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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> x <- array(list(358.59
+ ,122.36
+ ,362.96
+ ,123.33
+ ,362.42
+ ,123.04
+ ,364.97
+ ,124.53
+ ,364.04
+ ,125.13
+ ,361.06
+ ,125.85
+ ,358.48
+ ,126.50
+ ,352.96
+ ,126.53
+ ,359.59
+ ,127.07
+ ,360.39
+ ,124.55
+ ,357.40
+ ,124.90
+ ,362.93
+ ,124.32
+ ,364.55
+ ,122.84
+ ,365.73
+ ,123.31
+ ,364.70
+ ,123.31
+ ,364.65
+ ,124.87
+ ,359.43
+ ,124.64
+ ,362.14
+ ,124.73
+ ,356.97
+ ,124.90
+ ,354.82
+ ,124.04
+ ,353.17
+ ,123.28
+ ,357.06
+ ,123.86
+ ,356.18
+ ,122.29
+ ,355.01
+ ,124.09
+ ,355.65
+ ,124.54
+ ,357.31
+ ,125.65
+ ,357.07
+ ,125.70
+ ,357.91
+ ,125.53
+ ,358.48
+ ,125.61
+ ,358.97
+ ,125.55
+ ,351.77
+ ,125.41
+ ,352.16
+ ,127.60
+ ,359.08
+ ,124.68
+ ,360.35
+ ,124.41
+ ,359.53
+ ,126.43
+ ,359.30
+ ,126.38
+ ,358.41
+ ,125.78
+ ,359.68
+ ,124.70
+ ,355.31
+ ,125.07
+ ,357.08
+ ,125.25
+ ,349.71
+ ,126.58
+ ,354.13
+ ,127.13
+ ,345.49
+ ,125.82
+ ,341.69
+ ,123.70
+ ,344.25
+ ,124.39
+ ,340.17
+ ,123.70
+ ,342.47
+ ,124.42
+ ,344.43
+ ,121.05
+ ,333.23
+ ,121.02
+ ,339.72
+ ,123.23
+ ,342.61
+ ,121.32
+ ,346.36
+ ,120.91
+ ,339.09
+ ,120.72
+ ,339.73
+ ,123.31
+ ,341.12
+ ,119.58
+ ,335.94
+ ,119.53
+ ,333.46
+ ,120.59
+ ,335.66
+ ,118.63
+ ,341.12
+ ,118.47
+ ,342.21
+ ,111.81
+ ,342.62
+ ,114.71
+ ,346.06
+ ,117.34
+ ,344.43
+ ,115.77
+ ,346.65
+ ,118.38
+ ,343.74
+ ,117.84
+ ,335.67
+ ,118.83
+ ,342.75
+ ,120.02
+ ,341.77
+ ,116.21
+ ,345.84
+ ,117.08
+ ,346.52
+ ,120.20
+ ,350.79
+ ,119.83
+ ,345.44
+ ,118.92
+ ,345.87
+ ,118.03
+ ,338.48
+ ,117.71
+ ,337.21
+ ,119.55
+ ,340.81
+ ,116.13
+ ,339.86
+ ,115.97
+ ,342.86
+ ,115.99
+ ,343.33
+ ,114.96
+ ,341.73
+ ,116.46
+ ,351.38
+ ,116.55
+ ,351.13
+ ,113.05
+ ,345.99
+ ,117.44
+ ,347.55
+ ,118.84
+ ,346.02
+ ,117.06
+ ,345.29
+ ,117.54
+ ,347.03
+ ,119.31
+ ,348.01
+ ,118.72
+ ,345.48
+ ,121.55
+ ,349.40
+ ,122.61
+ ,351.05
+ ,121.53
+ ,349.70
+ ,123.31
+ ,350.86
+ ,124.07
+ ,354.45
+ ,123.59
+ ,355.30
+ ,122.97
+ ,357.48
+ ,123.22
+ ,355.24
+ ,123.04
+ ,351.79
+ ,122.96
+ ,355.22
+ ,122.81
+ ,351.02
+ ,122.81
+ ,350.28
+ ,122.62
+ ,350.17
+ ,120.82
+ ,348.16
+ ,119.41
+ ,340.30
+ ,121.56
+ ,343.75
+ ,121.59
+ ,344.71
+ ,118.50
+ ,344.13
+ ,118.77
+ ,342.14
+ ,118.86
+ ,345.04
+ ,117.60
+ ,346.02
+ ,119.90
+ ,346.43
+ ,121.83
+ ,347.07
+ ,121.84
+ ,339.33
+ ,122.12
+ ,339.10
+ ,122.12
+ ,337.19
+ ,121.36
+ ,339.58
+ ,119.66
+ ,327.85
+ ,119.32
+ ,326.81
+ ,120.36
+ ,321.73
+ ,117.06
+ ,320.45
+ ,117.48
+ ,327.69
+ ,115.60
+ ,323.95
+ ,113.86
+ ,320.47
+ ,116.92
+ ,322.13
+ ,117.75
+ ,316.34
+ ,117.75
+ ,314.78
+ ,115.31
+ ,308.90
+ ,116.28
+ ,308.62
+ ,115.22
+ ,314.41
+ ,115.65
+ ,306.88
+ ,115.11
+ ,310.60
+ ,118.67
+ ,321.60
+ ,118.04
+ ,321.50
+ ,116.50
+ ,325.68
+ ,119.78
+ ,324.35
+ ,119.95
+ ,320.01
+ ,120.37
+ ,326.88
+ ,119.79
+ ,332.39
+ ,119.43
+ ,331.48
+ ,121.06
+ ,332.62
+ ,121.74
+ ,324.79
+ ,121.09
+ ,327.12
+ ,122.97
+ ,328.91
+ ,120.50
+ ,328.37
+ ,117.18
+ ,324.83
+ ,115.03
+ ,325.90
+ ,113.36
+ ,326.18
+ ,112.59
+ ,328.94
+ ,111.65
+ ,333.78
+ ,111.98
+ ,328.06
+ ,114.87
+ ,325.87
+ ,114.67
+ ,325.41
+ ,114.09
+ ,318.86
+ ,114.77
+ ,319.13
+ ,117.05
+ ,310.16
+ ,117.22
+ ,311.73
+ ,113.18
+ ,306.54
+ ,110.95
+ ,311.16
+ ,112.14
+ ,311.98
+ ,112.72
+ ,306.72
+ ,110.01
+ ,308.05
+ ,110.29
+ ,300.76
+ ,110.74
+ ,301.90
+ ,110.32
+ ,293.09
+ ,105.89
+ ,292.76
+ ,108.97
+ ,294.58
+ ,109.34
+ ,289.90
+ ,106.57
+ ,296.69
+ ,99.49
+ ,297.21
+ ,101.81
+ ,293.31
+ ,104.29
+ ,296.25
+ ,109.73
+ ,298.60
+ ,105.06
+ ,296.87
+ ,107.97
+ ,301.02
+ ,108.13
+ ,304.73
+ ,109.86
+ ,301.92
+ ,108.95
+ ,295.72
+ ,111.20
+ ,293.18
+ ,110.69
+ ,298.35
+ ,106.10
+ ,297.99
+ ,105.68
+ ,299.85
+ ,104.12
+ ,299.85
+ ,104.71
+ ,304.45
+ ,104.30
+ ,299.45
+ ,103.52
+ ,298.14
+ ,107.76
+ ,298.78
+ ,107.80
+ ,297.02
+ ,107.30
+ ,301.33
+ ,108.64
+ ,294.96
+ ,105.03
+ ,296.69
+ ,108.30
+ ,300.73
+ ,107.21
+ ,301.96
+ ,109.27
+ ,297.38
+ ,109.50
+ ,293.87
+ ,111.68
+ ,285.96
+ ,111.80
+ ,285.41
+ ,111.75
+ ,283.70
+ ,106.68
+ ,284.76
+ ,106.37
+ ,277.11
+ ,105.76
+ ,274.73
+ ,109.01
+ ,274.73
+ ,109.01
+ ,274.73
+ ,109.01
+ ,274.73
+ ,109.01
+ ,274.69
+ ,107.69
+ ,275.42
+ ,105.19
+ ,264.15
+ ,105.48
+ ,276.24
+ ,102.22
+ ,268.88
+ ,100.54
+ ,277.97
+ ,105.00
+ ,280.49
+ ,105.44
+ ,281.09
+ ,107.89
+ ,276.16
+ ,108.64
+ ,272.58
+ ,106.70
+ ,270.94
+ ,109.10
+ ,284.31
+ ,105.23
+ ,283.94
+ ,108.41
+ ,284.18
+ ,108.80
+ ,282.83
+ ,110.39
+ ,283.84
+ ,110.22
+ ,282.71
+ ,110.86
+ ,279.29
+ ,108.58
+ ,280.70
+ ,107.70
+ ,274.47
+ ,106.62
+ ,273.44
+ ,109.84
+ ,275.49
+ ,107.16
+ ,279.46
+ ,107.26
+ ,280.19
+ ,108.70
+ ,288.21
+ ,109.85
+ ,284.80
+ ,109.41
+ ,281.41
+ ,112.36
+ ,283.39
+ ,111.03
+ ,287.97
+ ,110.67
+ ,290.77
+ ,109.21
+ ,290.60
+ ,113.58
+ ,289.67
+ ,113.88
+ ,289.84
+ ,114.08
+ ,298.55
+ ,112.33
+ ,296.07
+ ,113.92
+ ,297.14
+ ,114.41
+ ,295.34
+ ,114.57
+ ,296.25
+ ,115.35
+ ,294.30
+ ,113.13
+ ,296.15
+ ,113.29
+ ,296.49
+ ,112.56
+ ,298.05
+ ,113.06
+ ,301.03
+ ,113.46
+ ,300.52
+ ,115.39
+ ,301.50
+ ,116.62
+ ,296.93
+ ,117.04
+ ,289.84
+ ,117.42
+ ,291.44
+ ,115.62
+ ,286.88
+ ,115.16
+ ,286.74
+ ,115.69
+ ,288.93
+ ,112.85
+ ,292.19
+ ,114.05
+ ,295.39
+ ,112.00
+ ,295.86
+ ,113.74
+ ,293.36
+ ,116.26
+ ,292.86
+ ,118.63
+ ,292.73
+ ,116.49
+ ,296.73
+ ,118.23
+ ,285.02
+ ,116.83
+ ,285.24
+ ,118.82
+ ,288.62
+ ,114.36
+ ,283.36
+ ,112.02
+ ,285.84
+ ,113.24
+ ,291.48
+ ,109.75
+ ,291.41
+ ,110.33
+ ,287.77
+ ,112.86
+ ,284.97
+ ,113.04
+ ,286.05
+ ,113.80
+ ,278.19
+ ,110.90
+ ,281.21
+ ,109.96
+ ,277.92
+ ,108.69
+ ,280.08
+ ,108.84
+ ,269.24
+ ,108.47
+ ,268.48
+ ,108.07
+ ,268.83
+ ,107.94
+ ,269.54
+ ,108.11
+ ,262.37
+ ,108.11
+ ,265.12
+ ,106.81
+ ,265.34
+ ,105.58
+ ,263.32
+ ,105.61
+ ,267.18
+ ,106.52
+ ,260.75
+ ,103.86
+ ,261.78
+ ,104.60
+ ,257.27
+ ,104.73
+ ,255.63
+ ,105.12
+ ,251.39
+ ,104.76
+ ,259.49
+ ,103.85
+ ,261.18
+ ,103.83
+ ,261.65
+ ,103.22
+ ,262.01
+ ,101.64
+ ,265.23
+ ,102.13
+ ,268.10
+ ,104.33
+ ,262.27
+ ,104.92
+ ,263.59
+ ,107.78
+ ,257.85
+ ,104.49
+ ,265.69
+ ,102.80
+ ,271.15
+ ,102.86
+ ,266.69
+ ,104.51
+ ,265.77
+ ,104.73
+ ,262.32
+ ,102.58
+ ,270.48
+ ,99.93
+ ,273.03
+ ,101.41
+ ,269.13
+ ,101.05
+ ,280.65
+ ,99.86
+ ,282.75
+ ,101.11
+ ,281.44
+ ,100.89
+ ,281.99
+ ,101.09
+ ,282.86
+ ,98.31
+ ,287.21
+ ,98.08
+ ,283.11
+ ,99.55
+ ,280.66
+ ,99.62
+ ,282.39
+ ,97.37
+ ,280.83
+ ,98.16
+ ,284.71
+ ,97.98
+ ,279.99
+ ,98.15
+ ,283.50
+ ,97.10
+ ,284.88
+ ,97.24
+ ,288.60
+ ,96.70
+ ,284.80
+ ,96.64
+ ,287.20
+ ,100.65
+ ,286.22
+ ,96.75
+ ,286.54
+ ,97.74
+ ,279.58
+ ,97.92
+ ,283.08
+ ,98.34
+ ,288.88
+ ,93.84
+ ,280.18
+ ,97.80
+ ,284.16
+ ,96.20
+ ,290.57
+ ,95.99
+ ,286.82
+ ,95.18
+ ,273.00
+ ,95.95
+ ,278.69
+ ,92.23
+ ,264.54
+ ,91.78
+ ,271.92
+ ,92.97
+ ,283.60
+ ,89.76
+ ,269.25
+ ,92.88
+ ,263.58
+ ,96.23
+ ,264.16
+ ,95.79
+ ,268.85
+ ,93.97
+ ,269.67
+ ,93.90
+ ,249.41
+ ,93.60
+ ,268.99
+ ,93.96
+ ,268.65
+ ,88.69
+ ,260.16
+ ,88.57
+ ,256.55
+ ,85.62
+ ,251.47
+ ,86.25
+ ,234.93
+ ,85.33
+ ,232.96
+ ,83.33
+ ,215.49
+ ,77.78
+ ,213.68
+ ,78.70
+ ,236.07
+ ,72.05
+ ,235.41
+ ,80.75
+ ,214.77
+ ,81.41
+ ,225.85
+ ,82.65
+ ,224.64
+ ,75.85
+ ,238.26
+ ,75.70
+ ,232.44
+ ,78.25
+ ,222.50
+ ,77.41
+ ,225.28
+ ,76.84
+ ,220.49
+ ,74.25
+ ,216.86
+ ,74.95
+ ,234.70
+ ,68.78
+ ,230.06
+ ,73.21
+ ,238.27
+ ,73.26
+ ,238.56
+ ,78.67
+ ,242.70
+ ,75.63
+ ,249.14
+ ,74.99
+ ,234.89
+ ,83.87
+ ,227.78
+ ,79.62
+ ,234.04
+ ,80.13
+ ,230.70
+ ,79.76
+ ,230.17
+ ,78.20
+ ,218.23
+ ,78.05
+ ,232.20
+ ,79.05
+ ,220.76
+ ,73.32
+ ,215.60
+ ,75.17
+ ,217.69
+ ,73.26
+ ,204.35
+ ,73.72
+ ,191.44
+ ,73.57
+ ,203.84
+ ,70.60
+ ,211.86
+ ,71.25
+ ,210.57
+ ,74.22
+ ,219.57
+ ,73.32
+ ,219.98
+ ,73.01
+ ,226.01
+ ,74.21
+ ,207.04
+ ,75.32
+ ,212.52
+ ,71.73
+ ,217.92
+ ,71.94
+ ,210.45
+ ,72.94
+ ,218.53
+ ,72.47
+ ,223.32
+ ,71.94
+ ,218.76
+ ,74.30
+ ,217.63
+ ,74.30)
+ ,dim=c(2
+ ,395)
+ ,dimnames=list(c('Amerika'
+ ,'Japan')
+ ,1:395))
> y <- array(NA,dim=c(2,395),dimnames=list(c('Amerika','Japan'),1:395))
> 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
Amerika Japan M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 358.59 122.36 1 0 0 0 0 0 0 0 0 0 0 1
2 362.96 123.33 0 1 0 0 0 0 0 0 0 0 0 2
3 362.42 123.04 0 0 1 0 0 0 0 0 0 0 0 3
4 364.97 124.53 0 0 0 1 0 0 0 0 0 0 0 4
5 364.04 125.13 0 0 0 0 1 0 0 0 0 0 0 5
6 361.06 125.85 0 0 0 0 0 1 0 0 0 0 0 6
7 358.48 126.50 0 0 0 0 0 0 1 0 0 0 0 7
8 352.96 126.53 0 0 0 0 0 0 0 1 0 0 0 8
9 359.59 127.07 0 0 0 0 0 0 0 0 1 0 0 9
10 360.39 124.55 0 0 0 0 0 0 0 0 0 1 0 10
11 357.40 124.90 0 0 0 0 0 0 0 0 0 0 1 11
12 362.93 124.32 0 0 0 0 0 0 0 0 0 0 0 12
13 364.55 122.84 1 0 0 0 0 0 0 0 0 0 0 13
14 365.73 123.31 0 1 0 0 0 0 0 0 0 0 0 14
15 364.70 123.31 0 0 1 0 0 0 0 0 0 0 0 15
16 364.65 124.87 0 0 0 1 0 0 0 0 0 0 0 16
17 359.43 124.64 0 0 0 0 1 0 0 0 0 0 0 17
18 362.14 124.73 0 0 0 0 0 1 0 0 0 0 0 18
19 356.97 124.90 0 0 0 0 0 0 1 0 0 0 0 19
20 354.82 124.04 0 0 0 0 0 0 0 1 0 0 0 20
21 353.17 123.28 0 0 0 0 0 0 0 0 1 0 0 21
22 357.06 123.86 0 0 0 0 0 0 0 0 0 1 0 22
23 356.18 122.29 0 0 0 0 0 0 0 0 0 0 1 23
24 355.01 124.09 0 0 0 0 0 0 0 0 0 0 0 24
25 355.65 124.54 1 0 0 0 0 0 0 0 0 0 0 25
