R version 2.13.0 (2011-04-13)
Copyright (C) 2011 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-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 Quarterly Dummies'
> par1 = '2'
> #'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
> 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 Q1 Q2 Q3 t
1 255.0 87.28 1 0 0 1
2 280.2 87.28 0 1 0 2
3 299.9 87.09 0 0 1 3
4 339.2 86.92 0 0 0 4
5 374.2 87.59 1 0 0 5
6 393.5 90.72 0 1 0 6
7 389.2 90.69 0 0 1 7
8 381.7 90.30 0 0 0 8
9 375.2 89.55 1 0 0 9
10 369.0 88.94 0 1 0 10
11 357.4 88.41 0 0 1 11
12 352.1 87.82 0 0 0 12
13 346.5 87.07 1 0 0 13
14 342.9 86.82 0 1 0 14
15 340.3 86.40 0 0 1 15
16 328.3 86.02 0 0 0 16
17 322.9 85.66 1 0 0 17
18 314.3 85.32 0 1 0 18
19 308.9 85.00 0 0 1 19
20 294.0 84.67 0 0 0 20
21 285.6 83.94 1 0 0 21
22 281.2 82.83 0 1 0 22
23 280.3 81.95 0 0 1 23
24 278.8 81.19 0 0 0 24
25 274.5 80.48 1 0 0 25
26 270.4 78.86 0 1 0 26
27 263.4 69.47 0 0 1 27
28 259.9 68.77 0 0 0 28
29 258.0 70.06 1 0 0 29
30 262.7 73.95 0 1 0 30
31 284.7 75.80 0 0 1 31
32 311.3 77.79 0 0 0 32
33 322.1 81.57 1 0 0 33
34 327.0 83.07 0 1 0 34
35 331.3 84.34 0 0 1 35
36 333.3 85.10 0 0 0 36
37 321.4 85.25 1 0 0 37
38 327.0 84.26 0 1 0 38
39 320.0 83.63 0 0 1 39
40 314.7 86.44 0 0 0 40
41 316.7 85.30 1 0 0 41
42 314.4 84.10 0 1 0 42
43 321.3 83.36 0 0 1 43
44 318.2 82.48 0 0 0 44
45 307.2 81.58 1 0 0 45
46 301.3 80.47 0 1 0 46
47 287.5 79.34 0 0 1 47
48 277.7 82.13 0 0 0 48
49 274.4 81.69 1 0 0 49
50 258.8 80.70 0 1 0 50
51 253.3 79.88 0 0 1 51
52 251.0 79.16 0 0 0 52
53 248.4 78.38 1 0 0 53
54 249.5 77.42 0 1 0 54
55 246.1 76.47 0 0 1 55
56 244.5 75.46 0 0 0 56
57 243.6 74.48 1 0 0 57
58 244.0 78.27 0 1 0 58
59 240.8 80.70 0 0 1 59
60 249.8 79.91 0 0 0 60
61 248.0 78.75 1 0 0 61
62 259.4 77.78 0 1 0 62
63 260.5 81.14 0 0 1 63
64 260.8 81.08 0 0 0 64
65 261.3 80.03 1 0 0 65
66 259.5 78.91 0 1 0 66
67 256.6 78.01 0 0 1 67
68 257.9 76.90 0 0 0 68
69 256.5 75.97 1 0 0 69
70 254.2 81.93 0 1 0 70
71 253.3 80.27 0 0 1 71
72 253.8 78.67 0 0 0 72
73 255.5 77.42 1 0 0 73
74 257.1 76.16 0 1 0 74
75 257.3 74.70 0 0 1 75
76 253.2 76.39 0 0 0 76
77 252.8 76.04 1 0 0 77
78 252.0 74.65 0 1 0 78
79 250.7 73.29 0 0 1 79
80 252.2 71.79 0 0 0 80
81 250.0 74.39 1 0 0 81
82 251.0 74.91 0 1 0 82
83 253.4 74.54 0 0 1 83
84 251.2 73.08 0 0 0 84
85 255.6 72.75 1 0 0 85
86 261.1 71.32 0 1 0 86
87 258.9 70.38 0 0 1 87
88 259.9 70.35 0 0 0 88
89 261.2 70.01 1 0 0 89
90 264.7 69.36 0 1 0 90
91 267.1 67.77 0 0 1 91
92 266.4 69.26 0 0 0 92
93 267.7 69.80 1 0 0 93
94 268.6 68.38 0 1 0 94
95 267.5 67.62 0 0 1 95
96 268.5 68.39 0 0 0 96
97 268.5 66.95 1 0 0 97
98 270.5 65.21 0 1 0 98
99 270.9 66.64 0 0 1 99
100 270.1 63.45 0 0 0 100
101 269.3 60.66 1 0 0 101
102 269.8 62.34 0 1 0 102
103 270.1 60.32 0 0 1 103
104 264.9 58.64 0 0 0 104
105 263.7 60.46 1 0 0 105
106 264.8 58.59 0 1 0 106
107 263.7 61.87 0 0 1 107
108 255.9 61.85 0 0 0 108
109 276.2 67.44 1 0 0 109
110 360.1 77.06 0 1 0 110
111 380.5 91.74 0 0 1 111
112 373.7 93.15 0 0 0 112
113 369.8 94.15 1 0 0 113
114 366.6 93.11 0 1 0 114
115 359.3 91.51 0 0 1 115
116 345.8 89.96 0 0 0 116
117 326.2 88.16 1 0 0 117
118 324.5 86.98 0 1 0 118
119 328.1 88.03 0 0 1 119
120 327.5 86.24 0 0 0 120
121 324.4 84.65 1 0 0 121
122 316.5 83.23 0 1 0 122
123 310.9 81.70 0 0 1 123
124 301.5 80.25 0 0 0 124
125 291.7 78.80 1 0 0 125
126 290.4 77.51 0 1 0 126
127 287.4 76.20 0 0 1 127
128 277.7 75.04 0 0 0 128
129 281.6 74.00 1 0 0 129
130 288.0 75.49 0 1 0 130
131 276.0 77.14 0 0 1 131
132 272.9 76.15 0 0 0 132
133 283.0 76.27 1 0 0 133
134 283.3 78.19 0 1 0 134
135 276.8 76.49 0 0 1 135
136 284.5 77.31 0 0 0 136
137 282.7 76.65 1 0 0 137
138 281.2 74.99 0 1 0 138
139 287.4 73.51 0 0 1 139
140 283.1 72.07 0 0 0 140
141 284.0 70.59 1 0 0 141
142 285.5 71.96 0 1 0 142
143 289.2 76.29 0 0 1 143
144 292.5 74.86 0 0 0 144
145 296.4 74.93 1 0 0 145
146 305.2 71.90 0 1 0 146
147 303.9 71.01 0 0 1 147
148 311.5 77.47 0 0 0 148
149 316.3 75.78 1 0 0 149
150 316.7 76.60 0 1 0 150
151 322.5 76.07 0 0 1 151
152 317.1 74.57 0 0 0 152
153 309.8 73.02 1 0 0 153
154 303.8 72.65 0 1 0 154
155 290.3 73.16 0 0 1 155
156 293.7 71.53 0 0 0 156
157 291.7 69.78 1 0 0 157
158 296.5 67.98 0 1 0 158
159 289.1 69.96 0 0 1 159
160 288.5 72.16 0 0 0 160
161 293.8 70.47 1 0 0 161
162 297.7 68.86 0 1 0 162
163 305.4 67.37 0 0 1 163
164 302.7 65.87 0 0 0 164
165 302.5 72.16 1 0 0 165
166 303.0 71.34 0 1 0 166
167 294.5 69.93 0 0 1 167
168 294.1 68.44 0 0 0 168
169 294.5 67.16 1 0 0 169
170 297.1 66.01 0 1 0 170
171 289.4 67.25 0 0 1 171
172 292.4 70.91 0 0 0 172
173 287.9 69.75 1 0 0 173
174 286.6 68.59 0 1 0 174
175 280.5 67.48 0 0 1 175
176 272.4 66.31 0 0 0 176
177 269.2 64.81 1 0 0 177
178 270.6 66.58 0 1 0 178
179 267.3 65.97 0 0 1 179
180 262.5 64.70 0 0 0 180
181 266.8 64.70 1 0 0 181
182 268.8 60.94 0 1 0 182
183 263.1 59.08 0 0 1 183
184 261.2 58.42 0 0 0 184
185 266.0 57.77 1 0 0 185
186 262.5 57.11 0 1 0 186
187 265.2 53.31 0 0 1 187
188 261.3 49.96 0 0 0 188
189 253.7 49.40 1 0 0 189
190 249.2 48.84 0 1 0 190
191 239.1 48.30 0 0 1 191
192 236.4 47.74 0 0 0 192
193 235.2 47.24 1 0 0 193
194 245.2 46.76 0 1 0 194
195 246.2 46.29 0 0 1 195
196 247.7 48.90 0 0 0 196
197 251.4 49.23 1 0 0 197
198 253.3 48.53 0 1 0 198
199 254.8 48.03 0 0 1 199
200 250.0 54.34 0 0 0 200
201 249.3 53.79 1 0 0 201
202 241.5 53.24 0 1 0 202
203 243.3 52.96 0 0 1 203
204 248.0 52.17 0 0 0 204
205 253.0 51.70 1 0 0 205
206 252.9 58.55 0 1 0 206
207 251.5 78.20 0 0 1 207
208 251.6 77.03 0 0 0 208
209 253.5 76.19 1 0 0 209
210 259.8 77.15 0 1 0 210
211 334.1 75.87 0 0 1 211
212 448.0 95.47 0 0 0 212
213 445.8 109.67 1 0 0 213
214 445.0 112.28 0 1 0 214
215 448.2 112.01 0 0 1 215
216 438.2 107.93 0 0 0 216
217 439.8 105.96 1 0 0 217
218 423.4 105.06 0 1 0 218
219 410.8 102.98 0 0 1 219
220 408.4 102.20 0 0 0 220
221 406.7 105.23 1 0 0 221
222 405.9 101.85 0 1 0 222
223 402.7 99.89 0 0 1 223
224 405.1 96.23 0 0 0 224
225 399.6 94.76 1 0 0 225
226 386.5 91.51 0 1 0 226
227 381.4 91.63 0 0 1 227
228 375.2 91.54 0 0 0 228
229 357.7 85.23 1 0 0 229
230 359.0 87.83 0 1 0 230
231 355.0 87.38 0 0 1 231
232 352.7 84.44 0 0 0 232
233 344.4 85.19 1 0 0 233
234 343.8 84.03 0 1 0 234
235 338.0 86.73 0 0 1 235
236 339.0 102.52 0 0 0 236
237 333.3 104.45 1 0 0 237
238 334.4 106.98 0 1 0 238
239 328.3 107.02 0 0 1 239
240 330.7 99.26 0 0 0 240
241 330.0 94.45 1 0 0 241
242 331.6 113.44 0 1 0 242
243 351.2 157.33 0 0 1 243
244 389.4 147.38 0 0 0 244
245 410.9 171.89 1 0 0 245
246 442.8 171.95 0 1 0 246
247 462.8 132.71 0 0 1 247
248 466.9 126.02 0 0 0 248
249 461.7 121.18 1 0 0 249
250 439.2 115.45 0 1 0 250
251 430.3 110.48 0 0 1 251
252 416.1 117.85 0 0 0 252
253 402.5 117.63 1 0 0 253
254 397.3 124.65 0 1 0 254
255 403.3 109.59 0 0 1 255
256 395.9 111.27 0 0 0 256
257 387.8 99.78 1 0 0 257
258 378.6 98.21 0 1 0 258
259 377.1 99.20 0 0 1 259
260 370.4 97.97 0 0 0 260
261 362.0 89.55 1 0 0 261
262 350.3 87.91 0 1 0 262
263 348.2 93.34 0 0 1 263
264 344.6 94.42 0 0 0 264
265 343.5 93.20 1 0 0 265
266 342.8 90.29 0 1 0 266
267 347.6 91.46 0 0 1 267
268 346.6 89.98 0 0 0 268
269 349.5 88.35 1 0 0 269
270 342.1 88.41 0 1 0 270
271 342.0 82.44 0 0 1 271
272 342.8 79.89 0 0 0 272
273 339.3 75.69 1 0 0 273
274 348.2 75.66 0 1 0 274
275 333.7 84.50 0 0 1 275
276 334.7 96.73 0 0 0 276
277 354.0 87.48 1 0 0 277
278 367.7 82.39 0 1 0 278
279 363.3 83.48 0 0 1 279
280 358.4 79.31 0 0 0 280
281 353.1 78.16 1 0 0 281
282 343.1 72.77 0 1 0 282
283 344.6 72.45 0 0 1 283
284 344.4 68.46 0 0 0 284
285 333.9 67.62 1 0 0 285
286 331.7 68.76 0 1 0 286
287 324.3 70.07 0 0 1 287
288 321.2 68.55 0 0 0 288
289 322.4 65.30 1 0 0 289
290 321.7 58.96 0 1 0 290
291 320.5 59.17 0 0 1 291
292 312.8 62.37 0 0 0 292
293 309.7 66.28 1 0 0 293
294 315.6 55.62 0 1 0 294
295 309.7 55.23 0 0 1 295
296 304.6 55.85 0 0 0 296
297 302.5 56.75 1 0 0 297
298 301.5 50.89 0 1 0 298
