R version 2.15.1 (2012-06-22) -- "Roasted Marshmallows"
Copyright (C) 2012 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i686-pc-linux-gnu (32-bit)
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> x <- array(list(87.28
+ ,255
+ ,87.28
+ ,280.2
+ ,87.09
+ ,299.9
+ ,86.92
+ ,339.2
+ ,87.59
+ ,374.2
+ ,90.72
+ ,393.5
+ ,90.69
+ ,389.2
+ ,90.3
+ ,381.7
+ ,89.55
+ ,375.2
+ ,88.94
+ ,369
+ ,88.41
+ ,357.4
+ ,87.82
+ ,352.1
+ ,87.07
+ ,346.5
+ ,86.82
+ ,342.9
+ ,86.4
+ ,340.3
+ ,86.02
+ ,328.3
+ ,85.66
+ ,322.9
+ ,85.32
+ ,314.3
+ ,85
+ ,308.9
+ ,84.67
+ ,294
+ ,83.94
+ ,285.6
+ ,82.83
+ ,281.2
+ ,81.95
+ ,280.3
+ ,81.19
+ ,278.8
+ ,80.48
+ ,274.5
+ ,78.86
+ ,270.4
+ ,69.47
+ ,263.4
+ ,68.77
+ ,259.9
+ ,70.06
+ ,258
+ ,73.95
+ ,262.7
+ ,75.8
+ ,284.7
+ ,77.79
+ ,311.3
+ ,81.57
+ ,322.1
+ ,83.07
+ ,327
+ ,84.34
+ ,331.3
+ ,85.1
+ ,333.3
+ ,85.25
+ ,321.4
+ ,84.26
+ ,327
+ ,83.63
+ ,320
+ ,86.44
+ ,314.7
+ ,85.3
+ ,316.7
+ ,84.1
+ ,314.4
+ ,83.36
+ ,321.3
+ ,82.48
+ ,318.2
+ ,81.58
+ ,307.2
+ ,80.47
+ ,301.3
+ ,79.34
+ ,287.5
+ ,82.13
+ ,277.7
+ ,81.69
+ ,274.4
+ ,80.7
+ ,258.8
+ ,79.88
+ ,253.3
+ ,79.16
+ ,251
+ ,78.38
+ ,248.4
+ ,77.42
+ ,249.5
+ ,76.47
+ ,246.1
+ ,75.46
+ ,244.5
+ ,74.48
+ ,243.6
+ ,78.27
+ ,244
+ ,80.7
+ ,240.8
+ ,79.91
+ ,249.8
+ ,78.75
+ ,248
+ ,77.78
+ ,259.4
+ ,81.14
+ ,260.5
+ ,81.08
+ ,260.8
+ ,80.03
+ ,261.3
+ ,78.91
+ ,259.5
+ ,78.01
+ ,256.6
+ ,76.9
+ ,257.9
+ ,75.97
+ ,256.5
+ ,81.93
+ ,254.2
+ ,80.27
+ ,253.3
+ ,78.67
+ ,253.8
+ ,77.42
+ ,255.5
+ ,76.16
+ ,257.1
+ ,74.7
+ ,257.3
+ ,76.39
+ ,253.2
+ ,76.04
+ ,252.8
+ ,74.65
+ ,252
+ ,73.29
+ ,250.7
+ ,71.79
+ ,252.2
+ ,74.39
+ ,250
+ ,74.91
+ ,251
+ ,74.54
+ ,253.4
+ ,73.08
+ ,251.2
+ ,72.75
+ ,255.6
+ ,71.32
+ ,261.1
+ ,70.38
+ ,258.9
+ ,70.35
+ ,259.9
+ ,70.01
+ ,261.2
+ ,69.36
+ ,264.7
+ ,67.77
+ ,267.1
+ ,69.26
+ ,266.4
+ ,69.8
+ ,267.7
+ ,68.38
+ ,268.6
+ ,67.62
+ ,267.5
+ ,68.39
+ ,268.5
+ ,66.95
+ ,268.5
+ ,65.21
+ ,270.5
+ ,66.64
+ ,270.9
+ ,63.45
+ ,270.1
+ ,60.66
+ ,269.3
+ ,62.34
+ ,269.8
+ ,60.32
+ ,270.1
+ ,58.64
+ ,264.9
+ ,60.46
+ ,263.7
+ ,58.59
+ ,264.8
+ ,61.87
+ ,263.7
+ ,61.85
+ ,255.9
+ ,67.44
+ ,276.2
+ ,77.06
+ ,360.1
+ ,91.74
+ ,380.5
+ ,93.15
+ ,373.7
+ ,94.15
+ ,369.8
+ ,93.11
+ ,366.6
+ ,91.51
+ ,359.3
+ ,89.96
+ ,345.8
+ ,88.16
+ ,326.2
+ ,86.98
+ ,324.5
+ ,88.03
+ ,328.1
+ ,86.24
+ ,327.5
+ ,84.65
+ ,324.4
+ ,83.23
+ ,316.5
+ ,81.7
+ ,310.9
+ ,80.25
+ ,301.5
+ ,78.8
+ ,291.7
+ ,77.51
+ ,290.4
+ ,76.2
+ ,287.4
+ ,75.04
+ ,277.7
+ ,74
+ ,281.6
+ ,75.49
+ ,288
+ ,77.14
+ ,276
+ ,76.15
+ ,272.9
+ ,76.27
+ ,283
+ ,78.19
+ ,283.3
+ ,76.49
+ ,276.8
+ ,77.31
+ ,284.5
+ ,76.65
+ ,282.7
+ ,74.99
+ ,281.2
+ ,73.51
+ ,287.4
+ ,72.07
+ ,283.1
+ ,70.59
+ ,284
+ ,71.96
+ ,285.5
+ ,76.29
+ ,289.2
+ ,74.86
+ ,292.5
+ ,74.93
+ ,296.4
+ ,71.9
+ ,305.2
+ ,71.01
+ ,303.9
+ ,77.47
+ ,311.5
+ ,75.78
+ ,316.3
+ ,76.6
+ ,316.7
+ ,76.07
+ ,322.5
+ ,74.57
+ ,317.1
+ ,73.02
+ ,309.8
+ ,72.65
+ ,303.8
+ ,73.16
+ ,290.3
+ ,71.53
+ ,293.7
+ ,69.78
+ ,291.7
+ ,67.98
+ ,296.5
+ ,69.96
+ ,289.1
+ ,72.16
+ ,288.5
+ ,70.47
+ ,293.8
+ ,68.86
+ ,297.7
+ ,67.37
+ ,305.4
+ ,65.87
+ ,302.7
+ ,72.16
+ ,302.5
+ ,71.34
+ ,303
+ ,69.93
+ ,294.5
+ ,68.44
+ ,294.1
+ ,67.16
+ ,294.5
+ ,66.01
+ ,297.1
+ ,67.25
+ ,289.4
+ ,70.91
+ ,292.4
+ ,69.75
+ ,287.9
+ ,68.59
+ ,286.6
+ ,67.48
+ ,280.5
+ ,66.31
+ ,272.4
+ ,64.81
+ ,269.2
+ ,66.58
+ ,270.6
+ ,65.97
+ ,267.3
+ ,64.7
+ ,262.5
+ ,64.7
+ ,266.8
+ ,60.94
+ ,268.8
+ ,59.08
+ ,263.1
+ ,58.42
+ ,261.2
+ ,57.77
+ ,266
+ ,57.11
+ ,262.5
+ ,53.31
+ ,265.2
+ ,49.96
+ ,261.3
+ ,49.4
+ ,253.7
+ ,48.84
+ ,249.2
+ ,48.3
+ ,239.1
+ ,47.74
+ ,236.4
+ ,47.24
+ ,235.2
+ ,46.76
+ ,245.2
+ ,46.29
+ ,246.2
+ ,48.9
+ ,247.7
+ ,49.23
+ ,251.4
+ ,48.53
+ ,253.3
+ ,48.03
+ ,254.8
+ ,54.34
+ ,250
+ ,53.79
+ ,249.3
+ ,53.24
+ ,241.5
+ ,52.96
+ ,243.3
+ ,52.17
+ ,248
+ ,51.7
+ ,253
+ ,58.55
+ ,252.9
+ ,78.2
+ ,251.5
+ ,77.03
+ ,251.6
+ ,76.19
+ ,253.5
+ ,77.15
+ ,259.8
+ ,75.87
+ ,334.1
+ ,95.47
+ ,448
+ ,109.67
+ ,445.8
+ ,112.28
+ ,445
+ ,112.01
+ ,448.2
+ ,107.93
+ ,438.2
+ ,105.96
+ ,439.8
+ ,105.06
+ ,423.4
+ ,102.98
+ ,410.8
+ ,102.2
+ ,408.4
+ ,105.23
+ ,406.7
+ ,101.85
+ ,405.9
+ ,99.89
+ ,402.7
+ ,96.23
+ ,405.1
+ ,94.76
+ ,399.6
+ ,91.51
+ ,386.5
+ ,91.63
+ ,381.4
+ ,91.54
+ ,375.2
+ ,85.23
+ ,357.7
+ ,87.83
+ ,359
+ ,87.38
+ ,355
+ ,84.44
+ ,352.7
+ ,85.19
+ ,344.4
+ ,84.03
+ ,343.8
+ ,86.73
+ ,338
+ ,102.52
+ ,339
+ ,104.45
+ ,333.3
+ ,106.98
+ ,334.4
+ ,107.02
+ ,328.3
+ ,99.26
+ ,330.7
+ ,94.45
+ ,330
+ ,113.44
+ ,331.6
+ ,157.33
+ ,351.2
+ ,147.38
+ ,389.4
+ ,171.89
+ ,410.9
+ ,171.95
+ ,442.8
+ ,132.71
+ ,462.8
+ ,126.02
+ ,466.9
+ ,121.18
+ ,461.7
+ ,115.45
+ ,439.2
+ ,110.48
+ ,430.3
+ ,117.85
+ ,416.1
+ ,117.63
+ ,402.5
+ ,124.65
+ ,397.3
+ ,109.59
+ ,403.3
+ ,111.27
+ ,395.9
+ ,99.78
+ ,387.8
+ ,98.21
+ ,378.6
+ ,99.2
+ ,377.1
+ ,97.97
+ ,370.4
+ ,89.55
+ ,362
+ ,87.91
+ ,350.3
+ ,93.34
+ ,348.2
+ ,94.42
+ ,344.6
+ ,93.2
+ ,343.5
+ ,90.29
+ ,342.8
+ ,91.46
+ ,347.6
+ ,89.98
+ ,346.6
+ ,88.35
+ ,349.5
+ ,88.41
+ ,342.1
+ ,82.44
+ ,342
+ ,79.89
+ ,342.8
+ ,75.69
+ ,339.3
+ ,75.66
+ ,348.2
+ ,84.5
+ ,333.7
+ ,96.73
+ ,334.7
+ ,87.48
+ ,354
+ ,82.39
+ ,367.7
+ ,83.48
+ ,363.3
+ ,79.31
+ ,358.4
+ ,78.16
+ ,353.1
+ ,72.77
+ ,343.1
+ ,72.45
+ ,344.6
+ ,68.46
+ ,344.4
+ ,67.62
+ ,333.9
+ ,68.76
+ ,331.7
+ ,70.07
+ ,324.3
+ ,68.55
+ ,321.2
+ ,65.3
+ ,322.4
+ ,58.96
+ ,321.7
+ ,59.17
+ ,320.5
+ ,62.37
+ ,312.8
+ ,66.28
+ ,309.7
+ ,55.62
+ ,315.6
+ ,55.23
+ ,309.7
+ ,55.85
+ ,304.6
+ ,56.75
+ ,302.5
+ ,50.89
+ ,301.5
+ ,53.88
+ ,298.8
+ ,52.95
+ ,291.3
+ ,55.08
+ ,293.6
+ ,53.61
+ ,294.6
+ ,58.78
+ ,285.9
+ ,61.85
+ ,297.6
+ ,55.91
+ ,301.1
+ ,53.32
+ ,293.8
+ ,46.41
+ ,297.7
+ ,44.57
+ ,292.9
+ ,50
+ ,292.1
+ ,50
+ ,287.2
+ ,53.36
+ ,288.2
+ ,46.23
+ ,283.8
+ ,50.45
+ ,299.9
+ ,49.07
+ ,292.4
+ ,45.85
+ ,293.3
+ ,48.45
+ ,300.8
+ ,49.96
+ ,293.7
+ ,46.53
+ ,293.1
+ ,50.51
+ ,294.4
+ ,47.58
+ ,292.1
+ ,48.05
+ ,291.9
+ ,46.84
+ ,282.5
+ ,47.67
+ ,277.9
+ ,49.16
+ ,287.5
+ ,55.54
+ ,289.2
+ ,55.82
+ ,285.6
+ ,58.22
+ ,293.2
+ ,56.19
+ ,290.8
+ ,57.77
+ ,283.1
+ ,63.19
+ ,275
+ ,54.76
+ ,287.8
+ ,55.74
+ ,287.8
+ ,62.54
+ ,287.4
+ ,61.39
+ ,284
+ ,69.6
+ ,277.8
+ ,79.23
+ ,277.6
+ ,80
+ ,304.9
+ ,93.68
+ ,294
+ ,107.63
+ ,300.9
+ ,100.18
+ ,324
+ ,97.3
+ ,332.9
+ ,90.45
+ ,341.6
+ ,80.64
+ ,333.4
+ ,80.58
+ ,348.2
+ ,75.82
+ ,344.7
+ ,85.59
+ ,344.7
+ ,89.35
+ ,329.3
+ ,89.42
+ ,323.5
+ ,104.73
+ ,323.2
+ ,95.32
+ ,317.4
+ ,89.27
+ ,330.1
+ ,90.44
+ ,329.2
+ ,86.97
+ ,334.9
+ ,79.98
+ ,315.8
+ ,81.22
+ ,315.4
+ ,87.35
+ ,319.6
+ ,83.64
+ ,317.3
+ ,82.22
+ ,313.8
+ ,94.4
+ ,315.8
+ ,102.18
+ ,311.3)
+ ,dim=c(2
+ ,360)
+ ,dimnames=list(c('Colombia'
+ ,'USA')
+ ,1:360))
> y <- array(NA,dim=c(2,360),dimnames=list(c('Colombia','USA'),1:360))
> 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 = '2'
> library(lattice)
> library(lmtest)
Loading required package: zoo
Attaching package: 'zoo'
The following object(s) are masked from 'package:base':
as.Date, 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
USA Colombia M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 255.0 87.28 1 0 0 0 0 0 0 0 0 0 0 1
2 280.2 87.28 0 1 0 0 0 0 0 0 0 0 0 2
3 299.9 87.09 0 0 1 0 0 0 0 0 0 0 0 3
4 339.2 86.92 0 0 0 1 0 0 0 0 0 0 0 4
5 374.2 87.59 0 0 0 0 1 0 0 0 0 0 0 5
6 393.5 90.72 0 0 0 0 0 1 0 0 0 0 0 6
7 389.2 90.69 0 0 0 0 0 0 1 0 0 0 0 7
8 381.7 90.30 0 0 0 0 0 0 0 1 0 0 0 8
9 375.2 89.55 0 0 0 0 0 0 0 0 1 0 0 9
10 369.0 88.94 0 0 0 0 0 0 0 0 0 1 0 10
11 357.4 88.41 0 0 0 0 0 0 0 0 0 0 1 11
12 352.1 87.82 0 0 0 0 0 0 0 0 0 0 0 12
13 346.5 87.07 1 0 0 0 0 0 0 0 0 0 0 13