26 357.31 125.65 0 1 0 0 0 0 0 0 0 0 0 26
27 357.07 125.70 0 0 1 0 0 0 0 0 0 0 0 27
28 357.91 125.53 0 0 0 1 0 0 0 0 0 0 0 28
29 358.48 125.61 0 0 0 0 1 0 0 0 0 0 0 29
30 358.97 125.55 0 0 0 0 0 1 0 0 0 0 0 30
31 351.77 125.41 0 0 0 0 0 0 1 0 0 0 0 31
32 352.16 127.60 0 0 0 0 0 0 0 1 0 0 0 32
33 359.08 124.68 0 0 0 0 0 0 0 0 1 0 0 33
34 360.35 124.41 0 0 0 0 0 0 0 0 0 1 0 34
35 359.53 126.43 0 0 0 0 0 0 0 0 0 0 1 35
36 359.30 126.38 0 0 0 0 0 0 0 0 0 0 0 36
37 358.41 125.78 1 0 0 0 0 0 0 0 0 0 0 37
38 359.68 124.70 0 1 0 0 0 0 0 0 0 0 0 38
39 355.31 125.07 0 0 1 0 0 0 0 0 0 0 0 39
40 357.08 125.25 0 0 0 1 0 0 0 0 0 0 0 40
41 349.71 126.58 0 0 0 0 1 0 0 0 0 0 0 41
42 354.13 127.13 0 0 0 0 0 1 0 0 0 0 0 42
43 345.49 125.82 0 0 0 0 0 0 1 0 0 0 0 43
44 341.69 123.70 0 0 0 0 0 0 0 1 0 0 0 44
45 344.25 124.39 0 0 0 0 0 0 0 0 1 0 0 45
46 340.17 123.70 0 0 0 0 0 0 0 0 0 1 0 46
47 342.47 124.42 0 0 0 0 0 0 0 0 0 0 1 47
48 344.43 121.05 0 0 0 0 0 0 0 0 0 0 0 48
49 333.23 121.02 1 0 0 0 0 0 0 0 0 0 0 49
50 339.72 123.23 0 1 0 0 0 0 0 0 0 0 0 50
51 342.61 121.32 0 0 1 0 0 0 0 0 0 0 0 51
52 346.36 120.91 0 0 0 1 0 0 0 0 0 0 0 52
53 339.09 120.72 0 0 0 0 1 0 0 0 0 0 0 53
54 339.73 123.31 0 0 0 0 0 1 0 0 0 0 0 54
55 341.12 119.58 0 0 0 0 0 0 1 0 0 0 0 55
56 335.94 119.53 0 0 0 0 0 0 0 1 0 0 0 56
57 333.46 120.59 0 0 0 0 0 0 0 0 1 0 0 57
58 335.66 118.63 0 0 0 0 0 0 0 0 0 1 0 58
59 341.12 118.47 0 0 0 0 0 0 0 0 0 0 1 59
60 342.21 111.81 0 0 0 0 0 0 0 0 0 0 0 60
61 342.62 114.71 1 0 0 0 0 0 0 0 0 0 0 61
62 346.06 117.34 0 1 0 0 0 0 0 0 0 0 0 62
63 344.43 115.77 0 0 1 0 0 0 0 0 0 0 0 63
64 346.65 118.38 0 0 0 1 0 0 0 0 0 0 0 64
65 343.74 117.84 0 0 0 0 1 0 0 0 0 0 0 65
66 335.67 118.83 0 0 0 0 0 1 0 0 0 0 0 66
67 342.75 120.02 0 0 0 0 0 0 1 0 0 0 0 67
68 341.77 116.21 0 0 0 0 0 0 0 1 0 0 0 68
69 345.84 117.08 0 0 0 0 0 0 0 0 1 0 0 69
70 346.52 120.20 0 0 0 0 0 0 0 0 0 1 0 70
71 350.79 119.83 0 0 0 0 0 0 0 0 0 0 1 71
72 345.44 118.92 0 0 0 0 0 0 0 0 0 0 0 72
73 345.87 118.03 1 0 0 0 0 0 0 0 0 0 0 73
74 338.48 117.71 0 1 0 0 0 0 0 0 0 0 0 74
75 337.21 119.55 0 0 1 0 0 0 0 0 0 0 0 75
76 340.81 116.13 0 0 0 1 0 0 0 0 0 0 0 76
77 339.86 115.97 0 0 0 0 1 0 0 0 0 0 0 77
78 342.86 115.99 0 0 0 0 0 1 0 0 0 0 0 78
79 343.33 114.96 0 0 0 0 0 0 1 0 0 0 0 79
80 341.73 116.46 0 0 0 0 0 0 0 1 0 0 0 80
81 351.38 116.55 0 0 0 0 0 0 0 0 1 0 0 81
82 351.13 113.05 0 0 0 0 0 0 0 0 0 1 0 82
83 345.99 117.44 0 0 0 0 0 0 0 0 0 0 1 83
84 347.55 118.84 0 0 0 0 0 0 0 0 0 0 0 84
85 346.02 117.06 1 0 0 0 0 0 0 0 0 0 0 85
86 345.29 117.54 0 1 0 0 0 0 0 0 0 0 0 86
87 347.03 119.31 0 0 1 0 0 0 0 0 0 0 0 87
88 348.01 118.72 0 0 0 1 0 0 0 0 0 0 0 88
89 345.48 121.55 0 0 0 0 1 0 0 0 0 0 0 89
90 349.40 122.61 0 0 0 0 0 1 0 0 0 0 0 90
91 351.05 121.53 0 0 0 0 0 0 1 0 0 0 0 91
92 349.70 123.31 0 0 0 0 0 0 0 1 0 0 0 92
93 350.86 124.07 0 0 0 0 0 0 0 0 1 0 0 93
94 354.45 123.59 0 0 0 0 0 0 0 0 0 1 0 94
95 355.30 122.97 0 0 0 0 0 0 0 0 0 0 1 95
96 357.48 123.22 0 0 0 0 0 0 0 0 0 0 0 96
97 355.24 123.04 1 0 0 0 0 0 0 0 0 0 0 97
98 351.79 122.96 0 1 0 0 0 0 0 0 0 0 0 98
99 355.22 122.81 0 0 1 0 0 0 0 0 0 0 0 99
100 351.02 122.81 0 0 0 1 0 0 0 0 0 0 0 100
101 350.28 122.62 0 0 0 0 1 0 0 0 0 0 0 101
102 350.17 120.82 0 0 0 0 0 1 0 0 0 0 0 102
103 348.16 119.41 0 0 0 0 0 0 1 0 0 0 0 103
104 340.30 121.56 0 0 0 0 0 0 0 1 0 0 0 104
105 343.75 121.59 0 0 0 0 0 0 0 0 1 0 0 105
106 344.71 118.50 0 0 0 0 0 0 0 0 0 1 0 106
107 344.13 118.77 0 0 0 0 0 0 0 0 0 0 1 107
108 342.14 118.86 0 0 0 0 0 0 0 0 0 0 0 108
109 345.04 117.60 1 0 0 0 0 0 0 0 0 0 0 109
110 346.02 119.90 0 1 0 0 0 0 0 0 0 0 0 110
111 346.43 121.83 0 0 1 0 0 0 0 0 0 0 0 111
112 347.07 121.84 0 0 0 1 0 0 0 0 0 0 0 112
113 339.33 122.12 0 0 0 0 1 0 0 0 0 0 0 113
114 339.10 122.12 0 0 0 0 0 1 0 0 0 0 0 114
115 337.19 121.36 0 0 0 0 0 0 1 0 0 0 0 115
116 339.58 119.66 0 0 0 0 0 0 0 1 0 0 0 116
117 327.85 119.32 0 0 0 0 0 0 0 0 1 0 0 117
118 326.81 120.36 0 0 0 0 0 0 0 0 0 1 0 118
119 321.73 117.06 0 0 0 0 0 0 0 0 0 0 1 119
120 320.45 117.48 0 0 0 0 0 0 0 0 0 0 0 120
121 327.69 115.60 1 0 0 0 0 0 0 0 0 0 0 121
122 323.95 113.86 0 1 0 0 0 0 0 0 0 0 0 122
123 320.47 116.92 0 0 1 0 0 0 0 0 0 0 0 123
124 322.13 117.75 0 0 0 1 0 0 0 0 0 0 0 124
125 316.34 117.75 0 0 0 0 1 0 0 0 0 0 0 125
126 314.78 115.31 0 0 0 0 0 1 0 0 0 0 0 126
127 308.90 116.28 0 0 0 0 0 0 1 0 0 0 0 127
128 308.62 115.22 0 0 0 0 0 0 0 1 0 0 0 128
129 314.41 115.65 0 0 0 0 0 0 0 0 1 0 0 129
130 306.88 115.11 0 0 0 0 0 0 0 0 0 1 0 130
131 310.60 118.67 0 0 0 0 0 0 0 0 0 0 1 131
132 321.60 118.04 0 0 0 0 0 0 0 0 0 0 0 132
133 321.50 116.50 1 0 0 0 0 0 0 0 0 0 0 133
134 325.68 119.78 0 1 0 0 0 0 0 0 0 0 0 134
135 324.35 119.95 0 0 1 0 0 0 0 0 0 0 0 135
136 320.01 120.37 0 0 0 1 0 0 0 0 0 0 0 136
137 326.88 119.79 0 0 0 0 1 0 0 0 0 0 0 137
138 332.39 119.43 0 0 0 0 0 1 0 0 0 0 0 138
139 331.48 121.06 0 0 0 0 0 0 1 0 0 0 0 139
140 332.62 121.74 0 0 0 0 0 0 0 1 0 0 0 140
141 324.79 121.09 0 0 0 0 0 0 0 0 1 0 0 141
142 327.12 122.97 0 0 0 0 0 0 0 0 0 1 0 142
143 328.91 120.50 0 0 0 0 0 0 0 0 0 0 1 143
144 328.37 117.18 0 0 0 0 0 0 0 0 0 0 0 144
145 324.83 115.03 1 0 0 0 0 0 0 0 0 0 0 145
146 325.90 113.36 0 1 0 0 0 0 0 0 0 0 0 146
147 326.18 112.59 0 0 1 0 0 0 0 0 0 0 0 147
148 328.94 111.65 0 0 0 1 0 0 0 0 0 0 0 148
149 333.78 111.98 0 0 0 0 1 0 0 0 0 0 0 149
150 328.06 114.87 0 0 0 0 0 1 0 0 0 0 0 150
151 325.87 114.67 0 0 0 0 0 0 1 0 0 0 0 151
152 325.41 114.09 0 0 0 0 0 0 0 1 0 0 0 152
153 318.86 114.77 0 0 0 0 0 0 0 0 1 0 0 153
154 319.13 117.05 0 0 0 0 0 0 0 0 0 1 0 154
155 310.16 117.22 0 0 0 0 0 0 0 0 0 0 1 155
156 311.73 113.18 0 0 0 0 0 0 0 0 0 0 0 156
157 306.54 110.95 1 0 0 0 0 0 0 0 0 0 0 157
158 311.16 112.14 0 1 0 0 0 0 0 0 0 0 0 158
159 311.98 112.72 0 0 1 0 0 0 0 0 0 0 0 159
160 306.72 110.01 0 0 0 1 0 0 0 0 0 0 0 160
161 308.05 110.29 0 0 0 0 1 0 0 0 0 0 0 161
162 300.76 110.74 0 0 0 0 0 1 0 0 0 0 0 162
163 301.90 110.32 0 0 0 0 0 0 1 0 0 0 0 163
164 293.09 105.89 0 0 0 0 0 0 0 1 0 0 0 164
165 292.76 108.97 0 0 0 0 0 0 0 0 1 0 0 165
166 294.58 109.34 0 0 0 0 0 0 0 0 0 1 0 166
167 289.90 106.57 0 0 0 0 0 0 0 0 0 0 1 167
168 296.69 99.49 0 0 0 0 0 0 0 0 0 0 0 168
169 297.21 101.81 1 0 0 0 0 0 0 0 0 0 0 169
170 293.31 104.29 0 1 0 0 0 0 0 0 0 0 0 170
171 296.25 109.73 0 0 1 0 0 0 0 0 0 0 0 171
172 298.60 105.06 0 0 0 1 0 0 0 0 0 0 0 172
173 296.87 107.97 0 0 0 0 1 0 0 0 0 0 0 173
174 301.02 108.13 0 0 0 0 0 1 0 0 0 0 0 174
175 304.73 109.86 0 0 0 0 0 0 1 0 0 0 0 175
176 301.92 108.95 0 0 0 0 0 0 0 1 0 0 0 176
177 295.72 111.20 0 0 0 0 0 0 0 0 1 0 0 177
178 293.18 110.69 0 0 0 0 0 0 0 0 0 1 0 178
179 298.35 106.10 0 0 0 0 0 0 0 0 0 0 1 179
180 297.99 105.68 0 0 0 0 0 0 0 0 0 0 0 180
181 299.85 104.12 1 0 0 0 0 0 0 0 0 0 0 181
182 299.85 104.71 0 1 0 0 0 0 0 0 0 0 0 182
183 304.45 104.30 0 0 1 0 0 0 0 0 0 0 0 183
184 299.45 103.52 0 0 0 1 0 0 0 0 0 0 0 184
185 298.14 107.76 0 0 0 0 1 0 0 0 0 0 0 185
186 298.78 107.80 0 0 0 0 0 1 0 0 0 0 0 186
187 297.02 107.30 0 0 0 0 0 0 1 0 0 0 0 187
188 301.33 108.64 0 0 0 0 0 0 0 1 0 0 0 188
189 294.96 105.03 0 0 0 0 0 0 0 0 1 0 0 189
190 296.69 108.30 0 0 0 0 0 0 0 0 0 1 0 190
191 300.73 107.21 0 0 0 0 0 0 0 0 0 0 1 191
192 301.96 109.27 0 0 0 0 0 0 0 0 0 0 0 192
193 297.38 109.50 1 0 0 0 0 0 0 0 0 0 0 193
194 293.87 111.68 0 1 0 0 0 0 0 0 0 0 0 194
195 285.96 111.80 0 0 1 0 0 0 0 0 0 0 0 195
196 285.41 111.75 0 0 0 1 0 0 0 0 0 0 0 196
197 283.70 106.68 0 0 0 0 1 0 0 0 0 0 0 197
198 284.76 106.37 0 0 0 0 0 1 0 0 0 0 0 198
199 277.11 105.76 0 0 0 0 0 0 1 0 0 0 0 199
200 274.73 109.01 0 0 0 0 0 0 0 1 0 0 0 200
201 274.73 109.01 0 0 0 0 0 0 0 0 1 0 0 201
202 274.73 109.01 0 0 0 0 0 0 0 0 0 1 0 202
203 274.73 109.01 0 0 0 0 0 0 0 0 0 0 1 203
204 274.69 107.69 0 0 0 0 0 0 0 0 0 0 0 204
205 275.42 105.19 1 0 0 0 0 0 0 0 0 0 0 205
206 264.15 105.48 0 1 0 0 0 0 0 0 0 0 0 206
207 276.24 102.22 0 0 1 0 0 0 0 0 0 0 0 207
208 268.88 100.54 0 0 0 1 0 0 0 0 0 0 0 208
209 277.97 105.00 0 0 0 0 1 0 0 0 0 0 0 209
210 280.49 105.44 0 0 0 0 0 1 0 0 0 0 0 210
211 281.09 107.89 0 0 0 0 0 0 1 0 0 0 0 211
212 276.16 108.64 0 0 0 0 0 0 0 1 0 0 0 212
213 272.58 106.70 0 0 0 0 0 0 0 0 1 0 0 213
214 270.94 109.10 0 0 0 0 0 0 0 0 0 1 0 214
215 284.31 105.23 0 0 0 0 0 0 0 0 0 0 1 215
216 283.94 108.41 0 0 0 0 0 0 0 0 0 0 0 216
217 284.18 108.80 1 0 0 0 0 0 0 0 0 0 0 217
218 282.83 110.39 0 1 0 0 0 0 0 0 0 0 0 218
219 283.84 110.22 0 0 1 0 0 0 0 0 0 0 0 219
220 282.71 110.86 0 0 0 1 0 0 0 0 0 0 0 220
221 279.29 108.58 0 0 0 0 1 0 0 0 0 0 0 221
222 280.70 107.70 0 0 0 0 0 1 0 0 0 0 0 222
223 274.47 106.62 0 0 0 0 0 0 1 0 0 0 0 223
224 273.44 109.84 0 0 0 0 0 0 0 1 0 0 0 224
225 275.49 107.16 0 0 0 0 0 0 0 0 1 0 0 225
226 279.46 107.26 0 0 0 0 0 0 0 0 0 1 0 226
227 280.19 108.70 0 0 0 0 0 0 0 0 0 0 1 227
228 288.21 109.85 0 0 0 0 0 0 0 0 0 0 0 228
229 284.80 109.41 1 0 0 0 0 0 0 0 0 0 0 229
230 281.41 112.36 0 1 0 0 0 0 0 0 0 0 0 230
231 283.39 111.03 0 0 1 0 0 0 0 0 0 0 0 231
232 287.97 110.67 0 0 0 1 0 0 0 0 0 0 0 232
233 290.77 109.21 0 0 0 0 1 0 0 0 0 0 0 233
234 290.60 113.58 0 0 0 0 0 1 0 0 0 0 0 234
235 289.67 113.88 0 0 0 0 0 0 1 0 0 0 0 235
236 289.84 114.08 0 0 0 0 0 0 0 1 0 0 0 236
237 298.55 112.33 0 0 0 0 0 0 0 0 1 0 0 237
238 296.07 113.92 0 0 0 0 0 0 0 0 0 1 0 238