299 298.8 53.88 0 0 1 299
300 291.3 52.95 0 0 0 300
301 293.6 55.08 1 0 0 301
302 294.6 53.61 0 1 0 302
303 285.9 58.78 0 0 1 303
304 297.6 61.85 0 0 0 304
305 301.1 55.91 1 0 0 305
306 293.8 53.32 0 1 0 306
307 297.7 46.41 0 0 1 307
308 292.9 44.57 0 0 0 308
309 292.1 50.00 1 0 0 309
310 287.2 50.00 0 1 0 310
311 288.2 53.36 0 0 1 311
312 283.8 46.23 0 0 0 312
313 299.9 50.45 1 0 0 313
314 292.4 49.07 0 1 0 314
315 293.3 45.85 0 0 1 315
316 300.8 48.45 0 0 0 316
317 293.7 49.96 1 0 0 317
318 293.1 46.53 0 1 0 318
319 294.4 50.51 0 0 1 319
320 292.1 47.58 0 0 0 320
321 291.9 48.05 1 0 0 321
322 282.5 46.84 0 1 0 322
323 277.9 47.67 0 0 1 323
324 287.5 49.16 0 0 0 324
325 289.2 55.54 1 0 0 325
326 285.6 55.82 0 1 0 326
327 293.2 58.22 0 0 1 327
328 290.8 56.19 0 0 0 328
329 283.1 57.77 1 0 0 329
330 275.0 63.19 0 1 0 330
331 287.8 54.76 0 0 1 331
332 287.8 55.74 0 0 0 332
333 287.4 62.54 1 0 0 333
334 284.0 61.39 0 1 0 334
335 277.8 69.60 0 0 1 335
336 277.6 79.23 0 0 0 336
337 304.9 80.00 1 0 0 337
338 294.0 93.68 0 1 0 338
339 300.9 107.63 0 0 1 339
340 324.0 100.18 0 0 0 340
341 332.9 97.30 1 0 0 341
342 341.6 90.45 0 1 0 342
343 333.4 80.64 0 0 1 343
344 348.2 80.58 0 0 0 344
345 344.7 75.82 1 0 0 345
346 344.7 85.59 0 1 0 346
347 329.3 89.35 0 0 1 347
348 323.5 89.42 0 0 0 348
349 323.2 104.73 1 0 0 349
350 317.4 95.32 0 1 0 350
351 330.1 89.27 0 0 1 351
352 329.2 90.44 0 0 0 352
353 334.9 86.97 1 0 0 353
354 315.8 79.98 0 1 0 354
355 315.4 81.22 0 0 1 355
356 319.6 87.35 0 0 0 356
357 317.3 83.64 1 0 0 357
358 313.8 82.22 0 1 0 358
359 315.8 94.40 0 0 1 359
360 311.3 102.18 0 0 0 360
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Colombia Q1 Q2 Q3 t
135.6502 1.8813 -0.0365 0.5159 -0.3281 0.1484
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-116.173 -18.265 -0.854 18.876 101.277
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 135.65015 8.19800 16.547 <2e-16 ***
Colombia 1.88128 0.08742 21.519 <2e-16 ***
Q1 -0.03650 4.64968 -0.008 0.994
Q2 0.51588 4.64970 0.111 0.912
Q3 -0.32811 4.64945 -0.071 0.944
t 0.14843 0.01584 9.372 <2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 31.19 on 354 degrees of freedom
Multiple R-squared: 0.6008, Adjusted R-squared: 0.5951
F-statistic: 106.5 on 5 and 354 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,] 0.7823881214 4.352238e-01 2.176119e-01
[2,] 0.7679187455 4.641625e-01 2.320813e-01
[3,] 0.7148930507 5.702139e-01 2.851069e-01
[4,] 0.6763715563 6.472569e-01 3.236284e-01
[5,] 0.5784641843 8.430716e-01 4.215358e-01
[6,] 0.4760855575 9.521711e-01 5.239144e-01
[7,] 0.3801070177 7.602140e-01 6.198930e-01
[8,] 0.3236141752 6.472284e-01 6.763858e-01
[9,] 0.2563717246 5.127434e-01 7.436283e-01
[10,] 0.1931884876 3.863770e-01 8.068115e-01
[11,] 0.1450980165 2.901960e-01 8.549020e-01
[12,] 0.1372922297 2.745845e-01 8.627078e-01
[13,] 0.1060895411 2.121791e-01 8.939105e-01
[14,] 0.0766247191 1.532494e-01 9.233753e-01
[15,] 0.0620042347 1.240085e-01 9.379958e-01
[16,] 0.0522708903 1.045418e-01 9.477291e-01
[17,] 0.0493512047 9.870241e-02 9.506488e-01
[18,] 0.0794983611 1.589967e-01 9.205016e-01
[19,] 0.6935947874 6.128104e-01 3.064052e-01
[20,] 0.7490304470 5.019391e-01 2.509696e-01
[21,] 0.7421443328 5.157113e-01 2.578557e-01
[22,] 0.6941678539 6.116643e-01 3.058321e-01
[23,] 0.6458978387 7.082043e-01 3.541022e-01
[24,] 0.6188926655 7.622147e-01 3.811073e-01
[25,] 0.5830797435 8.338405e-01 4.169203e-01
[26,] 0.5387947636 9.224105e-01 4.612052e-01
[27,] 0.4930674538 9.861349e-01 5.069325e-01
[28,] 0.4517875275 9.035751e-01 5.482125e-01
[29,] 0.4089659413 8.179319e-01 5.910341e-01
[30,] 0.3647262759 7.294526e-01 6.352737e-01
[31,] 0.3245992460 6.491985e-01 6.754008e-01
[32,] 0.3227568688 6.455137e-01 6.772431e-01
[33,] 0.2845996109 5.691992e-01 7.154004e-01
[34,] 0.2467210802 4.934422e-01 7.532789e-01
[35,] 0.2133696567 4.267393e-01 7.866303e-01
[36,] 0.1827792685 3.655585e-01 8.172207e-01
[37,] 0.1535722114 3.071444e-01 8.464278e-01
[38,] 0.1271443785 2.542888e-01 8.728556e-01
[39,] 0.1073342042 2.146684e-01 8.926658e-01
[40,] 0.1184425450 2.368851e-01 8.815575e-01
[41,] 0.1144757550 2.289515e-01 8.855242e-01
[42,] 0.1280894277 2.561789e-01 8.719106e-01
[43,] 0.1508217160 3.016434e-01 8.491783e-01
[44,] 0.1635897420 3.271795e-01 8.364103e-01
[45,] 0.1574443327 3.148887e-01 8.425557e-01
[46,] 0.1431190745 2.862381e-01 8.568809e-01
[47,] 0.1317891330 2.635783e-01 8.682109e-01
[48,] 0.1167310834 2.334622e-01 8.832689e-01
[49,] 0.0990821518 1.981643e-01 9.009178e-01
[50,] 0.0942655705 1.885311e-01 9.057344e-01
[51,] 0.1155406997 2.310814e-01 8.844593e-01
[52,] 0.1123334666 2.246669e-01 8.876665e-01
[53,] 0.1003792927 2.007586e-01 8.996207e-01
[54,] 0.0847528626 1.695057e-01 9.152471e-01
[55,] 0.0745813135 1.491626e-01 9.254187e-01
[56,] 0.0650088191 1.300176e-01 9.349912e-01
[57,] 0.0542594589 1.085189e-01 9.457405e-01
[58,] 0.0451580288 9.031606e-02 9.548420e-01
[59,] 0.0374419252 7.488385e-02 9.625581e-01
[60,] 0.0312769562 6.255391e-02 9.687230e-01
[61,] 0.0275499666 5.509993e-02 9.724500e-01
[62,] 0.0251372798 5.027456e-02 9.748627e-01
[63,] 0.0217325577 4.346512e-02 9.782674e-01
[64,] 0.0181363607 3.627272e-02 9.818636e-01
[65,] 0.0154936936 3.098739e-02 9.845063e-01
[66,] 0.0140787737 2.815755e-02 9.859212e-01
[67,] 0.0134284855 2.685697e-02 9.865715e-01
[68,] 0.0114338124 2.286762e-02 9.885662e-01
[69,] 0.0101360672 2.027213e-02 9.898639e-01
[70,] 0.0095328319 1.906566e-02 9.904672e-01
[71,] 0.0091863223 1.837264e-02 9.908137e-01
[72,] 0.0098119227 1.962385e-02 9.901881e-01
[73,] 0.0091521980 1.830440e-02 9.908478e-01
[74,] 0.0084158313 1.683166e-02 9.915842e-01
[75,] 0.0077336364 1.546727e-02 9.922664e-01
[76,] 0.0074013107 1.480262e-02 9.925987e-01
[77,] 0.0080691965 1.613839e-02 9.919308e-01
[78,] 0.0106732987 2.134660e-02 9.893267e-01
[79,] 0.0132847571 2.656951e-02 9.867152e-01
[80,] 0.0158716205 3.174324e-02 9.841284e-01
[81,] 0.0205736535 4.114731e-02 9.794263e-01
[82,] 0.0279215653 5.584313e-02 9.720784e-01
[83,] 0.0399614817 7.992296e-02 9.600385e-01
[84,] 0.0472105146 9.442103e-02 9.527895e-01
[85,] 0.0561762429 1.123525e-01 9.438238e-01
[86,] 0.0692233148 1.384466e-01 9.307767e-01
[87,] 0.0811927847 1.623856e-01 9.188072e-01
[88,] 0.0899725951 1.799452e-01 9.100274e-01
[89,] 0.1067572904 2.135146e-01 8.932427e-01
[90,] 0.1308434119 2.616868e-01 8.691566e-01
[91,] 0.1448132719 2.896265e-01 8.551867e-01
[92,] 0.1682782988 3.365566e-01 8.317217e-01
[93,] 0.2047286224 4.094572e-01 7.952714e-01
[94,] 0.2255515113 4.511030e-01 7.744485e-01
[95,] 0.2478401607 4.956803e-01 7.521598e-01
[96,] 0.2584079696 5.168159e-01 7.415920e-01
[97,] 0.2624231820 5.248464e-01 7.375768e-01
[98,] 0.2660713263 5.321427e-01 7.339287e-01
[99,] 0.2595773685 5.191547e-01 7.404226e-01
[100,] 0.2458922545 4.917845e-01 7.541077e-01
[101,] 0.2490875157 4.981750e-01 7.509125e-01
[102,] 0.4999418049 9.998836e-01 5.000582e-01
[103,] 0.6364465382 7.271069e-01 3.635535e-01
[104,] 0.6725122081 6.549756e-01 3.274878e-01
[105,] 0.6774653787 6.450692e-01 3.225346e-01
[106,] 0.6724143075 6.551714e-01 3.275857e-01
[107,] 0.6608002797 6.783994e-01 3.391997e-01
[108,] 0.6368358363 7.263283e-01 3.631642e-01
[109,] 0.6061065759 7.877868e-01 3.938934e-01
[110,] 0.5748627778 8.502744e-01 4.251372e-01
[111,] 0.5435596428 9.128807e-01 4.564404e-01
[112,] 0.5124824988 9.750350e-01 4.875175e-01
[113,] 0.4824161363 9.648323e-01 5.175839e-01
[114,] 0.4505092510 9.010185e-01 5.494907e-01
[115,] 0.4188765943 8.377532e-01 5.811234e-01
[116,] 0.3883669369 7.767339e-01 6.116331e-01
[117,] 0.3610548426 7.221097e-01 6.389452e-01
[118,] 0.3339088690 6.678177e-01 6.660911e-01
[119,] 0.3074283899 6.148568e-01 6.925716e-01
[120,] 0.2863120008 5.726240e-01 7.136880e-01
[121,] 0.2634465807 5.268932e-01 7.365534e-01
[122,] 0.2401156966 4.802314e-01 7.598843e-01
[123,] 0.2284657621 4.569315e-01 7.715342e-01
