[40,] 1.301412e+01 1.000346e+00
[41,] 6.056485e+00 1.301412e+01
[42,] 9.715373e-01 6.056485e+00
[43,] 2.744719e+01 9.715373e-01
[44,] 5.853871e+00 2.744719e+01
[45,] 5.350204e+00 5.853871e+00
[46,] -4.779741e+00 5.350204e+00
[47,] 1.491791e-01 -4.779741e+00
[48,] 6.824504e+00 1.491791e-01
[49,] 7.702088e+00 6.824504e+00
[50,] 4.068365e+00 7.702088e+00
[51,] -6.402986e-01 4.068365e+00
[52,] 1.957709e+01 -6.402986e-01
[53,] 6.783710e+00 1.957709e+01
[54,] -2.217302e+00 6.783710e+00
[55,] 2.404229e+01 -2.217302e+00
[56,] 6.436513e+00 2.404229e+01
[57,] -9.386353e-01 6.436513e+00
[58,] 1.529045e+01 -9.386353e-01
[59,] 3.496080e+00 1.529045e+01
[60,] 1.187470e+00 3.496080e+00
[61,] 5.881118e+00 1.187470e+00
[62,] 1.807429e+01 5.881118e+00
[63,] 4.362019e+00 1.807429e+01
[64,] 2.134366e+01 4.362019e+00
[65,] 6.714547e+00 2.134366e+01
[66,] 1.533210e+00 6.714547e+00
[67,] 2.722854e+01 1.533210e+00
[68,] 1.715489e+01 2.722854e+01
[69,] 1.001549e+01 1.715489e+01
[70,] 1.686063e+01 1.001549e+01
[71,] 4.026916e+00 1.686063e+01
[72,] 2.734371e+00 4.026916e+00
[73,] 6.763760e+00 2.734371e+00
[74,] 8.369389e+00 6.763760e+00
[75,] 1.396465e+00 8.369389e+00
[76,] 9.258436e+00 1.396465e+00
[77,] -1.006422e+00 9.258436e+00
[78,] -1.797169e+01 -1.006422e+00
[79,] -9.763621e-01 -1.797169e+01
[80,] -1.096607e+01 -9.763621e-01
[81,] -2.885806e+00 -1.096607e+01
[82,] 1.018624e+01 -2.885806e+00
[83,] 2.497104e+00 1.018624e+01
[84,] 3.876039e+00 2.497104e+00
[85,] -1.894572e+00 3.876039e+00
[86,] 6.110569e-01 -1.894572e+00
[87,] -4.949412e+00 6.110569e-01
[88,] -1.080712e+01 -4.949412e+00
[89,] -3.000495e+00 -1.080712e+01
[90,] 1.034507e+01 -3.000495e+00
[91,] -1.506175e+00 1.034507e+01
[92,] 2.811334e+00 -1.506175e+00
[93,] 6.024343e-01 2.811334e+00
[94,] -2.768484e+00 6.024343e-01
[95,] -7.329098e+00 -2.768484e+00
[96,] -8.682293e+00 -7.329098e+00
[97,] -6.945682e+00 -8.682293e+00
[98,] -8.788248e+00 -6.945682e+00
[99,] -3.948717e+00 -8.788248e+00
[100,] -2.317790e+01 -3.948717e+00
[101,] -1.535883e+01 -2.317790e+01
[102,] -1.263655e+01 -1.535883e+01
[103,] -2.344844e+01 -1.263655e+01
[104,] -2.160241e+01 -2.344844e+01
[105,] 3.883883e-15 -2.160241e+01
[106,] 1.709124e+01 3.883883e-15
[107,] 1.789488e+01 1.709124e+01
[108,] 1.494169e+01 1.789488e+01
[109,] 8.303208e+00 1.494169e+01
[110,] 6.157031e+00 8.303208e+00
[111,] 1.349494e+01 6.157031e+00
[112,] -7.217925e-01 1.349494e+01
[113,] 1.186515e+01 -7.217925e-01
[114,] 9.591039e+00 1.186515e+01
[115,] -9.195941e+00 9.591039e+00
[116,] 2.909114e+00 -9.195941e+00
[117,] -9.971267e+00 2.909114e+00
[118,] -4.515289e+00 -9.971267e+00
[119,] -8.681502e+00 -4.515289e+00
[120,] 2.411876e+00 -8.681502e+00
[121,] -8.190865e+00 2.411876e+00
[122,] -5.406534e+00 -8.190865e+00
[123,] -3.913575e+00 -5.406534e+00
[124,] -8.915865e+00 -3.913575e+00
[125,] -4.936139e+00 -8.915865e+00
[126,] 1.725486e+00 -4.936139e+00
[127,] -1.899001e+01 1.725486e+00
[128,] -1.306366e+01 -1.899001e+01
[129,] -1.859747e+01 -1.306366e+01
[130,] -1.928084e+01 -1.859747e+01
[131,] -1.526312e+01 -1.928084e+01
[132,] -1.257335e+01 -1.526312e+01
[133,] -1.764234e+01 -1.257335e+01
[134,] -1.349014e+01 -1.764234e+01