14 342.9 86.82 0 1 0 0 0 0 0 0 0 0 0 14
15 340.3 86.40 0 0 1 0 0 0 0 0 0 0 0 15
16 328.3 86.02 0 0 0 1 0 0 0 0 0 0 0 16
17 322.9 85.66 0 0 0 0 1 0 0 0 0 0 0 17
18 314.3 85.32 0 0 0 0 0 1 0 0 0 0 0 18
19 308.9 85.00 0 0 0 0 0 0 1 0 0 0 0 19
20 294.0 84.67 0 0 0 0 0 0 0 1 0 0 0 20
21 285.6 83.94 0 0 0 0 0 0 0 0 1 0 0 21
22 281.2 82.83 0 0 0 0 0 0 0 0 0 1 0 22
23 280.3 81.95 0 0 0 0 0 0 0 0 0 0 1 23
24 278.8 81.19 0 0 0 0 0 0 0 0 0 0 0 24
25 274.5 80.48 1 0 0 0 0 0 0 0 0 0 0 25
26 270.4 78.86 0 1 0 0 0 0 0 0 0 0 0 26
27 263.4 69.47 0 0 1 0 0 0 0 0 0 0 0 27
28 259.9 68.77 0 0 0 1 0 0 0 0 0 0 0 28
29 258.0 70.06 0 0 0 0 1 0 0 0 0 0 0 29
30 262.7 73.95 0 0 0 0 0 1 0 0 0 0 0 30
31 284.7 75.80 0 0 0 0 0 0 1 0 0 0 0 31
32 311.3 77.79 0 0 0 0 0 0 0 1 0 0 0 32
33 322.1 81.57 0 0 0 0 0 0 0 0 1 0 0 33
34 327.0 83.07 0 0 0 0 0 0 0 0 0 1 0 34
35 331.3 84.34 0 0 0 0 0 0 0 0 0 0 1 35
36 333.3 85.10 0 0 0 0 0 0 0 0 0 0 0 36
37 321.4 85.25 1 0 0 0 0 0 0 0 0 0 0 37
38 327.0 84.26 0 1 0 0 0 0 0 0 0 0 0 38
39 320.0 83.63 0 0 1 0 0 0 0 0 0 0 0 39
40 314.7 86.44 0 0 0 1 0 0 0 0 0 0 0 40
41 316.7 85.30 0 0 0 0 1 0 0 0 0 0 0 41
42 314.4 84.10 0 0 0 0 0 1 0 0 0 0 0 42
43 321.3 83.36 0 0 0 0 0 0 1 0 0 0 0 43
44 318.2 82.48 0 0 0 0 0 0 0 1 0 0 0 44
45 307.2 81.58 0 0 0 0 0 0 0 0 1 0 0 45
46 301.3 80.47 0 0 0 0 0 0 0 0 0 1 0 46
47 287.5 79.34 0 0 0 0 0 0 0 0 0 0 1 47
48 277.7 82.13 0 0 0 0 0 0 0 0 0 0 0 48
49 274.4 81.69 1 0 0 0 0 0 0 0 0 0 0 49
50 258.8 80.70 0 1 0 0 0 0 0 0 0 0 0 50
51 253.3 79.88 0 0 1 0 0 0 0 0 0 0 0 51
52 251.0 79.16 0 0 0 1 0 0 0 0 0 0 0 52
53 248.4 78.38 0 0 0 0 1 0 0 0 0 0 0 53
54 249.5 77.42 0 0 0 0 0 1 0 0 0 0 0 54
55 246.1 76.47 0 0 0 0 0 0 1 0 0 0 0 55
56 244.5 75.46 0 0 0 0 0 0 0 1 0 0 0 56
57 243.6 74.48 0 0 0 0 0 0 0 0 1 0 0 57
58 244.0 78.27 0 0 0 0 0 0 0 0 0 1 0 58
59 240.8 80.70 0 0 0 0 0 0 0 0 0 0 1 59
60 249.8 79.91 0 0 0 0 0 0 0 0 0 0 0 60
61 248.0 78.75 1 0 0 0 0 0 0 0 0 0 0 61
62 259.4 77.78 0 1 0 0 0 0 0 0 0 0 0 62
63 260.5 81.14 0 0 1 0 0 0 0 0 0 0 0 63
64 260.8 81.08 0 0 0 1 0 0 0 0 0 0 0 64
65 261.3 80.03 0 0 0 0 1 0 0 0 0 0 0 65
66 259.5 78.91 0 0 0 0 0 1 0 0 0 0 0 66
67 256.6 78.01 0 0 0 0 0 0 1 0 0 0 0 67
68 257.9 76.90 0 0 0 0 0 0 0 1 0 0 0 68
69 256.5 75.97 0 0 0 0 0 0 0 0 1 0 0 69
70 254.2 81.93 0 0 0 0 0 0 0 0 0 1 0 70
71 253.3 80.27 0 0 0 0 0 0 0 0 0 0 1 71
72 253.8 78.67 0 0 0 0 0 0 0 0 0 0 0 72
73 255.5 77.42 1 0 0 0 0 0 0 0 0 0 0 73
74 257.1 76.16 0 1 0 0 0 0 0 0 0 0 0 74
75 257.3 74.70 0 0 1 0 0 0 0 0 0 0 0 75
76 253.2 76.39 0 0 0 1 0 0 0 0 0 0 0 76
77 252.8 76.04 0 0 0 0 1 0 0 0 0 0 0 77
78 252.0 74.65 0 0 0 0 0 1 0 0 0 0 0 78
79 250.7 73.29 0 0 0 0 0 0 1 0 0 0 0 79
80 252.2 71.79 0 0 0 0 0 0 0 1 0 0 0 80
81 250.0 74.39 0 0 0 0 0 0 0 0 1 0 0 81
82 251.0 74.91 0 0 0 0 0 0 0 0 0 1 0 82
83 253.4 74.54 0 0 0 0 0 0 0 0 0 0 1 83
84 251.2 73.08 0 0 0 0 0 0 0 0 0 0 0 84
85 255.6 72.75 1 0 0 0 0 0 0 0 0 0 0 85
86 261.1 71.32 0 1 0 0 0 0 0 0 0 0 0 86
87 258.9 70.38 0 0 1 0 0 0 0 0 0 0 0 87
88 259.9 70.35 0 0 0 1 0 0 0 0 0 0 0 88
89 261.2 70.01 0 0 0 0 1 0 0 0 0 0 0 89
90 264.7 69.36 0 0 0 0 0 1 0 0 0 0 0 90
91 267.1 67.77 0 0 0 0 0 0 1 0 0 0 0 91
92 266.4 69.26 0 0 0 0 0 0 0 1 0 0 0 92
93 267.7 69.80 0 0 0 0 0 0 0 0 1 0 0 93
94 268.6 68.38 0 0 0 0 0 0 0 0 0 1 0 94
95 267.5 67.62 0 0 0 0 0 0 0 0 0 0 1 95
96 268.5 68.39 0 0 0 0 0 0 0 0 0 0 0 96
97 268.5 66.95 1 0 0 0 0 0 0 0 0 0 0 97
98 270.5 65.21 0 1 0 0 0 0 0 0 0 0 0 98
99 270.9 66.64 0 0 1 0 0 0 0 0 0 0 0 99
100 270.1 63.45 0 0 0 1 0 0 0 0 0 0 0 100
101 269.3 60.66 0 0 0 0 1 0 0 0 0 0 0 101
102 269.8 62.34 0 0 0 0 0 1 0 0 0 0 0 102
103 270.1 60.32 0 0 0 0 0 0 1 0 0 0 0 103
104 264.9 58.64 0 0 0 0 0 0 0 1 0 0 0 104
105 263.7 60.46 0 0 0 0 0 0 0 0 1 0 0 105
106 264.8 58.59 0 0 0 0 0 0 0 0 0 1 0 106
107 263.7 61.87 0 0 0 0 0 0 0 0 0 0 1 107
108 255.9 61.85 0 0 0 0 0 0 0 0 0 0 0 108
109 276.2 67.44 1 0 0 0 0 0 0 0 0 0 0 109
110 360.1 77.06 0 1 0 0 0 0 0 0 0 0 0 110
111 380.5 91.74 0 0 1 0 0 0 0 0 0 0 0 111
112 373.7 93.15 0 0 0 1 0 0 0 0 0 0 0 112
113 369.8 94.15 0 0 0 0 1 0 0 0 0 0 0 113
114 366.6 93.11 0 0 0 0 0 1 0 0 0 0 0 114
115 359.3 91.51 0 0 0 0 0 0 1 0 0 0 0 115
116 345.8 89.96 0 0 0 0 0 0 0 1 0 0 0 116
117 326.2 88.16 0 0 0 0 0 0 0 0 1 0 0 117
118 324.5 86.98 0 0 0 0 0 0 0 0 0 1 0 118
119 328.1 88.03 0 0 0 0 0 0 0 0 0 0 1 119
120 327.5 86.24 0 0 0 0 0 0 0 0 0 0 0 120
121 324.4 84.65 1 0 0 0 0 0 0 0 0 0 0 121
122 316.5 83.23 0 1 0 0 0 0 0 0 0 0 0 122
123 310.9 81.70 0 0 1 0 0 0 0 0 0 0 0 123
124 301.5 80.25 0 0 0 1 0 0 0 0 0 0 0 124
125 291.7 78.80 0 0 0 0 1 0 0 0 0 0 0 125
126 290.4 77.51 0 0 0 0 0 1 0 0 0 0 0 126
127 287.4 76.20 0 0 0 0 0 0 1 0 0 0 0 127
128 277.7 75.04 0 0 0 0 0 0 0 1 0 0 0 128
129 281.6 74.00 0 0 0 0 0 0 0 0 1 0 0 129
130 288.0 75.49 0 0 0 0 0 0 0 0 0 1 0 130
131 276.0 77.14 0 0 0 0 0 0 0 0 0 0 1 131
132 272.9 76.15 0 0 0 0 0 0 0 0 0 0 0 132
133 283.0 76.27 1 0 0 0 0 0 0 0 0 0 0 133
134 283.3 78.19 0 1 0 0 0 0 0 0 0 0 0 134
135 276.8 76.49 0 0 1 0 0 0 0 0 0 0 0 135
136 284.5 77.31 0 0 0 1 0 0 0 0 0 0 0 136
137 282.7 76.65 0 0 0 0 1 0 0 0 0 0 0 137
138 281.2 74.99 0 0 0 0 0 1 0 0 0 0 0 138
139 287.4 73.51 0 0 0 0 0 0 1 0 0 0 0 139
140 283.1 72.07 0 0 0 0 0 0 0 1 0 0 0 140
141 284.0 70.59 0 0 0 0 0 0 0 0 1 0 0 141
142 285.5 71.96 0 0 0 0 0 0 0 0 0 1 0 142
143 289.2 76.29 0 0 0 0 0 0 0 0 0 0 1 143
144 292.5 74.86 0 0 0 0 0 0 0 0 0 0 0 144
145 296.4 74.93 1 0 0 0 0 0 0 0 0 0 0 145
146 305.2 71.90 0 1 0 0 0 0 0 0 0 0 0 146
147 303.9 71.01 0 0 1 0 0 0 0 0 0 0 0 147
148 311.5 77.47 0 0 0 1 0 0 0 0 0 0 0 148
149 316.3 75.78 0 0 0 0 1 0 0 0 0 0 0 149
150 316.7 76.60 0 0 0 0 0 1 0 0 0 0 0 150
151 322.5 76.07 0 0 0 0 0 0 1 0 0 0 0 151
152 317.1 74.57 0 0 0 0 0 0 0 1 0 0 0 152
153 309.8 73.02 0 0 0 0 0 0 0 0 1 0 0 153
154 303.8 72.65 0 0 0 0 0 0 0 0 0 1 0 154
155 290.3 73.16 0 0 0 0 0 0 0 0 0 0 1 155
156 293.7 71.53 0 0 0 0 0 0 0 0 0 0 0 156
157 291.7 69.78 1 0 0 0 0 0 0 0 0 0 0 157
158 296.5 67.98 0 1 0 0 0 0 0 0 0 0 0 158
159 289.1 69.96 0 0 1 0 0 0 0 0 0 0 0 159
160 288.5 72.16 0 0 0 1 0 0 0 0 0 0 0 160
161 293.8 70.47 0 0 0 0 1 0 0 0 0 0 0 161
162 297.7 68.86 0 0 0 0 0 1 0 0 0 0 0 162
163 305.4 67.37 0 0 0 0 0 0 1 0 0 0 0 163
164 302.7 65.87 0 0 0 0 0 0 0 1 0 0 0 164
165 302.5 72.16 0 0 0 0 0 0 0 0 1 0 0 165
166 303.0 71.34 0 0 0 0 0 0 0 0 0 1 0 166
167 294.5 69.93 0 0 0 0 0 0 0 0 0 0 1 167
168 294.1 68.44 0 0 0 0 0 0 0 0 0 0 0 168
169 294.5 67.16 1 0 0 0 0 0 0 0 0 0 0 169
170 297.1 66.01 0 1 0 0 0 0 0 0 0 0 0 170
171 289.4 67.25 0 0 1 0 0 0 0 0 0 0 0 171
172 292.4 70.91 0 0 0 1 0 0 0 0 0 0 0 172
173 287.9 69.75 0 0 0 0 1 0 0 0 0 0 0 173
174 286.6 68.59 0 0 0 0 0 1 0 0 0 0 0 174
175 280.5 67.48 0 0 0 0 0 0 1 0 0 0 0 175
176 272.4 66.31 0 0 0 0 0 0 0 1 0 0 0 176
177 269.2 64.81 0 0 0 0 0 0 0 0 1 0 0 177
178 270.6 66.58 0 0 0 0 0 0 0 0 0 1 0 178
179 267.3 65.97 0 0 0 0 0 0 0 0 0 0 1 179
180 262.5 64.70 0 0 0 0 0 0 0 0 0 0 0 180
181 266.8 64.70 1 0 0 0 0 0 0 0 0 0 0 181
182 268.8 60.94 0 1 0 0 0 0 0 0 0 0 0 182
183 263.1 59.08 0 0 1 0 0 0 0 0 0 0 0 183
184 261.2 58.42 0 0 0 1 0 0 0 0 0 0 0 184
185 266.0 57.77 0 0 0 0 1 0 0 0 0 0 0 185
186 262.5 57.11 0 0 0 0 0 1 0 0 0 0 0 186
187 265.2 53.31 0 0 0 0 0 0 1 0 0 0 0 187
188 261.3 49.96 0 0 0 0 0 0 0 1 0 0 0 188
189 253.7 49.40 0 0 0 0 0 0 0 0 1 0 0 189
190 249.2 48.84 0 0 0 0 0 0 0 0 0 1 0 190
191 239.1 48.30 0 0 0 0 0 0 0 0 0 0 1 191
192 236.4 47.74 0 0 0 0 0 0 0 0 0 0 0 192
193 235.2 47.24 1 0 0 0 0 0 0 0 0 0 0 193
194 245.2 46.76 0 1 0 0 0 0 0 0 0 0 0 194
195 246.2 46.29 0 0 1 0 0 0 0 0 0 0 0 195
196 247.7 48.90 0 0 0 1 0 0 0 0 0 0 0 196
197 251.4 49.23 0 0 0 0 1 0 0 0 0 0 0 197