[124,] 0.2182242791 4.364486e-01 7.817757e-01
[125,] 0.2004969246 4.009938e-01 7.995031e-01
[126,] 0.1871382971 3.742766e-01 8.128617e-01
[127,] 0.1756573877 3.513148e-01 8.243426e-01
[128,] 0.1613021181 3.226042e-01 8.386979e-01
[129,] 0.1481383954 2.962768e-01 8.518616e-01
[130,] 0.1349560425 2.699121e-01 8.650440e-01
[131,] 0.1212215008 2.424430e-01 8.787785e-01
[132,] 0.1093653370 2.187307e-01 8.906347e-01
[133,] 0.1000838469 2.001677e-01 8.999162e-01
[134,] 0.0897373874 1.794748e-01 9.102626e-01
[135,] 0.0796525413 1.593051e-01 9.203475e-01
[136,] 0.0703260413 1.406521e-01 9.296740e-01
[137,] 0.0622924332 1.245849e-01 9.377076e-01
[138,] 0.0592037221 1.184074e-01 9.407963e-01
[139,] 0.0569219636 1.138439e-01 9.430780e-01
[140,] 0.0499868846 9.997377e-02 9.500131e-01
[141,] 0.0464821986 9.296440e-02 9.535178e-01
[142,] 0.0416886747 8.337735e-02 9.583113e-01
[143,] 0.0394457835 7.889157e-02 9.605542e-01
[144,] 0.0370123770 7.402475e-02 9.629876e-01
[145,] 0.0342032359 6.840647e-02 9.657968e-01
[146,] 0.0301364133 6.027283e-02 9.698636e-01
[147,] 0.0257097165 5.141943e-02 9.742903e-01
[148,] 0.0221213622 4.424272e-02 9.778786e-01
[149,] 0.0193678897 3.873578e-02 9.806321e-01
[150,] 0.0176707443 3.534149e-02 9.823293e-01
[151,] 0.0150539085 3.010782e-02 9.849461e-01
[152,] 0.0127180144 2.543603e-02 9.872820e-01
[153,] 0.0108733035 2.174661e-02 9.891267e-01
[154,] 0.0095343954 1.906879e-02 9.904656e-01
[155,] 0.0094145882 1.882918e-02 9.905854e-01
[156,] 0.0094846275 1.896925e-02 9.905154e-01
[157,] 0.0079778786 1.595576e-02 9.920221e-01
[158,] 0.0066808339 1.336167e-02 9.933192e-01
[159,] 0.0055277621 1.105552e-02 9.944722e-01
[160,] 0.0046540308 9.308062e-03 9.953460e-01
[161,] 0.0040344357 8.068871e-03 9.959656e-01
[162,] 0.0035711331 7.142266e-03 9.964289e-01
[163,] 0.0029448631 5.889726e-03 9.970551e-01
[164,] 0.0023758456 4.751691e-03 9.976242e-01
[165,] 0.0019317493 3.863499e-03 9.980683e-01
[166,] 0.0015538537 3.107707e-03 9.984461e-01
[167,] 0.0012625781 2.525156e-03 9.987374e-01
[168,] 0.0010654867 2.130973e-03 9.989345e-01
[169,] 0.0009096786 1.819357e-03 9.990903e-01
[170,] 0.0007845658 1.569132e-03 9.992154e-01
[171,] 0.0006889635 1.377927e-03 9.993110e-01
[172,] 0.0006305898 1.261180e-03 9.993694e-01
[173,] 0.0005602696 1.120539e-03 9.994397e-01
[174,] 0.0004756865 9.513731e-04 9.995243e-01
[175,] 0.0004141513 8.283026e-04 9.995858e-01
[176,] 0.0003703240 7.406479e-04 9.996297e-01
[177,] 0.0003355670 6.711340e-04 9.996644e-01
[178,] 0.0002966088 5.932175e-04 9.997034e-01
[179,] 0.0002874773 5.749546e-04 9.997125e-01
[180,] 0.0003043443 6.086887e-04 9.996957e-01
[181,] 0.0003085902 6.171804e-04 9.996914e-01
[182,] 0.0002973725 5.947451e-04 9.997026e-01
[183,] 0.0002966398 5.932796e-04 9.997034e-01
[184,] 0.0003136419 6.272837e-04 9.996864e-01
[185,] 0.0003461978 6.923955e-04 9.996538e-01
[186,] 0.0003544808 7.089617e-04 9.996455e-01
[187,] 0.0003693148 7.386296e-04 9.996307e-01
[188,] 0.0003927916 7.855832e-04 9.996072e-01
[189,] 0.0004225323 8.450646e-04 9.995775e-01
[190,] 0.0004393253 8.786506e-04 9.995607e-01
[191,] 0.0004659106 9.318211e-04 9.995341e-01
[192,] 0.0005829775 1.165955e-03 9.994170e-01
[193,] 0.0007722037 1.544407e-03 9.992278e-01
[194,] 0.0012005704 2.401141e-03 9.987994e-01
[195,] 0.0018980001 3.796000e-03 9.981020e-01
[196,] 0.0030290218 6.058044e-03 9.969710e-01
[197,] 0.0047492844 9.498569e-03 9.952507e-01
[198,] 0.0091768681 1.835374e-02 9.908231e-01
[199,] 0.0561318001 1.122636e-01 9.438682e-01
[200,] 0.2253935603 4.507871e-01 7.746064e-01
[201,] 0.5503525234 8.992950e-01 4.496475e-01
[202,] 0.8467639950 3.064720e-01 1.532360e-01
[203,] 0.8581807916 2.836384e-01 1.418192e-01
[204,] 0.9411400346 1.177199e-01 5.885997e-02
[205,] 0.9534264631 9.314707e-02 4.657354e-02
[206,] 0.9607125633 7.857487e-02 3.928744e-02
[207,] 0.9703873574 5.922529e-02 2.961264e-02
[208,] 0.9759781434 4.804371e-02 2.402186e-02
[209,] 0.9828937370 3.421253e-02 1.710626e-02
[210,] 0.9840315848 3.193683e-02 1.596842e-02
[211,] 0.9831534341 3.369313e-02 1.684657e-02
[212,] 0.9819260437 3.614791e-02 1.807396e-02
[213,] 0.9798643985 4.027120e-02 2.013560e-02
[214,] 0.9785605180 4.287896e-02 2.143948e-02
[215,] 0.9773202442 4.535951e-02 2.267976e-02
[216,] 0.9784132525 4.317349e-02 2.158675e-02
[217,] 0.9784421455 4.311571e-02 2.155785e-02
[218,] 0.9764202446 4.715951e-02 2.357976e-02
[219,] 0.9732016152 5.359677e-02 2.679838e-02
[220,] 0.9684354727 6.312905e-02 3.156453e-02
[221,] 0.9623884719 7.522306e-02 3.761153e-02
[222,] 0.9554245006 8.915100e-02 4.457550e-02
[223,] 0.9477306860 1.045386e-01 5.226931e-02
[224,] 0.9387767456 1.224465e-01 6.122325e-02
[225,] 0.9317401866 1.365196e-01 6.825981e-02
[226,] 0.9231362522 1.537275e-01 7.686375e-02
[227,] 0.9203607790 1.592784e-01 7.963922e-02
[228,] 0.9509782846 9.804343e-02 4.902172e-02
[229,] 0.9783523005 4.329540e-02 2.164770e-02
[230,] 0.9921804487 1.563910e-02 7.819551e-03
[231,] 0.9981033084 3.793383e-03 1.896692e-03
[232,] 0.9992035852 1.592830e-03 7.964148e-04
[233,] 0.9996058783 7.882434e-04 3.941217e-04
[234,] 0.9999672216 6.555672e-05 3.277836e-05
[235,] 0.9999999973 5.391824e-09 2.695912e-09
[236,] 0.9999999998 3.090404e-10 1.545202e-10
[237,] 1.0000000000 1.550105e-12 7.750525e-13
[238,] 1.0000000000 3.302577e-13 1.651288e-13
[239,] 1.0000000000 1.367399e-13 6.836995e-14
[240,] 1.0000000000 6.921327e-15 3.460664e-15
[241,] 1.0000000000 1.541549e-16 7.707743e-17
[242,] 1.0000000000 1.500760e-17 7.503798e-18
[243,] 1.0000000000 1.035587e-18 5.177934e-19
[244,] 1.0000000000 9.129380e-19 4.564690e-19
[245,] 1.0000000000 1.897829e-18 9.489144e-19
[246,] 1.0000000000 4.048514e-18 2.024257e-18
[247,] 1.0000000000 3.537149e-18 1.768575e-18
[248,] 1.0000000000 5.499479e-18 2.749739e-18
[249,] 1.0000000000 6.732916e-18 3.366458e-18
[250,] 1.0000000000 1.162125e-17 5.810626e-18
[251,] 1.0000000000 1.969771e-17 9.848856e-18
[252,] 1.0000000000 4.084367e-17 2.042184e-17
[253,] 1.0000000000 8.540455e-17 4.270228e-17
[254,] 1.0000000000 1.940287e-16 9.701436e-17
[255,] 1.0000000000 3.923117e-16 1.961558e-16
[256,] 1.0000000000 6.232143e-16 3.116071e-16
[257,] 1.0000000000 8.532284e-16 4.266142e-16
[258,] 1.0000000000 1.361296e-15 6.806479e-16
[259,] 1.0000000000 2.715641e-15 1.357820e-15
[260,] 1.0000000000 5.377949e-15 2.688974e-15
[261,] 1.0000000000 1.121430e-14 5.607148e-15
[262,] 1.0000000000 1.796156e-14 8.980778e-15
[263,] 1.0000000000 3.798524e-14 1.899262e-14
[264,] 1.0000000000 8.173223e-14 4.086611e-14
[265,] 1.0000000000 1.687434e-13 8.437168e-14
[266,] 1.0000000000 3.037036e-13 1.518518e-13
[267,] 1.0000000000 4.600334e-13 2.300167e-13
[268,] 1.0000000000 1.908658e-13 9.543289e-14
[269,] 1.0000000000 4.132490e-13 2.066245e-13
[270,] 1.0000000000 4.129249e-13 2.064624e-13
[271,] 1.0000000000 4.885733e-13 2.442867e-13
[272,] 1.0000000000 5.344780e-13 2.672390e-13
[273,] 1.0000000000 7.321342e-13 3.660671e-13
[274,] 1.0000000000 1.045596e-12 5.227981e-13
[275,] 1.0000000000 1.070095e-12 5.350475e-13
[276,] 1.0000000000 6.848384e-13 3.424192e-13
[277,] 1.0000000000 9.562830e-13 4.781415e-13
[278,] 1.0000000000 1.342698e-12 6.713491e-13
[279,] 1.0000000000 2.565477e-12 1.282739e-12
[280,] 1.0000000000 5.148186e-12 2.574093e-12
[281,] 1.0000000000 9.069131e-12 4.534565e-12
[282,] 1.0000000000 9.424721e-12 4.712360e-12
[283,] 1.0000000000 8.862866e-12 4.431433e-12
[284,] 1.0000000000 1.609581e-11 8.047905e-12
[285,] 1.0000000000 3.574619e-11 1.787310e-11
[286,] 1.0000000000 3.201142e-11 1.600571e-11
[287,] 1.0000000000 3.733376e-11 1.866688e-11
[288,] 1.0000000000 6.372661e-11 3.186330e-11
[289,] 0.9999999999 1.300426e-10 6.502130e-11
[290,] 0.9999999999 1.869019e-10 9.345094e-11
[291,] 0.9999999998 3.202146e-10 1.601073e-10
[292,] 0.9999999996 7.013769e-10 3.506884e-10
[293,] 0.9999999992 1.542507e-09 7.712534e-10
[294,] 0.9999999985 3.001901e-09 1.500951e-09