[135,] -1.509880e+01 -1.349014e+01
[136,] -1.834767e+01 -1.509880e+01
[137,] -1.401613e+01 -1.834767e+01
[138,] -1.763353e+00 -1.401613e+01
[139,] -2.416640e+01 -1.763353e+00
[140,] -7.605928e+00 -2.416640e+01
[141,] -9.705984e+00 -7.605928e+00
[142,] -4.933941e+00 -9.705984e+00
[143,] -1.372344e+01 -4.933941e+00
[144,] -1.254613e+01 -1.372344e+01
[145,] -5.636414e+00 -1.254613e+01
[146,] -9.768148e+00 -5.636414e+00
[147,] -3.055514e+00 -9.768148e+00
[148,] -1.163651e+01 -3.055514e+00
[149,] -2.285298e+00 -1.163651e+01
[150,] -3.243349e+00 -2.285298e+00
[151,] -1.882311e+01 -3.243349e+00
[152,] 5.703829e-02 -1.882311e+01
[153,] 1.756982e+00 5.703829e-02
[154,] -1.330509e+01 1.756982e+00
[155,] -2.660474e+00 -1.330509e+01
[156,] -2.331356e+00 -2.660474e+00
[157,] -1.066821e+01 -2.331356e+00
[158,] -2.676663e+00 -1.066821e+01
[159,] 1.800231e+00 -2.676663e+00
[160,] -3.071551e+00 1.800231e+00
[161,] -2.529554e+00 -3.071551e+00
[162,] -9.876043e-01 -2.529554e+00
[163,] -2.165852e+01 -9.876043e-01
[164,] -2.190828e+00 -2.165852e+01
[165,] -3.923014e+00 -2.190828e+00
[166,] 1.249029e+00 -3.923014e+00
[167,] 5.386427e+00 1.249029e+00
[168,] -8.398707e-01 5.386427e+00
[169,] 6.014427e+00 -8.398707e-01
[170,] 8.775838e+00 6.014427e+00
[171,] 3.336519e+01 8.775838e+00
[172,] -1.985665e+00 3.336519e+01
[173,] 1.362457e+01 -1.985665e+00
[174,] 1.594161e+01 1.362457e+01
[175,] -3.225695e+00 1.594161e+01
[176,] 1.152232e+01 -3.225695e+00
[177,] 2.184393e+01 1.152232e+01
[178,] 1.373889e+01 2.184393e+01
[179,] 2.562647e+01 1.373889e+01
[180,] 1.052508e+01 2.562647e+01
[181,] 2.579382e+01 1.052508e+01
[182,] 3.414440e+01 2.579382e+01
[183,] 1.537111e+01 3.414440e+01
[184,] 8.025862e+00 1.537111e+01
[185,] 1.257707e+01 8.025862e+00
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 2.118094e+00 -9.491620e+00
2 -1.330317e+01 2.118094e+00
3 -1.010462e+01 -1.330317e+01
4 3.193094e+00 -1.010462e+01
5 -1.860932e+00 3.193094e+00
6 -9.181620e+00 -1.860932e+00
7 1.023862e+01 -9.181620e+00
8 2.810381e-01 1.023862e+01
9 -9.158370e+00 2.810381e-01
10 -1.218470e+01 -9.158370e+00
11 -9.968238e+00 -1.218470e+01
12 -3.965239e-01 -9.968238e+00
13 1.845319e+00 -3.965239e-01
14 -4.456273e+00 1.845319e+00
15 -1.197739e+01 -4.456273e+00
16 6.772125e+00 -1.197739e+01
17 -4.201577e+00 6.772125e+00
18 -2.589310e-03 -4.201577e+00
19 1.578552e+01 -2.589310e-03
20 4.027939e+00 1.578552e+01
21 3.556402e+00 4.027939e+00
22 -1.332535e+01 3.556402e+00
23 -7.208883e+00 -1.332535e+01
24 -5.753233e+00 -7.208883e+00
25 -1.254713e+01 -5.753233e+00
26 -1.398085e+01 -1.254713e+01
27 -1.710197e+01 -1.398085e+01
28 -2.520325e+00 -1.710197e+01
29 -8.426157e+00 -2.520325e+00
30 7.896117e+00 -8.426157e+00
31 1.724849e+01 7.896117e+00
32 4.374840e+00 1.724849e+01
33 1.205511e+01 4.374840e+00
34 6.769683e-01 1.205511e+01
35 5.757694e+00 6.769683e-01
36 1.011334e+01 5.757694e+00
37 -8.966189e-01 1.011334e+01
38 -8.330341e+00 -8.966189e-01
39 1.000346e+00 -8.330341e+00
40 1.301412e+01 1.000346e+00
41 6.056485e+00 1.301412e+01
42 9.715373e-01 6.056485e+00
43 2.744719e+01 9.715373e-01
44 5.853871e+00 2.744719e+01
45 5.350204e+00 5.853871e+00