198 253.3 48.53 0 0 0 0 0 1 0 0 0 0 0 198
199 254.8 48.03 0 0 0 0 0 0 1 0 0 0 0 199
200 250.0 54.34 0 0 0 0 0 0 0 1 0 0 0 200
201 249.3 53.79 0 0 0 0 0 0 0 0 1 0 0 201
202 241.5 53.24 0 0 0 0 0 0 0 0 0 1 0 202
203 243.3 52.96 0 0 0 0 0 0 0 0 0 0 1 203
204 248.0 52.17 0 0 0 0 0 0 0 0 0 0 0 204
205 253.0 51.70 1 0 0 0 0 0 0 0 0 0 0 205
206 252.9 58.55 0 1 0 0 0 0 0 0 0 0 0 206
207 251.5 78.20 0 0 1 0 0 0 0 0 0 0 0 207
208 251.6 77.03 0 0 0 1 0 0 0 0 0 0 0 208
209 253.5 76.19 0 0 0 0 1 0 0 0 0 0 0 209
210 259.8 77.15 0 0 0 0 0 1 0 0 0 0 0 210
211 334.1 75.87 0 0 0 0 0 0 1 0 0 0 0 211
212 448.0 95.47 0 0 0 0 0 0 0 1 0 0 0 212
213 445.8 109.67 0 0 0 0 0 0 0 0 1 0 0 213
214 445.0 112.28 0 0 0 0 0 0 0 0 0 1 0 214
215 448.2 112.01 0 0 0 0 0 0 0 0 0 0 1 215
216 438.2 107.93 0 0 0 0 0 0 0 0 0 0 0 216
217 439.8 105.96 1 0 0 0 0 0 0 0 0 0 0 217
218 423.4 105.06 0 1 0 0 0 0 0 0 0 0 0 218
219 410.8 102.98 0 0 1 0 0 0 0 0 0 0 0 219
220 408.4 102.20 0 0 0 1 0 0 0 0 0 0 0 220
221 406.7 105.23 0 0 0 0 1 0 0 0 0 0 0 221
222 405.9 101.85 0 0 0 0 0 1 0 0 0 0 0 222
223 402.7 99.89 0 0 0 0 0 0 1 0 0 0 0 223
224 405.1 96.23 0 0 0 0 0 0 0 1 0 0 0 224
225 399.6 94.76 0 0 0 0 0 0 0 0 1 0 0 225
226 386.5 91.51 0 0 0 0 0 0 0 0 0 1 0 226
227 381.4 91.63 0 0 0 0 0 0 0 0 0 0 1 227
228 375.2 91.54 0 0 0 0 0 0 0 0 0 0 0 228
229 357.7 85.23 1 0 0 0 0 0 0 0 0 0 0 229
230 359.0 87.83 0 1 0 0 0 0 0 0 0 0 0 230
231 355.0 87.38 0 0 1 0 0 0 0 0 0 0 0 231
232 352.7 84.44 0 0 0 1 0 0 0 0 0 0 0 232
233 344.4 85.19 0 0 0 0 1 0 0 0 0 0 0 233
234 343.8 84.03 0 0 0 0 0 1 0 0 0 0 0 234
235 338.0 86.73 0 0 0 0 0 0 1 0 0 0 0 235
236 339.0 102.52 0 0 0 0 0 0 0 1 0 0 0 236
237 333.3 104.45 0 0 0 0 0 0 0 0 1 0 0 237
238 334.4 106.98 0 0 0 0 0 0 0 0 0 1 0 238
239 328.3 107.02 0 0 0 0 0 0 0 0 0 0 1 239
240 330.7 99.26 0 0 0 0 0 0 0 0 0 0 0 240
241 330.0 94.45 1 0 0 0 0 0 0 0 0 0 0 241
242 331.6 113.44 0 1 0 0 0 0 0 0 0 0 0 242
243 351.2 157.33 0 0 1 0 0 0 0 0 0 0 0 243
244 389.4 147.38 0 0 0 1 0 0 0 0 0 0 0 244
245 410.9 171.89 0 0 0 0 1 0 0 0 0 0 0 245
246 442.8 171.95 0 0 0 0 0 1 0 0 0 0 0 246
247 462.8 132.71 0 0 0 0 0 0 1 0 0 0 0 247
248 466.9 126.02 0 0 0 0 0 0 0 1 0 0 0 248
249 461.7 121.18 0 0 0 0 0 0 0 0 1 0 0 249
250 439.2 115.45 0 0 0 0 0 0 0 0 0 1 0 250
251 430.3 110.48 0 0 0 0 0 0 0 0 0 0 1 251
252 416.1 117.85 0 0 0 0 0 0 0 0 0 0 0 252
253 402.5 117.63 1 0 0 0 0 0 0 0 0 0 0 253
254 397.3 124.65 0 1 0 0 0 0 0 0 0 0 0 254
255 403.3 109.59 0 0 1 0 0 0 0 0 0 0 0 255
256 395.9 111.27 0 0 0 1 0 0 0 0 0 0 0 256
257 387.8 99.78 0 0 0 0 1 0 0 0 0 0 0 257
258 378.6 98.21 0 0 0 0 0 1 0 0 0 0 0 258
259 377.1 99.20 0 0 0 0 0 0 1 0 0 0 0 259
260 370.4 97.97 0 0 0 0 0 0 0 1 0 0 0 260
261 362.0 89.55 0 0 0 0 0 0 0 0 1 0 0 261
262 350.3 87.91 0 0 0 0 0 0 0 0 0 1 0 262
263 348.2 93.34 0 0 0 0 0 0 0 0 0 0 1 263
264 344.6 94.42 0 0 0 0 0 0 0 0 0 0 0 264
265 343.5 93.20 1 0 0 0 0 0 0 0 0 0 0 265
266 342.8 90.29 0 1 0 0 0 0 0 0 0 0 0 266
267 347.6 91.46 0 0 1 0 0 0 0 0 0 0 0 267
268 346.6 89.98 0 0 0 1 0 0 0 0 0 0 0 268
269 349.5 88.35 0 0 0 0 1 0 0 0 0 0 0 269
270 342.1 88.41 0 0 0 0 0 1 0 0 0 0 0 270
271 342.0 82.44 0 0 0 0 0 0 1 0 0 0 0 271
272 342.8 79.89 0 0 0 0 0 0 0 1 0 0 0 272
273 339.3 75.69 0 0 0 0 0 0 0 0 1 0 0 273
274 348.2 75.66 0 0 0 0 0 0 0 0 0 1 0 274
275 333.7 84.50 0 0 0 0 0 0 0 0 0 0 1 275
276 334.7 96.73 0 0 0 0 0 0 0 0 0 0 0 276
277 354.0 87.48 1 0 0 0 0 0 0 0 0 0 0 277
278 367.7 82.39 0 1 0 0 0 0 0 0 0 0 0 278
279 363.3 83.48 0 0 1 0 0 0 0 0 0 0 0 279
280 358.4 79.31 0 0 0 1 0 0 0 0 0 0 0 280
281 353.1 78.16 0 0 0 0 1 0 0 0 0 0 0 281
282 343.1 72.77 0 0 0 0 0 1 0 0 0 0 0 282
283 344.6 72.45 0 0 0 0 0 0 1 0 0 0 0 283
284 344.4 68.46 0 0 0 0 0 0 0 1 0 0 0 284
285 333.9 67.62 0 0 0 0 0 0 0 0 1 0 0 285
286 331.7 68.76 0 0 0 0 0 0 0 0 0 1 0 286
287 324.3 70.07 0 0 0 0 0 0 0 0 0 0 1 287
288 321.2 68.55 0 0 0 0 0 0 0 0 0 0 0 288
289 322.4 65.30 1 0 0 0 0 0 0 0 0 0 0 289
290 321.7 58.96 0 1 0 0 0 0 0 0 0 0 0 290
291 320.5 59.17 0 0 1 0 0 0 0 0 0 0 0 291
292 312.8 62.37 0 0 0 1 0 0 0 0 0 0 0 292
293 309.7 66.28 0 0 0 0 1 0 0 0 0 0 0 293
294 315.6 55.62 0 0 0 0 0 1 0 0 0 0 0 294
295 309.7 55.23 0 0 0 0 0 0 1 0 0 0 0 295
296 304.6 55.85 0 0 0 0 0 0 0 1 0 0 0 296
297 302.5 56.75 0 0 0 0 0 0 0 0 1 0 0 297
298 301.5 50.89 0 0 0 0 0 0 0 0 0 1 0 298
299 298.8 53.88 0 0 0 0 0 0 0 0 0 0 1 299
300 291.3 52.95 0 0 0 0 0 0 0 0 0 0 0 300
301 293.6 55.08 1 0 0 0 0 0 0 0 0 0 0 301
302 294.6 53.61 0 1 0 0 0 0 0 0 0 0 0 302
303 285.9 58.78 0 0 1 0 0 0 0 0 0 0 0 303
304 297.6 61.85 0 0 0 1 0 0 0 0 0 0 0 304
305 301.1 55.91 0 0 0 0 1 0 0 0 0 0 0 305
306 293.8 53.32 0 0 0 0 0 1 0 0 0 0 0 306
307 297.7 46.41 0 0 0 0 0 0 1 0 0 0 0 307
308 292.9 44.57 0 0 0 0 0 0 0 1 0 0 0 308
309 292.1 50.00 0 0 0 0 0 0 0 0 1 0 0 309
310 287.2 50.00 0 0 0 0 0 0 0 0 0 1 0 310
311 288.2 53.36 0 0 0 0 0 0 0 0 0 0 1 311
312 283.8 46.23 0 0 0 0 0 0 0 0 0 0 0 312
313 299.9 50.45 1 0 0 0 0 0 0 0 0 0 0 313
314 292.4 49.07 0 1 0 0 0 0 0 0 0 0 0 314
315 293.3 45.85 0 0 1 0 0 0 0 0 0 0 0 315
316 300.8 48.45 0 0 0 1 0 0 0 0 0 0 0 316
317 293.7 49.96 0 0 0 0 1 0 0 0 0 0 0 317
318 293.1 46.53 0 0 0 0 0 1 0 0 0 0 0 318
319 294.4 50.51 0 0 0 0 0 0 1 0 0 0 0 319
320 292.1 47.58 0 0 0 0 0 0 0 1 0 0 0 320
321 291.9 48.05 0 0 0 0 0 0 0 0 1 0 0 321
322 282.5 46.84 0 0 0 0 0 0 0 0 0 1 0 322
323 277.9 47.67 0 0 0 0 0 0 0 0 0 0 1 323
324 287.5 49.16 0 0 0 0 0 0 0 0 0 0 0 324
325 289.2 55.54 1 0 0 0 0 0 0 0 0 0 0 325
326 285.6 55.82 0 1 0 0 0 0 0 0 0 0 0 326
327 293.2 58.22 0 0 1 0 0 0 0 0 0 0 0 327
328 290.8 56.19 0 0 0 1 0 0 0 0 0 0 0 328
329 283.1 57.77 0 0 0 0 1 0 0 0 0 0 0 329
330 275.0 63.19 0 0 0 0 0 1 0 0 0 0 0 330
331 287.8 54.76 0 0 0 0 0 0 1 0 0 0 0 331
332 287.8 55.74 0 0 0 0 0 0 0 1 0 0 0 332
333 287.4 62.54 0 0 0 0 0 0 0 0 1 0 0 333
334 284.0 61.39 0 0 0 0 0 0 0 0 0 1 0 334
335 277.8 69.60 0 0 0 0 0 0 0 0 0 0 1 335
336 277.6 79.23 0 0 0 0 0 0 0 0 0 0 0 336
337 304.9 80.00 1 0 0 0 0 0 0 0 0 0 0 337
338 294.0 93.68 0 1 0 0 0 0 0 0 0 0 0 338
339 300.9 107.63 0 0 1 0 0 0 0 0 0 0 0 339
340 324.0 100.18 0 0 0 1 0 0 0 0 0 0 0 340
341 332.9 97.30 0 0 0 0 1 0 0 0 0 0 0 341
342 341.6 90.45 0 0 0 0 0 1 0 0 0 0 0 342
343 333.4 80.64 0 0 0 0 0 0 1 0 0 0 0 343
344 348.2 80.58 0 0 0 0 0 0 0 1 0 0 0 344
345 344.7 75.82 0 0 0 0 0 0 0 0 1 0 0 345
346 344.7 85.59 0 0 0 0 0 0 0 0 0 1 0 346
347 329.3 89.35 0 0 0 0 0 0 0 0 0 0 1 347
348 323.5 89.42 0 0 0 0 0 0 0 0 0 0 0 348
349 323.2 104.73 1 0 0 0 0 0 0 0 0 0 0 349
350 317.4 95.32 0 1 0 0 0 0 0 0 0 0 0 350
351 330.1 89.27 0 0 1 0 0 0 0 0 0 0 0 351
352 329.2 90.44 0 0 0 1 0 0 0 0 0 0 0 352
353 334.9 86.97 0 0 0 0 1 0 0 0 0 0 0 353
354 315.8 79.98 0 0 0 0 0 1 0 0 0 0 0 354
355 315.4 81.22 0 0 0 0 0 0 1 0 0 0 0 355
356 319.6 87.35 0 0 0 0 0 0 0 1 0 0 0 356
357 317.3 83.64 0 0 0 0 0 0 0 0 1 0 0 357
358 313.8 82.22 0 0 0 0 0 0 0 0 0 1 0 358
359 315.8 94.40 0 0 0 0 0 0 0 0 0 0 1 359
360 311.3 102.18 0 0 0 0 0 0 0 0 0 0 0 360
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Colombia M1 M2 M3 M4
127.3994 1.8993 2.7206 5.0833 1.2928 3.5714
M5 M6 M7 M8 M9 M10
4.5887 6.9823 15.7899 17.1239 13.2850 10.2014
M11 t
2.6364 0.1482
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-112.312 -18.433 0.258 17.949 90.740
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 127.39936 9.42068 13.523 <2e-16 ***
Colombia 1.89928 0.08727 21.764 <2e-16 ***
M1 2.72059 8.01636 0.339 0.7345
M2 5.08328 8.01583 0.634 0.5264
M3 1.29283 8.01706 0.161 0.8720
M4 3.57139 8.01659 0.446 0.6562
M5 4.58872 8.01622 0.572 0.5674
M6 6.98232 8.01483 0.871 0.3843
M7 15.78987 8.01755 1.969 0.0497 *
M8 17.12394 8.01657 2.136 0.0334 *
M9 13.28502 8.01620 1.657 0.0984 .