[295,] 0.9999999969 6.289687e-09 3.144844e-09
[296,] 0.9999999935 1.304822e-08 6.524109e-09
[297,] 0.9999999878 2.446097e-08 1.223049e-08
[298,] 0.9999999771 4.583510e-08 2.291755e-08
[299,] 0.9999999702 5.953713e-08 2.976857e-08
[300,] 0.9999999502 9.962820e-08 4.981410e-08
[301,] 0.9999999002 1.995343e-07 9.976713e-08
[302,] 0.9999998026 3.947295e-07 1.973648e-07
[303,] 0.9999996122 7.756506e-07 3.878253e-07
[304,] 0.9999992252 1.549545e-06 7.747727e-07
[305,] 0.9999987698 2.460421e-06 1.230211e-06
[306,] 0.9999979640 4.072032e-06 2.036016e-06
[307,] 0.9999970135 5.973063e-06 2.986531e-06
[308,] 0.9999965069 6.986254e-06 3.493127e-06
[309,] 0.9999937658 1.246835e-05 6.234175e-06
[310,] 0.9999911543 1.769135e-05 8.845675e-06
[311,] 0.9999878193 2.436132e-05 1.218066e-05
[312,] 0.9999812221 3.755579e-05 1.877790e-05
[313,] 0.9999672114 6.557718e-05 3.278859e-05
[314,] 0.9999400511 1.198979e-04 5.994894e-05
[315,] 0.9998882144 2.235711e-04 1.117856e-04
[316,] 0.9998062220 3.875559e-04 1.937780e-04
[317,] 0.9996502752 6.994497e-04 3.497248e-04
[318,] 0.9993854803 1.229039e-03 6.145197e-04
[319,] 0.9990235009 1.952998e-03 9.764991e-04
[320,] 0.9983839270 3.232146e-03 1.616073e-03
[321,] 0.9975020134 4.995973e-03 2.497987e-03
[322,] 0.9968671919 6.265616e-03 3.132808e-03
[323,] 0.9947701876 1.045962e-02 5.229812e-03
[324,] 0.9915267482 1.694650e-02 8.473252e-03
[325,] 0.9895072906 2.098542e-02 1.049271e-02
[326,] 0.9882885945 2.342281e-02 1.171141e-02
[327,] 0.9940177495 1.196450e-02 5.982251e-03
[328,] 0.9996472103 7.055794e-04 3.527897e-04
[329,] 0.9999552827 8.943451e-05 4.471725e-05
[330,] 0.9999987472 2.505658e-06 1.252829e-06
[331,] 0.9999998473 3.053797e-07 1.526898e-07
[332,] 0.9999998753 2.493762e-07 1.246881e-07
[333,] 0.9999997418 5.163873e-07 2.581937e-07
[334,] 0.9999989330 2.134093e-06 1.067046e-06
[335,] 0.9999972757 5.448600e-06 2.724300e-06
[336,] 0.9999909557 1.808869e-05 9.044343e-06
[337,] 0.9999608653 7.826948e-05 3.913474e-05
[338,] 0.9999880251 2.394980e-05 1.197490e-05
[339,] 0.9999326571 1.346859e-04 6.734294e-05
[340,] 0.9997985997 4.028006e-04 2.014003e-04
[341,] 0.9994562778 1.087444e-03 5.437222e-04
[342,] 0.9994103679 1.179264e-03 5.896321e-04
[343,] 0.9954154827 9.169035e-03 4.584517e-03
> postscript(file="/var/wessaorg/rcomp/tmp/12t1r1321370291.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/287ox1321370291.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3qz411321370291.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/45oy41321370291.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/5z0qa1321370291.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
-44.9601806 -20.4609978 0.2920074 39.4352833 73.0628968 85.7736740
7 8 9 10 11 12
82.2256744 74.9828319 69.7818627 64.0286262 54.1212665 49.4546799
13 14 15 16 17 18
45.1537107 41.3232134 40.2089129 28.4472576 23.6125893 14.9514072
19 20 21 22 23 24
10.8489788 -3.9067406 -11.0453353 -14.0579320 -12.6068438 -13.1536128
25 26 27 28 29 30
-16.2298332 -17.9829772 -6.6221982 -9.2818440 -13.7206239 -17.0396194
31 32 33 34 35 36
2.1755751 24.5552867 28.1321202 29.5093834 32.1157201 32.2094058
37 38 39 40 41 42
19.9152849 26.6769346 21.5577029 10.4947651 14.5274950 13.7842136
43 44 45 46 47 48
22.7719226 20.8509072 11.4321299 6.9195333 -4.0590586 -19.5843708
49 50 51 52 53 54
-22.1685367 -36.6068869 -39.8686755 -41.2906957 -42.5352265 -40.3300151
55 56 57 58 59 60
-41.2472373 -41.4236864 -40.5919613 -48.0228287 -55.0987765 -45.0891072
61 62 63 64 65 66
-44.8187517 -32.2947275 -36.8202654 -36.8839303 -34.5205156 -34.9142994
67 68 69 70 71 72
-35.4255856 -32.5139068 -32.2762456 -46.4894901 -43.5710037 -40.5374978
73 74 75 76 77 78
-36.5978271 -33.3282318 -29.6860013 -37.4419057 -37.2953868 -36.1812251
79 80 81 82 83 84
-34.2271226 -30.3817447 -37.5850011 -38.2640837 -34.4724482 -34.4023214
85 86 87 88 89 90
-29.4934281 -22.0040152 -21.7400502 -21.1601535 -19.3324474 -15.3104327
91 92 93 94 95 96
-9.2236359 -13.2032844 -13.0311044 -10.1605044 -9.1351697 -10.0602968
97 98 99 100 101 102
-7.4631830 -2.8905734 -4.4852414 0.2394994 4.5763409 1.2149737
103 104 105 106 107 108
6.0107209 3.4947292 -1.2411290 2.6760470 -3.8989886 -12.1379046
109 110 111 112 113 114
-2.4661875 62.6350840 56.1134592 46.1843131 40.2911043 38.3468181
115 116 117 118 119 120
34.7524277 23.6918697 7.3662442 7.1853372 9.5055554 11.7965045
121 122 123 124 125 126
11.5758103 5.6464104 3.6203305 -3.5283555 -10.7124289 -10.2863952
127 128 129 130 131 132
-10.1263567 -18.1206138 -12.3760119 -9.4799359 -23.8884855 -25.6025602
133 134 135 136 137 138
-15.8402428 -19.8531171 -22.4593795 -16.7785705 -17.4488549 -16.5267477
139 140 141 142 143 144
-6.8468916 -8.9143904 -5.3420254 -7.1201958 -10.8705752 -5.3568868
145 146 147 148 149 150
-1.7005054 12.0989551 13.1688561 8.1392472 16.0066810 14.1632144
151 152 153 154 155 156
21.6558547 18.6012327 14.1052873 8.1005437 -5.6633470 0.3265974
157 158 159 160 161 162
1.5069079 8.9923943 -1.4369776 -6.6523347 1.7150991 7.9431423
163 164 165 166 167 168
19.1418112 18.7871891 6.6420104 7.9838427 2.8320091 4.7585743
169 170 171 172 173 174
7.4546834 11.5173380 2.1801131 -2.1819125 -4.6115570 -4.4300897
175 176 177 178 179 180
-7.7463071 -14.1217514 -14.6117608 -17.2424432 -18.6993005 -21.5866169
181 182 183 184 185 186
-17.3985459 -9.0257511 -10.5310088 -11.6659058 -5.7550030 -8.7141755
187 188 189 190 191 192
1.8302496 3.7559951 -2.9024172 -7.0497177 -15.4382646 -17.5612896
193 194 195 196 197 198
-17.9325787 -7.7303816 -5.1506181 -9.0373000 -6.0700513 -3.5539726
199 200 201 202 203 204
-0.4177707 -17.5651877 -17.3424128 -24.8085261 -21.7862058 -16.0765364
205 206 207 208 209 210
-10.3042640 -23.9918475 -61.6634327 -59.8388771 -56.4705311 -52.6773768
211 212 213 214 215 216
24.7262233 101.2765983 72.2504967 65.8395394 70.2430470 67.4421267
217 218 219 220 221 222
72.6363188 57.2286534 49.2372774 47.8281339 40.3159272 45.1738356
223 224 225 226 227 228
46.3567060 55.1656482 52.3192005 44.6325425 40.0023510 33.4951245
229 230 231 232 233 234
27.7540708 23.4619262 21.0040641 23.7584850 13.9355961 14.8170635
235 236 237 238 239 240
4.6331701 -24.5487789 -33.9915779 -38.3520328 -43.8317220 -27.3095327
241 242 243 244 245 246
-19.0725061 -53.8988259 -116.1726325 -59.7304406 -84.4525365 -53.3662305
247 248 249 250 251 252
41.1507493 57.3599693 61.1534343 48.7323501 49.8778725 21.3362991
253 254 255 256 257 258
8.0382516 -11.0691495 23.9584857 12.9213940 26.3253695 19.3781615
259 260 261 262 263 264
16.7112566 11.8486890 19.1771356 9.8616172 -1.7581699 -7.8664937
265 266 267 268 269 270
-6.7832614 -2.7095545 0.5849103 1.8926626 7.7472196 -0.4664743
271 272 273 274 275 276
11.3603279 16.4810496 20.7704956 29.0261168 -1.4088343 -23.8934274
277 278 279 280 281 282
12.6964814 35.2713782 29.5163453 31.9847402 28.7362829 28.1755636
283 284 285 286 287 288
30.9731352 37.8028998 28.7712457 23.7257696 14.5568552 13.8398587
289 290 291 292 293 294
21.0420889 31.5685854 30.6690787 16.4724418 5.9047090 31.1583340
295 296 297 298 299 300
26.6875951 19.9446600 16.0395792 25.3630614 17.7335970 11.5066455
301 302 303 304 305 306
9.6875906 12.7522547 -4.9783997 0.4695298 15.0324026 11.9041000
307 308 309 310 311 312
29.4993051 27.6843182 16.5570401 10.9562230 6.3306850 14.8676680
313 314 315 316 317 318
22.9167384 17.3120873 24.9653701 27.0975011 17.0448397 22.1968121
319 320 321 322 323 324
16.7048806 19.4404887 18.2443582 10.4198895 4.9539893 11.2743408
325 326 327 328 329 330
0.8598470 -3.9677286 -0.1872380 0.7552183 -10.0291327 -29.0264862
331 332 333 334 335 336
0.3282642 -1.9919316 -15.2965630 -17.2339085 -38.1836533 -56.9769190
337 338 339 340 341 342
-31.2374334 -68.5741577 -87.2224483 -50.5834558 -36.3772991 -15.4913499
343 344 345 346 347 348
-4.5404335 9.8959017 15.2388643 -3.8420561 -25.6201060 -32.0283372
349 350 351 352 353 354