239 297.14 114.41 0 0 0 0 0 0 0 0 0 0 1 239
240 295.34 114.57 0 0 0 0 0 0 0 0 0 0 0 240
241 296.25 115.35 1 0 0 0 0 0 0 0 0 0 0 241
242 294.30 113.13 0 1 0 0 0 0 0 0 0 0 0 242
243 296.15 113.29 0 0 1 0 0 0 0 0 0 0 0 243
244 296.49 112.56 0 0 0 1 0 0 0 0 0 0 0 244
245 298.05 113.06 0 0 0 0 1 0 0 0 0 0 0 245
246 301.03 113.46 0 0 0 0 0 1 0 0 0 0 0 246
247 300.52 115.39 0 0 0 0 0 0 1 0 0 0 0 247
248 301.50 116.62 0 0 0 0 0 0 0 1 0 0 0 248
249 296.93 117.04 0 0 0 0 0 0 0 0 1 0 0 249
250 289.84 117.42 0 0 0 0 0 0 0 0 0 1 0 250
251 291.44 115.62 0 0 0 0 0 0 0 0 0 0 1 251
252 286.88 115.16 0 0 0 0 0 0 0 0 0 0 0 252
253 286.74 115.69 1 0 0 0 0 0 0 0 0 0 0 253
254 288.93 112.85 0 1 0 0 0 0 0 0 0 0 0 254
255 292.19 114.05 0 0 1 0 0 0 0 0 0 0 0 255
256 295.39 112.00 0 0 0 1 0 0 0 0 0 0 0 256
257 295.86 113.74 0 0 0 0 1 0 0 0 0 0 0 257
258 293.36 116.26 0 0 0 0 0 1 0 0 0 0 0 258
259 292.86 118.63 0 0 0 0 0 0 1 0 0 0 0 259
260 292.73 116.49 0 0 0 0 0 0 0 1 0 0 0 260
261 296.73 118.23 0 0 0 0 0 0 0 0 1 0 0 261
262 285.02 116.83 0 0 0 0 0 0 0 0 0 1 0 262
263 285.24 118.82 0 0 0 0 0 0 0 0 0 0 1 263
264 288.62 114.36 0 0 0 0 0 0 0 0 0 0 0 264
265 283.36 112.02 1 0 0 0 0 0 0 0 0 0 0 265
266 285.84 113.24 0 1 0 0 0 0 0 0 0 0 0 266
267 291.48 109.75 0 0 1 0 0 0 0 0 0 0 0 267
268 291.41 110.33 0 0 0 1 0 0 0 0 0 0 0 268
269 287.77 112.86 0 0 0 0 1 0 0 0 0 0 0 269
270 284.97 113.04 0 0 0 0 0 1 0 0 0 0 0 270
271 286.05 113.80 0 0 0 0 0 0 1 0 0 0 0 271
272 278.19 110.90 0 0 0 0 0 0 0 1 0 0 0 272
273 281.21 109.96 0 0 0 0 0 0 0 0 1 0 0 273
274 277.92 108.69 0 0 0 0 0 0 0 0 0 1 0 274
275 280.08 108.84 0 0 0 0 0 0 0 0 0 0 1 275
276 269.24 108.47 0 0 0 0 0 0 0 0 0 0 0 276
277 268.48 108.07 1 0 0 0 0 0 0 0 0 0 0 277
278 268.83 107.94 0 1 0 0 0 0 0 0 0 0 0 278
279 269.54 108.11 0 0 1 0 0 0 0 0 0 0 0 279
280 262.37 108.11 0 0 0 1 0 0 0 0 0 0 0 280
281 265.12 106.81 0 0 0 0 1 0 0 0 0 0 0 281
282 265.34 105.58 0 0 0 0 0 1 0 0 0 0 0 282
283 263.32 105.61 0 0 0 0 0 0 1 0 0 0 0 283
284 267.18 106.52 0 0 0 0 0 0 0 1 0 0 0 284
285 260.75 103.86 0 0 0 0 0 0 0 0 1 0 0 285
286 261.78 104.60 0 0 0 0 0 0 0 0 0 1 0 286
287 257.27 104.73 0 0 0 0 0 0 0 0 0 0 1 287
288 255.63 105.12 0 0 0 0 0 0 0 0 0 0 0 288
289 251.39 104.76 1 0 0 0 0 0 0 0 0 0 0 289
290 259.49 103.85 0 1 0 0 0 0 0 0 0 0 0 290
291 261.18 103.83 0 0 1 0 0 0 0 0 0 0 0 291
292 261.65 103.22 0 0 0 1 0 0 0 0 0 0 0 292
293 262.01 101.64 0 0 0 0 1 0 0 0 0 0 0 293
294 265.23 102.13 0 0 0 0 0 1 0 0 0 0 0 294
295 268.10 104.33 0 0 0 0 0 0 1 0 0 0 0 295
296 262.27 104.92 0 0 0 0 0 0 0 1 0 0 0 296
297 263.59 107.78 0 0 0 0 0 0 0 0 1 0 0 297
298 257.85 104.49 0 0 0 0 0 0 0 0 0 1 0 298
299 265.69 102.80 0 0 0 0 0 0 0 0 0 0 1 299
300 271.15 102.86 0 0 0 0 0 0 0 0 0 0 0 300
301 266.69 104.51 1 0 0 0 0 0 0 0 0 0 0 301
302 265.77 104.73 0 1 0 0 0 0 0 0 0 0 0 302
303 262.32 102.58 0 0 1 0 0 0 0 0 0 0 0 303
304 270.48 99.93 0 0 0 1 0 0 0 0 0 0 0 304
305 273.03 101.41 0 0 0 0 1 0 0 0 0 0 0 305
306 269.13 101.05 0 0 0 0 0 1 0 0 0 0 0 306
307 280.65 99.86 0 0 0 0 0 0 1 0 0 0 0 307
308 282.75 101.11 0 0 0 0 0 0 0 1 0 0 0 308
309 281.44 100.89 0 0 0 0 0 0 0 0 1 0 0 309
310 281.99 101.09 0 0 0 0 0 0 0 0 0 1 0 310
311 282.86 98.31 0 0 0 0 0 0 0 0 0 0 1 311
312 287.21 98.08 0 0 0 0 0 0 0 0 0 0 0 312
313 283.11 99.55 1 0 0 0 0 0 0 0 0 0 0 313
314 280.66 99.62 0 1 0 0 0 0 0 0 0 0 0 314
315 282.39 97.37 0 0 1 0 0 0 0 0 0 0 0 315
316 280.83 98.16 0 0 0 1 0 0 0 0 0 0 0 316
317 284.71 97.98 0 0 0 0 1 0 0 0 0 0 0 317
318 279.99 98.15 0 0 0 0 0 1 0 0 0 0 0 318
319 283.50 97.10 0 0 0 0 0 0 1 0 0 0 0 319
320 284.88 97.24 0 0 0 0 0 0 0 1 0 0 0 320
321 288.60 96.70 0 0 0 0 0 0 0 0 1 0 0 321
322 284.80 96.64 0 0 0 0 0 0 0 0 0 1 0 322
323 287.20 100.65 0 0 0 0 0 0 0 0 0 0 1 323
324 286.22 96.75 0 0 0 0 0 0 0 0 0 0 0 324
325 286.54 97.74 1 0 0 0 0 0 0 0 0 0 0 325
326 279.58 97.92 0 1 0 0 0 0 0 0 0 0 0 326
327 283.08 98.34 0 0 1 0 0 0 0 0 0 0 0 327
328 288.88 93.84 0 0 0 1 0 0 0 0 0 0 0 328
329 280.18 97.80 0 0 0 0 1 0 0 0 0 0 0 329
330 284.16 96.20 0 0 0 0 0 1 0 0 0 0 0 330
331 290.57 95.99 0 0 0 0 0 0 1 0 0 0 0 331
332 286.82 95.18 0 0 0 0 0 0 0 1 0 0 0 332
333 273.00 95.95 0 0 0 0 0 0 0 0 1 0 0 333
334 278.69 92.23 0 0 0 0 0 0 0 0 0 1 0 334
335 264.54 91.78 0 0 0 0 0 0 0 0 0 0 1 335
336 271.92 92.97 0 0 0 0 0 0 0 0 0 0 0 336
337 283.60 89.76 1 0 0 0 0 0 0 0 0 0 0 337
338 269.25 92.88 0 1 0 0 0 0 0 0 0 0 0 338
339 263.58 96.23 0 0 1 0 0 0 0 0 0 0 0 339
340 264.16 95.79 0 0 0 1 0 0 0 0 0 0 0 340
341 268.85 93.97 0 0 0 0 1 0 0 0 0 0 0 341
342 269.67 93.90 0 0 0 0 0 1 0 0 0 0 0 342
343 249.41 93.60 0 0 0 0 0 0 1 0 0 0 0 343
344 268.99 93.96 0 0 0 0 0 0 0 1 0 0 0 344
345 268.65 88.69 0 0 0 0 0 0 0 0 1 0 0 345
346 260.16 88.57 0 0 0 0 0 0 0 0 0 1 0 346
347 256.55 85.62 0 0 0 0 0 0 0 0 0 0 1 347
348 251.47 86.25 0 0 0 0 0 0 0 0 0 0 0 348
349 234.93 85.33 1 0 0 0 0 0 0 0 0 0 0 349
350 232.96 83.33 0 1 0 0 0 0 0 0 0 0 0 350
351 215.49 77.78 0 0 1 0 0 0 0 0 0 0 0 351
352 213.68 78.70 0 0 0 1 0 0 0 0 0 0 0 352
353 236.07 72.05 0 0 0 0 1 0 0 0 0 0 0 353
354 235.41 80.75 0 0 0 0 0 1 0 0 0 0 0 354
355 214.77 81.41 0 0 0 0 0 0 1 0 0 0 0 355
356 225.85 82.65 0 0 0 0 0 0 0 1 0 0 0 356
357 224.64 75.85 0 0 0 0 0 0 0 0 1 0 0 357
358 238.26 75.70 0 0 0 0 0 0 0 0 0 1 0 358
359 232.44 78.25 0 0 0 0 0 0 0 0 0 0 1 359
360 222.50 77.41 0 0 0 0 0 0 0 0 0 0 0 360
361 225.28 76.84 1 0 0 0 0 0 0 0 0 0 0 361
362 220.49 74.25 0 1 0 0 0 0 0 0 0 0 0 362
363 216.86 74.95 0 0 1 0 0 0 0 0 0 0 0 363
364 234.70 68.78 0 0 0 1 0 0 0 0 0 0 0 364
365 230.06 73.21 0 0 0 0 1 0 0 0 0 0 0 365
366 238.27 73.26 0 0 0 0 0 1 0 0 0 0 0 366
367 238.56 78.67 0 0 0 0 0 0 1 0 0 0 0 367
368 242.70 75.63 0 0 0 0 0 0 0 1 0 0 0 368
369 249.14 74.99 0 0 0 0 0 0 0 0 1 0 0 369
370 234.89 83.87 0 0 0 0 0 0 0 0 0 1 0 370
371 227.78 79.62 0 0 0 0 0 0 0 0 0 0 1 371
372 234.04 80.13 0 0 0 0 0 0 0 0 0 0 0 372
373 230.70 79.76 1 0 0 0 0 0 0 0 0 0 0 373
374 230.17 78.20 0 1 0 0 0 0 0 0 0 0 0 374
375 218.23 78.05 0 0 1 0 0 0 0 0 0 0 0 375
376 232.20 79.05 0 0 0 1 0 0 0 0 0 0 0 376
377 220.76 73.32 0 0 0 0 1 0 0 0 0 0 0 377
378 215.60 75.17 0 0 0 0 0 1 0 0 0 0 0 378
379 217.69 73.26 0 0 0 0 0 0 1 0 0 0 0 379
380 204.35 73.72 0 0 0 0 0 0 0 1 0 0 0 380
381 191.44 73.57 0 0 0 0 0 0 0 0 1 0 0 381
382 203.84 70.60 0 0 0 0 0 0 0 0 0 1 0 382
383 211.86 71.25 0 0 0 0 0 0 0 0 0 0 1 383
384 210.57 74.22 0 0 0 0 0 0 0 0 0 0 0 384
385 219.57 73.32 1 0 0 0 0 0 0 0 0 0 0 385
386 219.98 73.01 0 1 0 0 0 0 0 0 0 0 0 386
387 226.01 74.21 0 0 1 0 0 0 0 0 0 0 0 387
388 207.04 75.32 0 0 0 1 0 0 0 0 0 0 0 388
389 212.52 71.73 0 0 0 0 1 0 0 0 0 0 0 389
390 217.92 71.94 0 0 0 0 0 1 0 0 0 0 0 390
391 210.45 72.94 0 0 0 0 0 0 1 0 0 0 0 391
392 218.53 72.47 0 0 0 0 0 0 0 1 0 0 0 392
393 223.32 71.94 0 0 0 0 0 0 0 0 1 0 0 393
394 218.76 74.30 0 0 0 0 0 0 0 0 0 1 0 394
395 217.63 74.30 0 0 0 0 0 0 0 0 0 0 1 395
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Japan M1 M2 M3 M4
235.96716 1.01776 -0.25413 -1.30117 -1.26485 0.23065
M5 M6 M7 M8 M9 M10
0.19291 0.09745 -1.71115 -2.05082 -1.71784 -2.22647
M11 t
-1.61852 -0.23037
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-30.4139 -7.7542 -0.9875 6.6046 34.8705
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 235.96716 11.36129 20.769 <2e-16 ***
Japan 1.01776 0.08514 11.954 <2e-16 ***
M1 -0.25413 2.98318 -0.085 0.932
M2 -1.30117 2.98270 -0.436 0.663
M3 -1.26485 2.98265 -0.424 0.672
M4 0.23065 2.98301 0.077 0.938
M5 0.19291 2.98284 0.065 0.948
M6 0.09745 2.98269 0.033 0.974
M7 -1.71115 2.98302 -0.574 0.567
M8 -2.05082 2.98313 -0.687 0.492
M9 -1.71784 2.98273 -0.576 0.565
M10 -2.22647 2.98294 -0.746 0.456
M11 -1.61852 2.98278 -0.543 0.588
t -0.23037 0.01099 -20.967 <2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 12.02 on 381 degrees of freedom
Multiple R-squared: 0.92, Adjusted R-squared: 0.9173
F-statistic: 337.2 on 13 and 381 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,] 5.291189e-03 1.058238e-02 0.9947088
[2,] 3.139333e-03 6.278666e-03 0.9968607
[3,] 5.557180e-04 1.111436e-03 0.9994443
[4,] 1.870477e-04 3.740954e-04 0.9998130
[5,] 4.968365e-05 9.936729e-05 0.9999503
[6,] 1.590156e-05 3.180311e-05 0.9999841
[7,] 3.049718e-06 6.099436e-06 0.9999970
[8,] 8.019155e-06 1.603831e-05 0.9999920
[9,] 6.311604e-06 1.262321e-05 0.9999937
[10,] 2.676711e-06 5.353422e-06 0.9999973
[11,] 7.487804e-07 1.497561e-06 0.9999993
[12,] 2.280007e-07 4.560014e-07 0.9999998
[13,] 5.283373e-08 1.056675e-07 0.9999999
[14,] 1.223442e-08 2.446885e-08 1.0000000
[15,] 3.252351e-09 6.504702e-09 1.0000000
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[343,] 5.119418e-01 9.761163e-01 0.4880582
[344,] 4.746519e-01 9.493037e-01 0.5253481
[345,] 4.385254e-01 8.770508e-01 0.5614746
[346,] 4.277750e-01 8.555501e-01 0.5722250
[347,] 4.416197e-01 8.832395e-01 0.5583803
[348,] 4.147716e-01 8.295431e-01 0.5852284
[349,] 3.478669e-01 6.957337e-01 0.6521331
[350,] 3.301414e-01 6.602827e-01 0.6698586
[351,] 2.810726e-01 5.621451e-01 0.7189274
[352,] 3.513790e-01 7.027581e-01 0.6486210
[353,] 8.285099e-01 3.429801e-01 0.1714901
[354,] 7.633401e-01 4.733198e-01 0.2366599
[355,] 6.851090e-01 6.297821e-01 0.3148910
[356,] 6.600672e-01 6.798656e-01 0.3399328
[357,] 5.618260e-01 8.763480e-01 0.4381740
[358,] 4.634221e-01 9.268442e-01 0.5365779
