R version 2.8.0 (2008-10-20)
Copyright (C) 2008 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> x <- array(list(358.59
+ ,122.36
+ ,362.96
+ ,123.33
+ ,362.42
+ ,123.04
+ ,364.97
+ ,124.53
+ ,364.04
+ ,125.13
+ ,361.06
+ ,125.85
+ ,358.48
+ ,126.50
+ ,352.96
+ ,126.53
+ ,359.59
+ ,127.07
+ ,360.39
+ ,124.55
+ ,357.40
+ ,124.90
+ ,362.93
+ ,124.32
+ ,364.55
+ ,122.84
+ ,365.73
+ ,123.31
+ ,364.70
+ ,123.31
+ ,364.65
+ ,124.87
+ ,359.43
+ ,124.64
+ ,362.14
+ ,124.73
+ ,356.97
+ ,124.90
+ ,354.82
+ ,124.04
+ ,353.17
+ ,123.28
+ ,357.06
+ ,123.86
+ ,356.18
+ ,122.29
+ ,355.01
+ ,124.09
+ ,355.65
+ ,124.54
+ ,357.31
+ ,125.65
+ ,357.07
+ ,125.70
+ ,357.91
+ ,125.53
+ ,358.48
+ ,125.61
+ ,358.97
+ ,125.55
+ ,351.77
+ ,125.41
+ ,352.16
+ ,127.60
+ ,359.08
+ ,124.68
+ ,360.35
+ ,124.41
+ ,359.53
+ ,126.43
+ ,359.30
+ ,126.38
+ ,358.41
+ ,125.78
+ ,359.68
+ ,124.70
+ ,355.31
+ ,125.07
+ ,357.08
+ ,125.25
+ ,349.71
+ ,126.58
+ ,354.13
+ ,127.13
+ ,345.49
+ ,125.82
+ ,341.69
+ ,123.70
+ ,344.25
+ ,124.39
+ ,340.17
+ ,123.70
+ ,342.47
+ ,124.42
+ ,344.43
+ ,121.05
+ ,333.23
+ ,121.02
+ ,339.72
+ ,123.23
+ ,342.61
+ ,121.32
+ ,346.36
+ ,120.91
+ ,339.09
+ ,120.72
+ ,339.73
+ ,123.31
+ ,341.12
+ ,119.58
+ ,335.94
+ ,119.53
+ ,333.46
+ ,120.59
+ ,335.66
+ ,118.63
+ ,341.12
+ ,118.47
+ ,342.21
+ ,111.81
+ ,342.62
+ ,114.71
+ ,346.06
+ ,117.34
+ ,344.43
+ ,115.77
+ ,346.65
+ ,118.38
+ ,343.74
+ ,117.84
+ ,335.67
+ ,118.83
+ ,342.75
+ ,120.02
+ ,341.77
+ ,116.21
+ ,345.84
+ ,117.08
+ ,346.52
+ ,120.20
+ ,350.79
+ ,119.83
+ ,345.44
+ ,118.92
+ ,345.87
+ ,118.03
+ ,338.48
+ ,117.71
+ ,337.21
+ ,119.55
+ ,340.81
+ ,116.13
+ ,339.86
+ ,115.97
+ ,342.86
+ ,115.99
+ ,343.33
+ ,114.96
+ ,341.73
+ ,116.46
+ ,351.38
+ ,116.55
+ ,351.13
+ ,113.05
+ ,345.99
+ ,117.44
+ ,347.55
+ ,118.84
+ ,346.02
+ ,117.06
+ ,345.29
+ ,117.54
+ ,347.03
+ ,119.31
+ ,348.01
+ ,118.72
+ ,345.48
+ ,121.55
+ ,349.40
+ ,122.61
+ ,351.05
+ ,121.53
+ ,349.70
+ ,123.31
+ ,350.86
+ ,124.07
+ ,354.45
+ ,123.59
+ ,355.30
+ ,122.97
+ ,357.48
+ ,123.22
+ ,355.24
+ ,123.04
+ ,351.79
+ ,122.96
+ ,355.22
+ ,122.81
+ ,351.02
+ ,122.81
+ ,350.28
+ ,122.62
+ ,350.17
+ ,120.82
+ ,348.16
+ ,119.41
+ ,340.30
+ ,121.56
+ ,343.75
+ ,121.59
+ ,344.71
+ ,118.50
+ ,344.13
+ ,118.77
+ ,342.14
+ ,118.86
+ ,345.04
+ ,117.60
+ ,346.02
+ ,119.90
+ ,346.43
+ ,121.83
+ ,347.07
+ ,121.84
+ ,339.33
+ ,122.12
+ ,339.10
+ ,122.12
+ ,337.19
+ ,121.36
+ ,339.58
+ ,119.66
+ ,327.85
+ ,119.32
+ ,326.81
+ ,120.36
+ ,321.73
+ ,117.06
+ ,320.45
+ ,117.48
+ ,327.69
+ ,115.60
+ ,323.95
+ ,113.86
+ ,320.47
+ ,116.92
+ ,322.13
+ ,117.75
+ ,316.34
+ ,117.75
+ ,314.78
+ ,115.31
+ ,308.90
+ ,116.28
+ ,308.62
+ ,115.22
+ ,314.41
+ ,115.65
+ ,306.88
+ ,115.11
+ ,310.60
+ ,118.67
+ ,321.60
+ ,118.04
+ ,321.50
+ ,116.50