M10 10.20144 8.01595 1.273 0.2040
M11 2.63636 8.01428 0.329 0.7424
t 0.14817 0.01577 9.397 <2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 31.04 on 346 degrees of freedom
Multiple R-squared: 0.6135, Adjusted R-squared: 0.599
F-statistic: 42.26 on 13 and 346 DF, p-value: < 2.2e-16
> if (n > n25) {
+ kp3 <- k + 3
+ nmkm3 <- n - k - 3
+ gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
+ numgqtests <- 0
+ numsignificant1 <- 0
+ numsignificant5 <- 0
+ numsignificant10 <- 0
+ for (mypoint in kp3:nmkm3) {
+ j <- 0
+ numgqtests <- numgqtests + 1
+ for (myalt in c('greater', 'two.sided', 'less')) {
+ j <- j + 1
+ gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
+ }
+ if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
+ }
+ gqarr
+ }
[,1] [,2] [,3]
[1,] 0.1569382362 3.138765e-01 8.430618e-01
[2,] 0.6038744573 7.922511e-01 3.961255e-01
[3,] 0.4915041838 9.830084e-01 5.084958e-01
[4,] 0.3627623707 7.255247e-01 6.372376e-01
[5,] 0.2537643936 5.075288e-01 7.462356e-01
[6,] 0.1787999040 3.575998e-01 8.212001e-01
[7,] 0.1494012858 2.988026e-01 8.505987e-01
[8,] 0.1288768394 2.577537e-01 8.711232e-01
[9,] 0.1889426092 3.778852e-01 8.110574e-01
[10,] 0.2800816032 5.601632e-01 7.199184e-01
[11,] 0.8926612512 2.146775e-01 1.073387e-01
[12,] 0.8930081169 2.139838e-01 1.069919e-01
[13,] 0.8566464393 2.867071e-01 1.433536e-01
[14,] 0.8147859001 3.704282e-01 1.852141e-01
[15,] 0.7656084579 4.687831e-01 2.343915e-01
[16,] 0.7398386625 5.203227e-01 2.601613e-01
[17,] 0.6958029624 6.083941e-01 3.041970e-01
[18,] 0.6446044422 7.107911e-01 3.553956e-01
[19,] 0.5933746301 8.132507e-01 4.066254e-01
[20,] 0.5423690035 9.152620e-01 4.576310e-01
[21,] 0.4879889359 9.759779e-01 5.120111e-01
[22,] 0.4369154123 8.738308e-01 5.630846e-01
[23,] 0.4033952345 8.067905e-01 5.966048e-01
[24,] 0.4467129777 8.934260e-01 5.532870e-01
[25,] 0.4457200972 8.914402e-01 5.542799e-01
[26,] 0.4073137483 8.146275e-01 5.926863e-01
[27,] 0.3587130201 7.174260e-01 6.412870e-01
[28,] 0.3109131142 6.218262e-01 6.890869e-01
[29,] 0.2656576627 5.313153e-01 7.343423e-01
[30,] 0.2239855438 4.479711e-01 7.760145e-01
[31,] 0.1875554075 3.751108e-01 8.124446e-01
[32,] 0.1810023442 3.620047e-01 8.189977e-01
[33,] 0.1494240708 2.988481e-01 8.505759e-01
[34,] 0.1390477644 2.780955e-01 8.609522e-01
[35,] 0.1531330491 3.062661e-01 8.468670e-01
[36,] 0.1640028007 3.280056e-01 8.359972e-01
[37,] 0.1817610415 3.635221e-01 8.182390e-01
[38,] 0.1754477886 3.508956e-01 8.245522e-01
[39,] 0.1735439611 3.470879e-01 8.264560e-01
[40,] 0.1646136914 3.292274e-01 8.353863e-01
[41,] 0.1450044765 2.900090e-01 8.549955e-01
[42,] 0.1463348053 2.926696e-01 8.536652e-01
[43,] 0.1673810316 3.347621e-01 8.326190e-01
[44,] 0.1520376869 3.040754e-01 8.479623e-01
[45,] 0.1318758448 2.637517e-01 8.681242e-01
[46,] 0.1171411180 2.342822e-01 8.828589e-01
[47,] 0.1002491458 2.004983e-01 8.997509e-01
[48,] 0.0859863907 1.719728e-01 9.140136e-01
[49,] 0.0728557187 1.457114e-01 9.271443e-01
[50,] 0.0604527540 1.209055e-01 9.395472e-01
[51,] 0.0514895425 1.029791e-01 9.485105e-01
[52,] 0.0431798223 8.635964e-02 9.568202e-01
[53,] 0.0361429012 7.228580e-02 9.638571e-01
[54,] 0.0341848918 6.836978e-02 9.658151e-01
[55,] 0.0285049120 5.700982e-02 9.714951e-01
[56,] 0.0232350462 4.647009e-02 9.767650e-01
[57,] 0.0240385635 4.807713e-02 9.759614e-01
[58,] 0.0244784639 4.895693e-02 9.755215e-01
[59,] 0.0243164823 4.863296e-02 9.756835e-01
[60,] 0.0208791033 4.175821e-02 9.791209e-01
[61,] 0.0174103178 3.482064e-02 9.825897e-01
[62,] 0.0151662212 3.033244e-02 9.848338e-01
[63,] 0.0139705091 2.794102e-02 9.860295e-01
[64,] 0.0137443816 2.748876e-02 9.862556e-01
[65,] 0.0121918093 2.438362e-02 9.878082e-01
[66,] 0.0113311466 2.266229e-02 9.886689e-01
[67,] 0.0110051799 2.201036e-02 9.889948e-01
[68,] 0.0113476786 2.269536e-02 9.886523e-01
[69,] 0.0168046984 3.360940e-02 9.831953e-01
[70,] 0.0252863380 5.057268e-02 9.747137e-01
[71,] 0.0318526353 6.370527e-02 9.681474e-01
[72,] 0.0389811561 7.796231e-02 9.610188e-01
[73,] 0.0440121034 8.802421e-02 9.559879e-01
[74,] 0.0525123197 1.050246e-01 9.474877e-01
[75,] 0.0666149927 1.332300e-01 9.333850e-01
[76,] 0.0724900183 1.449800e-01 9.275100e-01
[77,] 0.0795906609 1.591813e-01 9.204093e-01
[78,] 0.1000143318 2.000287e-01 8.999857e-01
[79,] 0.1252028838 2.504058e-01 8.747971e-01
[80,] 0.1458195293 2.916391e-01 8.541805e-01
[81,] 0.1958380163 3.916760e-01 8.041620e-01
[82,] 0.2460287066 4.920574e-01 7.539713e-01
[83,] 0.2732080771 5.464162e-01 7.267919e-01
[84,] 0.3136672635 6.273345e-01 6.863327e-01
[85,] 0.3513045099 7.026090e-01 6.486955e-01
[86,] 0.3686492453 7.372985e-01 6.313508e-01
[87,] 0.3851011896 7.702024e-01 6.148988e-01
[88,] 0.3912317012 7.824634e-01 6.087683e-01
[89,] 0.3901976649 7.803953e-01 6.098023e-01
[90,] 0.3951748944 7.903498e-01 6.048251e-01
[91,] 0.3901430785 7.802862e-01 6.098569e-01
[92,] 0.3741891264 7.483783e-01 6.258109e-01
[93,] 0.3944629862 7.889260e-01 6.055370e-01
[94,] 0.6705917235 6.588166e-01 3.294083e-01
[95,] 0.7890634656 4.218731e-01 2.109365e-01
[96,] 0.8165105762 3.669788e-01 1.834894e-01
[97,] 0.8166224238 3.667552e-01 1.833776e-01
[98,] 0.8110455168 3.779090e-01 1.889545e-01
[99,] 0.7937159747 4.125681e-01 2.062840e-01
[100,] 0.7696667989 4.606664e-01 2.303332e-01
[101,] 0.7443954327 5.112091e-01 2.556046e-01
[102,] 0.7168451426 5.663097e-01 2.831549e-01
[103,] 0.6891511359 6.216977e-01 3.108489e-01
[104,] 0.6637539555 6.724921e-01 3.362460e-01
[105,] 0.6399663801 7.200672e-01 3.600336e-01
[106,] 0.6090251819 7.819496e-01 3.909748e-01
[107,] 0.5778991140 8.442018e-01 4.221009e-01
[108,] 0.5454241161 9.091518e-01 4.545759e-01
[109,] 0.5158040911 9.683918e-01 4.841959e-01
[110,] 0.4856805096 9.713610e-01 5.143195e-01
[111,] 0.4622175796 9.244352e-01 5.377824e-01
[112,] 0.4497757670 8.995515e-01 5.502242e-01
[113,] 0.4267610644 8.535221e-01 5.732389e-01
[114,] 0.4002340085 8.004680e-01 5.997660e-01
[115,] 0.3800753655 7.601507e-01 6.199246e-01
[116,] 0.3588261664 7.176523e-01 6.411738e-01
[117,] 0.3344676267 6.689353e-01 6.655324e-01
[118,] 0.3143482836 6.286966e-01 6.856517e-01
[119,] 0.2937867943 5.875736e-01 7.062132e-01
[120,] 0.2712592729 5.425185e-01 7.287407e-01
[121,] 0.2509220241 5.018440e-01 7.490780e-01
[122,] 0.2314433555 4.628867e-01 7.685566e-01
[123,] 0.2145712615 4.291425e-01 7.854287e-01
[124,] 0.2016570558 4.033141e-01 7.983429e-01
[125,] 0.1883587783 3.767176e-01 8.116412e-01
[126,] 0.1741392644 3.482785e-01 8.258607e-01
[127,] 0.1571596829 3.143194e-01 8.428403e-01
[128,] 0.1416197136 2.832394e-01 8.583803e-01
[129,] 0.1302443446 2.604887e-01 8.697557e-01
[130,] 0.1252300622 2.504601e-01 8.747699e-01
[131,] 0.1220382517 2.440765e-01 8.779617e-01
[132,] 0.1094242527 2.188485e-01 8.905757e-01
[133,] 0.1013839646 2.027679e-01 8.986160e-01
[134,] 0.0916959192 1.833918e-01 9.083041e-01
[135,] 0.0836542063 1.673084e-01 9.163458e-01
[136,] 0.0762731312 1.525463e-01 9.237269e-01
[137,] 0.0696867421 1.393735e-01 9.303133e-01
[138,] 0.0628884425 1.257769e-01 9.371116e-01
[139,] 0.0550031250 1.100063e-01 9.449969e-01
[140,] 0.0488007001 9.760140e-02 9.511993e-01
[141,] 0.0448544267 8.970885e-02 9.551456e-01
[142,] 0.0413630912 8.272618e-02 9.586369e-01
[143,] 0.0355018203 7.100364e-02 9.644982e-01
[144,] 0.0301377732 6.027555e-02 9.698622e-01
[145,] 0.0256539730 5.130795e-02 9.743460e-01
[146,] 0.0225448529 4.508971e-02 9.774551e-01
[147,] 0.0208703183 4.174064e-02 9.791297e-01
[148,] 0.0197238949 3.944779e-02 9.802761e-01
[149,] 0.0168355308 3.367106e-02 9.831645e-01
[150,] 0.0144766091 2.895322e-02 9.855234e-01
[151,] 0.0124939427 2.498789e-02 9.875061e-01
[152,] 0.0109469714 2.189394e-02 9.890530e-01
[153,] 0.0100337872 2.006757e-02 9.899662e-01
[154,] 0.0089660615 1.793212e-02 9.910339e-01
[155,] 0.0074635527 1.492711e-02 9.925364e-01
[156,] 0.0060577798 1.211556e-02 9.939422e-01
[157,] 0.0048883226 9.776645e-03 9.951117e-01
[158,] 0.0039550813 7.910163e-03 9.960449e-01
[159,] 0.0034674888 6.934978e-03 9.965325e-01
[160,] 0.0033331381 6.666276e-03 9.966669e-01
[161,] 0.0031106500 6.221300e-03 9.968893e-01
[162,] 0.0028683269 5.736654e-03 9.971317e-01
[163,] 0.0025092272 5.018454e-03 9.974908e-01
[164,] 0.0021681583 4.336317e-03 9.978318e-01
[165,] 0.0019121169 3.824234e-03 9.980879e-01
[166,] 0.0015911548 3.182310e-03 9.984088e-01
[167,] 0.0013182555 2.636511e-03 9.986817e-01
[168,] 0.0011381741 2.276348e-03 9.988618e-01
[169,] 0.0009682923 1.936585e-03 9.990317e-01
[170,] 0.0008363544 1.672709e-03 9.991636e-01
[171,] 0.0008133044 1.626609e-03 9.991867e-01
[172,] 0.0008780953 1.756191e-03 9.991219e-01
[173,] 0.0009483253 1.896651e-03 9.990517e-01
[174,] 0.0010118735 2.023747e-03 9.989881e-01
[175,] 0.0010515237 2.103047e-03 9.989485e-01
[176,] 0.0010527025 2.105405e-03 9.989473e-01
[177,] 0.0011561457 2.312291e-03 9.988439e-01
[178,] 0.0011096192 2.219238e-03 9.988904e-01
[179,] 0.0010427178 2.085436e-03 9.989573e-01
[180,] 0.0010195568 2.039114e-03 9.989804e-01
[181,] 0.0009681524 1.936305e-03 9.990318e-01
[182,] 0.0009508501 1.901700e-03 9.990491e-01
[183,] 0.0010860012 2.172002e-03 9.989140e-01
[184,] 0.0017599458 3.519892e-03 9.982401e-01
[185,] 0.0027869446 5.573889e-03 9.972131e-01
[186,] 0.0049789299 9.957860e-03 9.950211e-01
[187,] 0.0075754552 1.515091e-02 9.924245e-01
[188,] 0.0102496946 2.049939e-02 9.897503e-01
[189,] 0.0148024302 2.960486e-02 9.851976e-01
[190,] 0.0240363731 4.807275e-02 9.759636e-01
[191,] 0.0988510745 1.977021e-01 9.011489e-01
[192,] 0.3028745505 6.057491e-01 6.971254e-01
[193,] 0.6197054413 7.605891e-01 3.802946e-01
[194,] 0.8833672443 2.332655e-01 1.166328e-01
[195,] 0.8974255805 2.051488e-01 1.025744e-01
[196,] 0.9478572806 1.042854e-01 5.214272e-02
[197,] 0.9540530371 9.189393e-02 4.594696e-02
[198,] 0.9587164975 8.256701e-02 4.128350e-02
[199,] 0.9712754592 5.744908e-02 2.872454e-02
[200,] 0.9807623454 3.847531e-02 1.923765e-02
[201,] 0.9884247435 2.315051e-02 1.157526e-02
[202,] 0.9905445307 1.891094e-02 9.455469e-03
[203,] 0.9909398028 1.812039e-02 9.060197e-03
[204,] 0.9904048384 1.919032e-02 9.595162e-03
[205,] 0.9893700637 2.125987e-02 1.062994e-02
[206,] 0.9883636005 2.327280e-02 1.163640e-02
[207,] 0.9863500689 2.729986e-02 1.364993e-02
[208,] 0.9849417479 3.011650e-02 1.505825e-02
[209,] 0.9834717986 3.305640e-02 1.652820e-02
[210,] 0.9810926957 3.781461e-02 1.890730e-02
[211,] 0.9792002491 4.159950e-02 2.079975e-02
[212,] 0.9767500144 4.649997e-02 2.324999e-02
[213,] 0.9720150497 5.596990e-02 2.798495e-02
[214,] 0.9665865206 6.682696e-02 3.341348e-02
[215,] 0.9600133308 7.997334e-02 3.998667e-02
[216,] 0.9525331208 9.493376e-02 4.746688e-02
[217,] 0.9460198071 1.079604e-01 5.398019e-02
[218,] 0.9392414066 1.215172e-01 6.075859e-02
[219,] 0.9458368366 1.083263e-01 5.416316e-02
[220,] 0.9778806235 4.423875e-02 2.211938e-02
[221,] 0.9938774874 1.224503e-02 6.122513e-03
[222,] 0.9985939216 2.812157e-03 1.406078e-03