-61.2426594 -50.0406340 -25.2633294 -28.8409684 -16.7248567 -23.3755283
355 356 357 358 359 360
-25.4127532 -33.2215398 -28.6539209 -30.1833208 -50.4017463 -70.0146444
> postscript(file="/var/wessaorg/rcomp/tmp/6mrti1321370291.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 -44.9601806 NA
1 -20.4609978 -44.9601806
2 0.2920074 -20.4609978
3 39.4352833 0.2920074
4 73.0628968 39.4352833
5 85.7736740 73.0628968
6 82.2256744 85.7736740
7 74.9828319 82.2256744
8 69.7818627 74.9828319
9 64.0286262 69.7818627
10 54.1212665 64.0286262
11 49.4546799 54.1212665
12 45.1537107 49.4546799
13 41.3232134 45.1537107
14 40.2089129 41.3232134
15 28.4472576 40.2089129
16 23.6125893 28.4472576
17 14.9514072 23.6125893
18 10.8489788 14.9514072
19 -3.9067406 10.8489788
20 -11.0453353 -3.9067406
21 -14.0579320 -11.0453353
22 -12.6068438 -14.0579320
23 -13.1536128 -12.6068438
24 -16.2298332 -13.1536128
25 -17.9829772 -16.2298332
26 -6.6221982 -17.9829772
27 -9.2818440 -6.6221982
28 -13.7206239 -9.2818440
29 -17.0396194 -13.7206239
30 2.1755751 -17.0396194
31 24.5552867 2.1755751
32 28.1321202 24.5552867
33 29.5093834 28.1321202
34 32.1157201 29.5093834
35 32.2094058 32.1157201
36 19.9152849 32.2094058
37 26.6769346 19.9152849
38 21.5577029 26.6769346
39 10.4947651 21.5577029
40 14.5274950 10.4947651
41 13.7842136 14.5274950
42 22.7719226 13.7842136
43 20.8509072 22.7719226
44 11.4321299 20.8509072
45 6.9195333 11.4321299
46 -4.0590586 6.9195333
47 -19.5843708 -4.0590586
48 -22.1685367 -19.5843708
49 -36.6068869 -22.1685367
50 -39.8686755 -36.6068869
51 -41.2906957 -39.8686755
52 -42.5352265 -41.2906957
53 -40.3300151 -42.5352265
54 -41.2472373 -40.3300151
55 -41.4236864 -41.2472373
56 -40.5919613 -41.4236864
57 -48.0228287 -40.5919613
58 -55.0987765 -48.0228287
59 -45.0891072 -55.0987765
60 -44.8187517 -45.0891072
61 -32.2947275 -44.8187517
62 -36.8202654 -32.2947275
63 -36.8839303 -36.8202654
64 -34.5205156 -36.8839303
65 -34.9142994 -34.5205156
66 -35.4255856 -34.9142994
67 -32.5139068 -35.4255856
68 -32.2762456 -32.5139068
69 -46.4894901 -32.2762456
70 -43.5710037 -46.4894901
71 -40.5374978 -43.5710037
72 -36.5978271 -40.5374978
73 -33.3282318 -36.5978271
74 -29.6860013 -33.3282318
75 -37.4419057 -29.6860013
76 -37.2953868 -37.4419057
77 -36.1812251 -37.2953868
78 -34.2271226 -36.1812251
79 -30.3817447 -34.2271226
80 -37.5850011 -30.3817447
81 -38.2640837 -37.5850011
82 -34.4724482 -38.2640837
83 -34.4023214 -34.4724482
84 -29.4934281 -34.4023214
85 -22.0040152 -29.4934281
86 -21.7400502 -22.0040152
87 -21.1601535 -21.7400502
88 -19.3324474 -21.1601535
89 -15.3104327 -19.3324474
90 -9.2236359 -15.3104327
91 -13.2032844 -9.2236359
92 -13.0311044 -13.2032844
93 -10.1605044 -13.0311044
94 -9.1351697 -10.1605044
95 -10.0602968 -9.1351697
96 -7.4631830 -10.0602968
97 -2.8905734 -7.4631830
98 -4.4852414 -2.8905734
99 0.2394994 -4.4852414
100 4.5763409 0.2394994
101 1.2149737 4.5763409
102 6.0107209 1.2149737
103 3.4947292 6.0107209
104 -1.2411290 3.4947292
105 2.6760470 -1.2411290
106 -3.8989886 2.6760470
107 -12.1379046 -3.8989886
108 -2.4661875 -12.1379046
109 62.6350840 -2.4661875
110 56.1134592 62.6350840
111 46.1843131 56.1134592
112 40.2911043 46.1843131
113 38.3468181 40.2911043
114 34.7524277 38.3468181
115 23.6918697 34.7524277
116 7.3662442 23.6918697
117 7.1853372 7.3662442
118 9.5055554 7.1853372
119 11.7965045 9.5055554
120 11.5758103 11.7965045
121 5.6464104 11.5758103
122 3.6203305 5.6464104
123 -3.5283555 3.6203305
124 -10.7124289 -3.5283555
125 -10.2863952 -10.7124289
126 -10.1263567 -10.2863952
127 -18.1206138 -10.1263567
128 -12.3760119 -18.1206138
129 -9.4799359 -12.3760119
130 -23.8884855 -9.4799359
131 -25.6025602 -23.8884855
132 -15.8402428 -25.6025602
133 -19.8531171 -15.8402428
134 -22.4593795 -19.8531171
135 -16.7785705 -22.4593795
136 -17.4488549 -16.7785705
137 -16.5267477 -17.4488549
138 -6.8468916 -16.5267477
139 -8.9143904 -6.8468916
140 -5.3420254 -8.9143904
141 -7.1201958 -5.3420254
142 -10.8705752 -7.1201958
143 -5.3568868 -10.8705752
144 -1.7005054 -5.3568868
145 12.0989551 -1.7005054
146 13.1688561 12.0989551
147 8.1392472 13.1688561
148 16.0066810 8.1392472
149 14.1632144 16.0066810
150 21.6558547 14.1632144
151 18.6012327 21.6558547
152 14.1052873 18.6012327
153 8.1005437 14.1052873
154 -5.6633470 8.1005437
155 0.3265974 -5.6633470
156 1.5069079 0.3265974
157 8.9923943 1.5069079
158 -1.4369776 8.9923943
159 -6.6523347 -1.4369776
160 1.7150991 -6.6523347
161 7.9431423 1.7150991
162 19.1418112 7.9431423
163 18.7871891 19.1418112
164 6.6420104 18.7871891
165 7.9838427 6.6420104
166 2.8320091 7.9838427
167 4.7585743 2.8320091
168 7.4546834 4.7585743
169 11.5173380 7.4546834
170 2.1801131 11.5173380
171 -2.1819125 2.1801131
172 -4.6115570 -2.1819125
173 -4.4300897 -4.6115570
174 -7.7463071 -4.4300897
175 -14.1217514 -7.7463071
176 -14.6117608 -14.1217514
177 -17.2424432 -14.6117608
178 -18.6993005 -17.2424432
179 -21.5866169 -18.6993005
180 -17.3985459 -21.5866169
181 -9.0257511 -17.3985459
182 -10.5310088 -9.0257511
183 -11.6659058 -10.5310088
184 -5.7550030 -11.6659058
185 -8.7141755 -5.7550030
186 1.8302496 -8.7141755
187 3.7559951 1.8302496
188 -2.9024172 3.7559951
189 -7.0497177 -2.9024172
190 -15.4382646 -7.0497177
191 -17.5612896 -15.4382646
192 -17.9325787 -17.5612896
193 -7.7303816 -17.9325787
194 -5.1506181 -7.7303816
195 -9.0373000 -5.1506181
196 -6.0700513 -9.0373000
197 -3.5539726 -6.0700513
198 -0.4177707 -3.5539726
199 -17.5651877 -0.4177707
200 -17.3424128 -17.5651877
201 -24.8085261 -17.3424128
202 -21.7862058 -24.8085261
203 -16.0765364 -21.7862058
204 -10.3042640 -16.0765364
205 -23.9918475 -10.3042640
206 -61.6634327 -23.9918475
207 -59.8388771 -61.6634327
208 -56.4705311 -59.8388771
209 -52.6773768 -56.4705311
210 24.7262233 -52.6773768
211 101.2765983 24.7262233
212 72.2504967 101.2765983
213 65.8395394 72.2504967
214 70.2430470 65.8395394
215 67.4421267 70.2430470
216 72.6363188 67.4421267
217 57.2286534 72.6363188
218 49.2372774 57.2286534
219 47.8281339 49.2372774
220 40.3159272 47.8281339
221 45.1738356 40.3159272
222 46.3567060 45.1738356
223 55.1656482 46.3567060
224 52.3192005 55.1656482
225 44.6325425 52.3192005
226 40.0023510 44.6325425
227 33.4951245 40.0023510
228 27.7540708 33.4951245
229 23.4619262 27.7540708
230 21.0040641 23.4619262
231 23.7584850 21.0040641
232 13.9355961 23.7584850
233 14.8170635 13.9355961
234 4.6331701 14.8170635
235 -24.5487789 4.6331701
236 -33.9915779 -24.5487789
237 -38.3520328 -33.9915779
238 -43.8317220 -38.3520328
239 -27.3095327 -43.8317220
240 -19.0725061 -27.3095327
241 -53.8988259 -19.0725061
242 -116.1726325 -53.8988259
243 -59.7304406 -116.1726325
244 -84.4525365 -59.7304406
245 -53.3662305 -84.4525365
246 41.1507493 -53.3662305
247 57.3599693 41.1507493
248 61.1534343 57.3599693
249 48.7323501 61.1534343
250 49.8778725 48.7323501
251 21.3362991 49.8778725
252 8.0382516 21.3362991
253 -11.0691495 8.0382516
254 23.9584857 -11.0691495
255 12.9213940 23.9584857
256 26.3253695 12.9213940
257 19.3781615 26.3253695
258 16.7112566 19.3781615
259 11.8486890 16.7112566
260 19.1771356 11.8486890
261 9.8616172 19.1771356
262 -1.7581699 9.8616172
263 -7.8664937 -1.7581699
264 -6.7832614 -7.8664937
265 -2.7095545 -6.7832614
266 0.5849103 -2.7095545
267 1.8926626 0.5849103
268 7.7472196 1.8926626
269 -0.4664743 7.7472196
270 11.3603279 -0.4664743
271 16.4810496 11.3603279
272 20.7704956 16.4810496
273 29.0261168 20.7704956
274 -1.4088343 29.0261168
275 -23.8934274 -1.4088343
276 12.6964814 -23.8934274
277 35.2713782 12.6964814
278 29.5163453 35.2713782
279 31.9847402 29.5163453
280 28.7362829 31.9847402
281 28.1755636 28.7362829
282 30.9731352 28.1755636
283 37.8028998 30.9731352
284 28.7712457 37.8028998
285 23.7257696 28.7712457
286 14.5568552 23.7257696
287 13.8398587 14.5568552
288 21.0420889 13.8398587
289 31.5685854 21.0420889
290 30.6690787 31.5685854