+ ,325.68
+ ,119.78
+ ,324.35
+ ,119.95
+ ,320.01
+ ,120.37
+ ,326.88
+ ,119.79
+ ,332.39
+ ,119.43
+ ,331.48
+ ,121.06
+ ,332.62
+ ,121.74
+ ,324.79
+ ,121.09
+ ,327.12
+ ,122.97
+ ,328.91
+ ,120.50
+ ,328.37
+ ,117.18
+ ,324.83
+ ,115.03
+ ,325.90
+ ,113.36
+ ,326.18
+ ,112.59
+ ,328.94
+ ,111.65
+ ,333.78
+ ,111.98
+ ,328.06
+ ,114.87
+ ,325.87
+ ,114.67
+ ,325.41
+ ,114.09
+ ,318.86
+ ,114.77
+ ,319.13
+ ,117.05
+ ,310.16
+ ,117.22
+ ,311.73
+ ,113.18
+ ,306.54
+ ,110.95
+ ,311.16
+ ,112.14
+ ,311.98
+ ,112.72
+ ,306.72
+ ,110.01
+ ,308.05
+ ,110.29
+ ,300.76
+ ,110.74
+ ,301.90
+ ,110.32
+ ,293.09
+ ,105.89
+ ,292.76
+ ,108.97
+ ,294.58
+ ,109.34
+ ,289.90
+ ,106.57
+ ,296.69
+ ,99.49
+ ,297.21
+ ,101.81
+ ,293.31
+ ,104.29
+ ,296.25
+ ,109.73
+ ,298.60
+ ,105.06
+ ,296.87
+ ,107.97
+ ,301.02
+ ,108.13
+ ,304.73
+ ,109.86
+ ,301.92
+ ,108.95
+ ,295.72
+ ,111.20
+ ,293.18
+ ,110.69
+ ,298.35
+ ,106.10
+ ,297.99
+ ,105.68
+ ,299.85
+ ,104.12
+ ,299.85
+ ,104.71
+ ,304.45
+ ,104.30
+ ,299.45
+ ,103.52
+ ,298.14
+ ,107.76
+ ,298.78
+ ,107.80
+ ,297.02
+ ,107.30
+ ,301.33
+ ,108.64
+ ,294.96
+ ,105.03
+ ,296.69
+ ,108.30
+ ,300.73
+ ,107.21
+ ,301.96
+ ,109.27
+ ,297.38
+ ,109.50
+ ,293.87
+ ,111.68
+ ,285.96
+ ,111.80
+ ,285.41
+ ,111.75
+ ,283.70
+ ,106.68
+ ,284.76
+ ,106.37
+ ,277.11
+ ,105.76
+ ,274.73
+ ,109.01
+ ,274.73
+ ,109.01
+ ,274.73
+ ,109.01
+ ,274.73
+ ,109.01
+ ,274.69
+ ,107.69
+ ,275.42
+ ,105.19
+ ,264.15
+ ,105.48
+ ,276.24
+ ,102.22
+ ,268.88
+ ,100.54
+ ,277.97
+ ,105.00
+ ,280.49
+ ,105.44
+ ,281.09
+ ,107.89
+ ,276.16
+ ,108.64
+ ,272.58
+ ,106.70
+ ,270.94
+ ,109.10
+ ,284.31
+ ,105.23
+ ,283.94
+ ,108.41
+ ,284.18
+ ,108.80
+ ,282.83
+ ,110.39
+ ,283.84
+ ,110.22
+ ,282.71
+ ,110.86
+ ,279.29
+ ,108.58
+ ,280.70
+ ,107.70
+ ,274.47
+ ,106.62
+ ,273.44
+ ,109.84
+ ,275.49
+ ,107.16
+ ,279.46
+ ,107.26
+ ,280.19
+ ,108.70
+ ,288.21
+ ,109.85
+ ,284.80
+ ,109.41
+ ,281.41
+ ,112.36
+ ,283.39
+ ,111.03
+ ,287.97
+ ,110.67
+ ,290.77
+ ,109.21
+ ,290.60
+ ,113.58
+ ,289.67
+ ,113.88
+ ,289.84
+ ,114.08
+ ,298.55
+ ,112.33
+ ,296.07
+ ,113.92
+ ,297.14
+ ,114.41
+ ,295.34
+ ,114.57
+ ,296.25
+ ,115.35
+ ,294.30
+ ,113.13
+ ,296.15
+ ,113.29
+ ,296.49
+ ,112.56
+ ,298.05
+ ,113.06
+ ,301.03
+ ,113.46
+ ,300.52
+ ,115.39
+ ,301.50
+ ,116.62
+ ,296.93
+ ,117.04
+ ,289.84
+ ,117.42
+ ,291.44
+ ,115.62
+ ,286.88
+ ,115.16
+ ,286.74
+ ,115.69
+ ,288.93
+ ,112.85
+ ,292.19
+ ,114.05
+ ,295.39
+ ,112.00
+ ,295.86
+ ,113.74
+ ,293.36
+ ,116.26
+ ,292.86
+ ,118.63
+ ,292.73
+ ,116.49
+ ,296.73
+ ,118.23
+ ,285.02
+ ,116.83
+ ,285.24
+ ,118.82
+ ,288.62
+ ,114.36
+ ,283.36
+ ,112.02
+ ,285.84
+ ,113.24
+ ,291.48
+ ,109.75
+ ,291.41
+ ,110.33
+ ,287.77
+ ,112.86
+ ,284.97
+ ,113.04
+ ,286.05
+ ,113.80
+ ,278.19
+ ,110.90