[359,] 3.904433e-01 7.808866e-01 0.6095567
[360,] 5.409118e-01 9.181764e-01 0.4590882
[361,] 5.439098e-01 9.121804e-01 0.4560902
[362,] 4.521890e-01 9.043780e-01 0.5478110
> postscript(file="/var/www/html/rcomp/tmp/19w7t1228923628.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
> points(x[,1]-mysum$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2s2d41228923628.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/36kui1228923628.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/47m2c1228923628.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/562o61228923628.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 = 395
Frequency = 1
1 2 3 4 5 6
-1.42592399 3.23425843 3.18344870 2.95185561 1.67930913 -1.70765455
7 8 9 10 11 12
-2.91023559 -7.89072587 -1.91293774 2.19082245 -1.53297858 3.19917104
13 14 15 16 17 18
6.80995373 8.78901673 7.95305626 5.05021989 0.33241518 3.27664105
19 20 21 22 23 24
-0.02741463 -0.73209746 -1.71121981 2.32748074 2.66778117 -1.72234080
25 26 27 28 29 30
-1.05583719 0.75185866 0.65501013 0.40290060 1.15958993 2.03647996
31 32 33 34 35 36
-2.98206975 -4.25092416 5.53831763 7.82211518 4.56865299 3.00138919
37 38 39 40 41 42
3.20654203 6.85313486 2.30060276 2.62227681 -5.83323533 -1.64717961
43 44 45 46 47 48
-6.91494875 -7.98725250 -6.23212855 -8.87087130 -7.68124397 -3.67954067
49 50 51 52 53 54
-14.36451169 -8.84635313 -3.81838975 -0.91623661 -7.72475176 -9.39492884
55 56 57 58 59 60
-2.16971593 -6.72878531 -10.39023300 -5.45641906 -0.21116189 6.26897568
61 62 63 64 65 66
4.21196441 6.25266328 6.41458785 4.71310225 2.62080351 -6.13095569
67 68 69 70 71 72
1.77687223 5.24458487 8.32651181 6.57009898 10.83908599 5.02709680
73 74 75 76 77 78
6.84740039 1.06049472 -1.88814631 3.92746798 3.40841999 6.71388913
79 80 81 82 83 84
10.27114686 7.71454766 17.17032831 21.22149446 11.23593829 9.98292078
85 86 87 88 89 90
10.74903181 10.80791721 10.94051946 11.25586961 6.11371571 9.28071323
91 92 93 94 95 96
14.06885902 11.47728669 11.76116736 16.57869475 17.68212207 18.21952991
97 98 99 100 101 102
16.64722306 14.55605472 18.33275842 12.86762949 12.58911433 14.63690882
103 104 105 106 107 108
16.10091580 6.62277183 9.93961815 14.78350222 13.55112209 10.08137172
109 110 111 112 113 114
14.74824694 14.66480700 13.30456746 12.66926091 4.91239800 5.00822237
115 116 117 118 119 120
5.91068459 10.60092115 -0.88566090 -2.24513048 -4.34410322 -7.43971478
121 122 123 124 125 126
2.19817237 1.50648758 -4.89382209 -5.34369280 -10.86558258 -9.61642094
127 128 129 130 131 132
-14.44468556 -13.07581615 -7.82607430 -14.06748123 -14.34829563 -4.09525795
133 134 135 136 137 138
-2.14340960 -0.02425550 -1.33323537 -7.36582400 0.36258771 6.56480610
139 140 141 142 143 144
6.03481910 7.05278406 -0.21829201 0.93731901 4.86360450 6.31441974
145 146 147 148 149 150
5.44710241 9.49417433 10.75188997 13.20345654 17.97570557 9.64020014
151 152 153 154 155 156
9.69271610 10.39306014 3.04836170 1.73686825 -7.78373576 -3.49013248
157 158 159 160 161 162
-5.92602891 -1.23975395 -0.81601591 -4.58301205 -3.26987496 -10.69204312
163 164 165 166 167 168
-7.08561971 -10.81689514 -14.38422040 -12.20179000 -14.44017616 -1.83257890
169 170 171 172 173 174
-3.18928869 -8.33592564 -10.73850691 -4.90069115 -9.32426595 -5.01128337
175 176 177 178 179 180
-1.02304648 -2.33684125 -10.92942474 -12.21136451 -2.74742533 -4.06811749
181 182 183 184 185 186
-0.13591392 0.54101774 5.75233936 0.28106414 -5.07613302 -4.15101910
187 188 189 190 191 192
-3.36317479 0.15306779 -2.64543520 -3.50451222 1.26726285 -0.98747703
193 194 195 196 197 198
-5.31706596 -9.76837457 -17.60646638 -19.37070725 -15.65254787 -13.95121754
199 200 201 202 203 204
-18.94141950 -24.05910076 -24.16172160 -23.42271957 -23.80030418 -23.88501129
205 206 207 208 209 210
-20.12611221 -30.41385220 -14.81191123 -21.72720139 -16.90830602 -14.51029657
211 212 213 214 215 216
-14.36484772 -19.48812604 -21.19629020 -24.53991499 -7.60876386 -12.60339626
217 218 219 220 221 222
-12.27582698 -13.96665649 -12.58959756 -15.63609364 -16.46748794 -13.83603374
223 224 225 226 227 228
-16.92788795 -20.66503637 -15.99005726 -11.38283135 -12.49599206 -7.03456927
229 230 231 232 233 234
-9.51225821 -14.62724292 -11.09958103 -7.41831594 -2.86427440 -7.15606637
235 236 237 238 239 240
-6.35243100 -5.81594067 4.57252054 1.21328231 1.40699471 -1.94399894
241 242 243 244 245 246
-1.34335651 0.24348406 2.12468180 1.94251852 3.26174816 6.16046805
247 248 249 250 251 252
5.72515271 6.02334902 0.92326849 -5.81447873 -2.76009323 -8.24007495
253 254 255 256 257 258
-8.43499223 -2.07713973 0.15558639 4.17686786 3.14407364 -1.59486016
259 260 261 262 263 264
-2.46799042 0.15006106 2.27653577 -7.26959655 -9.45252591 -2.92146292
265 266 267 268 269 270
-5.31540563 -2.79966351 6.58636252 4.66093211 -1.28589345 -3.94326609
271 272 273 274 275 276
-1.59780086 -5.93625089 -2.06217623 -3.32061750 -1.69086629 -13.54244652
277 278 279 280 281 282
-13.41084591 -11.65112620 -10.92010607 -19.35523500 -15.01403525 -13.21636464
283 284 285 286 287 288
-13.22793375 -9.72405386 -13.54942997 -12.53357121 -17.55346478 -20.97854350
289 290 291 292 293 294
-24.36765333 -14.06407991 -12.15968515 -12.33397977 -10.09780689 -7.05068550
295 296 297 298 299 300
-4.38079636 -10.24123290 -11.93465070 -13.58721440 -4.40478263 -0.39400016
301 302 303 304 305 306
-6.04880996 -5.91530666 -6.98308060 2.60885758 3.92068126 0.71289965
307 308 309 310 311 312
15.48299917 16.88084026 15.69212688 16.77757668 20.09936813 23.29530134
313 314 315 316 317 318
18.18368856 16.93985603 21.15385821 17.52469794 21.85600518 17.28881014
319 320 321 322 323 324
23.90642310 25.71397910 29.88094929 26.88101699 24.82221006 26.42332679
325 326 327 328 329 330
26.22023936 20.35445311 23.62103295 32.73582930 20.27360527 26.20784752
331 332 333 334 335 336
34.87054109 32.51497020 17.80867325 28.02374686 13.95415477 18.73486711
337 338 339 340 341 342
34.16637663 17.91837252 9.03291211 8.79559809 15.60603365 16.82310130
343 344 345 346 347 348
-1.09260662 18.69104192 23.61202247 15.98315585 14.99796670 7.88862530
349 350 351 352 353 354
-7.23053828 -5.88760517 -17.51499112 -21.52646033 7.89976170 -1.28893616
355 356 357 358 359 360
-20.56169481 -10.17367611 -4.56552095 9.94614526 1.15326964 -9.31996283
361 362 363 364 365 366
-5.47534282 -6.35193062 -10.50032391 12.35413361 3.47356182 11.95849813
367 368 369 370 371 372
8.78137389 16.58541043 23.57415674 1.02543953 -2.13666008 2.21612985
373 374 375 376 377 378
-0.26280237 2.07231582 -9.52098047 2.16612942 -3.17398882 -9.89102263
379 380 381 382 383 384
-3.81813506 -17.05626264 -29.91621931 -13.75446658 -6.77359596 -12.47449852
385 386 387 388 389 390
-2.07401732 -0.07110060 4.93162552 -16.43321832 -7.03134547 -1.51925095
391 392 393 394 395
-7.96804841 1.16034191 6.38713449 0.16422015 -1.34336447
> postscript(file="/var/www/html/rcomp/tmp/66t8h1228923628.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 = 395
Frequency = 1
lag(myerror, k = 1) myerror
0 -1.42592399 NA
1 3.23425843 -1.42592399
2 3.18344870 3.23425843
3 2.95185561 3.18344870
4 1.67930913 2.95185561
5 -1.70765455 1.67930913
6 -2.91023559 -1.70765455
7 -7.89072587 -2.91023559
8 -1.91293774 -7.89072587
9 2.19082245 -1.91293774
10 -1.53297858 2.19082245
11 3.19917104 -1.53297858
12 6.80995373 3.19917104
13 8.78901673 6.80995373
14 7.95305626 8.78901673
15 5.05021989 7.95305626
16 0.33241518 5.05021989
17 3.27664105 0.33241518
18 -0.02741463 3.27664105
19 -0.73209746 -0.02741463
20 -1.71121981 -0.73209746
21 2.32748074 -1.71121981
22 2.66778117 2.32748074
23 -1.72234080 2.66778117
24 -1.05583719 -1.72234080
25 0.75185866 -1.05583719
26 0.65501013 0.75185866
27 0.40290060 0.65501013
28 1.15958993 0.40290060
29 2.03647996 1.15958993
30 -2.98206975 2.03647996
31 -4.25092416 -2.98206975
32 5.53831763 -4.25092416
33 7.82211518 5.53831763
34 4.56865299 7.82211518
35 3.00138919 4.56865299
36 3.20654203 3.00138919
37 6.85313486 3.20654203
38 2.30060276 6.85313486
39 2.62227681 2.30060276
40 -5.83323533 2.62227681
41 -1.64717961 -5.83323533
42 -6.91494875 -1.64717961
43 -7.98725250 -6.91494875
44 -6.23212855 -7.98725250
45 -8.87087130 -6.23212855
46 -7.68124397 -8.87087130
47 -3.67954067 -7.68124397
48 -14.36451169 -3.67954067
49 -8.84635313 -14.36451169
50 -3.81838975 -8.84635313
51 -0.91623661 -3.81838975
52 -7.72475176 -0.91623661
53 -9.39492884 -7.72475176
54 -2.16971593 -9.39492884
55 -6.72878531 -2.16971593
56 -10.39023300 -6.72878531
57 -5.45641906 -10.39023300
58 -0.21116189 -5.45641906
59 6.26897568 -0.21116189
60 4.21196441 6.26897568
61 6.25266328 4.21196441
62 6.41458785 6.25266328
63 4.71310225 6.41458785
64 2.62080351 4.71310225
65 -6.13095569 2.62080351
66 1.77687223 -6.13095569
67 5.24458487 1.77687223
68 8.32651181 5.24458487
69 6.57009898 8.32651181
70 10.83908599 6.57009898
71 5.02709680 10.83908599
72 6.84740039 5.02709680
73 1.06049472 6.84740039
74 -1.88814631 1.06049472
75 3.92746798 -1.88814631
76 3.40841999 3.92746798
77 6.71388913 3.40841999
78 10.27114686 6.71388913
79 7.71454766 10.27114686
80 17.17032831 7.71454766
81 21.22149446 17.17032831
82 11.23593829 21.22149446
83 9.98292078 11.23593829
84 10.74903181 9.98292078
85 10.80791721 10.74903181