291 16.4724418 30.6690787
292 5.9047090 16.4724418
293 31.1583340 5.9047090
294 26.6875951 31.1583340
295 19.9446600 26.6875951
296 16.0395792 19.9446600
297 25.3630614 16.0395792
298 17.7335970 25.3630614
299 11.5066455 17.7335970
300 9.6875906 11.5066455
301 12.7522547 9.6875906
302 -4.9783997 12.7522547
303 0.4695298 -4.9783997
304 15.0324026 0.4695298
305 11.9041000 15.0324026
306 29.4993051 11.9041000
307 27.6843182 29.4993051
308 16.5570401 27.6843182
309 10.9562230 16.5570401
310 6.3306850 10.9562230
311 14.8676680 6.3306850
312 22.9167384 14.8676680
313 17.3120873 22.9167384
314 24.9653701 17.3120873
315 27.0975011 24.9653701
316 17.0448397 27.0975011
317 22.1968121 17.0448397
318 16.7048806 22.1968121
319 19.4404887 16.7048806
320 18.2443582 19.4404887
321 10.4198895 18.2443582
322 4.9539893 10.4198895
323 11.2743408 4.9539893
324 0.8598470 11.2743408
325 -3.9677286 0.8598470
326 -0.1872380 -3.9677286
327 0.7552183 -0.1872380
328 -10.0291327 0.7552183
329 -29.0264862 -10.0291327
330 0.3282642 -29.0264862
331 -1.9919316 0.3282642
332 -15.2965630 -1.9919316
333 -17.2339085 -15.2965630
334 -38.1836533 -17.2339085
335 -56.9769190 -38.1836533
336 -31.2374334 -56.9769190
337 -68.5741577 -31.2374334
338 -87.2224483 -68.5741577
339 -50.5834558 -87.2224483
340 -36.3772991 -50.5834558
341 -15.4913499 -36.3772991
342 -4.5404335 -15.4913499
343 9.8959017 -4.5404335
344 15.2388643 9.8959017
345 -3.8420561 15.2388643
346 -25.6201060 -3.8420561
347 -32.0283372 -25.6201060
348 -61.2426594 -32.0283372
349 -50.0406340 -61.2426594
350 -25.2633294 -50.0406340
351 -28.8409684 -25.2633294
352 -16.7248567 -28.8409684
353 -23.3755283 -16.7248567
354 -25.4127532 -23.3755283
355 -33.2215398 -25.4127532
356 -28.6539209 -33.2215398
357 -30.1833208 -28.6539209
358 -50.4017463 -30.1833208
359 -70.0146444 -50.4017463
360 NA -70.0146444
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -20.4609978 -44.9601806
[2,] 0.2920074 -20.4609978
[3,] 39.4352833 0.2920074
[4,] 73.0628968 39.4352833
[5,] 85.7736740 73.0628968
[6,] 82.2256744 85.7736740
[7,] 74.9828319 82.2256744
[8,] 69.7818627 74.9828319
[9,] 64.0286262 69.7818627
[10,] 54.1212665 64.0286262
[11,] 49.4546799 54.1212665
[12,] 45.1537107 49.4546799
[13,] 41.3232134 45.1537107
[14,] 40.2089129 41.3232134
[15,] 28.4472576 40.2089129
[16,] 23.6125893 28.4472576
[17,] 14.9514072 23.6125893
[18,] 10.8489788 14.9514072
[19,] -3.9067406 10.8489788
[20,] -11.0453353 -3.9067406
[21,] -14.0579320 -11.0453353
[22,] -12.6068438 -14.0579320
[23,] -13.1536128 -12.6068438
[24,] -16.2298332 -13.1536128
[25,] -17.9829772 -16.2298332
[26,] -6.6221982 -17.9829772
[27,] -9.2818440 -6.6221982
[28,] -13.7206239 -9.2818440
[29,] -17.0396194 -13.7206239
[30,] 2.1755751 -17.0396194
[31,] 24.5552867 2.1755751
[32,] 28.1321202 24.5552867
[33,] 29.5093834 28.1321202
[34,] 32.1157201 29.5093834
[35,] 32.2094058 32.1157201
[36,] 19.9152849 32.2094058
[37,] 26.6769346 19.9152849
[38,] 21.5577029 26.6769346
[39,] 10.4947651 21.5577029
[40,] 14.5274950 10.4947651
[41,] 13.7842136 14.5274950
[42,] 22.7719226 13.7842136
[43,] 20.8509072 22.7719226
[44,] 11.4321299 20.8509072
[45,] 6.9195333 11.4321299
[46,] -4.0590586 6.9195333
[47,] -19.5843708 -4.0590586
[48,] -22.1685367 -19.5843708
[49,] -36.6068869 -22.1685367
[50,] -39.8686755 -36.6068869
[51,] -41.2906957 -39.8686755
[52,] -42.5352265 -41.2906957
[53,] -40.3300151 -42.5352265
[54,] -41.2472373 -40.3300151
[55,] -41.4236864 -41.2472373
[56,] -40.5919613 -41.4236864
[57,] -48.0228287 -40.5919613
[58,] -55.0987765 -48.0228287
[59,] -45.0891072 -55.0987765
[60,] -44.8187517 -45.0891072
[61,] -32.2947275 -44.8187517
[62,] -36.8202654 -32.2947275
[63,] -36.8839303 -36.8202654
[64,] -34.5205156 -36.8839303
[65,] -34.9142994 -34.5205156
[66,] -35.4255856 -34.9142994
[67,] -32.5139068 -35.4255856
[68,] -32.2762456 -32.5139068
[69,] -46.4894901 -32.2762456
[70,] -43.5710037 -46.4894901
[71,] -40.5374978 -43.5710037
[72,] -36.5978271 -40.5374978
[73,] -33.3282318 -36.5978271
[74,] -29.6860013 -33.3282318
[75,] -37.4419057 -29.6860013
[76,] -37.2953868 -37.4419057
[77,] -36.1812251 -37.2953868
[78,] -34.2271226 -36.1812251
[79,] -30.3817447 -34.2271226
[80,] -37.5850011 -30.3817447
[81,] -38.2640837 -37.5850011
[82,] -34.4724482 -38.2640837
[83,] -34.4023214 -34.4724482
[84,] -29.4934281 -34.4023214
[85,] -22.0040152 -29.4934281
[86,] -21.7400502 -22.0040152
[87,] -21.1601535 -21.7400502
[88,] -19.3324474 -21.1601535
[89,] -15.3104327 -19.3324474
[90,] -9.2236359 -15.3104327
[91,] -13.2032844 -9.2236359
[92,] -13.0311044 -13.2032844
[93,] -10.1605044 -13.0311044
[94,] -9.1351697 -10.1605044
[95,] -10.0602968 -9.1351697
[96,] -7.4631830 -10.0602968
[97,] -2.8905734 -7.4631830
[98,] -4.4852414 -2.8905734
[99,] 0.2394994 -4.4852414
[100,] 4.5763409 0.2394994
[101,] 1.2149737 4.5763409
[102,] 6.0107209 1.2149737
[103,] 3.4947292 6.0107209
[104,] -1.2411290 3.4947292
[105,] 2.6760470 -1.2411290
[106,] -3.8989886 2.6760470
[107,] -12.1379046 -3.8989886
[108,] -2.4661875 -12.1379046
[109,] 62.6350840 -2.4661875
[110,] 56.1134592 62.6350840
[111,] 46.1843131 56.1134592
[112,] 40.2911043 46.1843131
[113,] 38.3468181 40.2911043
[114,] 34.7524277 38.3468181
[115,] 23.6918697 34.7524277
[116,] 7.3662442 23.6918697
[117,] 7.1853372 7.3662442
[118,] 9.5055554 7.1853372
[119,] 11.7965045 9.5055554
[120,] 11.5758103 11.7965045
[121,] 5.6464104 11.5758103
[122,] 3.6203305 5.6464104
[123,] -3.5283555 3.6203305
[124,] -10.7124289 -3.5283555
[125,] -10.2863952 -10.7124289
[126,] -10.1263567 -10.2863952
[127,] -18.1206138 -10.1263567
[128,] -12.3760119 -18.1206138
[129,] -9.4799359 -12.3760119
[130,] -23.8884855 -9.4799359
[131,] -25.6025602 -23.8884855
[132,] -15.8402428 -25.6025602
[133,] -19.8531171 -15.8402428
[134,] -22.4593795 -19.8531171
[135,] -16.7785705 -22.4593795
[136,] -17.4488549 -16.7785705
[137,] -16.5267477 -17.4488549
[138,] -6.8468916 -16.5267477
[139,] -8.9143904 -6.8468916
[140,] -5.3420254 -8.9143904
[141,] -7.1201958 -5.3420254
[142,] -10.8705752 -7.1201958
[143,] -5.3568868 -10.8705752
[144,] -1.7005054 -5.3568868
[145,] 12.0989551 -1.7005054
[146,] 13.1688561 12.0989551
[147,] 8.1392472 13.1688561
[148,] 16.0066810 8.1392472
[149,] 14.1632144 16.0066810
[150,] 21.6558547 14.1632144
[151,] 18.6012327 21.6558547
[152,] 14.1052873 18.6012327
[153,] 8.1005437 14.1052873
[154,] -5.6633470 8.1005437
[155,] 0.3265974 -5.6633470
[156,] 1.5069079 0.3265974
[157,] 8.9923943 1.5069079
[158,] -1.4369776 8.9923943
[159,] -6.6523347 -1.4369776
[160,] 1.7150991 -6.6523347
[161,] 7.9431423 1.7150991
[162,] 19.1418112 7.9431423
[163,] 18.7871891 19.1418112
[164,] 6.6420104 18.7871891
[165,] 7.9838427 6.6420104
[166,] 2.8320091 7.9838427
[167,] 4.7585743 2.8320091
[168,] 7.4546834 4.7585743
[169,] 11.5173380 7.4546834
[170,] 2.1801131 11.5173380
[171,] -2.1819125 2.1801131
[172,] -4.6115570 -2.1819125
[173,] -4.4300897 -4.6115570
[174,] -7.7463071 -4.4300897
[175,] -14.1217514 -7.7463071
[176,] -14.6117608 -14.1217514
[177,] -17.2424432 -14.6117608
[178,] -18.6993005 -17.2424432
[179,] -21.5866169 -18.6993005
[180,] -17.3985459 -21.5866169
[181,] -9.0257511 -17.3985459
[182,] -10.5310088 -9.0257511
[183,] -11.6659058 -10.5310088
[184,] -5.7550030 -11.6659058
[185,] -8.7141755 -5.7550030
[186,] 1.8302496 -8.7141755
[187,] 3.7559951 1.8302496
[188,] -2.9024172 3.7559951
[189,] -7.0497177 -2.9024172
[190,] -15.4382646 -7.0497177
[191,] -17.5612896 -15.4382646
[192,] -17.9325787 -17.5612896
[193,] -7.7303816 -17.9325787
[194,] -5.1506181 -7.7303816
[195,] -9.0373000 -5.1506181
[196,] -6.0700513 -9.0373000
[197,] -3.5539726 -6.0700513
[198,] -0.4177707 -3.5539726
[199,] -17.5651877 -0.4177707
[200,] -17.3424128 -17.5651877
[201,] -24.8085261 -17.3424128
[202,] -21.7862058 -24.8085261
[203,] -16.0765364 -21.7862058
[204,] -10.3042640 -16.0765364
[205,] -23.9918475 -10.3042640