+ ,281.21
+ ,109.96
+ ,277.92
+ ,108.69
+ ,280.08
+ ,108.84
+ ,269.24
+ ,108.47
+ ,268.48
+ ,108.07
+ ,268.83
+ ,107.94
+ ,269.54
+ ,108.11
+ ,262.37
+ ,108.11
+ ,265.12
+ ,106.81
+ ,265.34
+ ,105.58
+ ,263.32
+ ,105.61
+ ,267.18
+ ,106.52
+ ,260.75
+ ,103.86
+ ,261.78
+ ,104.60
+ ,257.27
+ ,104.73
+ ,255.63
+ ,105.12
+ ,251.39
+ ,104.76
+ ,259.49
+ ,103.85
+ ,261.18
+ ,103.83
+ ,261.65
+ ,103.22
+ ,262.01
+ ,101.64
+ ,265.23
+ ,102.13
+ ,268.10
+ ,104.33
+ ,262.27
+ ,104.92
+ ,263.59
+ ,107.78
+ ,257.85
+ ,104.49
+ ,265.69
+ ,102.80
+ ,271.15
+ ,102.86
+ ,266.69
+ ,104.51
+ ,265.77
+ ,104.73
+ ,262.32
+ ,102.58
+ ,270.48
+ ,99.93
+ ,273.03
+ ,101.41
+ ,269.13
+ ,101.05
+ ,280.65
+ ,99.86
+ ,282.75
+ ,101.11
+ ,281.44
+ ,100.89
+ ,281.99
+ ,101.09
+ ,282.86
+ ,98.31
+ ,287.21
+ ,98.08
+ ,283.11
+ ,99.55
+ ,280.66
+ ,99.62
+ ,282.39
+ ,97.37
+ ,280.83
+ ,98.16
+ ,284.71
+ ,97.98
+ ,279.99
+ ,98.15
+ ,283.50
+ ,97.10
+ ,284.88
+ ,97.24
+ ,288.60
+ ,96.70
+ ,284.80
+ ,96.64
+ ,287.20
+ ,100.65
+ ,286.22
+ ,96.75
+ ,286.54
+ ,97.74
+ ,279.58
+ ,97.92
+ ,283.08
+ ,98.34
+ ,288.88
+ ,93.84
+ ,280.18
+ ,97.80
+ ,284.16
+ ,96.20
+ ,290.57
+ ,95.99
+ ,286.82
+ ,95.18
+ ,273.00
+ ,95.95
+ ,278.69
+ ,92.23
+ ,264.54
+ ,91.78
+ ,271.92
+ ,92.97
+ ,283.60
+ ,89.76
+ ,269.25
+ ,92.88
+ ,263.58
+ ,96.23
+ ,264.16
+ ,95.79
+ ,268.85
+ ,93.97
+ ,269.67
+ ,93.90
+ ,249.41
+ ,93.60
+ ,268.99
+ ,93.96
+ ,268.65
+ ,88.69
+ ,260.16
+ ,88.57
+ ,256.55
+ ,85.62
+ ,251.47
+ ,86.25
+ ,234.93
+ ,85.33
+ ,232.96
+ ,83.33
+ ,215.49
+ ,77.78
+ ,213.68
+ ,78.70
+ ,236.07
+ ,72.05
+ ,235.41
+ ,80.75
+ ,214.77
+ ,81.41
+ ,225.85
+ ,82.65
+ ,224.64
+ ,75.85
+ ,238.26
+ ,75.70
+ ,232.44
+ ,78.25
+ ,222.50
+ ,77.41
+ ,225.28
+ ,76.84
+ ,220.49
+ ,74.25
+ ,216.86
+ ,74.95
+ ,234.70
+ ,68.78
+ ,230.06
+ ,73.21
+ ,238.27
+ ,73.26
+ ,238.56
+ ,78.67
+ ,242.70
+ ,75.63
+ ,249.14
+ ,74.99
+ ,234.89
+ ,83.87
+ ,227.78
+ ,79.62
+ ,234.04
+ ,80.13
+ ,230.70
+ ,79.76
+ ,230.17
+ ,78.20
+ ,218.23
+ ,78.05
+ ,232.20
+ ,79.05
+ ,220.76
+ ,73.32
+ ,215.60
+ ,75.17
+ ,217.69
+ ,73.26
+ ,204.35
+ ,73.72
+ ,191.44
+ ,73.57
+ ,203.84
+ ,70.60
+ ,211.86
+ ,71.25
+ ,210.57
+ ,74.22
+ ,219.57
+ ,73.32
+ ,219.98
+ ,73.01
+ ,226.01
+ ,74.21
+ ,207.04
+ ,75.32
+ ,212.52
+ ,71.73
+ ,217.92
+ ,71.94
+ ,210.45
+ ,72.94
+ ,218.53
+ ,72.47
+ ,223.32
+ ,71.94
+ ,218.76
+ ,74.30
+ ,217.63
+ ,74.30)
+ ,dim=c(2
+ ,395)
+ ,dimnames=list(c('Amerika'
+ ,'Japan')
+ ,1:395))
> y <- array(NA,dim=c(2,395),dimnames=list(c('Amerika','Japan'),1:395))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par3 = 'Linear Trend'
> par2 = 'Do not include Seasonal Dummies'
> par1 = '1'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: Write here your technical program description (don't use hard returns!)