[223,] 0.9997013489 5.973022e-04 2.986511e-04
[224,] 0.9998446052 3.107896e-04 1.553948e-04
[225,] 0.9999122087 1.755827e-04 8.779133e-05
[226,] 0.9999924649 1.507026e-05 7.535128e-06
[227,] 0.9999999995 9.376078e-10 4.688039e-10
[228,] 1.0000000000 4.398056e-11 2.199028e-11
[229,] 1.0000000000 1.136848e-13 5.684242e-14
[230,] 1.0000000000 1.476779e-14 7.383895e-15
[231,] 1.0000000000 1.195730e-14 5.978649e-15
[232,] 1.0000000000 2.195019e-15 1.097510e-15
[233,] 1.0000000000 1.324374e-16 6.621871e-17
[234,] 1.0000000000 2.625492e-17 1.312746e-17
[235,] 1.0000000000 7.327549e-19 3.663774e-19
[236,] 1.0000000000 2.203007e-19 1.101503e-19
[237,] 1.0000000000 3.838850e-19 1.919425e-19
[238,] 1.0000000000 8.834761e-19 4.417380e-19
[239,] 1.0000000000 6.412164e-19 3.206082e-19
[240,] 1.0000000000 1.192703e-18 5.963516e-19
[241,] 1.0000000000 1.615504e-18 8.077522e-19
[242,] 1.0000000000 3.205207e-18 1.602604e-18
[243,] 1.0000000000 7.788921e-18 3.894461e-18
[244,] 1.0000000000 1.886201e-17 9.431003e-18
[245,] 1.0000000000 4.578546e-17 2.289273e-17
[246,] 1.0000000000 9.851522e-17 4.925761e-17
[247,] 1.0000000000 2.284846e-16 1.142423e-16
[248,] 1.0000000000 5.184338e-16 2.592169e-16
[249,] 1.0000000000 8.885479e-16 4.442740e-16
[250,] 1.0000000000 1.692376e-15 8.461879e-16
[251,] 1.0000000000 3.592544e-15 1.796272e-15
[252,] 1.0000000000 6.504581e-15 3.252291e-15
[253,] 1.0000000000 1.343499e-14 6.717495e-15
[254,] 1.0000000000 1.865031e-14 9.325156e-15
[255,] 1.0000000000 2.822104e-14 1.411052e-14
[256,] 1.0000000000 4.632353e-14 2.316177e-14
[257,] 1.0000000000 8.884660e-14 4.442330e-14
[258,] 1.0000000000 1.879435e-13 9.397175e-14
[259,] 1.0000000000 3.310177e-13 1.655089e-13
[260,] 1.0000000000 2.520336e-13 1.260168e-13
[261,] 1.0000000000 5.731770e-13 2.865885e-13
[262,] 1.0000000000 3.613005e-13 1.806503e-13
[263,] 1.0000000000 3.269061e-13 1.634530e-13
[264,] 1.0000000000 3.756427e-13 1.878213e-13
[265,] 1.0000000000 5.558119e-13 2.779060e-13
[266,] 1.0000000000 1.002365e-12 5.011825e-13
[267,] 1.0000000000 1.979505e-12 9.897525e-13
[268,] 1.0000000000 3.147423e-12 1.573711e-12
[269,] 1.0000000000 6.429289e-12 3.214645e-12
[270,] 1.0000000000 1.273536e-11 6.367679e-12
[271,] 1.0000000000 2.384287e-11 1.192143e-11
[272,] 1.0000000000 3.773825e-11 1.886913e-11
[273,] 1.0000000000 5.800367e-11 2.900183e-11
[274,] 1.0000000000 3.581147e-11 1.790573e-11
[275,] 1.0000000000 2.440649e-11 1.220324e-11
[276,] 1.0000000000 5.107345e-11 2.553672e-11
[277,] 0.9999999999 1.195366e-10 5.976828e-11
[278,] 0.9999999999 1.514489e-10 7.572444e-11
[279,] 0.9999999998 3.119869e-10 1.559935e-10
[280,] 0.9999999996 7.186339e-10 3.593169e-10
[281,] 0.9999999992 1.638343e-09 8.191716e-10
[282,] 0.9999999984 3.138365e-09 1.569183e-09
[283,] 0.9999999975 4.953579e-09 2.476790e-09
[284,] 0.9999999956 8.879955e-09 4.439977e-09
[285,] 0.9999999905 1.909105e-08 9.545526e-09
[286,] 0.9999999848 3.047905e-08 1.523952e-08
[287,] 0.9999999672 6.569696e-08 3.284848e-08
[288,] 0.9999999291 1.418232e-07 7.091162e-08
[289,] 0.9999998563 2.873668e-07 1.436834e-07
[290,] 0.9999997016 5.967350e-07 2.983675e-07
[291,] 0.9999994451 1.109746e-06 5.548731e-07
[292,] 0.9999988706 2.258811e-06 1.129405e-06
[293,] 0.9999977023 4.595342e-06 2.297671e-06
[294,] 0.9999953862 9.227518e-06 4.613759e-06
[295,] 0.9999916331 1.673374e-05 8.366872e-06
[296,] 0.9999864858 2.702847e-05 1.351423e-05
[297,] 0.9999828796 3.424072e-05 1.712036e-05
[298,] 0.9999800047 3.999058e-05 1.999529e-05
[299,] 0.9999738669 5.226622e-05 2.613311e-05
[300,] 0.9999642019 7.159615e-05 3.579807e-05
[301,] 0.9999339014 1.321971e-04 6.609855e-05
[302,] 0.9998957803 2.084393e-04 1.042197e-04
[303,] 0.9998135025 3.729950e-04 1.864975e-04
[304,] 0.9996526664 6.946672e-04 3.473336e-04
[305,] 0.9993724794 1.255041e-03 6.275206e-04
[306,] 0.9988613127 2.277375e-03 1.138687e-03
[307,] 0.9980590433 3.881913e-03 1.940957e-03
[308,] 0.9979816582 4.036684e-03 2.018342e-03
[309,] 0.9968518816 6.296237e-03 3.148118e-03
[310,] 0.9960842429 7.831514e-03 3.915757e-03
[311,] 0.9956564974 8.687005e-03 4.343503e-03
[312,] 0.9934931807 1.301364e-02 6.506819e-03
[313,] 0.9888722831 2.225543e-02 1.112772e-02
[314,] 0.9865494271 2.690115e-02 1.345057e-02
[315,] 0.9773695783 4.526084e-02 2.263042e-02
[316,] 0.9654485805 6.910284e-02 3.455142e-02
[317,] 0.9577307848 8.453843e-02 4.226922e-02
[318,] 0.9509520755 9.809585e-02 4.904792e-02
[319,] 0.9587491274 8.250175e-02 4.125087e-02
[320,] 0.9847772970 3.044541e-02 1.522270e-02
[321,] 0.9928852629 1.422947e-02 7.114737e-03
[322,] 0.9976588827 4.682235e-03 2.341117e-03
[323,] 0.9987113722 2.577256e-03 1.288628e-03
[324,] 0.9983956457 3.208709e-03 1.604354e-03
[325,] 0.9995669282 8.661436e-04 4.330718e-04
[326,] 0.9976141525 4.771695e-03 2.385848e-03
[327,] 0.9907936559 1.841269e-02 9.206344e-03
> postscript(file="/var/wessaorg/rcomp/tmp/1bqz31351857978.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
> points(x[,1]-mysum$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/2542q1351857978.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/3335l1351857978.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/4tpdp1351857978.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/53asc1351857978.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
> qqline(mysum$resid)
> grid()
> dev.off()
null device
1
> (myerror <- as.ts(mysum$resid))
Time Series:
Start = 1
End = 360
Frequency = 1
1 2 3 4 5 6
-41.0370827 -18.3479520 5.3551924 42.5513314 75.1133192 85.9268045
7 8 9 10 11 12
72.7280546 64.4865320 63.1017333 60.9956978 57.8192216 56.1279866
13 14 15 16 17 18
49.0836840 43.4476341 45.2876125 31.5825997 25.7008436 15.2048225
19 20 21 22 23 24
1.4568631 -14.2986162 -17.6214004 -16.9777971 -8.7895261 -6.3578839
25 26 27 28 29 30
-12.1781576 -15.7121970 -1.2356977 -5.8329416 -11.3485059 -16.5784717
31 32 33 34 35 36
-7.0478637 14.2903328 21.6018061 26.5882946 35.8931186 38.9378587
37 38 39 40 41 42
23.8842062 28.8536218 26.6924485 13.6287399 16.6284204 14.0657780
43 44 45 46 47 48
13.4155153 10.5046388 4.9047318 4.0483350 -0.1885745 -12.7993682
49 50 51 52 53 54
-18.1324468 -34.3630312 -34.6633418 -38.0226001 -40.3066596 -39.9251286
55 56 57 58 59 60
-50.4765430 -51.6405134 -46.9884782 -50.8513356 -51.2496738 -38.2610533
61 62 63 64 65 66
-40.7266520 -29.9952219 -31.6345133 -33.6472949 -32.3185494 -34.5331339
67 68 69 70 71 72
-44.6795122 -42.7535549 -38.6964836 -49.3807736 -39.7110660 -33.6840305
73 74 75 76 77 78
-32.4786943 -30.9964737 -24.3812465 -34.1177641 -35.0185130 -35.7202925
79 80 81 82 83 84
-43.3930031 -40.5263275 -43.9737064 -41.0259258 -30.5062864 -27.4451498
85 86 87 88 89 90
-25.2871490 -19.5820512 -16.3544485 -17.7242084 -16.9439501 -14.7511951
91 92 93 94 95 96
-18.2870718 -23.2992365 -19.3341034 -12.8017240 -5.0413663 -3.0156190
97 98 99 100 101 102
-3.1494200 -0.3555461 0.9707685 3.8027261 7.1362148 1.9036527
103 104 105 106 107 108
-2.9155346 -6.4069890 -7.3729313 0.2141230 0.3013988 -4.9724245
109 110 111 112 113 114
1.8418523 64.9599316 61.1208167 49.2160969 42.2513231 38.4847964
115 116 117 118 119 120
25.2679124 13.2295520 0.7389949 4.2155476 13.2382127 18.5261109
121 122 123 124 125 126
15.5772016 7.8633066 8.8114832 -0.2613024 -8.4728459 -9.8645532
127 128 129 130 131 132
-19.3322276 -28.3113064 -18.7453145 -12.2398333 -19.9567348 -18.6882588
133 134 135 136 137 138
-11.6849329 -17.5424154 -17.1713616 -13.4555076 -15.1674804 -16.0564550
139 140 141 142 143 144
-16.0012522 -19.0485332 -11.6468592 -9.8134646 -6.9204304 1.5837279
145 146 147 148 149 150
2.4820176 14.5259597 18.5585985 11.4625264 18.3068096 14.6076263
151 152 153 154 155 156
12.4585153 8.4251909 7.7598144 5.3979522 -1.6537728 7.3302410
157 158 159 160 161 162
5.7852161 11.4930466 3.9747585 -3.2303906 4.1138925 8.5299541
163 164 165 166 167 168
10.1041496 8.7708253 0.3151116 5.3079243 6.9028125 11.8209275
169 170 171 172 173 174
11.7832421 14.0565421 7.6437195 1.2656249 -2.1967091 -3.8353225
175 176 177 178 179 180
-16.7828525 -24.1429385 -20.8032789 -19.8295954 -14.5541294 -14.4538556
181 182 183 184 185 186
-13.0226164 -6.3922016 -4.9172633 -7.9904783 -3.1214439 -7.9096962
187 188 189 190 191 192
-6.9481692 -5.9678298 -8.8134912 -9.3144907 -10.9719741 -10.1201874
193 194 195 196 197 198
-13.2393094 -4.8385254 0.6964168 -5.1874362 -3.2796940 -2.5919752
199 200 201 202 203 204
-9.0980645 -27.3647477 -23.3294019 -27.1493942 -17.4006898 -8.7120692
205 206 207 208 209 210
-5.6881696 -21.3090911 -56.3876161 -56.4921994 -54.1623023 -52.2273844
211 212 213 214 215 216
15.5479628 90.7398790 65.2608788 62.4391690 73.5688806 73.8061248
217 218 219 220 221 222
76.2789410 59.0774216 54.0702009 50.7248993 42.1045918 45.1823748
223 224 225 226 227 228
36.7492309 44.6183464 45.6010276 41.6090852 43.6980785 40.1572046
229 230 231 232 233 234
31.7728861 25.6238947 26.1208514 26.9779896 16.0880352 15.1494218
235 236 237 238 239 240
-4.7343562 -35.2061919 -40.8810549 -41.6508224 -40.4098869 -20.7833008
241 242 243 244 245 246
-15.2165359 -52.1946887 -112.3117051 -57.6406302 -83.8574227 -54.6131549
247 248 249 250 251 252
30.9587737 46.2827006 53.9659477 45.2842139 53.2405307 27.5310452
253 254 255 256 257 258
11.4801255 -9.5636733 28.6817306 15.6642058 28.2214104 19.4615008
259 260 261 262 263 264
7.1254877 1.2793584 12.5620196 6.9122401 1.9160688 -1.2469599
265 266 267 268 269 270
-2.8986020 -0.5825732 5.6375536 5.0217464 9.8520729 -0.2036593
271 272 273 274 275 276
2.0793003 6.2402175 14.4079269 26.3003102 2.4276021 -17.3123730
277 278 279 280 281 282
16.6871848 37.5436390 34.7157080 35.3089578 31.0276310 28.7229622
283 284 285 286 287 288
21.8750029 27.7708800 22.5570163 21.1272448 18.6560976 20.9311909
289 290 291 292 293 294
25.4350825 34.2656338 36.3090672 20.1046404 8.4129684 32.0174931
295 296 297 298 299 300
17.9024832 10.1426901 10.0240833 23.0892556 22.1273219 18.8818413
301 302 303 304 305 306
14.2676190 15.5486879 0.6717039 4.1141832 17.7303965 12.8077502
307 308 309 310 311 312
20.8760309 18.0884609 10.6661261 8.7015311 10.7368647 22.3669058
313 314 315 316 317 318
27.5831931 20.1933270 30.8512829 30.9864227 19.8530172 23.2257642
319 320 321 322 323 324
8.0109107 9.7935535 12.3916360 8.2251670 9.4656732 18.7239406
325 326 327 328 329 330
5.4377880 -1.2048790 5.4791362 4.5079317 -7.3584232 -28.2942839
331 332 333 334 335 336
-8.4391011 -11.7826341 -21.4069794 -19.6874050 -34.0635683 -50.0654214
337 338 339 340 341 342
-27.0966260 -66.4896142 -82.4422564 -47.6193758 -34.4149521 -15.2466755
343 344 345 346 347 348
-13.7704895 -0.3387737 8.8925312 -6.7280069 -21.8523844 -25.2971427
349 350 351 352 353 354
-57.5438451 -47.9825113 -20.1495995 -25.6984926 -14.5734951 -22.9393196
355 356 357 358 359 360
-34.6501522 -43.5749653 -35.1379020 -33.0055227 -46.7218184 -63.5100077