86 10.94051946 10.80791721
87 11.25586961 10.94051946
88 6.11371571 11.25586961
89 9.28071323 6.11371571
90 14.06885902 9.28071323
91 11.47728669 14.06885902
92 11.76116736 11.47728669
93 16.57869475 11.76116736
94 17.68212207 16.57869475
95 18.21952991 17.68212207
96 16.64722306 18.21952991
97 14.55605472 16.64722306
98 18.33275842 14.55605472
99 12.86762949 18.33275842
100 12.58911433 12.86762949
101 14.63690882 12.58911433
102 16.10091580 14.63690882
103 6.62277183 16.10091580
104 9.93961815 6.62277183
105 14.78350222 9.93961815
106 13.55112209 14.78350222
107 10.08137172 13.55112209
108 14.74824694 10.08137172
109 14.66480700 14.74824694
110 13.30456746 14.66480700
111 12.66926091 13.30456746
112 4.91239800 12.66926091
113 5.00822237 4.91239800
114 5.91068459 5.00822237
115 10.60092115 5.91068459
116 -0.88566090 10.60092115
117 -2.24513048 -0.88566090
118 -4.34410322 -2.24513048
119 -7.43971478 -4.34410322
120 2.19817237 -7.43971478
121 1.50648758 2.19817237
122 -4.89382209 1.50648758
123 -5.34369280 -4.89382209
124 -10.86558258 -5.34369280
125 -9.61642094 -10.86558258
126 -14.44468556 -9.61642094
127 -13.07581615 -14.44468556
128 -7.82607430 -13.07581615
129 -14.06748123 -7.82607430
130 -14.34829563 -14.06748123
131 -4.09525795 -14.34829563
132 -2.14340960 -4.09525795
133 -0.02425550 -2.14340960
134 -1.33323537 -0.02425550
135 -7.36582400 -1.33323537
136 0.36258771 -7.36582400
137 6.56480610 0.36258771
138 6.03481910 6.56480610
139 7.05278406 6.03481910
140 -0.21829201 7.05278406
141 0.93731901 -0.21829201
142 4.86360450 0.93731901
143 6.31441974 4.86360450
144 5.44710241 6.31441974
145 9.49417433 5.44710241
146 10.75188997 9.49417433
147 13.20345654 10.75188997
148 17.97570557 13.20345654
149 9.64020014 17.97570557
150 9.69271610 9.64020014
151 10.39306014 9.69271610
152 3.04836170 10.39306014
153 1.73686825 3.04836170
154 -7.78373576 1.73686825
155 -3.49013248 -7.78373576
156 -5.92602891 -3.49013248
157 -1.23975395 -5.92602891
158 -0.81601591 -1.23975395
159 -4.58301205 -0.81601591
160 -3.26987496 -4.58301205
161 -10.69204312 -3.26987496
162 -7.08561971 -10.69204312
163 -10.81689514 -7.08561971
164 -14.38422040 -10.81689514
165 -12.20179000 -14.38422040
166 -14.44017616 -12.20179000
167 -1.83257890 -14.44017616
168 -3.18928869 -1.83257890
169 -8.33592564 -3.18928869
170 -10.73850691 -8.33592564
171 -4.90069115 -10.73850691
172 -9.32426595 -4.90069115
173 -5.01128337 -9.32426595
174 -1.02304648 -5.01128337
175 -2.33684125 -1.02304648
176 -10.92942474 -2.33684125
177 -12.21136451 -10.92942474
178 -2.74742533 -12.21136451
179 -4.06811749 -2.74742533
180 -0.13591392 -4.06811749
181 0.54101774 -0.13591392
182 5.75233936 0.54101774
183 0.28106414 5.75233936
184 -5.07613302 0.28106414
185 -4.15101910 -5.07613302
186 -3.36317479 -4.15101910
187 0.15306779 -3.36317479
188 -2.64543520 0.15306779
189 -3.50451222 -2.64543520
190 1.26726285 -3.50451222
191 -0.98747703 1.26726285
192 -5.31706596 -0.98747703
193 -9.76837457 -5.31706596
194 -17.60646638 -9.76837457
195 -19.37070725 -17.60646638
196 -15.65254787 -19.37070725
197 -13.95121754 -15.65254787
198 -18.94141950 -13.95121754
199 -24.05910076 -18.94141950
200 -24.16172160 -24.05910076
201 -23.42271957 -24.16172160
202 -23.80030418 -23.42271957
203 -23.88501129 -23.80030418
204 -20.12611221 -23.88501129
205 -30.41385220 -20.12611221
206 -14.81191123 -30.41385220
207 -21.72720139 -14.81191123
208 -16.90830602 -21.72720139
209 -14.51029657 -16.90830602
210 -14.36484772 -14.51029657
211 -19.48812604 -14.36484772
212 -21.19629020 -19.48812604
213 -24.53991499 -21.19629020
214 -7.60876386 -24.53991499
215 -12.60339626 -7.60876386
216 -12.27582698 -12.60339626
217 -13.96665649 -12.27582698
218 -12.58959756 -13.96665649
219 -15.63609364 -12.58959756
220 -16.46748794 -15.63609364
221 -13.83603374 -16.46748794
222 -16.92788795 -13.83603374
223 -20.66503637 -16.92788795
224 -15.99005726 -20.66503637
225 -11.38283135 -15.99005726
226 -12.49599206 -11.38283135
227 -7.03456927 -12.49599206
228 -9.51225821 -7.03456927
229 -14.62724292 -9.51225821
230 -11.09958103 -14.62724292
231 -7.41831594 -11.09958103
232 -2.86427440 -7.41831594
233 -7.15606637 -2.86427440
234 -6.35243100 -7.15606637
235 -5.81594067 -6.35243100
236 4.57252054 -5.81594067
237 1.21328231 4.57252054
238 1.40699471 1.21328231
239 -1.94399894 1.40699471
240 -1.34335651 -1.94399894
241 0.24348406 -1.34335651
242 2.12468180 0.24348406
243 1.94251852 2.12468180
244 3.26174816 1.94251852
245 6.16046805 3.26174816
246 5.72515271 6.16046805
247 6.02334902 5.72515271
248 0.92326849 6.02334902
249 -5.81447873 0.92326849
250 -2.76009323 -5.81447873
251 -8.24007495 -2.76009323
252 -8.43499223 -8.24007495
253 -2.07713973 -8.43499223
254 0.15558639 -2.07713973
255 4.17686786 0.15558639
256 3.14407364 4.17686786
257 -1.59486016 3.14407364
258 -2.46799042 -1.59486016
259 0.15006106 -2.46799042
260 2.27653577 0.15006106
261 -7.26959655 2.27653577
262 -9.45252591 -7.26959655
263 -2.92146292 -9.45252591
264 -5.31540563 -2.92146292
265 -2.79966351 -5.31540563
266 6.58636252 -2.79966351
267 4.66093211 6.58636252
268 -1.28589345 4.66093211
269 -3.94326609 -1.28589345
270 -1.59780086 -3.94326609
271 -5.93625089 -1.59780086
272 -2.06217623 -5.93625089
273 -3.32061750 -2.06217623
274 -1.69086629 -3.32061750
275 -13.54244652 -1.69086629
276 -13.41084591 -13.54244652
277 -11.65112620 -13.41084591
278 -10.92010607 -11.65112620
279 -19.35523500 -10.92010607
280 -15.01403525 -19.35523500
281 -13.21636464 -15.01403525
282 -13.22793375 -13.21636464
283 -9.72405386 -13.22793375
284 -13.54942997 -9.72405386
285 -12.53357121 -13.54942997
286 -17.55346478 -12.53357121
287 -20.97854350 -17.55346478
288 -24.36765333 -20.97854350
289 -14.06407991 -24.36765333
290 -12.15968515 -14.06407991
291 -12.33397977 -12.15968515
292 -10.09780689 -12.33397977
293 -7.05068550 -10.09780689
294 -4.38079636 -7.05068550
295 -10.24123290 -4.38079636
296 -11.93465070 -10.24123290
297 -13.58721440 -11.93465070
298 -4.40478263 -13.58721440
299 -0.39400016 -4.40478263
300 -6.04880996 -0.39400016
301 -5.91530666 -6.04880996
302 -6.98308060 -5.91530666
303 2.60885758 -6.98308060
304 3.92068126 2.60885758
305 0.71289965 3.92068126
306 15.48299917 0.71289965
307 16.88084026 15.48299917
308 15.69212688 16.88084026
309 16.77757668 15.69212688
310 20.09936813 16.77757668
311 23.29530134 20.09936813
312 18.18368856 23.29530134
313 16.93985603 18.18368856
314 21.15385821 16.93985603
315 17.52469794 21.15385821
316 21.85600518 17.52469794
317 17.28881014 21.85600518
318 23.90642310 17.28881014
319 25.71397910 23.90642310
320 29.88094929 25.71397910
321 26.88101699 29.88094929
322 24.82221006 26.88101699
323 26.42332679 24.82221006
324 26.22023936 26.42332679
325 20.35445311 26.22023936
326 23.62103295 20.35445311
327 32.73582930 23.62103295
328 20.27360527 32.73582930
329 26.20784752 20.27360527
330 34.87054109 26.20784752
331 32.51497020 34.87054109
332 17.80867325 32.51497020
333 28.02374686 17.80867325
334 13.95415477 28.02374686
335 18.73486711 13.95415477
336 34.16637663 18.73486711
337 17.91837252 34.16637663
338 9.03291211 17.91837252
339 8.79559809 9.03291211
340 15.60603365 8.79559809
341 16.82310130 15.60603365
342 -1.09260662 16.82310130
343 18.69104192 -1.09260662
344 23.61202247 18.69104192
345 15.98315585 23.61202247
346 14.99796670 15.98315585
347 7.88862530 14.99796670
348 -7.23053828 7.88862530
349 -5.88760517 -7.23053828
350 -17.51499112 -5.88760517
351 -21.52646033 -17.51499112
352 7.89976170 -21.52646033
353 -1.28893616 7.89976170
354 -20.56169481 -1.28893616
355 -10.17367611 -20.56169481
356 -4.56552095 -10.17367611
357 9.94614526 -4.56552095
358 1.15326964 9.94614526
359 -9.31996283 1.15326964
360 -5.47534282 -9.31996283
361 -6.35193062 -5.47534282
362 -10.50032391 -6.35193062
363 12.35413361 -10.50032391
364 3.47356182 12.35413361
365 11.95849813 3.47356182
366 8.78137389 11.95849813
367 16.58541043 8.78137389
368 23.57415674 16.58541043
369 1.02543953 23.57415674
370 -2.13666008 1.02543953
371 2.21612985 -2.13666008
372 -0.26280237 2.21612985
373 2.07231582 -0.26280237
374 -9.52098047 2.07231582
375 2.16612942 -9.52098047
376 -3.17398882 2.16612942
377 -9.89102263 -3.17398882
378 -3.81813506 -9.89102263
379 -17.05626264 -3.81813506
380 -29.91621931 -17.05626264
381 -13.75446658 -29.91621931
382 -6.77359596 -13.75446658
383 -12.47449852 -6.77359596
384 -2.07401732 -12.47449852
385 -0.07110060 -2.07401732
386 4.93162552 -0.07110060
387 -16.43321832 4.93162552
388 -7.03134547 -16.43321832
389 -1.51925095 -7.03134547
390 -7.96804841 -1.51925095
391 1.16034191 -7.96804841
392 6.38713449 1.16034191
393 0.16422015 6.38713449
394 -1.34336447 0.16422015
395 NA -1.34336447
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 3.23425843 -1.42592399
[2,] 3.18344870 3.23425843
[3,] 2.95185561 3.18344870
[4,] 1.67930913 2.95185561
[5,] -1.70765455 1.67930913
[6,] -2.91023559 -1.70765455
[7,] -7.89072587 -2.91023559
[8,] -1.91293774 -7.89072587
[9,] 2.19082245 -1.91293774
[10,] -1.53297858 2.19082245
[11,] 3.19917104 -1.53297858
[12,] 6.80995373 3.19917104
[13,] 8.78901673 6.80995373
[14,] 7.95305626 8.78901673
[15,] 5.05021989 7.95305626
[16,] 0.33241518 5.05021989
[17,] 3.27664105 0.33241518
[18,] -0.02741463 3.27664105