> library(lattice)
> library(lmtest)
Loading required package: zoo
Attaching package: 'zoo'
The following object(s) are masked from package:base :
as.Date.numeric
> n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
> par1 <- as.numeric(par1)
> x <- t(y)
> k <- length(x[1,])
> n <- length(x[,1])
> x1 <- cbind(x[,par1], x[,1:k!=par1])
> mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
> colnames(x1) <- mycolnames #colnames(x)[par1]
> x <- x1
> if (par3 == 'First Differences'){
+ x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
+ for (i in 1:n-1) {
+ for (j in 1:k) {
+ x2[i,j] <- x[i+1,j] - x[i,j]
+ }
+ }
+ x <- x2
+ }
> if (par2 == 'Include Monthly Dummies'){
+ x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
+ for (i in 1:11){
+ x2[seq(i,n,12),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> if (par2 == 'Include Quarterly Dummies'){
+ x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
+ for (i in 1:3){
+ x2[seq(i,n,4),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> k <- length(x[1,])
> if (par3 == 'Linear Trend'){
+ x <- cbind(x, c(1:n))
+ colnames(x)[k+1] <- 't'
+ }
> x
Amerika Japan t
1 358.59 122.36 1
2 362.96 123.33 2
3 362.42 123.04 3
4 364.97 124.53 4
5 364.04 125.13 5
6 361.06 125.85 6
7 358.48 126.50 7
8 352.96 126.53 8
9 359.59 127.07 9
10 360.39 124.55 10
11 357.40 124.90 11
12 362.93 124.32 12
13 364.55 122.84 13
14 365.73 123.31 14
15 364.70 123.31 15
16 364.65 124.87 16
17 359.43 124.64 17
18 362.14 124.73 18
19 356.97 124.90 19
20 354.82 124.04 20
21 353.17 123.28 21
22 357.06 123.86 22
23 356.18 122.29 23
24 355.01 124.09 24
25 355.65 124.54 25
26 357.31 125.65 26
27 357.07 125.70 27
28 357.91 125.53 28
29 358.48 125.61 29
30 358.97 125.55 30
31 351.77 125.41 31
32 352.16 127.60 32
33 359.08 124.68 33
34 360.35 124.41 34
35 359.53 126.43 35
36 359.30 126.38 36
37 358.41 125.78 37
38 359.68 124.70 38
39 355.31 125.07 39
40 357.08 125.25 40
41 349.71 126.58 41
42 354.13 127.13 42
43 345.49 125.82 43
44 341.69 123.70 44
45 344.25 124.39 45
46 340.17 123.70 46
47 342.47 124.42 47
48 344.43 121.05 48
49 333.23 121.02 49
50 339.72 123.23 50
51 342.61 121.32 51
52 346.36 120.91 52
53 339.09 120.72 53
54 339.73 123.31 54
55 341.12 119.58 55
56 335.94 119.53 56
57 333.46 120.59 57
58 335.66 118.63 58
59 341.12 118.47 59
60 342.21 111.81 60
61 342.62 114.71 61
62 346.06 117.34 62
63 344.43 115.77 63
64 346.65 118.38 64
65 343.74 117.84 65
66 335.67 118.83 66
67 342.75 120.02 67
68 341.77 116.21 68
69 345.84 117.08 69
70 346.52 120.20 70
71 350.79 119.83 71
72 345.44 118.92 72
73 345.87 118.03 73
74 338.48 117.71 74
75 337.21 119.55 75
76 340.81 116.13 76
77 339.86 115.97 77
78 342.86 115.99 78
79 343.33 114.96 79
80 341.73 116.46 80
81 351.38 116.55 81
82 351.13 113.05 82
83 345.99 117.44 83
84 347.55 118.84 84
85 346.02 117.06 85
86 345.29 117.54 86
87 347.03 119.31 87
88 348.01 118.72 88
89 345.48 121.55 89
90 349.40 122.61 90
91 351.05 121.53 91
92 349.70 123.31 92
93 350.86 124.07 93
94 354.45 123.59 94
95 355.30 122.97 95
96 357.48 123.22 96
97 355.24 123.04 97
98 351.79 122.96 98
99 355.22 122.81 99
100 351.02 122.81 100
101 350.28 122.62 101
102 350.17 120.82 102
103 348.16 119.41 103
104 340.30 121.56 104
105 343.75 121.59 105
106 344.71 118.50 106
107 344.13 118.77 107
108 342.14 118.86 108
109 345.04 117.60 109
110 346.02 119.90 110
111 346.43 121.83 111
112 347.07 121.84 112
113 339.33 122.12 113
114 339.10 122.12 114
115 337.19 121.36 115
116 339.58 119.66 116
117 327.85 119.32 117
118 326.81 120.36 118
119 321.73 117.06 119
120 320.45 117.48 120
121 327.69 115.60 121
122 323.95 113.86 122
123 320.47 116.92 123
124 322.13 117.75 124
125 316.34 117.75 125
126 314.78 115.31 126
127 308.90 116.28 127
128 308.62 115.22 128
129 314.41 115.65 129
130 306.88 115.11 130
131 310.60 118.67 131
132 321.60 118.04 132
133 321.50 116.50 133
134 325.68 119.78 134
135 324.35 119.95 135
136 320.01 120.37 136
137 326.88 119.79 137
138 332.39 119.43 138
139 331.48 121.06 139
140 332.62 121.74 140
141 324.79 121.09 141
142 327.12 122.97 142
143 328.91 120.50 143