> postscript(file="/var/wessaorg/rcomp/tmp/64fq11351857978.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> dum <- cbind(lag(myerror,k=1),myerror)
> dum
Time Series:
Start = 0
End = 360
Frequency = 1
lag(myerror, k = 1) myerror
0 -41.0370827 NA
1 -18.3479520 -41.0370827
2 5.3551924 -18.3479520
3 42.5513314 5.3551924
4 75.1133192 42.5513314
5 85.9268045 75.1133192
6 72.7280546 85.9268045
7 64.4865320 72.7280546
8 63.1017333 64.4865320
9 60.9956978 63.1017333
10 57.8192216 60.9956978
11 56.1279866 57.8192216
12 49.0836840 56.1279866
13 43.4476341 49.0836840
14 45.2876125 43.4476341
15 31.5825997 45.2876125
16 25.7008436 31.5825997
17 15.2048225 25.7008436
18 1.4568631 15.2048225
19 -14.2986162 1.4568631
20 -17.6214004 -14.2986162
21 -16.9777971 -17.6214004
22 -8.7895261 -16.9777971
23 -6.3578839 -8.7895261
24 -12.1781576 -6.3578839
25 -15.7121970 -12.1781576
26 -1.2356977 -15.7121970
27 -5.8329416 -1.2356977
28 -11.3485059 -5.8329416
29 -16.5784717 -11.3485059
30 -7.0478637 -16.5784717
31 14.2903328 -7.0478637
32 21.6018061 14.2903328
33 26.5882946 21.6018061
34 35.8931186 26.5882946
35 38.9378587 35.8931186
36 23.8842062 38.9378587
37 28.8536218 23.8842062
38 26.6924485 28.8536218
39 13.6287399 26.6924485
40 16.6284204 13.6287399
41 14.0657780 16.6284204
42 13.4155153 14.0657780
43 10.5046388 13.4155153
44 4.9047318 10.5046388
45 4.0483350 4.9047318
46 -0.1885745 4.0483350
47 -12.7993682 -0.1885745
48 -18.1324468 -12.7993682
49 -34.3630312 -18.1324468
50 -34.6633418 -34.3630312
51 -38.0226001 -34.6633418
52 -40.3066596 -38.0226001
53 -39.9251286 -40.3066596
54 -50.4765430 -39.9251286
55 -51.6405134 -50.4765430
56 -46.9884782 -51.6405134
57 -50.8513356 -46.9884782
58 -51.2496738 -50.8513356
59 -38.2610533 -51.2496738
60 -40.7266520 -38.2610533
61 -29.9952219 -40.7266520
62 -31.6345133 -29.9952219
63 -33.6472949 -31.6345133
64 -32.3185494 -33.6472949
65 -34.5331339 -32.3185494
66 -44.6795122 -34.5331339
67 -42.7535549 -44.6795122
68 -38.6964836 -42.7535549
69 -49.3807736 -38.6964836
70 -39.7110660 -49.3807736
71 -33.6840305 -39.7110660
72 -32.4786943 -33.6840305
73 -30.9964737 -32.4786943
74 -24.3812465 -30.9964737
75 -34.1177641 -24.3812465
76 -35.0185130 -34.1177641
77 -35.7202925 -35.0185130
78 -43.3930031 -35.7202925
79 -40.5263275 -43.3930031
80 -43.9737064 -40.5263275
81 -41.0259258 -43.9737064
82 -30.5062864 -41.0259258
83 -27.4451498 -30.5062864
84 -25.2871490 -27.4451498
85 -19.5820512 -25.2871490
86 -16.3544485 -19.5820512
87 -17.7242084 -16.3544485
88 -16.9439501 -17.7242084
89 -14.7511951 -16.9439501
90 -18.2870718 -14.7511951
91 -23.2992365 -18.2870718
92 -19.3341034 -23.2992365
93 -12.8017240 -19.3341034
94 -5.0413663 -12.8017240
95 -3.0156190 -5.0413663
96 -3.1494200 -3.0156190
97 -0.3555461 -3.1494200
98 0.9707685 -0.3555461
99 3.8027261 0.9707685
100 7.1362148 3.8027261
101 1.9036527 7.1362148
102 -2.9155346 1.9036527
103 -6.4069890 -2.9155346
104 -7.3729313 -6.4069890
105 0.2141230 -7.3729313
106 0.3013988 0.2141230
107 -4.9724245 0.3013988
108 1.8418523 -4.9724245
109 64.9599316 1.8418523
110 61.1208167 64.9599316
111 49.2160969 61.1208167
112 42.2513231 49.2160969
113 38.4847964 42.2513231
114 25.2679124 38.4847964
115 13.2295520 25.2679124
116 0.7389949 13.2295520
117 4.2155476 0.7389949
118 13.2382127 4.2155476
119 18.5261109 13.2382127
120 15.5772016 18.5261109
121 7.8633066 15.5772016
122 8.8114832 7.8633066
123 -0.2613024 8.8114832
124 -8.4728459 -0.2613024
125 -9.8645532 -8.4728459
126 -19.3322276 -9.8645532
127 -28.3113064 -19.3322276
128 -18.7453145 -28.3113064
129 -12.2398333 -18.7453145
130 -19.9567348 -12.2398333
131 -18.6882588 -19.9567348
132 -11.6849329 -18.6882588
133 -17.5424154 -11.6849329
134 -17.1713616 -17.5424154
135 -13.4555076 -17.1713616
136 -15.1674804 -13.4555076
137 -16.0564550 -15.1674804
138 -16.0012522 -16.0564550
139 -19.0485332 -16.0012522
140 -11.6468592 -19.0485332
141 -9.8134646 -11.6468592
142 -6.9204304 -9.8134646
143 1.5837279 -6.9204304
144 2.4820176 1.5837279
145 14.5259597 2.4820176
146 18.5585985 14.5259597
147 11.4625264 18.5585985
148 18.3068096 11.4625264
149 14.6076263 18.3068096
150 12.4585153 14.6076263
151 8.4251909 12.4585153
152 7.7598144 8.4251909
153 5.3979522 7.7598144
154 -1.6537728 5.3979522
155 7.3302410 -1.6537728
156 5.7852161 7.3302410
157 11.4930466 5.7852161
158 3.9747585 11.4930466
159 -3.2303906 3.9747585
160 4.1138925 -3.2303906
161 8.5299541 4.1138925
162 10.1041496 8.5299541
163 8.7708253 10.1041496
164 0.3151116 8.7708253
165 5.3079243 0.3151116
166 6.9028125 5.3079243
167 11.8209275 6.9028125
168 11.7832421 11.8209275
169 14.0565421 11.7832421
170 7.6437195 14.0565421
171 1.2656249 7.6437195
172 -2.1967091 1.2656249
173 -3.8353225 -2.1967091
174 -16.7828525 -3.8353225
175 -24.1429385 -16.7828525
176 -20.8032789 -24.1429385
177 -19.8295954 -20.8032789
178 -14.5541294 -19.8295954
179 -14.4538556 -14.5541294
180 -13.0226164 -14.4538556
181 -6.3922016 -13.0226164
182 -4.9172633 -6.3922016
183 -7.9904783 -4.9172633
184 -3.1214439 -7.9904783
185 -7.9096962 -3.1214439
186 -6.9481692 -7.9096962
187 -5.9678298 -6.9481692
188 -8.8134912 -5.9678298
189 -9.3144907 -8.8134912
190 -10.9719741 -9.3144907
191 -10.1201874 -10.9719741
192 -13.2393094 -10.1201874
193 -4.8385254 -13.2393094
194 0.6964168 -4.8385254
195 -5.1874362 0.6964168
196 -3.2796940 -5.1874362
197 -2.5919752 -3.2796940
198 -9.0980645 -2.5919752
199 -27.3647477 -9.0980645
200 -23.3294019 -27.3647477
201 -27.1493942 -23.3294019
202 -17.4006898 -27.1493942
203 -8.7120692 -17.4006898
204 -5.6881696 -8.7120692
205 -21.3090911 -5.6881696
206 -56.3876161 -21.3090911
207 -56.4921994 -56.3876161
208 -54.1623023 -56.4921994
209 -52.2273844 -54.1623023
210 15.5479628 -52.2273844
211 90.7398790 15.5479628
212 65.2608788 90.7398790
213 62.4391690 65.2608788
214 73.5688806 62.4391690
215 73.8061248 73.5688806
216 76.2789410 73.8061248
217 59.0774216 76.2789410
218 54.0702009 59.0774216
219 50.7248993 54.0702009
220 42.1045918 50.7248993
221 45.1823748 42.1045918
222 36.7492309 45.1823748
223 44.6183464 36.7492309
224 45.6010276 44.6183464
225 41.6090852 45.6010276
226 43.6980785 41.6090852
227 40.1572046 43.6980785
228 31.7728861 40.1572046
229 25.6238947 31.7728861
230 26.1208514 25.6238947
231 26.9779896 26.1208514
232 16.0880352 26.9779896
233 15.1494218 16.0880352
234 -4.7343562 15.1494218
235 -35.2061919 -4.7343562
236 -40.8810549 -35.2061919
237 -41.6508224 -40.8810549
238 -40.4098869 -41.6508224
239 -20.7833008 -40.4098869
240 -15.2165359 -20.7833008
241 -52.1946887 -15.2165359
242 -112.3117051 -52.1946887
243 -57.6406302 -112.3117051
244 -83.8574227 -57.6406302
245 -54.6131549 -83.8574227
246 30.9587737 -54.6131549
247 46.2827006 30.9587737
248 53.9659477 46.2827006
249 45.2842139 53.9659477
250 53.2405307 45.2842139
251 27.5310452 53.2405307
252 11.4801255 27.5310452
253 -9.5636733 11.4801255
254 28.6817306 -9.5636733
255 15.6642058 28.6817306
256 28.2214104 15.6642058
257 19.4615008 28.2214104
258 7.1254877 19.4615008
259 1.2793584 7.1254877
260 12.5620196 1.2793584
261 6.9122401 12.5620196
262 1.9160688 6.9122401
263 -1.2469599 1.9160688
264 -2.8986020 -1.2469599
265 -0.5825732 -2.8986020
266 5.6375536 -0.5825732
267 5.0217464 5.6375536
268 9.8520729 5.0217464
269 -0.2036593 9.8520729
270 2.0793003 -0.2036593
271 6.2402175 2.0793003
272 14.4079269 6.2402175
273 26.3003102 14.4079269
274 2.4276021 26.3003102
275 -17.3123730 2.4276021
276 16.6871848 -17.3123730
277 37.5436390 16.6871848
278 34.7157080 37.5436390
279 35.3089578 34.7157080
280 31.0276310 35.3089578
281 28.7229622 31.0276310
282 21.8750029 28.7229622
283 27.7708800 21.8750029
284 22.5570163 27.7708800
285 21.1272448 22.5570163
286 18.6560976 21.1272448
287 20.9311909 18.6560976
288 25.4350825 20.9311909
289 34.2656338 25.4350825
290 36.3090672 34.2656338
291 20.1046404 36.3090672
292 8.4129684 20.1046404
293 32.0174931 8.4129684
294 17.9024832 32.0174931
295 10.1426901 17.9024832
296 10.0240833 10.1426901
297 23.0892556 10.0240833
298 22.1273219 23.0892556
299 18.8818413 22.1273219
300 14.2676190 18.8818413
301 15.5486879 14.2676190
302 0.6717039 15.5486879
303 4.1141832 0.6717039
304 17.7303965 4.1141832
305 12.8077502 17.7303965
306 20.8760309 12.8077502
307 18.0884609 20.8760309
308 10.6661261 18.0884609
309 8.7015311 10.6661261
310 10.7368647 8.7015311
311 22.3669058 10.7368647
312 27.5831931 22.3669058
313 20.1933270 27.5831931
314 30.8512829 20.1933270
315 30.9864227 30.8512829
316 19.8530172 30.9864227
317 23.2257642 19.8530172
318 8.0109107 23.2257642
319 9.7935535 8.0109107
320 12.3916360 9.7935535
321 8.2251670 12.3916360
322 9.4656732 8.2251670
323 18.7239406 9.4656732
324 5.4377880 18.7239406
325 -1.2048790 5.4377880
326 5.4791362 -1.2048790
327 4.5079317 5.4791362
328 -7.3584232 4.5079317
329 -28.2942839 -7.3584232
330 -8.4391011 -28.2942839
331 -11.7826341 -8.4391011
332 -21.4069794 -11.7826341
333 -19.6874050 -21.4069794
334 -34.0635683 -19.6874050
335 -50.0654214 -34.0635683
336 -27.0966260 -50.0654214
337 -66.4896142 -27.0966260
338 -82.4422564 -66.4896142
339 -47.6193758 -82.4422564
340 -34.4149521 -47.6193758
341 -15.2466755 -34.4149521
342 -13.7704895 -15.2466755
343 -0.3387737 -13.7704895
344 8.8925312 -0.3387737
345 -6.7280069 8.8925312
346 -21.8523844 -6.7280069
347 -25.2971427 -21.8523844
348 -57.5438451 -25.2971427
349 -47.9825113 -57.5438451
350 -20.1495995 -47.9825113
351 -25.6984926 -20.1495995
352 -14.5734951 -25.6984926
353 -22.9393196 -14.5734951
354 -34.6501522 -22.9393196
355 -43.5749653 -34.6501522
356 -35.1379020 -43.5749653
357 -33.0055227 -35.1379020
358 -46.7218184 -33.0055227
359 -63.5100077 -46.7218184
360 NA -63.5100077
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -18.3479520 -41.0370827
[2,] 5.3551924 -18.3479520
[3,] 42.5513314 5.3551924
[4,] 75.1133192 42.5513314
[5,] 85.9268045 75.1133192
[6,] 72.7280546 85.9268045
[7,] 64.4865320 72.7280546
[8,] 63.1017333 64.4865320
[9,] 60.9956978 63.1017333
[10,] 57.8192216 60.9956978
[11,] 56.1279866 57.8192216
[12,] 49.0836840 56.1279866
[13,] 43.4476341 49.0836840
[14,] 45.2876125 43.4476341
[15,] 31.5825997 45.2876125
[16,] 25.7008436 31.5825997
[17,] 15.2048225 25.7008436
[18,] 1.4568631 15.2048225
[19,] -14.2986162 1.4568631
[20,] -17.6214004 -14.2986162
[21,] -16.9777971 -17.6214004
[22,] -8.7895261 -16.9777971
[23,] -6.3578839 -8.7895261
[24,] -12.1781576 -6.3578839
[25,] -15.7121970 -12.1781576
[26,] -1.2356977 -15.7121970
[27,] -5.8329416 -1.2356977
[28,] -11.3485059 -5.8329416
[29,] -16.5784717 -11.3485059
[30,] -7.0478637 -16.5784717
[31,] 14.2903328 -7.0478637
[32,] 21.6018061 14.2903328
[33,] 26.5882946 21.6018061
[34,] 35.8931186 26.5882946
[35,] 38.9378587 35.8931186
[36,] 23.8842062 38.9378587
[37,] 28.8536218 23.8842062
[38,] 26.6924485 28.8536218
[39,] 13.6287399 26.6924485
[40,] 16.6284204 13.6287399
[41,] 14.0657780 16.6284204
[42,] 13.4155153 14.0657780
[43,] 10.5046388 13.4155153
[44,] 4.9047318 10.5046388
[45,] 4.0483350 4.9047318