[206,] -61.6634327 -23.9918475
[207,] -59.8388771 -61.6634327
[208,] -56.4705311 -59.8388771
[209,] -52.6773768 -56.4705311
[210,] 24.7262233 -52.6773768
[211,] 101.2765983 24.7262233
[212,] 72.2504967 101.2765983
[213,] 65.8395394 72.2504967
[214,] 70.2430470 65.8395394
[215,] 67.4421267 70.2430470
[216,] 72.6363188 67.4421267
[217,] 57.2286534 72.6363188
[218,] 49.2372774 57.2286534
[219,] 47.8281339 49.2372774
[220,] 40.3159272 47.8281339
[221,] 45.1738356 40.3159272
[222,] 46.3567060 45.1738356
[223,] 55.1656482 46.3567060
[224,] 52.3192005 55.1656482
[225,] 44.6325425 52.3192005
[226,] 40.0023510 44.6325425
[227,] 33.4951245 40.0023510
[228,] 27.7540708 33.4951245
[229,] 23.4619262 27.7540708
[230,] 21.0040641 23.4619262
[231,] 23.7584850 21.0040641
[232,] 13.9355961 23.7584850
[233,] 14.8170635 13.9355961
[234,] 4.6331701 14.8170635
[235,] -24.5487789 4.6331701
[236,] -33.9915779 -24.5487789
[237,] -38.3520328 -33.9915779
[238,] -43.8317220 -38.3520328
[239,] -27.3095327 -43.8317220
[240,] -19.0725061 -27.3095327
[241,] -53.8988259 -19.0725061
[242,] -116.1726325 -53.8988259
[243,] -59.7304406 -116.1726325
[244,] -84.4525365 -59.7304406
[245,] -53.3662305 -84.4525365
[246,] 41.1507493 -53.3662305
[247,] 57.3599693 41.1507493
[248,] 61.1534343 57.3599693
[249,] 48.7323501 61.1534343
[250,] 49.8778725 48.7323501
[251,] 21.3362991 49.8778725
[252,] 8.0382516 21.3362991
[253,] -11.0691495 8.0382516
[254,] 23.9584857 -11.0691495
[255,] 12.9213940 23.9584857
[256,] 26.3253695 12.9213940
[257,] 19.3781615 26.3253695
[258,] 16.7112566 19.3781615
[259,] 11.8486890 16.7112566
[260,] 19.1771356 11.8486890
[261,] 9.8616172 19.1771356
[262,] -1.7581699 9.8616172
[263,] -7.8664937 -1.7581699
[264,] -6.7832614 -7.8664937
[265,] -2.7095545 -6.7832614
[266,] 0.5849103 -2.7095545
[267,] 1.8926626 0.5849103
[268,] 7.7472196 1.8926626
[269,] -0.4664743 7.7472196
[270,] 11.3603279 -0.4664743
[271,] 16.4810496 11.3603279
[272,] 20.7704956 16.4810496
[273,] 29.0261168 20.7704956
[274,] -1.4088343 29.0261168
[275,] -23.8934274 -1.4088343
[276,] 12.6964814 -23.8934274
[277,] 35.2713782 12.6964814
[278,] 29.5163453 35.2713782
[279,] 31.9847402 29.5163453
[280,] 28.7362829 31.9847402
[281,] 28.1755636 28.7362829
[282,] 30.9731352 28.1755636
[283,] 37.8028998 30.9731352
[284,] 28.7712457 37.8028998
[285,] 23.7257696 28.7712457
[286,] 14.5568552 23.7257696
[287,] 13.8398587 14.5568552
[288,] 21.0420889 13.8398587
[289,] 31.5685854 21.0420889
[290,] 30.6690787 31.5685854
[291,] 16.4724418 30.6690787
[292,] 5.9047090 16.4724418
[293,] 31.1583340 5.9047090
[294,] 26.6875951 31.1583340
[295,] 19.9446600 26.6875951
[296,] 16.0395792 19.9446600
[297,] 25.3630614 16.0395792
[298,] 17.7335970 25.3630614
[299,] 11.5066455 17.7335970
[300,] 9.6875906 11.5066455
[301,] 12.7522547 9.6875906
[302,] -4.9783997 12.7522547
[303,] 0.4695298 -4.9783997
[304,] 15.0324026 0.4695298
[305,] 11.9041000 15.0324026
[306,] 29.4993051 11.9041000
[307,] 27.6843182 29.4993051
[308,] 16.5570401 27.6843182
[309,] 10.9562230 16.5570401
[310,] 6.3306850 10.9562230
[311,] 14.8676680 6.3306850
[312,] 22.9167384 14.8676680
[313,] 17.3120873 22.9167384
[314,] 24.9653701 17.3120873
[315,] 27.0975011 24.9653701
[316,] 17.0448397 27.0975011
[317,] 22.1968121 17.0448397
[318,] 16.7048806 22.1968121
[319,] 19.4404887 16.7048806
[320,] 18.2443582 19.4404887
[321,] 10.4198895 18.2443582
[322,] 4.9539893 10.4198895
[323,] 11.2743408 4.9539893
[324,] 0.8598470 11.2743408
[325,] -3.9677286 0.8598470
[326,] -0.1872380 -3.9677286
[327,] 0.7552183 -0.1872380
[328,] -10.0291327 0.7552183
[329,] -29.0264862 -10.0291327
[330,] 0.3282642 -29.0264862
[331,] -1.9919316 0.3282642
[332,] -15.2965630 -1.9919316
[333,] -17.2339085 -15.2965630
[334,] -38.1836533 -17.2339085
[335,] -56.9769190 -38.1836533
[336,] -31.2374334 -56.9769190
[337,] -68.5741577 -31.2374334
[338,] -87.2224483 -68.5741577
[339,] -50.5834558 -87.2224483
[340,] -36.3772991 -50.5834558
[341,] -15.4913499 -36.3772991
[342,] -4.5404335 -15.4913499
[343,] 9.8959017 -4.5404335
[344,] 15.2388643 9.8959017
[345,] -3.8420561 15.2388643
[346,] -25.6201060 -3.8420561
[347,] -32.0283372 -25.6201060
[348,] -61.2426594 -32.0283372
[349,] -50.0406340 -61.2426594
[350,] -25.2633294 -50.0406340
[351,] -28.8409684 -25.2633294
[352,] -16.7248567 -28.8409684
[353,] -23.3755283 -16.7248567
[354,] -25.4127532 -23.3755283
[355,] -33.2215398 -25.4127532
[356,] -28.6539209 -33.2215398
[357,] -30.1833208 -28.6539209
[358,] -50.4017463 -30.1833208
[359,] -70.0146444 -50.4017463
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -20.4609978 -44.9601806
2 0.2920074 -20.4609978
3 39.4352833 0.2920074
4 73.0628968 39.4352833
5 85.7736740 73.0628968
6 82.2256744 85.7736740
7 74.9828319 82.2256744
8 69.7818627 74.9828319
9 64.0286262 69.7818627
10 54.1212665 64.0286262
11 49.4546799 54.1212665
12 45.1537107 49.4546799
13 41.3232134 45.1537107
14 40.2089129 41.3232134
15 28.4472576 40.2089129
16 23.6125893 28.4472576
17 14.9514072 23.6125893
18 10.8489788 14.9514072
19 -3.9067406 10.8489788
20 -11.0453353 -3.9067406
21 -14.0579320 -11.0453353
22 -12.6068438 -14.0579320
23 -13.1536128 -12.6068438
24 -16.2298332 -13.1536128
25 -17.9829772 -16.2298332
26 -6.6221982 -17.9829772
27 -9.2818440 -6.6221982
28 -13.7206239 -9.2818440
29 -17.0396194 -13.7206239
30 2.1755751 -17.0396194
31 24.5552867 2.1755751
32 28.1321202 24.5552867
33 29.5093834 28.1321202
34 32.1157201 29.5093834
35 32.2094058 32.1157201
36 19.9152849 32.2094058
37 26.6769346 19.9152849
38 21.5577029 26.6769346
39 10.4947651 21.5577029
40 14.5274950 10.4947651
41 13.7842136 14.5274950
42 22.7719226 13.7842136
43 20.8509072 22.7719226
44 11.4321299 20.8509072
45 6.9195333 11.4321299
46 -4.0590586 6.9195333
47 -19.5843708 -4.0590586
48 -22.1685367 -19.5843708
49 -36.6068869 -22.1685367
50 -39.8686755 -36.6068869
51 -41.2906957 -39.8686755
52 -42.5352265 -41.2906957
53 -40.3300151 -42.5352265
54 -41.2472373 -40.3300151
55 -41.4236864 -41.2472373
56 -40.5919613 -41.4236864
57 -48.0228287 -40.5919613
58 -55.0987765 -48.0228287
59 -45.0891072 -55.0987765
60 -44.8187517 -45.0891072
61 -32.2947275 -44.8187517
62 -36.8202654 -32.2947275
63 -36.8839303 -36.8202654
64 -34.5205156 -36.8839303
65 -34.9142994 -34.5205156
66 -35.4255856 -34.9142994
67 -32.5139068 -35.4255856
68 -32.2762456 -32.5139068
69 -46.4894901 -32.2762456
70 -43.5710037 -46.4894901
71 -40.5374978 -43.5710037
72 -36.5978271 -40.5374978
73 -33.3282318 -36.5978271
74 -29.6860013 -33.3282318
75 -37.4419057 -29.6860013
76 -37.2953868 -37.4419057
77 -36.1812251 -37.2953868
78 -34.2271226 -36.1812251
79 -30.3817447 -34.2271226
80 -37.5850011 -30.3817447
81 -38.2640837 -37.5850011
82 -34.4724482 -38.2640837
83 -34.4023214 -34.4724482
84 -29.4934281 -34.4023214
85 -22.0040152 -29.4934281
86 -21.7400502 -22.0040152
87 -21.1601535 -21.7400502
88 -19.3324474 -21.1601535
89 -15.3104327 -19.3324474
90 -9.2236359 -15.3104327
91 -13.2032844 -9.2236359
92 -13.0311044 -13.2032844
93 -10.1605044 -13.0311044
94 -9.1351697 -10.1605044
95 -10.0602968 -9.1351697
96 -7.4631830 -10.0602968
97 -2.8905734 -7.4631830
98 -4.4852414 -2.8905734
99 0.2394994 -4.4852414
100 4.5763409 0.2394994
101 1.2149737 4.5763409
102 6.0107209 1.2149737
103 3.4947292 6.0107209
104 -1.2411290 3.4947292
105 2.6760470 -1.2411290
106 -3.8989886 2.6760470
107 -12.1379046 -3.8989886
108 -2.4661875 -12.1379046
109 62.6350840 -2.4661875
110 56.1134592 62.6350840
111 46.1843131 56.1134592
112 40.2911043 46.1843131
113 38.3468181 40.2911043
114 34.7524277 38.3468181
115 23.6918697 34.7524277
116 7.3662442 23.6918697
117 7.1853372 7.3662442
118 9.5055554 7.1853372
119 11.7965045 9.5055554
120 11.5758103 11.7965045
121 5.6464104 11.5758103
122 3.6203305 5.6464104
123 -3.5283555 3.6203305
124 -10.7124289 -3.5283555
125 -10.2863952 -10.7124289
126 -10.1263567 -10.2863952
127 -18.1206138 -10.1263567