144 328.37 117.18 144
145 324.83 115.03 145
146 325.90 113.36 146
147 326.18 112.59 147
148 328.94 111.65 148
149 333.78 111.98 149
150 328.06 114.87 150
151 325.87 114.67 151
152 325.41 114.09 152
153 318.86 114.77 153
154 319.13 117.05 154
155 310.16 117.22 155
156 311.73 113.18 156
157 306.54 110.95 157
158 311.16 112.14 158
159 311.98 112.72 159
160 306.72 110.01 160
161 308.05 110.29 161
162 300.76 110.74 162
163 301.90 110.32 163
164 293.09 105.89 164
165 292.76 108.97 165
166 294.58 109.34 166
167 289.90 106.57 167
168 296.69 99.49 168
169 297.21 101.81 169
170 293.31 104.29 170
171 296.25 109.73 171
172 298.60 105.06 172
173 296.87 107.97 173
174 301.02 108.13 174
175 304.73 109.86 175
176 301.92 108.95 176
177 295.72 111.20 177
178 293.18 110.69 178
179 298.35 106.10 179
180 297.99 105.68 180
181 299.85 104.12 181
182 299.85 104.71 182
183 304.45 104.30 183
184 299.45 103.52 184
185 298.14 107.76 185
186 298.78 107.80 186
187 297.02 107.30 187
188 301.33 108.64 188
189 294.96 105.03 189
190 296.69 108.30 190
191 300.73 107.21 191
192 301.96 109.27 192
193 297.38 109.50 193
194 293.87 111.68 194
195 285.96 111.80 195
196 285.41 111.75 196
197 283.70 106.68 197
198 284.76 106.37 198
199 277.11 105.76 199
200 274.73 109.01 200
201 274.73 109.01 201
202 274.73 109.01 202
203 274.73 109.01 203
204 274.69 107.69 204
205 275.42 105.19 205
206 264.15 105.48 206
207 276.24 102.22 207
208 268.88 100.54 208
209 277.97 105.00 209
210 280.49 105.44 210
211 281.09 107.89 211
212 276.16 108.64 212
213 272.58 106.70 213
214 270.94 109.10 214
215 284.31 105.23 215
216 283.94 108.41 216
217 284.18 108.80 217
218 282.83 110.39 218
219 283.84 110.22 219
220 282.71 110.86 220
221 279.29 108.58 221
222 280.70 107.70 222
223 274.47 106.62 223
224 273.44 109.84 224
225 275.49 107.16 225
226 279.46 107.26 226
227 280.19 108.70 227
228 288.21 109.85 228
229 284.80 109.41 229
230 281.41 112.36 230
231 283.39 111.03 231
232 287.97 110.67 232
233 290.77 109.21 233
234 290.60 113.58 234
235 289.67 113.88 235
236 289.84 114.08 236
237 298.55 112.33 237
238 296.07 113.92 238
239 297.14 114.41 239
240 295.34 114.57 240
241 296.25 115.35 241
242 294.30 113.13 242
243 296.15 113.29 243
244 296.49 112.56 244
245 298.05 113.06 245
246 301.03 113.46 246
247 300.52 115.39 247
248 301.50 116.62 248
249 296.93 117.04 249
250 289.84 117.42 250
251 291.44 115.62 251
252 286.88 115.16 252
253 286.74 115.69 253
254 288.93 112.85 254
255 292.19 114.05 255
256 295.39 112.00 256
257 295.86 113.74 257
258 293.36 116.26 258
259 292.86 118.63 259
260 292.73 116.49 260
261 296.73 118.23 261
262 285.02 116.83 262
263 285.24 118.82 263
264 288.62 114.36 264
265 283.36 112.02 265
266 285.84 113.24 266
267 291.48 109.75 267
268 291.41 110.33 268
269 287.77 112.86 269
270 284.97 113.04 270
271 286.05 113.80 271
272 278.19 110.90 272
273 281.21 109.96 273
274 277.92 108.69 274
275 280.08 108.84 275
276 269.24 108.47 276
277 268.48 108.07 277
278 268.83 107.94 278
279 269.54 108.11 279
280 262.37 108.11 280
281 265.12 106.81 281
282 265.34 105.58 282
283 263.32 105.61 283
284 267.18 106.52 284
285 260.75 103.86 285
286 261.78 104.60 286
287 257.27 104.73 287
288 255.63 105.12 288
289 251.39 104.76 289
290 259.49 103.85 290
291 261.18 103.83 291
292 261.65 103.22 292
293 262.01 101.64 293
294 265.23 102.13 294
295 268.10 104.33 295
296 262.27 104.92 296
297 263.59 107.78 297
298 257.85 104.49 298
299 265.69 102.80 299
300 271.15 102.86 300
301 266.69 104.51 301
302 265.77 104.73 302
303 262.32 102.58 303
304 270.48 99.93 304
305 273.03 101.41 305
306 269.13 101.05 306
307 280.65 99.86 307
308 282.75 101.11 308
309 281.44 100.89 309
310 281.99 101.09 310
311 282.86 98.31 311
312 287.21 98.08 312
313 283.11 99.55 313
314 280.66 99.62 314
315 282.39 97.37 315
316 280.83 98.16 316
317 284.71 97.98 317
318 279.99 98.15 318
319 283.50 97.10 319
320 284.88 97.24 320
321 288.60 96.70 321
322 284.80 96.64 322
323 287.20 100.65 323
324 286.22 96.75 324
325 286.54 97.74 325
326 279.58 97.92 326
327 283.08 98.34 327
328 288.88 93.84 328
329 280.18 97.80 329
330 284.16 96.20 330