[46,] -0.1885745 4.0483350
[47,] -12.7993682 -0.1885745
[48,] -18.1324468 -12.7993682
[49,] -34.3630312 -18.1324468
[50,] -34.6633418 -34.3630312
[51,] -38.0226001 -34.6633418
[52,] -40.3066596 -38.0226001
[53,] -39.9251286 -40.3066596
[54,] -50.4765430 -39.9251286
[55,] -51.6405134 -50.4765430
[56,] -46.9884782 -51.6405134
[57,] -50.8513356 -46.9884782
[58,] -51.2496738 -50.8513356
[59,] -38.2610533 -51.2496738
[60,] -40.7266520 -38.2610533
[61,] -29.9952219 -40.7266520
[62,] -31.6345133 -29.9952219
[63,] -33.6472949 -31.6345133
[64,] -32.3185494 -33.6472949
[65,] -34.5331339 -32.3185494
[66,] -44.6795122 -34.5331339
[67,] -42.7535549 -44.6795122
[68,] -38.6964836 -42.7535549
[69,] -49.3807736 -38.6964836
[70,] -39.7110660 -49.3807736
[71,] -33.6840305 -39.7110660
[72,] -32.4786943 -33.6840305
[73,] -30.9964737 -32.4786943
[74,] -24.3812465 -30.9964737
[75,] -34.1177641 -24.3812465
[76,] -35.0185130 -34.1177641
[77,] -35.7202925 -35.0185130
[78,] -43.3930031 -35.7202925
[79,] -40.5263275 -43.3930031
[80,] -43.9737064 -40.5263275
[81,] -41.0259258 -43.9737064
[82,] -30.5062864 -41.0259258
[83,] -27.4451498 -30.5062864
[84,] -25.2871490 -27.4451498
[85,] -19.5820512 -25.2871490
[86,] -16.3544485 -19.5820512
[87,] -17.7242084 -16.3544485
[88,] -16.9439501 -17.7242084
[89,] -14.7511951 -16.9439501
[90,] -18.2870718 -14.7511951
[91,] -23.2992365 -18.2870718
[92,] -19.3341034 -23.2992365
[93,] -12.8017240 -19.3341034
[94,] -5.0413663 -12.8017240
[95,] -3.0156190 -5.0413663
[96,] -3.1494200 -3.0156190
[97,] -0.3555461 -3.1494200
[98,] 0.9707685 -0.3555461
[99,] 3.8027261 0.9707685
[100,] 7.1362148 3.8027261
[101,] 1.9036527 7.1362148
[102,] -2.9155346 1.9036527
[103,] -6.4069890 -2.9155346
[104,] -7.3729313 -6.4069890
[105,] 0.2141230 -7.3729313
[106,] 0.3013988 0.2141230
[107,] -4.9724245 0.3013988
[108,] 1.8418523 -4.9724245
[109,] 64.9599316 1.8418523
[110,] 61.1208167 64.9599316
[111,] 49.2160969 61.1208167
[112,] 42.2513231 49.2160969
[113,] 38.4847964 42.2513231
[114,] 25.2679124 38.4847964
[115,] 13.2295520 25.2679124
[116,] 0.7389949 13.2295520
[117,] 4.2155476 0.7389949
[118,] 13.2382127 4.2155476
[119,] 18.5261109 13.2382127
[120,] 15.5772016 18.5261109
[121,] 7.8633066 15.5772016
[122,] 8.8114832 7.8633066
[123,] -0.2613024 8.8114832
[124,] -8.4728459 -0.2613024
[125,] -9.8645532 -8.4728459
[126,] -19.3322276 -9.8645532
[127,] -28.3113064 -19.3322276
[128,] -18.7453145 -28.3113064
[129,] -12.2398333 -18.7453145
[130,] -19.9567348 -12.2398333
[131,] -18.6882588 -19.9567348
[132,] -11.6849329 -18.6882588
[133,] -17.5424154 -11.6849329
[134,] -17.1713616 -17.5424154
[135,] -13.4555076 -17.1713616
[136,] -15.1674804 -13.4555076
[137,] -16.0564550 -15.1674804
[138,] -16.0012522 -16.0564550
[139,] -19.0485332 -16.0012522
[140,] -11.6468592 -19.0485332
[141,] -9.8134646 -11.6468592
[142,] -6.9204304 -9.8134646
[143,] 1.5837279 -6.9204304
[144,] 2.4820176 1.5837279
[145,] 14.5259597 2.4820176
[146,] 18.5585985 14.5259597
[147,] 11.4625264 18.5585985
[148,] 18.3068096 11.4625264
[149,] 14.6076263 18.3068096
[150,] 12.4585153 14.6076263
[151,] 8.4251909 12.4585153
[152,] 7.7598144 8.4251909
[153,] 5.3979522 7.7598144
[154,] -1.6537728 5.3979522
[155,] 7.3302410 -1.6537728
[156,] 5.7852161 7.3302410
[157,] 11.4930466 5.7852161
[158,] 3.9747585 11.4930466
[159,] -3.2303906 3.9747585
[160,] 4.1138925 -3.2303906
[161,] 8.5299541 4.1138925
[162,] 10.1041496 8.5299541
[163,] 8.7708253 10.1041496
[164,] 0.3151116 8.7708253
[165,] 5.3079243 0.3151116
[166,] 6.9028125 5.3079243
[167,] 11.8209275 6.9028125
[168,] 11.7832421 11.8209275
[169,] 14.0565421 11.7832421
[170,] 7.6437195 14.0565421
[171,] 1.2656249 7.6437195
[172,] -2.1967091 1.2656249
[173,] -3.8353225 -2.1967091
[174,] -16.7828525 -3.8353225
[175,] -24.1429385 -16.7828525
[176,] -20.8032789 -24.1429385
[177,] -19.8295954 -20.8032789
[178,] -14.5541294 -19.8295954
[179,] -14.4538556 -14.5541294
[180,] -13.0226164 -14.4538556
[181,] -6.3922016 -13.0226164
[182,] -4.9172633 -6.3922016
[183,] -7.9904783 -4.9172633
[184,] -3.1214439 -7.9904783
[185,] -7.9096962 -3.1214439
[186,] -6.9481692 -7.9096962
[187,] -5.9678298 -6.9481692
[188,] -8.8134912 -5.9678298
[189,] -9.3144907 -8.8134912
[190,] -10.9719741 -9.3144907
[191,] -10.1201874 -10.9719741
[192,] -13.2393094 -10.1201874
[193,] -4.8385254 -13.2393094
[194,] 0.6964168 -4.8385254
[195,] -5.1874362 0.6964168
[196,] -3.2796940 -5.1874362
[197,] -2.5919752 -3.2796940
[198,] -9.0980645 -2.5919752
[199,] -27.3647477 -9.0980645
[200,] -23.3294019 -27.3647477
[201,] -27.1493942 -23.3294019
[202,] -17.4006898 -27.1493942
[203,] -8.7120692 -17.4006898
[204,] -5.6881696 -8.7120692
[205,] -21.3090911 -5.6881696
[206,] -56.3876161 -21.3090911
[207,] -56.4921994 -56.3876161
[208,] -54.1623023 -56.4921994
[209,] -52.2273844 -54.1623023
[210,] 15.5479628 -52.2273844
[211,] 90.7398790 15.5479628
[212,] 65.2608788 90.7398790
[213,] 62.4391690 65.2608788
[214,] 73.5688806 62.4391690
[215,] 73.8061248 73.5688806
[216,] 76.2789410 73.8061248
[217,] 59.0774216 76.2789410
[218,] 54.0702009 59.0774216
[219,] 50.7248993 54.0702009
[220,] 42.1045918 50.7248993
[221,] 45.1823748 42.1045918
[222,] 36.7492309 45.1823748
[223,] 44.6183464 36.7492309
[224,] 45.6010276 44.6183464
[225,] 41.6090852 45.6010276
[226,] 43.6980785 41.6090852
[227,] 40.1572046 43.6980785
[228,] 31.7728861 40.1572046
[229,] 25.6238947 31.7728861
[230,] 26.1208514 25.6238947
[231,] 26.9779896 26.1208514
[232,] 16.0880352 26.9779896
[233,] 15.1494218 16.0880352
[234,] -4.7343562 15.1494218
[235,] -35.2061919 -4.7343562
[236,] -40.8810549 -35.2061919
[237,] -41.6508224 -40.8810549
[238,] -40.4098869 -41.6508224
[239,] -20.7833008 -40.4098869
[240,] -15.2165359 -20.7833008
[241,] -52.1946887 -15.2165359
[242,] -112.3117051 -52.1946887
[243,] -57.6406302 -112.3117051
[244,] -83.8574227 -57.6406302
[245,] -54.6131549 -83.8574227
[246,] 30.9587737 -54.6131549
[247,] 46.2827006 30.9587737
[248,] 53.9659477 46.2827006
[249,] 45.2842139 53.9659477
[250,] 53.2405307 45.2842139
[251,] 27.5310452 53.2405307
[252,] 11.4801255 27.5310452
[253,] -9.5636733 11.4801255
[254,] 28.6817306 -9.5636733
[255,] 15.6642058 28.6817306
[256,] 28.2214104 15.6642058
[257,] 19.4615008 28.2214104
[258,] 7.1254877 19.4615008
[259,] 1.2793584 7.1254877
[260,] 12.5620196 1.2793584
[261,] 6.9122401 12.5620196
[262,] 1.9160688 6.9122401
[263,] -1.2469599 1.9160688
[264,] -2.8986020 -1.2469599
[265,] -0.5825732 -2.8986020
[266,] 5.6375536 -0.5825732
[267,] 5.0217464 5.6375536
[268,] 9.8520729 5.0217464
[269,] -0.2036593 9.8520729
[270,] 2.0793003 -0.2036593
[271,] 6.2402175 2.0793003
[272,] 14.4079269 6.2402175
[273,] 26.3003102 14.4079269
[274,] 2.4276021 26.3003102
[275,] -17.3123730 2.4276021
[276,] 16.6871848 -17.3123730
[277,] 37.5436390 16.6871848
[278,] 34.7157080 37.5436390
[279,] 35.3089578 34.7157080
[280,] 31.0276310 35.3089578
[281,] 28.7229622 31.0276310
[282,] 21.8750029 28.7229622
[283,] 27.7708800 21.8750029
[284,] 22.5570163 27.7708800
[285,] 21.1272448 22.5570163
[286,] 18.6560976 21.1272448
[287,] 20.9311909 18.6560976
[288,] 25.4350825 20.9311909
[289,] 34.2656338 25.4350825
[290,] 36.3090672 34.2656338
[291,] 20.1046404 36.3090672
[292,] 8.4129684 20.1046404
[293,] 32.0174931 8.4129684
[294,] 17.9024832 32.0174931
[295,] 10.1426901 17.9024832
[296,] 10.0240833 10.1426901
[297,] 23.0892556 10.0240833
[298,] 22.1273219 23.0892556
[299,] 18.8818413 22.1273219
[300,] 14.2676190 18.8818413
[301,] 15.5486879 14.2676190
[302,] 0.6717039 15.5486879
[303,] 4.1141832 0.6717039
[304,] 17.7303965 4.1141832
[305,] 12.8077502 17.7303965
[306,] 20.8760309 12.8077502
[307,] 18.0884609 20.8760309
[308,] 10.6661261 18.0884609
[309,] 8.7015311 10.6661261
[310,] 10.7368647 8.7015311
[311,] 22.3669058 10.7368647
[312,] 27.5831931 22.3669058
[313,] 20.1933270 27.5831931
[314,] 30.8512829 20.1933270
[315,] 30.9864227 30.8512829
[316,] 19.8530172 30.9864227
[317,] 23.2257642 19.8530172
[318,] 8.0109107 23.2257642
[319,] 9.7935535 8.0109107
[320,] 12.3916360 9.7935535
[321,] 8.2251670 12.3916360
[322,] 9.4656732 8.2251670
[323,] 18.7239406 9.4656732
[324,] 5.4377880 18.7239406
[325,] -1.2048790 5.4377880
[326,] 5.4791362 -1.2048790
[327,] 4.5079317 5.4791362
[328,] -7.3584232 4.5079317
[329,] -28.2942839 -7.3584232
[330,] -8.4391011 -28.2942839
[331,] -11.7826341 -8.4391011
[332,] -21.4069794 -11.7826341
[333,] -19.6874050 -21.4069794
[334,] -34.0635683 -19.6874050
[335,] -50.0654214 -34.0635683
[336,] -27.0966260 -50.0654214
[337,] -66.4896142 -27.0966260
[338,] -82.4422564 -66.4896142
[339,] -47.6193758 -82.4422564
[340,] -34.4149521 -47.6193758
[341,] -15.2466755 -34.4149521
[342,] -13.7704895 -15.2466755
[343,] -0.3387737 -13.7704895
[344,] 8.8925312 -0.3387737
[345,] -6.7280069 8.8925312
[346,] -21.8523844 -6.7280069
[347,] -25.2971427 -21.8523844
[348,] -57.5438451 -25.2971427
[349,] -47.9825113 -57.5438451
[350,] -20.1495995 -47.9825113
[351,] -25.6984926 -20.1495995
[352,] -14.5734951 -25.6984926
[353,] -22.9393196 -14.5734951
[354,] -34.6501522 -22.9393196
[355,] -43.5749653 -34.6501522
[356,] -35.1379020 -43.5749653
[357,] -33.0055227 -35.1379020
[358,] -46.7218184 -33.0055227
[359,] -63.5100077 -46.7218184
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -18.3479520 -41.0370827
2 5.3551924 -18.3479520
3 42.5513314 5.3551924
4 75.1133192 42.5513314
5 85.9268045 75.1133192
6 72.7280546 85.9268045
7 64.4865320 72.7280546
8 63.1017333 64.4865320
9 60.9956978 63.1017333
10 57.8192216 60.9956978
11 56.1279866 57.8192216
12 49.0836840 56.1279866
13 43.4476341 49.0836840
14 45.2876125 43.4476341
15 31.5825997 45.2876125
16 25.7008436 31.5825997
17 15.2048225 25.7008436
18 1.4568631 15.2048225
19 -14.2986162 1.4568631
20 -17.6214004 -14.2986162
21 -16.9777971 -17.6214004
22 -8.7895261 -16.9777971
23 -6.3578839 -8.7895261
24 -12.1781576 -6.3578839
25 -15.7121970 -12.1781576
26 -1.2356977 -15.7121970
27 -5.8329416 -1.2356977
28 -11.3485059 -5.8329416
29 -16.5784717 -11.3485059
30 -7.0478637 -16.5784717
31 14.2903328 -7.0478637
32 21.6018061 14.2903328
33 26.5882946 21.6018061
34 35.8931186 26.5882946
35 38.9378587 35.8931186
36 23.8842062 38.9378587
37 28.8536218 23.8842062
38 26.6924485 28.8536218
39 13.6287399 26.6924485
40 16.6284204 13.6287399
41 14.0657780 16.6284204
42 13.4155153 14.0657780
43 10.5046388 13.4155153
44 4.9047318 10.5046388
45 4.0483350 4.9047318
46 -0.1885745 4.0483350
47 -12.7993682 -0.1885745
48 -18.1324468 -12.7993682
49 -34.3630312 -18.1324468
50 -34.6633418 -34.3630312
51 -38.0226001 -34.6633418
52 -40.3066596 -38.0226001
53 -39.9251286 -40.3066596
54 -50.4765430 -39.9251286
55 -51.6405134 -50.4765430
56 -46.9884782 -51.6405134
57 -50.8513356 -46.9884782
58 -51.2496738 -50.8513356
59 -38.2610533 -51.2496738
60 -40.7266520 -38.2610533
61 -29.9952219 -40.7266520
62 -31.6345133 -29.9952219
63 -33.6472949 -31.6345133
64 -32.3185494 -33.6472949