128 -12.3760119 -18.1206138
129 -9.4799359 -12.3760119
130 -23.8884855 -9.4799359
131 -25.6025602 -23.8884855
132 -15.8402428 -25.6025602
133 -19.8531171 -15.8402428
134 -22.4593795 -19.8531171
135 -16.7785705 -22.4593795
136 -17.4488549 -16.7785705
137 -16.5267477 -17.4488549
138 -6.8468916 -16.5267477
139 -8.9143904 -6.8468916
140 -5.3420254 -8.9143904
141 -7.1201958 -5.3420254
142 -10.8705752 -7.1201958
143 -5.3568868 -10.8705752
144 -1.7005054 -5.3568868
145 12.0989551 -1.7005054
146 13.1688561 12.0989551
147 8.1392472 13.1688561
148 16.0066810 8.1392472
149 14.1632144 16.0066810
150 21.6558547 14.1632144
151 18.6012327 21.6558547
152 14.1052873 18.6012327
153 8.1005437 14.1052873
154 -5.6633470 8.1005437
155 0.3265974 -5.6633470
156 1.5069079 0.3265974
157 8.9923943 1.5069079
158 -1.4369776 8.9923943
159 -6.6523347 -1.4369776
160 1.7150991 -6.6523347
161 7.9431423 1.7150991
162 19.1418112 7.9431423
163 18.7871891 19.1418112
164 6.6420104 18.7871891
165 7.9838427 6.6420104
166 2.8320091 7.9838427
167 4.7585743 2.8320091
168 7.4546834 4.7585743
169 11.5173380 7.4546834
170 2.1801131 11.5173380
171 -2.1819125 2.1801131
172 -4.6115570 -2.1819125
173 -4.4300897 -4.6115570
174 -7.7463071 -4.4300897
175 -14.1217514 -7.7463071
176 -14.6117608 -14.1217514
177 -17.2424432 -14.6117608
178 -18.6993005 -17.2424432
179 -21.5866169 -18.6993005
180 -17.3985459 -21.5866169
181 -9.0257511 -17.3985459
182 -10.5310088 -9.0257511
183 -11.6659058 -10.5310088
184 -5.7550030 -11.6659058
185 -8.7141755 -5.7550030
186 1.8302496 -8.7141755
187 3.7559951 1.8302496
188 -2.9024172 3.7559951
189 -7.0497177 -2.9024172
190 -15.4382646 -7.0497177
191 -17.5612896 -15.4382646
192 -17.9325787 -17.5612896
193 -7.7303816 -17.9325787
194 -5.1506181 -7.7303816
195 -9.0373000 -5.1506181
196 -6.0700513 -9.0373000
197 -3.5539726 -6.0700513
198 -0.4177707 -3.5539726
199 -17.5651877 -0.4177707
200 -17.3424128 -17.5651877
201 -24.8085261 -17.3424128
202 -21.7862058 -24.8085261
203 -16.0765364 -21.7862058
204 -10.3042640 -16.0765364
205 -23.9918475 -10.3042640
206 -61.6634327 -23.9918475
207 -59.8388771 -61.6634327
208 -56.4705311 -59.8388771
209 -52.6773768 -56.4705311
210 24.7262233 -52.6773768
211 101.2765983 24.7262233
212 72.2504967 101.2765983
213 65.8395394 72.2504967
214 70.2430470 65.8395394
215 67.4421267 70.2430470
216 72.6363188 67.4421267
217 57.2286534 72.6363188
218 49.2372774 57.2286534
219 47.8281339 49.2372774
220 40.3159272 47.8281339
221 45.1738356 40.3159272
222 46.3567060 45.1738356
223 55.1656482 46.3567060
224 52.3192005 55.1656482
225 44.6325425 52.3192005
226 40.0023510 44.6325425
227 33.4951245 40.0023510
228 27.7540708 33.4951245
229 23.4619262 27.7540708
230 21.0040641 23.4619262
231 23.7584850 21.0040641
232 13.9355961 23.7584850
233 14.8170635 13.9355961
234 4.6331701 14.8170635
235 -24.5487789 4.6331701
236 -33.9915779 -24.5487789
237 -38.3520328 -33.9915779
238 -43.8317220 -38.3520328
239 -27.3095327 -43.8317220
240 -19.0725061 -27.3095327
241 -53.8988259 -19.0725061
242 -116.1726325 -53.8988259
243 -59.7304406 -116.1726325
244 -84.4525365 -59.7304406
245 -53.3662305 -84.4525365
246 41.1507493 -53.3662305
247 57.3599693 41.1507493
248 61.1534343 57.3599693
249 48.7323501 61.1534343
250 49.8778725 48.7323501
251 21.3362991 49.8778725
252 8.0382516 21.3362991
253 -11.0691495 8.0382516
254 23.9584857 -11.0691495
255 12.9213940 23.9584857
256 26.3253695 12.9213940
257 19.3781615 26.3253695
258 16.7112566 19.3781615
259 11.8486890 16.7112566
260 19.1771356 11.8486890
261 9.8616172 19.1771356
262 -1.7581699 9.8616172
263 -7.8664937 -1.7581699
264 -6.7832614 -7.8664937
265 -2.7095545 -6.7832614
266 0.5849103 -2.7095545
267 1.8926626 0.5849103
268 7.7472196 1.8926626
269 -0.4664743 7.7472196
270 11.3603279 -0.4664743
271 16.4810496 11.3603279
272 20.7704956 16.4810496
273 29.0261168 20.7704956
274 -1.4088343 29.0261168
275 -23.8934274 -1.4088343
276 12.6964814 -23.8934274
277 35.2713782 12.6964814
278 29.5163453 35.2713782
279 31.9847402 29.5163453
280 28.7362829 31.9847402
281 28.1755636 28.7362829
282 30.9731352 28.1755636
283 37.8028998 30.9731352
284 28.7712457 37.8028998
285 23.7257696 28.7712457
286 14.5568552 23.7257696
287 13.8398587 14.5568552
288 21.0420889 13.8398587
289 31.5685854 21.0420889
290 30.6690787 31.5685854
291 16.4724418 30.6690787
292 5.9047090 16.4724418
293 31.1583340 5.9047090
294 26.6875951 31.1583340
295 19.9446600 26.6875951
296 16.0395792 19.9446600
297 25.3630614 16.0395792
298 17.7335970 25.3630614
299 11.5066455 17.7335970
300 9.6875906 11.5066455
301 12.7522547 9.6875906
302 -4.9783997 12.7522547
303 0.4695298 -4.9783997
304 15.0324026 0.4695298
305 11.9041000 15.0324026
306 29.4993051 11.9041000
307 27.6843182 29.4993051
308 16.5570401 27.6843182
309 10.9562230 16.5570401
310 6.3306850 10.9562230
311 14.8676680 6.3306850
312 22.9167384 14.8676680
313 17.3120873 22.9167384
314 24.9653701 17.3120873
315 27.0975011 24.9653701
316 17.0448397 27.0975011
317 22.1968121 17.0448397
318 16.7048806 22.1968121
319 19.4404887 16.7048806
320 18.2443582 19.4404887
321 10.4198895 18.2443582
322 4.9539893 10.4198895
323 11.2743408 4.9539893
324 0.8598470 11.2743408
325 -3.9677286 0.8598470
326 -0.1872380 -3.9677286
327 0.7552183 -0.1872380
328 -10.0291327 0.7552183
329 -29.0264862 -10.0291327
330 0.3282642 -29.0264862
331 -1.9919316 0.3282642
332 -15.2965630 -1.9919316
333 -17.2339085 -15.2965630
334 -38.1836533 -17.2339085
335 -56.9769190 -38.1836533
336 -31.2374334 -56.9769190
337 -68.5741577 -31.2374334
338 -87.2224483 -68.5741577
339 -50.5834558 -87.2224483
340 -36.3772991 -50.5834558
341 -15.4913499 -36.3772991
342 -4.5404335 -15.4913499
343 9.8959017 -4.5404335
344 15.2388643 9.8959017
345 -3.8420561 15.2388643
346 -25.6201060 -3.8420561
347 -32.0283372 -25.6201060
348 -61.2426594 -32.0283372
349 -50.0406340 -61.2426594
350 -25.2633294 -50.0406340
351 -28.8409684 -25.2633294
352 -16.7248567 -28.8409684
353 -23.3755283 -16.7248567
354 -25.4127532 -23.3755283
355 -33.2215398 -25.4127532
356 -28.6539209 -33.2215398
357 -30.1833208 -28.6539209
358 -50.4017463 -30.1833208
359 -70.0146444 -50.4017463
> 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/78ozh1321370291.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/85qj71321370291.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/9jkzs1321370291.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/wessaorg/rcomp/tmp/10sopi1321370291.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11ntjt1321370291.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/12iiyh1321370291.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/13ipr51321370291.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/14glnp1321370291.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/159m7e1321370291.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/16dqmw1321370291.tab")
+ }
>
> try(system("convert tmp/12t1r1321370291.ps tmp/12t1r1321370291.png",intern=TRUE))
character(0)
> try(system("convert tmp/287ox1321370291.ps tmp/287ox1321370291.png",intern=TRUE))
character(0)
> try(system("convert tmp/3qz411321370291.ps tmp/3qz411321370291.png",intern=TRUE))
character(0)
> try(system("convert tmp/45oy41321370291.ps tmp/45oy41321370291.png",intern=TRUE))
character(0)
> try(system("convert tmp/5z0qa1321370291.ps tmp/5z0qa1321370291.png",intern=TRUE))
character(0)
> try(system("convert tmp/6mrti1321370291.ps tmp/6mrti1321370291.png",intern=TRUE))
character(0)
> try(system("convert tmp/78ozh1321370291.ps tmp/78ozh1321370291.png",intern=TRUE))
character(0)
> try(system("convert tmp/85qj71321370291.ps tmp/85qj71321370291.png",intern=TRUE))
character(0)
> try(system("convert tmp/9jkzs1321370291.ps tmp/9jkzs1321370291.png",intern=TRUE))
character(0)
> try(system("convert tmp/10sopi1321370291.ps tmp/10sopi1321370291.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
9.277 0.571 9.943