331 290.57 95.99 331
332 286.82 95.18 332
333 273.00 95.95 333
334 278.69 92.23 334
335 264.54 91.78 335
336 271.92 92.97 336
337 283.60 89.76 337
338 269.25 92.88 338
339 263.58 96.23 339
340 264.16 95.79 340
341 268.85 93.97 341
342 269.67 93.90 342
343 249.41 93.60 343
344 268.99 93.96 344
345 268.65 88.69 345
346 260.16 88.57 346
347 256.55 85.62 347
348 251.47 86.25 348
349 234.93 85.33 349
350 232.96 83.33 350
351 215.49 77.78 351
352 213.68 78.70 352
353 236.07 72.05 353
354 235.41 80.75 354
355 214.77 81.41 355
356 225.85 82.65 356
357 224.64 75.85 357
358 238.26 75.70 358
359 232.44 78.25 359
360 222.50 77.41 360
361 225.28 76.84 361
362 220.49 74.25 362
363 216.86 74.95 363
364 234.70 68.78 364
365 230.06 73.21 365
366 238.27 73.26 366
367 238.56 78.67 367
368 242.70 75.63 368
369 249.14 74.99 369
370 234.89 83.87 370
371 227.78 79.62 371
372 234.04 80.13 372
373 230.70 79.76 373
374 230.17 78.20 374
375 218.23 78.05 375
376 232.20 79.05 376
377 220.76 73.32 377
378 215.60 75.17 378
379 217.69 73.26 379
380 204.35 73.72 380
381 191.44 73.57 381
382 203.84 70.60 382
383 211.86 71.25 383
384 210.57 74.22 384
385 219.57 73.32 385
386 219.98 73.01 386
387 226.01 74.21 387
388 207.04 75.32 388
389 212.52 71.73 389
390 217.92 71.94 390
391 210.45 72.94 391
392 218.53 72.47 392
393 223.32 71.94 393
394 218.76 74.30 394
395 217.63 74.30 395
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Japan t
235.7390 1.0122 -0.2311
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-30.7529 -8.2199 -0.7766 6.8755 34.8847
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 235.73898 11.03633 21.36 <2e-16 ***
Japan 1.01225 0.08404 12.04 <2e-16 ***
t -0.23111 0.01084 -21.31 <2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 11.89 on 392 degrees of freedom
Multiple R-squared: 0.9196, Adjusted R-squared: 0.9192
F-statistic: 2241 on 2 and 392 DF, p-value: < 2.2e-16
> if (n > n25) {
+ kp3 <- k + 3
+ nmkm3 <- n - k - 3
+ gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
+ numgqtests <- 0
+ numsignificant1 <- 0
+ numsignificant5 <- 0
+ numsignificant10 <- 0
+ for (mypoint in kp3:nmkm3) {
+ j <- 0
+ numgqtests <- numgqtests + 1
+ for (myalt in c('greater', 'two.sided', 'less')) {
+ j <- j + 1
+ gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
+ }
+ if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
+ }
+ gqarr
+ }
[,1] [,2] [,3]
[1,] 1.433451e-02 2.866901e-02 0.985665493
[2,] 8.186618e-03 1.637324e-02 0.991813382
[3,] 6.429899e-03 1.285980e-02 0.993570101
[4,] 2.590053e-03 5.180107e-03 0.997409947
[5,] 1.079631e-03 2.159262e-03 0.998920369
[6,] 3.023244e-04 6.046487e-04 0.999697676
[7,] 1.363881e-04 2.727761e-04 0.999863612
[8,] 4.381713e-05 8.763427e-05 0.999956183
[9,] 1.512253e-05 3.024506e-05 0.999984877
[10,] 3.894235e-06 7.788471e-06 0.999996106
[11,] 1.201677e-06 2.403354e-06 0.999998798
[12,] 5.197998e-07 1.039600e-06 0.999999480
[13,] 1.248406e-07 2.496812e-07 0.999999875
[14,] 9.732165e-08 1.946433e-07 0.999999903
[15,] 1.939867e-07 3.879733e-07 0.999999806
[16,] 4.303334e-07 8.606669e-07 0.999999570
[17,] 1.457290e-07 2.914581e-07 0.999999854
[18,] 6.223410e-08 1.244682e-07 0.999999938
[19,] 2.212480e-08 4.424960e-08 0.999999978
[20,] 6.538099e-09 1.307620e-08 0.999999993
[21,] 2.038090e-09 4.076180e-09 0.999999998
[22,] 6.065319e-10 1.213064e-09 0.999999999
[23,] 1.950331e-10 3.900662e-10 1.000000000
[24,] 6.772526e-11 1.354505e-10 1.000000000
[25,] 2.478049e-11 4.956099e-11 1.000000000
[26,] 1.369855e-11 2.739710e-11 1.000000000
[27,] 4.329078e-12 8.658156e-12 1.000000000
[28,] 1.885952e-12 3.771904e-12 1.000000000
[29,] 1.060007e-12 2.120014e-12 1.000000000
[30,] 6.209112e-13 1.241822e-12 1.000000000
[31,] 2.931475e-13 5.862950e-13 1.000000000
[32,] 9.825631e-14 1.965126e-13 1.000000000
[33,] 3.706795e-14 7.413591e-14 1.000000000
[34,] 1.057122e-14 2.114243e-14 1.000000000
[35,] 2.854463e-15 5.708926e-15 1.000000000
[36,] 2.640764e-15 5.281528e-15 1.000000000
[37,] 7.000308e-16 1.400062e-15 1.000000000
[38,] 4.806879e-15 9.613758e-15 1.000000000
[39,] 2.056859e-13 4.113718e-13 1.000000000