65 -34.5331339 -32.3185494
66 -44.6795122 -34.5331339
67 -42.7535549 -44.6795122
68 -38.6964836 -42.7535549
69 -49.3807736 -38.6964836
70 -39.7110660 -49.3807736
71 -33.6840305 -39.7110660
72 -32.4786943 -33.6840305
73 -30.9964737 -32.4786943
74 -24.3812465 -30.9964737
75 -34.1177641 -24.3812465
76 -35.0185130 -34.1177641
77 -35.7202925 -35.0185130
78 -43.3930031 -35.7202925
79 -40.5263275 -43.3930031
80 -43.9737064 -40.5263275
81 -41.0259258 -43.9737064
82 -30.5062864 -41.0259258
83 -27.4451498 -30.5062864
84 -25.2871490 -27.4451498
85 -19.5820512 -25.2871490
86 -16.3544485 -19.5820512
87 -17.7242084 -16.3544485
88 -16.9439501 -17.7242084
89 -14.7511951 -16.9439501
90 -18.2870718 -14.7511951
91 -23.2992365 -18.2870718
92 -19.3341034 -23.2992365
93 -12.8017240 -19.3341034
94 -5.0413663 -12.8017240
95 -3.0156190 -5.0413663
96 -3.1494200 -3.0156190
97 -0.3555461 -3.1494200
98 0.9707685 -0.3555461
99 3.8027261 0.9707685
100 7.1362148 3.8027261
101 1.9036527 7.1362148
102 -2.9155346 1.9036527
103 -6.4069890 -2.9155346
104 -7.3729313 -6.4069890
105 0.2141230 -7.3729313
106 0.3013988 0.2141230
107 -4.9724245 0.3013988
108 1.8418523 -4.9724245
109 64.9599316 1.8418523
110 61.1208167 64.9599316
111 49.2160969 61.1208167
112 42.2513231 49.2160969
113 38.4847964 42.2513231
114 25.2679124 38.4847964
115 13.2295520 25.2679124
116 0.7389949 13.2295520
117 4.2155476 0.7389949
118 13.2382127 4.2155476
119 18.5261109 13.2382127
120 15.5772016 18.5261109
121 7.8633066 15.5772016
122 8.8114832 7.8633066
123 -0.2613024 8.8114832
124 -8.4728459 -0.2613024
125 -9.8645532 -8.4728459
126 -19.3322276 -9.8645532
127 -28.3113064 -19.3322276
128 -18.7453145 -28.3113064
129 -12.2398333 -18.7453145
130 -19.9567348 -12.2398333
131 -18.6882588 -19.9567348
132 -11.6849329 -18.6882588
133 -17.5424154 -11.6849329
134 -17.1713616 -17.5424154
135 -13.4555076 -17.1713616
136 -15.1674804 -13.4555076
137 -16.0564550 -15.1674804
138 -16.0012522 -16.0564550
139 -19.0485332 -16.0012522
140 -11.6468592 -19.0485332
141 -9.8134646 -11.6468592
142 -6.9204304 -9.8134646
143 1.5837279 -6.9204304
144 2.4820176 1.5837279
145 14.5259597 2.4820176
146 18.5585985 14.5259597
147 11.4625264 18.5585985
148 18.3068096 11.4625264
149 14.6076263 18.3068096
150 12.4585153 14.6076263
151 8.4251909 12.4585153
152 7.7598144 8.4251909
153 5.3979522 7.7598144
154 -1.6537728 5.3979522
155 7.3302410 -1.6537728
156 5.7852161 7.3302410
157 11.4930466 5.7852161
158 3.9747585 11.4930466
159 -3.2303906 3.9747585
160 4.1138925 -3.2303906
161 8.5299541 4.1138925
162 10.1041496 8.5299541
163 8.7708253 10.1041496
164 0.3151116 8.7708253
165 5.3079243 0.3151116
166 6.9028125 5.3079243
167 11.8209275 6.9028125
168 11.7832421 11.8209275
169 14.0565421 11.7832421
170 7.6437195 14.0565421
171 1.2656249 7.6437195
172 -2.1967091 1.2656249
173 -3.8353225 -2.1967091
174 -16.7828525 -3.8353225
175 -24.1429385 -16.7828525
176 -20.8032789 -24.1429385
177 -19.8295954 -20.8032789
178 -14.5541294 -19.8295954
179 -14.4538556 -14.5541294
180 -13.0226164 -14.4538556
181 -6.3922016 -13.0226164
182 -4.9172633 -6.3922016
183 -7.9904783 -4.9172633
184 -3.1214439 -7.9904783
185 -7.9096962 -3.1214439
186 -6.9481692 -7.9096962
187 -5.9678298 -6.9481692
188 -8.8134912 -5.9678298
189 -9.3144907 -8.8134912
190 -10.9719741 -9.3144907
191 -10.1201874 -10.9719741
192 -13.2393094 -10.1201874
193 -4.8385254 -13.2393094
194 0.6964168 -4.8385254
195 -5.1874362 0.6964168
196 -3.2796940 -5.1874362
197 -2.5919752 -3.2796940
198 -9.0980645 -2.5919752
199 -27.3647477 -9.0980645
200 -23.3294019 -27.3647477
201 -27.1493942 -23.3294019
202 -17.4006898 -27.1493942
203 -8.7120692 -17.4006898
204 -5.6881696 -8.7120692
205 -21.3090911 -5.6881696
206 -56.3876161 -21.3090911
207 -56.4921994 -56.3876161
208 -54.1623023 -56.4921994
209 -52.2273844 -54.1623023
210 15.5479628 -52.2273844
211 90.7398790 15.5479628
212 65.2608788 90.7398790
213 62.4391690 65.2608788
214 73.5688806 62.4391690
215 73.8061248 73.5688806
216 76.2789410 73.8061248
217 59.0774216 76.2789410
218 54.0702009 59.0774216
219 50.7248993 54.0702009
220 42.1045918 50.7248993
221 45.1823748 42.1045918
222 36.7492309 45.1823748
223 44.6183464 36.7492309
224 45.6010276 44.6183464
225 41.6090852 45.6010276
226 43.6980785 41.6090852
227 40.1572046 43.6980785
228 31.7728861 40.1572046
229 25.6238947 31.7728861
230 26.1208514 25.6238947
231 26.9779896 26.1208514
232 16.0880352 26.9779896
233 15.1494218 16.0880352
234 -4.7343562 15.1494218
235 -35.2061919 -4.7343562
236 -40.8810549 -35.2061919
237 -41.6508224 -40.8810549
238 -40.4098869 -41.6508224
239 -20.7833008 -40.4098869
240 -15.2165359 -20.7833008
241 -52.1946887 -15.2165359
242 -112.3117051 -52.1946887
243 -57.6406302 -112.3117051
244 -83.8574227 -57.6406302
245 -54.6131549 -83.8574227
246 30.9587737 -54.6131549
247 46.2827006 30.9587737
248 53.9659477 46.2827006
249 45.2842139 53.9659477
250 53.2405307 45.2842139
251 27.5310452 53.2405307
252 11.4801255 27.5310452
253 -9.5636733 11.4801255
254 28.6817306 -9.5636733
255 15.6642058 28.6817306
256 28.2214104 15.6642058
257 19.4615008 28.2214104
258 7.1254877 19.4615008
259 1.2793584 7.1254877
260 12.5620196 1.2793584
261 6.9122401 12.5620196
262 1.9160688 6.9122401
263 -1.2469599 1.9160688
264 -2.8986020 -1.2469599
265 -0.5825732 -2.8986020
266 5.6375536 -0.5825732
267 5.0217464 5.6375536
268 9.8520729 5.0217464
269 -0.2036593 9.8520729
270 2.0793003 -0.2036593
271 6.2402175 2.0793003
272 14.4079269 6.2402175
273 26.3003102 14.4079269
274 2.4276021 26.3003102
275 -17.3123730 2.4276021
276 16.6871848 -17.3123730
277 37.5436390 16.6871848
278 34.7157080 37.5436390
279 35.3089578 34.7157080
280 31.0276310 35.3089578
281 28.7229622 31.0276310
282 21.8750029 28.7229622
283 27.7708800 21.8750029
284 22.5570163 27.7708800
285 21.1272448 22.5570163
286 18.6560976 21.1272448
287 20.9311909 18.6560976
288 25.4350825 20.9311909
289 34.2656338 25.4350825
290 36.3090672 34.2656338
291 20.1046404 36.3090672
292 8.4129684 20.1046404
293 32.0174931 8.4129684
294 17.9024832 32.0174931
295 10.1426901 17.9024832
296 10.0240833 10.1426901
297 23.0892556 10.0240833
298 22.1273219 23.0892556
299 18.8818413 22.1273219
300 14.2676190 18.8818413
301 15.5486879 14.2676190
302 0.6717039 15.5486879
303 4.1141832 0.6717039
304 17.7303965 4.1141832
305 12.8077502 17.7303965
306 20.8760309 12.8077502
307 18.0884609 20.8760309
308 10.6661261 18.0884609
309 8.7015311 10.6661261
310 10.7368647 8.7015311
311 22.3669058 10.7368647
312 27.5831931 22.3669058
313 20.1933270 27.5831931
314 30.8512829 20.1933270
315 30.9864227 30.8512829
316 19.8530172 30.9864227
317 23.2257642 19.8530172
318 8.0109107 23.2257642
319 9.7935535 8.0109107
320 12.3916360 9.7935535
321 8.2251670 12.3916360
322 9.4656732 8.2251670
323 18.7239406 9.4656732
324 5.4377880 18.7239406
325 -1.2048790 5.4377880
326 5.4791362 -1.2048790
327 4.5079317 5.4791362
328 -7.3584232 4.5079317
329 -28.2942839 -7.3584232
330 -8.4391011 -28.2942839
331 -11.7826341 -8.4391011
332 -21.4069794 -11.7826341
333 -19.6874050 -21.4069794
334 -34.0635683 -19.6874050
335 -50.0654214 -34.0635683
336 -27.0966260 -50.0654214
337 -66.4896142 -27.0966260
338 -82.4422564 -66.4896142
339 -47.6193758 -82.4422564
340 -34.4149521 -47.6193758
341 -15.2466755 -34.4149521
342 -13.7704895 -15.2466755
343 -0.3387737 -13.7704895
344 8.8925312 -0.3387737
345 -6.7280069 8.8925312
346 -21.8523844 -6.7280069
347 -25.2971427 -21.8523844
348 -57.5438451 -25.2971427
349 -47.9825113 -57.5438451
350 -20.1495995 -47.9825113
351 -25.6984926 -20.1495995
352 -14.5734951 -25.6984926
353 -22.9393196 -14.5734951
354 -34.6501522 -22.9393196
355 -43.5749653 -34.6501522
356 -35.1379020 -43.5749653
357 -33.0055227 -35.1379020
358 -46.7218184 -33.0055227
359 -63.5100077 -46.7218184
> 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/wessaorg/rcomp/tmp/7copc1351857978.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/8do291351857978.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/9o24t1351857978.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/wessaorg/rcomp/tmp/10t2kr1351857978.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/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$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
+ }
+ }
> myeq <- paste(myeq, ' + e[t]')
> a<-table.row.start(a)
> a<-table.element(a, myeq)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/11lr5z1351857978.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Variable',header=TRUE)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
> a<-table.element(a,'2-tail p-value',header=TRUE)
> a<-table.element(a,'1-tail p-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:k){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(mysum$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$coefficients[i,4]/2,6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/1224ml1351857978.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple R',1,TRUE)
> a<-table.element(a, sqrt(mysum$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$sigma)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a, sum(myerror*myerror))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/132n6r1351857978.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Time or Index', 1, TRUE)
> a<-table.element(a, 'Actuals', 1, TRUE)
> a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
> a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
> a<-table.row.end(a)
> for (i in 1:n) {
+ a<-table.row.start(a)
+ a<-table.element(a,i, 1, TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]-mysum$resid[i])
+ a<-table.element(a,mysum$resid[i])
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/14vvmm1351857978.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/wessaorg/rcomp/tmp/15trex1351857978.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/wessaorg/rcomp/tmp/16egld1351857978.tab")
+ }
>
> try(system("convert tmp/1bqz31351857978.ps tmp/1bqz31351857978.png",intern=TRUE))
character(0)
> try(system("convert tmp/2542q1351857978.ps tmp/2542q1351857978.png",intern=TRUE))
character(0)
> try(system("convert tmp/3335l1351857978.ps tmp/3335l1351857978.png",intern=TRUE))
character(0)
> try(system("convert tmp/4tpdp1351857978.ps tmp/4tpdp1351857978.png",intern=TRUE))
character(0)
> try(system("convert tmp/53asc1351857978.ps tmp/53asc1351857978.png",intern=TRUE))
character(0)
> try(system("convert tmp/64fq11351857978.ps tmp/64fq11351857978.png",intern=TRUE))
character(0)
> try(system("convert tmp/7copc1351857978.ps tmp/7copc1351857978.png",intern=TRUE))
character(0)
> try(system("convert tmp/8do291351857978.ps tmp/8do291351857978.png",intern=TRUE))
character(0)
> try(system("convert tmp/9o24t1351857978.ps tmp/9o24t1351857978.png",intern=TRUE))
character(0)
> try(system("convert tmp/10t2kr1351857978.ps tmp/10t2kr1351857978.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
16.940 1.009 17.957