46 -4.779741e+00 5.350204e+00
47 1.491791e-01 -4.779741e+00
48 6.824504e+00 1.491791e-01
49 7.702088e+00 6.824504e+00
50 4.068365e+00 7.702088e+00
51 -6.402986e-01 4.068365e+00
52 1.957709e+01 -6.402986e-01
53 6.783710e+00 1.957709e+01
54 -2.217302e+00 6.783710e+00
55 2.404229e+01 -2.217302e+00
56 6.436513e+00 2.404229e+01
57 -9.386353e-01 6.436513e+00
58 1.529045e+01 -9.386353e-01
59 3.496080e+00 1.529045e+01
60 1.187470e+00 3.496080e+00
61 5.881118e+00 1.187470e+00
62 1.807429e+01 5.881118e+00
63 4.362019e+00 1.807429e+01
64 2.134366e+01 4.362019e+00
65 6.714547e+00 2.134366e+01
66 1.533210e+00 6.714547e+00
67 2.722854e+01 1.533210e+00
68 1.715489e+01 2.722854e+01
69 1.001549e+01 1.715489e+01
70 1.686063e+01 1.001549e+01
71 4.026916e+00 1.686063e+01
72 2.734371e+00 4.026916e+00
73 6.763760e+00 2.734371e+00
74 8.369389e+00 6.763760e+00
75 1.396465e+00 8.369389e+00
76 9.258436e+00 1.396465e+00
77 -1.006422e+00 9.258436e+00
78 -1.797169e+01 -1.006422e+00
79 -9.763621e-01 -1.797169e+01
80 -1.096607e+01 -9.763621e-01
81 -2.885806e+00 -1.096607e+01
82 1.018624e+01 -2.885806e+00
83 2.497104e+00 1.018624e+01
84 3.876039e+00 2.497104e+00
85 -1.894572e+00 3.876039e+00
86 6.110569e-01 -1.894572e+00
87 -4.949412e+00 6.110569e-01
88 -1.080712e+01 -4.949412e+00
89 -3.000495e+00 -1.080712e+01
90 1.034507e+01 -3.000495e+00
91 -1.506175e+00 1.034507e+01
92 2.811334e+00 -1.506175e+00
93 6.024343e-01 2.811334e+00
94 -2.768484e+00 6.024343e-01
95 -7.329098e+00 -2.768484e+00
96 -8.682293e+00 -7.329098e+00
97 -6.945682e+00 -8.682293e+00
98 -8.788248e+00 -6.945682e+00
99 -3.948717e+00 -8.788248e+00
100 -2.317790e+01 -3.948717e+00
101 -1.535883e+01 -2.317790e+01
102 -1.263655e+01 -1.535883e+01
103 -2.344844e+01 -1.263655e+01
104 -2.160241e+01 -2.344844e+01
105 3.883883e-15 -2.160241e+01
106 1.709124e+01 3.883883e-15
107 1.789488e+01 1.709124e+01
108 1.494169e+01 1.789488e+01
109 8.303208e+00 1.494169e+01
110 6.157031e+00 8.303208e+00
111 1.349494e+01 6.157031e+00
112 -7.217925e-01 1.349494e+01
113 1.186515e+01 -7.217925e-01
114 9.591039e+00 1.186515e+01
115 -9.195941e+00 9.591039e+00
116 2.909114e+00 -9.195941e+00
117 -9.971267e+00 2.909114e+00
118 -4.515289e+00 -9.971267e+00
119 -8.681502e+00 -4.515289e+00
120 2.411876e+00 -8.681502e+00
121 -8.190865e+00 2.411876e+00
122 -5.406534e+00 -8.190865e+00
123 -3.913575e+00 -5.406534e+00
124 -8.915865e+00 -3.913575e+00
125 -4.936139e+00 -8.915865e+00
126 1.725486e+00 -4.936139e+00
127 -1.899001e+01 1.725486e+00
128 -1.306366e+01 -1.899001e+01
129 -1.859747e+01 -1.306366e+01
130 -1.928084e+01 -1.859747e+01
131 -1.526312e+01 -1.928084e+01
132 -1.257335e+01 -1.526312e+01
133 -1.764234e+01 -1.257335e+01
134 -1.349014e+01 -1.764234e+01
135 -1.509880e+01 -1.349014e+01
136 -1.834767e+01 -1.509880e+01
137 -1.401613e+01 -1.834767e+01
138 -1.763353e+00 -1.401613e+01
139 -2.416640e+01 -1.763353e+00
140 -7.605928e+00 -2.416640e+01
141 -9.705984e+00 -7.605928e+00
142 -4.933941e+00 -9.705984e+00
143 -1.372344e+01 -4.933941e+00
144 -1.254613e+01 -1.372344e+01
145 -5.636414e+00 -1.254613e+01
146 -9.768148e+00 -5.636414e+00
147 -3.055514e+00 -9.768148e+00
148 -1.163651e+01 -3.055514e+00