[40,] 3.924349e-13 7.848698e-13 1.000000000
[41,] 2.092341e-12 4.184682e-12 1.000000000
[42,] 2.347308e-12 4.694616e-12 1.000000000
[43,] 9.995000e-13 1.999000e-12 1.000000000
[44,] 5.891631e-12 1.178326e-11 1.000000000
[45,] 4.013829e-12 8.027659e-12 1.000000000
[46,] 1.518435e-12 3.036871e-12 1.000000000
[47,] 7.987242e-13 1.597448e-12 1.000000000
[48,] 3.409073e-13 6.818146e-13 1.000000000
[49,] 1.734898e-13 3.469797e-13 1.000000000
[50,] 6.798862e-14 1.359772e-13 1.000000000
[51,] 2.984442e-14 5.968883e-14 1.000000000
[52,] 2.115731e-14 4.231462e-14 1.000000000
[53,] 7.865937e-15 1.573187e-14 1.000000000
[54,] 4.940105e-15 9.880209e-15 1.000000000
[55,] 1.607547e-14 3.215094e-14 1.000000000
[56,] 1.362444e-14 2.724888e-14 1.000000000
[57,] 1.675172e-14 3.350344e-14 1.000000000
[58,] 1.417027e-14 2.834054e-14 1.000000000
[59,] 1.523076e-14 3.046151e-14 1.000000000
[60,] 8.900973e-15 1.780195e-14 1.000000000
[61,] 4.082308e-15 8.164616e-15 1.000000000
[62,] 2.051264e-15 4.102529e-15 1.000000000
[63,] 1.064123e-15 2.128245e-15 1.000000000
[64,] 1.204385e-15 2.408770e-15 1.000000000
[65,] 1.276324e-15 2.552649e-15 1.000000000
[66,] 4.771694e-15 9.543387e-15 1.000000000
[67,] 3.749192e-15 7.498383e-15 1.000000000
[68,] 3.352481e-15 6.704962e-15 1.000000000
[69,] 1.356458e-15 2.712916e-15 1.000000000
[70,] 5.590059e-16 1.118012e-15 1.000000000
[71,] 2.684466e-16 5.368932e-16 1.000000000
[72,] 1.194034e-16 2.388068e-16 1.000000000
[73,] 7.972366e-17 1.594473e-16 1.000000000
[74,] 6.049068e-17 1.209814e-16 1.000000000
[75,] 3.321017e-17 6.642034e-17 1.000000000
[76,] 2.583907e-16 5.167814e-16 1.000000000
[77,] 1.528340e-15 3.056681e-15 1.000000000
[78,] 1.550871e-15 3.101743e-15 1.000000000
[79,] 2.108870e-15 4.217740e-15 1.000000000
[80,] 2.070589e-15 4.141178e-15 1.000000000
[81,] 1.737617e-15 3.475234e-15 1.000000000
[82,] 1.898394e-15 3.796787e-15 1.000000000
[83,] 2.504557e-15 5.009114e-15 1.000000000
[84,] 1.738075e-15 3.476151e-15 1.000000000
[85,] 2.130010e-15 4.260020e-15 1.000000000
[86,] 3.590357e-15 7.180714e-15 1.000000000
[87,] 3.346216e-15 6.692433e-15 1.000000000
[88,] 3.198541e-15 6.397082e-15 1.000000000
[89,] 5.983880e-15 1.196776e-14 1.000000000
[90,] 1.261330e-14 2.522660e-14 1.000000000
[91,] 3.572958e-14 7.145916e-14 1.000000000
[92,] 5.305240e-14 1.061048e-13 1.000000000
[93,] 4.305319e-14 8.610638e-14 1.000000000
[94,] 5.976729e-14 1.195346e-13 1.000000000
[95,] 4.392934e-14 8.785869e-14 1.000000000
[96,] 3.082376e-14 6.164752e-14 1.000000000
[97,] 2.659694e-14 5.319389e-14 1.000000000
[98,] 2.195470e-14 4.390940e-14 1.000000000
[99,] 1.562651e-14 3.125303e-14 1.000000000
[100,] 9.355591e-15 1.871118e-14 1.000000000
[101,] 6.603957e-15 1.320791e-14 1.000000000
[102,] 4.476785e-15 8.953571e-15 1.000000000
[103,] 2.832394e-15 5.664788e-15 1.000000000
[104,] 2.442580e-15 4.885160e-15 1.000000000
[105,] 1.861187e-15 3.722374e-15 1.000000000
[106,] 1.291909e-15 2.583819e-15 1.000000000
[107,] 9.525244e-16 1.905049e-15 1.000000000
[108,] 8.137372e-16 1.627474e-15 1.000000000
[109,] 6.837317e-16 1.367463e-15 1.000000000
[110,] 6.237983e-16 1.247597e-15 1.000000000
[111,] 4.368678e-16 8.737355e-16 1.000000000
[112,] 1.318215e-15 2.636429e-15 1.000000000
[113,] 5.191059e-15 1.038212e-14 1.000000000
[114,] 2.567240e-14 5.134480e-14 1.000000000
[115,] 1.418565e-13 2.837130e-13 1.000000000
[116,] 1.336336e-13 2.672672e-13 1.000000000
[117,] 1.476748e-13 2.953497e-13 1.000000000
[118,] 4.242947e-13 8.485895e-13 1.000000000
[119,] 8.725821e-13 1.745164e-12 1.000000000
[120,] 4.906362e-12 9.812723e-12 1.000000000
[121,] 1.624495e-11 3.248989e-11 1.000000000
[122,] 1.885498e-10 3.770995e-10 1.000000000
[123,] 1.096145e-09 2.192291e-09 0.999999999
[124,] 1.954558e-09 3.909117e-09 0.999999998
[125,] 8.976668e-09 1.795334e-08 0.999999991
[126,] 3.486189e-08 6.972378e-08 0.999999965
[127,] 3.028815e-08 6.057629e-08 0.999999970
[128,] 2.360030e-08 4.720060e-08 0.999999976
[129,] 1.792233e-08 3.584467e-08 0.999999982
[130,] 1.416043e-08 2.832087e-08 0.999999986
[131,] 1.467864e-08 2.935728e-08 0.999999985