[19,] -0.73209746 -0.02741463
[20,] -1.71121981 -0.73209746
[21,] 2.32748074 -1.71121981
[22,] 2.66778117 2.32748074
[23,] -1.72234080 2.66778117
[24,] -1.05583719 -1.72234080
[25,] 0.75185866 -1.05583719
[26,] 0.65501013 0.75185866
[27,] 0.40290060 0.65501013
[28,] 1.15958993 0.40290060
[29,] 2.03647996 1.15958993
[30,] -2.98206975 2.03647996
[31,] -4.25092416 -2.98206975
[32,] 5.53831763 -4.25092416
[33,] 7.82211518 5.53831763
[34,] 4.56865299 7.82211518
[35,] 3.00138919 4.56865299
[36,] 3.20654203 3.00138919
[37,] 6.85313486 3.20654203
[38,] 2.30060276 6.85313486
[39,] 2.62227681 2.30060276
[40,] -5.83323533 2.62227681
[41,] -1.64717961 -5.83323533
[42,] -6.91494875 -1.64717961
[43,] -7.98725250 -6.91494875
[44,] -6.23212855 -7.98725250
[45,] -8.87087130 -6.23212855
[46,] -7.68124397 -8.87087130
[47,] -3.67954067 -7.68124397
[48,] -14.36451169 -3.67954067
[49,] -8.84635313 -14.36451169
[50,] -3.81838975 -8.84635313
[51,] -0.91623661 -3.81838975
[52,] -7.72475176 -0.91623661
[53,] -9.39492884 -7.72475176
[54,] -2.16971593 -9.39492884
[55,] -6.72878531 -2.16971593
[56,] -10.39023300 -6.72878531
[57,] -5.45641906 -10.39023300
[58,] -0.21116189 -5.45641906
[59,] 6.26897568 -0.21116189
[60,] 4.21196441 6.26897568
[61,] 6.25266328 4.21196441
[62,] 6.41458785 6.25266328
[63,] 4.71310225 6.41458785
[64,] 2.62080351 4.71310225
[65,] -6.13095569 2.62080351
[66,] 1.77687223 -6.13095569
[67,] 5.24458487 1.77687223
[68,] 8.32651181 5.24458487
[69,] 6.57009898 8.32651181
[70,] 10.83908599 6.57009898
[71,] 5.02709680 10.83908599
[72,] 6.84740039 5.02709680
[73,] 1.06049472 6.84740039
[74,] -1.88814631 1.06049472
[75,] 3.92746798 -1.88814631
[76,] 3.40841999 3.92746798
[77,] 6.71388913 3.40841999
[78,] 10.27114686 6.71388913
[79,] 7.71454766 10.27114686
[80,] 17.17032831 7.71454766
[81,] 21.22149446 17.17032831
[82,] 11.23593829 21.22149446
[83,] 9.98292078 11.23593829
[84,] 10.74903181 9.98292078
[85,] 10.80791721 10.74903181
[86,] 10.94051946 10.80791721
[87,] 11.25586961 10.94051946
[88,] 6.11371571 11.25586961
[89,] 9.28071323 6.11371571
[90,] 14.06885902 9.28071323
[91,] 11.47728669 14.06885902
[92,] 11.76116736 11.47728669
[93,] 16.57869475 11.76116736
[94,] 17.68212207 16.57869475
[95,] 18.21952991 17.68212207
[96,] 16.64722306 18.21952991
[97,] 14.55605472 16.64722306
[98,] 18.33275842 14.55605472
[99,] 12.86762949 18.33275842
[100,] 12.58911433 12.86762949
[101,] 14.63690882 12.58911433
[102,] 16.10091580 14.63690882
[103,] 6.62277183 16.10091580
[104,] 9.93961815 6.62277183
[105,] 14.78350222 9.93961815
[106,] 13.55112209 14.78350222
[107,] 10.08137172 13.55112209
[108,] 14.74824694 10.08137172
[109,] 14.66480700 14.74824694
[110,] 13.30456746 14.66480700
[111,] 12.66926091 13.30456746
[112,] 4.91239800 12.66926091
[113,] 5.00822237 4.91239800
[114,] 5.91068459 5.00822237
[115,] 10.60092115 5.91068459
[116,] -0.88566090 10.60092115
[117,] -2.24513048 -0.88566090
[118,] -4.34410322 -2.24513048
[119,] -7.43971478 -4.34410322
[120,] 2.19817237 -7.43971478
[121,] 1.50648758 2.19817237
[122,] -4.89382209 1.50648758
[123,] -5.34369280 -4.89382209
[124,] -10.86558258 -5.34369280
[125,] -9.61642094 -10.86558258
[126,] -14.44468556 -9.61642094
[127,] -13.07581615 -14.44468556
[128,] -7.82607430 -13.07581615
[129,] -14.06748123 -7.82607430
[130,] -14.34829563 -14.06748123
[131,] -4.09525795 -14.34829563
[132,] -2.14340960 -4.09525795
[133,] -0.02425550 -2.14340960
[134,] -1.33323537 -0.02425550
[135,] -7.36582400 -1.33323537
[136,] 0.36258771 -7.36582400
[137,] 6.56480610 0.36258771
[138,] 6.03481910 6.56480610
[139,] 7.05278406 6.03481910
[140,] -0.21829201 7.05278406
[141,] 0.93731901 -0.21829201
[142,] 4.86360450 0.93731901
[143,] 6.31441974 4.86360450
[144,] 5.44710241 6.31441974
[145,] 9.49417433 5.44710241
[146,] 10.75188997 9.49417433
[147,] 13.20345654 10.75188997
[148,] 17.97570557 13.20345654
[149,] 9.64020014 17.97570557
[150,] 9.69271610 9.64020014
[151,] 10.39306014 9.69271610
[152,] 3.04836170 10.39306014
[153,] 1.73686825 3.04836170
[154,] -7.78373576 1.73686825
[155,] -3.49013248 -7.78373576
[156,] -5.92602891 -3.49013248
[157,] -1.23975395 -5.92602891
[158,] -0.81601591 -1.23975395
[159,] -4.58301205 -0.81601591
[160,] -3.26987496 -4.58301205
[161,] -10.69204312 -3.26987496
[162,] -7.08561971 -10.69204312
[163,] -10.81689514 -7.08561971
[164,] -14.38422040 -10.81689514
[165,] -12.20179000 -14.38422040
[166,] -14.44017616 -12.20179000
[167,] -1.83257890 -14.44017616
[168,] -3.18928869 -1.83257890
[169,] -8.33592564 -3.18928869
[170,] -10.73850691 -8.33592564
[171,] -4.90069115 -10.73850691
[172,] -9.32426595 -4.90069115
[173,] -5.01128337 -9.32426595
[174,] -1.02304648 -5.01128337
[175,] -2.33684125 -1.02304648
[176,] -10.92942474 -2.33684125
[177,] -12.21136451 -10.92942474
[178,] -2.74742533 -12.21136451
[179,] -4.06811749 -2.74742533
[180,] -0.13591392 -4.06811749
[181,] 0.54101774 -0.13591392
[182,] 5.75233936 0.54101774
[183,] 0.28106414 5.75233936
[184,] -5.07613302 0.28106414
[185,] -4.15101910 -5.07613302
[186,] -3.36317479 -4.15101910
[187,] 0.15306779 -3.36317479
[188,] -2.64543520 0.15306779
[189,] -3.50451222 -2.64543520
[190,] 1.26726285 -3.50451222
[191,] -0.98747703 1.26726285
[192,] -5.31706596 -0.98747703
[193,] -9.76837457 -5.31706596
[194,] -17.60646638 -9.76837457
[195,] -19.37070725 -17.60646638
[196,] -15.65254787 -19.37070725
[197,] -13.95121754 -15.65254787
[198,] -18.94141950 -13.95121754
[199,] -24.05910076 -18.94141950
[200,] -24.16172160 -24.05910076
[201,] -23.42271957 -24.16172160
[202,] -23.80030418 -23.42271957
[203,] -23.88501129 -23.80030418
[204,] -20.12611221 -23.88501129
[205,] -30.41385220 -20.12611221
[206,] -14.81191123 -30.41385220
[207,] -21.72720139 -14.81191123
[208,] -16.90830602 -21.72720139
[209,] -14.51029657 -16.90830602
[210,] -14.36484772 -14.51029657
[211,] -19.48812604 -14.36484772
[212,] -21.19629020 -19.48812604
[213,] -24.53991499 -21.19629020
[214,] -7.60876386 -24.53991499
[215,] -12.60339626 -7.60876386
[216,] -12.27582698 -12.60339626
[217,] -13.96665649 -12.27582698
[218,] -12.58959756 -13.96665649
[219,] -15.63609364 -12.58959756
[220,] -16.46748794 -15.63609364
[221,] -13.83603374 -16.46748794
[222,] -16.92788795 -13.83603374
[223,] -20.66503637 -16.92788795
[224,] -15.99005726 -20.66503637
[225,] -11.38283135 -15.99005726
[226,] -12.49599206 -11.38283135
[227,] -7.03456927 -12.49599206
[228,] -9.51225821 -7.03456927
[229,] -14.62724292 -9.51225821
[230,] -11.09958103 -14.62724292
[231,] -7.41831594 -11.09958103
[232,] -2.86427440 -7.41831594
[233,] -7.15606637 -2.86427440
[234,] -6.35243100 -7.15606637
[235,] -5.81594067 -6.35243100
[236,] 4.57252054 -5.81594067
[237,] 1.21328231 4.57252054
[238,] 1.40699471 1.21328231
[239,] -1.94399894 1.40699471
[240,] -1.34335651 -1.94399894
[241,] 0.24348406 -1.34335651
[242,] 2.12468180 0.24348406
[243,] 1.94251852 2.12468180
[244,] 3.26174816 1.94251852
[245,] 6.16046805 3.26174816
[246,] 5.72515271 6.16046805
[247,] 6.02334902 5.72515271
[248,] 0.92326849 6.02334902
[249,] -5.81447873 0.92326849
[250,] -2.76009323 -5.81447873
[251,] -8.24007495 -2.76009323
[252,] -8.43499223 -8.24007495
[253,] -2.07713973 -8.43499223
[254,] 0.15558639 -2.07713973
[255,] 4.17686786 0.15558639
[256,] 3.14407364 4.17686786
[257,] -1.59486016 3.14407364
[258,] -2.46799042 -1.59486016
[259,] 0.15006106 -2.46799042
[260,] 2.27653577 0.15006106
[261,] -7.26959655 2.27653577
[262,] -9.45252591 -7.26959655
[263,] -2.92146292 -9.45252591
[264,] -5.31540563 -2.92146292
[265,] -2.79966351 -5.31540563
[266,] 6.58636252 -2.79966351
[267,] 4.66093211 6.58636252
[268,] -1.28589345 4.66093211
[269,] -3.94326609 -1.28589345
[270,] -1.59780086 -3.94326609
[271,] -5.93625089 -1.59780086
[272,] -2.06217623 -5.93625089
[273,] -3.32061750 -2.06217623
[274,] -1.69086629 -3.32061750
[275,] -13.54244652 -1.69086629
[276,] -13.41084591 -13.54244652
[277,] -11.65112620 -13.41084591
[278,] -10.92010607 -11.65112620
[279,] -19.35523500 -10.92010607
[280,] -15.01403525 -19.35523500
[281,] -13.21636464 -15.01403525
[282,] -13.22793375 -13.21636464
[283,] -9.72405386 -13.22793375
[284,] -13.54942997 -9.72405386
[285,] -12.53357121 -13.54942997
[286,] -17.55346478 -12.53357121
[287,] -20.97854350 -17.55346478
[288,] -24.36765333 -20.97854350
[289,] -14.06407991 -24.36765333
[290,] -12.15968515 -14.06407991
[291,] -12.33397977 -12.15968515
[292,] -10.09780689 -12.33397977
[293,] -7.05068550 -10.09780689
[294,] -4.38079636 -7.05068550
[295,] -10.24123290 -4.38079636
[296,] -11.93465070 -10.24123290
[297,] -13.58721440 -11.93465070
[298,] -4.40478263 -13.58721440
[299,] -0.39400016 -4.40478263
[300,] -6.04880996 -0.39400016
[301,] -5.91530666 -6.04880996
[302,] -6.98308060 -5.91530666
[303,] 2.60885758 -6.98308060
[304,] 3.92068126 2.60885758
[305,] 0.71289965 3.92068126
[306,] 15.48299917 0.71289965
[307,] 16.88084026 15.48299917
[308,] 15.69212688 16.88084026
[309,] 16.77757668 15.69212688
[310,] 20.09936813 16.77757668
[311,] 23.29530134 20.09936813
[312,] 18.18368856 23.29530134
[313,] 16.93985603 18.18368856
[314,] 21.15385821 16.93985603
[315,] 17.52469794 21.15385821
[316,] 21.85600518 17.52469794
[317,] 17.28881014 21.85600518
[318,] 23.90642310 17.28881014
[319,] 25.71397910 23.90642310