149 -2.285298e+00 -1.163651e+01
150 -3.243349e+00 -2.285298e+00
151 -1.882311e+01 -3.243349e+00
152 5.703829e-02 -1.882311e+01
153 1.756982e+00 5.703829e-02
154 -1.330509e+01 1.756982e+00
155 -2.660474e+00 -1.330509e+01
156 -2.331356e+00 -2.660474e+00
157 -1.066821e+01 -2.331356e+00
158 -2.676663e+00 -1.066821e+01
159 1.800231e+00 -2.676663e+00
160 -3.071551e+00 1.800231e+00
161 -2.529554e+00 -3.071551e+00
162 -9.876043e-01 -2.529554e+00
163 -2.165852e+01 -9.876043e-01
164 -2.190828e+00 -2.165852e+01
165 -3.923014e+00 -2.190828e+00
166 1.249029e+00 -3.923014e+00
167 5.386427e+00 1.249029e+00
168 -8.398707e-01 5.386427e+00
169 6.014427e+00 -8.398707e-01
170 8.775838e+00 6.014427e+00
171 3.336519e+01 8.775838e+00
172 -1.985665e+00 3.336519e+01
173 1.362457e+01 -1.985665e+00
174 1.594161e+01 1.362457e+01
175 -3.225695e+00 1.594161e+01
176 1.152232e+01 -3.225695e+00
177 2.184393e+01 1.152232e+01
178 1.373889e+01 2.184393e+01
179 2.562647e+01 1.373889e+01
180 1.052508e+01 2.562647e+01
181 2.579382e+01 1.052508e+01
182 3.414440e+01 2.579382e+01
183 1.537111e+01 3.414440e+01
184 8.025862e+00 1.537111e+01
185 1.257707e+01 8.025862e+00
> 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/rcomp/tmp/74n5y1261082312.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/8e3zy1261082312.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/95pzq1261082312.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
Warning messages:
1: Not plotting observations with leverage one:
106
2: Not plotting observations with leverage one:
106
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/rcomp/tmp/10wzh01261082312.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/rcomp/tmp/11evan1261082312.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/rcomp/tmp/12cwnh1261082312.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/rcomp/tmp/13h16a1261082312.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/rcomp/tmp/1455rv1261082313.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/rcomp/tmp/154j531261082313.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/rcomp/tmp/161ni41261082313.tab")
+ }
>
> try(system("convert tmp/1vi191261082312.ps tmp/1vi191261082312.png",intern=TRUE))
character(0)
> try(system("convert tmp/2zlbw1261082312.ps tmp/2zlbw1261082312.png",intern=TRUE))
character(0)
> try(system("convert tmp/3vge31261082312.ps tmp/3vge31261082312.png",intern=TRUE))
character(0)
> try(system("convert tmp/45qcd1261082312.ps tmp/45qcd1261082312.png",intern=TRUE))
character(0)
> try(system("convert tmp/5i7561261082312.ps tmp/5i7561261082312.png",intern=TRUE))
character(0)
> try(system("convert tmp/6x8sm1261082312.ps tmp/6x8sm1261082312.png",intern=TRUE))
character(0)
> try(system("convert tmp/74n5y1261082312.ps tmp/74n5y1261082312.png",intern=TRUE))
character(0)
> try(system("convert tmp/8e3zy1261082312.ps tmp/8e3zy1261082312.png",intern=TRUE))
character(0)
> try(system("convert tmp/95pzq1261082312.ps tmp/95pzq1261082312.png",intern=TRUE))
character(0)
> try(system("convert tmp/10wzh01261082312.ps tmp/10wzh01261082312.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
6.160 3.170 8.196