[320,] 29.88094929 25.71397910
[321,] 26.88101699 29.88094929
[322,] 24.82221006 26.88101699
[323,] 26.42332679 24.82221006
[324,] 26.22023936 26.42332679
[325,] 20.35445311 26.22023936
[326,] 23.62103295 20.35445311
[327,] 32.73582930 23.62103295
[328,] 20.27360527 32.73582930
[329,] 26.20784752 20.27360527
[330,] 34.87054109 26.20784752
[331,] 32.51497020 34.87054109
[332,] 17.80867325 32.51497020
[333,] 28.02374686 17.80867325
[334,] 13.95415477 28.02374686
[335,] 18.73486711 13.95415477
[336,] 34.16637663 18.73486711
[337,] 17.91837252 34.16637663
[338,] 9.03291211 17.91837252
[339,] 8.79559809 9.03291211
[340,] 15.60603365 8.79559809
[341,] 16.82310130 15.60603365
[342,] -1.09260662 16.82310130
[343,] 18.69104192 -1.09260662
[344,] 23.61202247 18.69104192
[345,] 15.98315585 23.61202247
[346,] 14.99796670 15.98315585
[347,] 7.88862530 14.99796670
[348,] -7.23053828 7.88862530
[349,] -5.88760517 -7.23053828
[350,] -17.51499112 -5.88760517
[351,] -21.52646033 -17.51499112
[352,] 7.89976170 -21.52646033
[353,] -1.28893616 7.89976170
[354,] -20.56169481 -1.28893616
[355,] -10.17367611 -20.56169481
[356,] -4.56552095 -10.17367611
[357,] 9.94614526 -4.56552095
[358,] 1.15326964 9.94614526
[359,] -9.31996283 1.15326964
[360,] -5.47534282 -9.31996283
[361,] -6.35193062 -5.47534282
[362,] -10.50032391 -6.35193062
[363,] 12.35413361 -10.50032391
[364,] 3.47356182 12.35413361
[365,] 11.95849813 3.47356182
[366,] 8.78137389 11.95849813
[367,] 16.58541043 8.78137389
[368,] 23.57415674 16.58541043
[369,] 1.02543953 23.57415674
[370,] -2.13666008 1.02543953
[371,] 2.21612985 -2.13666008
[372,] -0.26280237 2.21612985
[373,] 2.07231582 -0.26280237
[374,] -9.52098047 2.07231582
[375,] 2.16612942 -9.52098047
[376,] -3.17398882 2.16612942
[377,] -9.89102263 -3.17398882
[378,] -3.81813506 -9.89102263
[379,] -17.05626264 -3.81813506
[380,] -29.91621931 -17.05626264
[381,] -13.75446658 -29.91621931
[382,] -6.77359596 -13.75446658
[383,] -12.47449852 -6.77359596
[384,] -2.07401732 -12.47449852
[385,] -0.07110060 -2.07401732
[386,] 4.93162552 -0.07110060
[387,] -16.43321832 4.93162552
[388,] -7.03134547 -16.43321832
[389,] -1.51925095 -7.03134547
[390,] -7.96804841 -1.51925095
[391,] 1.16034191 -7.96804841
[392,] 6.38713449 1.16034191
[393,] 0.16422015 6.38713449
[394,] -1.34336447 0.16422015
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 3.23425843 -1.42592399
2 3.18344870 3.23425843
3 2.95185561 3.18344870
4 1.67930913 2.95185561
5 -1.70765455 1.67930913
6 -2.91023559 -1.70765455
7 -7.89072587 -2.91023559
8 -1.91293774 -7.89072587
9 2.19082245 -1.91293774
10 -1.53297858 2.19082245
11 3.19917104 -1.53297858
12 6.80995373 3.19917104
13 8.78901673 6.80995373
14 7.95305626 8.78901673
15 5.05021989 7.95305626
16 0.33241518 5.05021989
17 3.27664105 0.33241518
18 -0.02741463 3.27664105
19 -0.73209746 -0.02741463
20 -1.71121981 -0.73209746
21 2.32748074 -1.71121981
22 2.66778117 2.32748074
23 -1.72234080 2.66778117
24 -1.05583719 -1.72234080
25 0.75185866 -1.05583719
26 0.65501013 0.75185866
27 0.40290060 0.65501013
28 1.15958993 0.40290060
29 2.03647996 1.15958993
30 -2.98206975 2.03647996
31 -4.25092416 -2.98206975
32 5.53831763 -4.25092416
33 7.82211518 5.53831763
34 4.56865299 7.82211518
35 3.00138919 4.56865299
36 3.20654203 3.00138919
37 6.85313486 3.20654203
38 2.30060276 6.85313486
39 2.62227681 2.30060276
40 -5.83323533 2.62227681
41 -1.64717961 -5.83323533
42 -6.91494875 -1.64717961
43 -7.98725250 -6.91494875
44 -6.23212855 -7.98725250
45 -8.87087130 -6.23212855
46 -7.68124397 -8.87087130
47 -3.67954067 -7.68124397
48 -14.36451169 -3.67954067
49 -8.84635313 -14.36451169
50 -3.81838975 -8.84635313
51 -0.91623661 -3.81838975
52 -7.72475176 -0.91623661
53 -9.39492884 -7.72475176
54 -2.16971593 -9.39492884
55 -6.72878531 -2.16971593
56 -10.39023300 -6.72878531
57 -5.45641906 -10.39023300
58 -0.21116189 -5.45641906
59 6.26897568 -0.21116189
60 4.21196441 6.26897568
61 6.25266328 4.21196441
62 6.41458785 6.25266328
63 4.71310225 6.41458785
64 2.62080351 4.71310225
65 -6.13095569 2.62080351
66 1.77687223 -6.13095569
67 5.24458487 1.77687223
68 8.32651181 5.24458487
69 6.57009898 8.32651181
70 10.83908599 6.57009898
71 5.02709680 10.83908599
72 6.84740039 5.02709680
73 1.06049472 6.84740039
74 -1.88814631 1.06049472
75 3.92746798 -1.88814631
76 3.40841999 3.92746798
77 6.71388913 3.40841999
78 10.27114686 6.71388913
79 7.71454766 10.27114686
80 17.17032831 7.71454766
81 21.22149446 17.17032831
82 11.23593829 21.22149446
83 9.98292078 11.23593829
84 10.74903181 9.98292078
85 10.80791721 10.74903181
86 10.94051946 10.80791721
87 11.25586961 10.94051946
88 6.11371571 11.25586961
89 9.28071323 6.11371571
90 14.06885902 9.28071323
91 11.47728669 14.06885902
92 11.76116736 11.47728669
93 16.57869475 11.76116736
94 17.68212207 16.57869475
95 18.21952991 17.68212207
96 16.64722306 18.21952991
97 14.55605472 16.64722306
98 18.33275842 14.55605472
99 12.86762949 18.33275842
100 12.58911433 12.86762949
101 14.63690882 12.58911433
102 16.10091580 14.63690882
103 6.62277183 16.10091580
104 9.93961815 6.62277183
105 14.78350222 9.93961815
106 13.55112209 14.78350222
107 10.08137172 13.55112209
108 14.74824694 10.08137172
109 14.66480700 14.74824694
110 13.30456746 14.66480700
111 12.66926091 13.30456746
112 4.91239800 12.66926091
113 5.00822237 4.91239800
114 5.91068459 5.00822237
115 10.60092115 5.91068459
116 -0.88566090 10.60092115
117 -2.24513048 -0.88566090
118 -4.34410322 -2.24513048
119 -7.43971478 -4.34410322
120 2.19817237 -7.43971478
121 1.50648758 2.19817237
122 -4.89382209 1.50648758
123 -5.34369280 -4.89382209
124 -10.86558258 -5.34369280
125 -9.61642094 -10.86558258
126 -14.44468556 -9.61642094
127 -13.07581615 -14.44468556
128 -7.82607430 -13.07581615
129 -14.06748123 -7.82607430
130 -14.34829563 -14.06748123
131 -4.09525795 -14.34829563
132 -2.14340960 -4.09525795
133 -0.02425550 -2.14340960
134 -1.33323537 -0.02425550
135 -7.36582400 -1.33323537
136 0.36258771 -7.36582400
137 6.56480610 0.36258771
138 6.03481910 6.56480610
139 7.05278406 6.03481910
140 -0.21829201 7.05278406
141 0.93731901 -0.21829201
142 4.86360450 0.93731901
143 6.31441974 4.86360450
144 5.44710241 6.31441974
145 9.49417433 5.44710241
146 10.75188997 9.49417433
147 13.20345654 10.75188997
148 17.97570557 13.20345654
149 9.64020014 17.97570557
150 9.69271610 9.64020014
151 10.39306014 9.69271610
152 3.04836170 10.39306014
153 1.73686825 3.04836170
154 -7.78373576 1.73686825
155 -3.49013248 -7.78373576
156 -5.92602891 -3.49013248
157 -1.23975395 -5.92602891
158 -0.81601591 -1.23975395
159 -4.58301205 -0.81601591
160 -3.26987496 -4.58301205
161 -10.69204312 -3.26987496
162 -7.08561971 -10.69204312
163 -10.81689514 -7.08561971
164 -14.38422040 -10.81689514
165 -12.20179000 -14.38422040
166 -14.44017616 -12.20179000
167 -1.83257890 -14.44017616
168 -3.18928869 -1.83257890
169 -8.33592564 -3.18928869
170 -10.73850691 -8.33592564
171 -4.90069115 -10.73850691
172 -9.32426595 -4.90069115
173 -5.01128337 -9.32426595
174 -1.02304648 -5.01128337
175 -2.33684125 -1.02304648
176 -10.92942474 -2.33684125
177 -12.21136451 -10.92942474
178 -2.74742533 -12.21136451
179 -4.06811749 -2.74742533
180 -0.13591392 -4.06811749
181 0.54101774 -0.13591392
182 5.75233936 0.54101774
183 0.28106414 5.75233936
184 -5.07613302 0.28106414
185 -4.15101910 -5.07613302
186 -3.36317479 -4.15101910
187 0.15306779 -3.36317479
188 -2.64543520 0.15306779
189 -3.50451222 -2.64543520
190 1.26726285 -3.50451222
191 -0.98747703 1.26726285
192 -5.31706596 -0.98747703
193 -9.76837457 -5.31706596
194 -17.60646638 -9.76837457
195 -19.37070725 -17.60646638
196 -15.65254787 -19.37070725
197 -13.95121754 -15.65254787
198 -18.94141950 -13.95121754
199 -24.05910076 -18.94141950
200 -24.16172160 -24.05910076
201 -23.42271957 -24.16172160
202 -23.80030418 -23.42271957
203 -23.88501129 -23.80030418
204 -20.12611221 -23.88501129
205 -30.41385220 -20.12611221
206 -14.81191123 -30.41385220
207 -21.72720139 -14.81191123
208 -16.90830602 -21.72720139
209 -14.51029657 -16.90830602
210 -14.36484772 -14.51029657
211 -19.48812604 -14.36484772
212 -21.19629020 -19.48812604
213 -24.53991499 -21.19629020
214 -7.60876386 -24.53991499
215 -12.60339626 -7.60876386
216 -12.27582698 -12.60339626
217 -13.96665649 -12.27582698
218 -12.58959756 -13.96665649
219 -15.63609364 -12.58959756
220 -16.46748794 -15.63609364
221 -13.83603374 -16.46748794
222 -16.92788795 -13.83603374
223 -20.66503637 -16.92788795
224 -15.99005726 -20.66503637
225 -11.38283135 -15.99005726
226 -12.49599206 -11.38283135
227 -7.03456927 -12.49599206
228 -9.51225821 -7.03456927
229 -14.62724292 -9.51225821
230 -11.09958103 -14.62724292
231 -7.41831594 -11.09958103
232 -2.86427440 -7.41831594
233 -7.15606637 -2.86427440
234 -6.35243100 -7.15606637
235 -5.81594067 -6.35243100
236 4.57252054 -5.81594067
237 1.21328231 4.57252054
238 1.40699471 1.21328231
239 -1.94399894 1.40699471
240 -1.34335651 -1.94399894
241 0.24348406 -1.34335651
242 2.12468180 0.24348406
243 1.94251852 2.12468180
244 3.26174816 1.94251852
245 6.16046805 3.26174816
246 5.72515271 6.16046805
247 6.02334902 5.72515271
248 0.92326849 6.02334902
249 -5.81447873 0.92326849
250 -2.76009323 -5.81447873
251 -8.24007495 -2.76009323
252 -8.43499223 -8.24007495
253 -2.07713973 -8.43499223
254 0.15558639 -2.07713973
255 4.17686786 0.15558639
256 3.14407364 4.17686786
257 -1.59486016 3.14407364
258 -2.46799042 -1.59486016
259 0.15006106 -2.46799042
260 2.27653577 0.15006106
261 -7.26959655 2.27653577
262 -9.45252591 -7.26959655
263 -2.92146292 -9.45252591
264 -5.31540563 -2.92146292
265 -2.79966351 -5.31540563
266 6.58636252 -2.79966351
267 4.66093211 6.58636252
268 -1.28589345 4.66093211
269 -3.94326609 -1.28589345
270 -1.59780086 -3.94326609
271 -5.93625089 -1.59780086
272 -2.06217623 -5.93625089
273 -3.32061750 -2.06217623
274 -1.69086629 -3.32061750
275 -13.54244652 -1.69086629
276 -13.41084591 -13.54244652
277 -11.65112620 -13.41084591
278 -10.92010607 -11.65112620
279 -19.35523500 -10.92010607
280 -15.01403525 -19.35523500
281 -13.21636464 -15.01403525
282 -13.22793375 -13.21636464
283 -9.72405386 -13.22793375
284 -13.54942997 -9.72405386
285 -12.53357121 -13.54942997
286 -17.55346478 -12.53357121
287 -20.97854350 -17.55346478
288 -24.36765333 -20.97854350
289 -14.06407991 -24.36765333
290 -12.15968515 -14.06407991
291 -12.33397977 -12.15968515
292 -10.09780689 -12.33397977
293 -7.05068550 -10.09780689
294 -4.38079636 -7.05068550
295 -10.24123290 -4.38079636
296 -11.93465070 -10.24123290
297 -13.58721440 -11.93465070
298 -4.40478263 -13.58721440
299 -0.39400016 -4.40478263
300 -6.04880996 -0.39400016
301 -5.91530666 -6.04880996
302 -6.98308060 -5.91530666
303 2.60885758 -6.98308060
304 3.92068126 2.60885758
305 0.71289965 3.92068126
306 15.48299917 0.71289965
307 16.88084026 15.48299917
308 15.69212688 16.88084026
309 16.77757668 15.69212688
310 20.09936813 16.77757668
311 23.29530134 20.09936813
312 18.18368856 23.29530134
313 16.93985603 18.18368856
314 21.15385821 16.93985603
315 17.52469794 21.15385821
316 21.85600518 17.52469794
317 17.28881014 21.85600518
318 23.90642310 17.28881014
319 25.71397910 23.90642310
320 29.88094929 25.71397910
321 26.88101699 29.88094929
322 24.82221006 26.88101699
323 26.42332679 24.82221006
324 26.22023936 26.42332679
325 20.35445311 26.22023936
326 23.62103295 20.35445311
327 32.73582930 23.62103295
328 20.27360527 32.73582930
329 26.20784752 20.27360527
330 34.87054109 26.20784752
331 32.51497020 34.87054109
332 17.80867325 32.51497020
333 28.02374686 17.80867325
334 13.95415477 28.02374686
335 18.73486711 13.95415477
336 34.16637663 18.73486711
337 17.91837252 34.16637663
338 9.03291211 17.91837252
339 8.79559809 9.03291211
340 15.60603365 8.79559809
341 16.82310130 15.60603365
342 -1.09260662 16.82310130
343 18.69104192 -1.09260662
344 23.61202247 18.69104192
345 15.98315585 23.61202247
346 14.99796670 15.98315585
347 7.88862530 14.99796670
348 -7.23053828 7.88862530
349 -5.88760517 -7.23053828
350 -17.51499112 -5.88760517
351 -21.52646033 -17.51499112
352 7.89976170 -21.52646033
353 -1.28893616 7.89976170
354 -20.56169481 -1.28893616
355 -10.17367611 -20.56169481
356 -4.56552095 -10.17367611
357 9.94614526 -4.56552095
358 1.15326964 9.94614526
359 -9.31996283 1.15326964
360 -5.47534282 -9.31996283
361 -6.35193062 -5.47534282
362 -10.50032391 -6.35193062
363 12.35413361 -10.50032391
364 3.47356182 12.35413361
365 11.95849813 3.47356182
366 8.78137389 11.95849813
367 16.58541043 8.78137389
368 23.57415674 16.58541043
369 1.02543953 23.57415674
370 -2.13666008 1.02543953
371 2.21612985 -2.13666008
372 -0.26280237 2.21612985
373 2.07231582 -0.26280237
374 -9.52098047 2.07231582
375 2.16612942 -9.52098047
376 -3.17398882 2.16612942
377 -9.89102263 -3.17398882
378 -3.81813506 -9.89102263
379 -17.05626264 -3.81813506
380 -29.91621931 -17.05626264
381 -13.75446658 -29.91621931
382 -6.77359596 -13.75446658
383 -12.47449852 -6.77359596
384 -2.07401732 -12.47449852
385 -0.07110060 -2.07401732
386 4.93162552 -0.07110060
387 -16.43321832 4.93162552
388 -7.03134547 -16.43321832
389 -1.51925095 -7.03134547
390 -7.96804841 -1.51925095
391 1.16034191 -7.96804841
392 6.38713449 1.16034191
393 0.16422015 6.38713449
394 -1.34336447 0.16422015
> plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
> lines(lowess(z))
> abline(lm(z))
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/7xj831228923628.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8bgce1228923628.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9tz8e1228923628.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10bx3a1228923628.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
+ myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ')
+ if (rownames(mysum$coefficients)[i] != '(Intercept)') {
+ myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
+ if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
+ }
+ }
> myeq <- paste(myeq, ' + e[t]')
> a<-table.row.start(a)
> a<-table.element(a, myeq)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/110lkz1228923628.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Variable',header=TRUE)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
> a<-table.element(a,'2-tail p-value',header=TRUE)
> a<-table.element(a,'1-tail p-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:k){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
+ a<-table.element(a,mysum$coefficients[i,1])
+ a<-table.element(a, round(mysum$coefficients[i,2],6))
+ a<-table.element(a, round(mysum$coefficients[i,3],4))
+ a<-table.element(a, round(mysum$coefficients[i,4],6))
+ a<-table.element(a, round(mysum$coefficients[i,4]/2,6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/12xk8l1228923628.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple R',1,TRUE)
> a<-table.element(a, sqrt(mysum$r.squared))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'R-squared',1,TRUE)
> a<-table.element(a, mysum$r.squared)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Adjusted R-squared',1,TRUE)
> a<-table.element(a, mysum$adj.r.squared)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (value)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[1])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[2])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[3])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'p-value',1,TRUE)
> a<-table.element(a, 1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
> a<-table.element(a, mysum$sigma)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a, sum(myerror*myerror))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/135yjw1228923629.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Time or Index', 1, TRUE)
> a<-table.element(a, 'Actuals', 1, TRUE)
> a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
> a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
> a<-table.row.end(a)
> for (i in 1:n) {
+ a<-table.row.start(a)
+ a<-table.element(a,i, 1, TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]-mysum$resid[i])
+ a<-table.element(a,mysum$resid[i])
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/14ucn71228923629.tab")
> if (n > n25) {
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'p-values',header=TRUE)
+ a<-table.element(a,'Alternative Hypothesis',3,header=TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'breakpoint index',header=TRUE)
+ a<-table.element(a,'greater',header=TRUE)
+ a<-table.element(a,'2-sided',header=TRUE)
+ a<-table.element(a,'less',header=TRUE)
+ a<-table.row.end(a)
+ for (mypoint in kp3:nmkm3) {
+ a<-table.row.start(a)
+ a<-table.element(a,mypoint,header=TRUE)
+ a<-table.element(a,gqarr[mypoint-kp3+1,1])
+ a<-table.element(a,gqarr[mypoint-kp3+1,2])
+ a<-table.element(a,gqarr[mypoint-kp3+1,3])
+ a<-table.row.end(a)
+ }
+ a<-table.end(a)
+ table.save(a,file="/var/www/html/rcomp/tmp/15qhwb1228923629.tab")
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'Description',header=TRUE)
+ a<-table.element(a,'# significant tests',header=TRUE)
+ a<-table.element(a,'% significant tests',header=TRUE)
+ a<-table.element(a,'OK/NOK',header=TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'1% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant1)
+ a<-table.element(a,numsignificant1/numgqtests)
+ if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'5% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant5)
+ a<-table.element(a,numsignificant5/numgqtests)
+ if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'10% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant10)
+ a<-table.element(a,numsignificant10/numgqtests)
+ if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.end(a)
+ table.save(a,file="/var/www/html/rcomp/tmp/16r9241228923629.tab")
+ }
>
> system("convert tmp/19w7t1228923628.ps tmp/19w7t1228923628.png")
> system("convert tmp/2s2d41228923628.ps tmp/2s2d41228923628.png")
> system("convert tmp/36kui1228923628.ps tmp/36kui1228923628.png")
> system("convert tmp/47m2c1228923628.ps tmp/47m2c1228923628.png")
> system("convert tmp/562o61228923628.ps tmp/562o61228923628.png")
> system("convert tmp/66t8h1228923628.ps tmp/66t8h1228923628.png")
> system("convert tmp/7xj831228923628.ps tmp/7xj831228923628.png")
> system("convert tmp/8bgce1228923628.ps tmp/8bgce1228923628.png")
> system("convert tmp/9tz8e1228923628.ps tmp/9tz8e1228923628.png")
> system("convert tmp/10bx3a1228923628.ps tmp/10bx3a1228923628.png")
>
>
> proc.time()
user system elapsed
11.472 2.056 12.598