[132,] 1.038789e-08 2.077579e-08 0.999999990
[133,] 8.255884e-09 1.651177e-08 0.999999992
[134,] 5.991602e-09 1.198320e-08 0.999999994
[135,] 4.419422e-09 8.838844e-09 0.999999996
[136,] 3.330815e-09 6.661630e-09 0.999999997
[137,] 2.435141e-09 4.870282e-09 0.999999998
[138,] 1.734999e-09 3.469997e-09 0.999999998
[139,] 1.407902e-09 2.815804e-09 0.999999999
[140,] 1.106988e-09 2.213976e-09 0.999999999
[141,] 1.059762e-09 2.119523e-09 0.999999999
[142,] 1.143475e-09 2.286949e-09 0.999999999
[143,] 1.897346e-09 3.794693e-09 0.999999998
[144,] 6.082500e-09 1.216500e-08 0.999999994
[145,] 6.769198e-09 1.353840e-08 0.999999993
[146,] 6.760644e-09 1.352129e-08 0.999999993
[147,] 7.064962e-09 1.412992e-08 0.999999993
[148,] 5.893602e-09 1.178720e-08 0.999999994
[149,] 4.883866e-09 9.767732e-09 0.999999995
[150,] 6.758261e-09 1.351652e-08 0.999999993
[151,] 6.234025e-09 1.246805e-08 0.999999994
[152,] 6.627146e-09 1.325429e-08 0.999999993
[153,] 5.792554e-09 1.158511e-08 0.999999994
[154,] 4.955587e-09 9.911174e-09 0.999999995
[155,] 4.574881e-09 9.149762e-09 0.999999995
[156,] 3.999999e-09 7.999998e-09 0.999999996
[157,] 5.241391e-09 1.048278e-08 0.999999995
[158,] 5.633458e-09 1.126692e-08 0.999999994
[159,] 7.487502e-09 1.497500e-08 0.999999993
[160,] 1.339991e-08 2.679983e-08 0.999999987
[161,] 1.840186e-08 3.680372e-08 0.999999982
[162,] 2.483156e-08 4.966311e-08 0.999999975
[163,] 2.234757e-08 4.469513e-08 0.999999978
[164,] 1.855243e-08 3.710485e-08 0.999999981
[165,] 1.540163e-08 3.080325e-08 0.999999985
[166,] 1.568565e-08 3.137130e-08 0.999999984
[167,] 1.243748e-08 2.487495e-08 0.999999988
[168,] 1.037252e-08 2.074504e-08 0.999999990
[169,] 8.138259e-09 1.627652e-08 0.999999992
[170,] 6.528820e-09 1.305764e-08 0.999999993
[171,] 5.174516e-09 1.034903e-08 0.999999995
[172,] 5.542753e-09 1.108551e-08 0.999999994
[173,] 6.516675e-09 1.303335e-08 0.999999993
[174,] 5.247731e-09 1.049546e-08 0.999999995
[175,] 4.330644e-09 8.661288e-09 0.999999996
[176,] 4.564934e-09 9.129868e-09 0.999999995
[177,] 4.734701e-09 9.469401e-09 0.999999995
[178,] 8.349368e-09 1.669874e-08 0.999999992
[179,] 1.084396e-08 2.168791e-08 0.999999989
[180,] 9.744846e-09 1.948969e-08 0.999999990
[181,] 9.050820e-09 1.810164e-08 0.999999991
[182,] 8.415417e-09 1.683083e-08 0.999999992
[183,] 8.602637e-09 1.720527e-08 0.999999991
[184,] 9.092516e-09 1.818503e-08 0.999999991
[185,] 8.722270e-09 1.744454e-08 0.999999991
[186,] 1.133765e-08 2.267531e-08 0.999999989
[187,] 1.334838e-08 2.669676e-08 0.999999987
[188,] 1.345803e-08 2.691606e-08 0.999999987
[189,] 1.435428e-08 2.870856e-08 0.999999986
[190,] 2.674102e-08 5.348204e-08 0.999999973
[191,] 4.717861e-08 9.435721e-08 0.999999953
[192,] 5.301180e-08 1.060236e-07 0.999999947
[193,] 5.503958e-08 1.100792e-07 0.999999945
[194,] 8.041877e-08 1.608375e-07 0.999999920
[195,] 2.249406e-07 4.498812e-07 0.999999775
[196,] 5.405438e-07 1.081088e-06 0.999999459
[197,] 1.143226e-06 2.286452e-06 0.999998857
[198,] 2.169900e-06 4.339799e-06 0.999997830
[199,] 3.172667e-06 6.345334e-06 0.999996827
[200,] 3.306096e-06 6.612192e-06 0.999996694
[201,] 8.665541e-06 1.733108e-05 0.999991334
[202,] 7.427363e-06 1.485473e-05 0.999992573
[203,] 6.981656e-06 1.396331e-05 0.999993018
[204,] 5.955383e-06 1.191077e-05 0.999994045
[205,] 4.918035e-06 9.836070e-06 0.999995082
[206,] 4.171148e-06 8.342296e-06 0.999995829
[207,] 4.491436e-06 8.982873e-06 0.999995509
[208,] 4.846693e-06 9.693386e-06 0.999995153
[209,] 7.603748e-06 1.520750e-05 0.999992396
[210,] 6.409547e-06 1.281909e-05 0.999993590
[211,] 4.960698e-06 9.921396e-06 0.999995039
[212,] 3.813796e-06 7.627592e-06 0.999996186
[213,] 3.049017e-06 6.098033e-06 0.999996951
[214,] 2.339701e-06 4.679403e-06 0.999997660
[215,] 1.855120e-06 3.710241e-06 0.999998145
[216,] 1.454693e-06 2.909387e-06 0.999998545
[217,] 1.083631e-06 2.167262e-06 0.999998916
[218,] 8.766099e-07 1.753220e-06 0.999999123
[219,] 9.528533e-07 1.905707e-06 0.999999047
[220,] 7.408812e-07 1.481762e-06 0.999999259
[221,] 5.331175e-07 1.066235e-06 0.999999467
[222,] 3.830782e-07 7.661565e-07 0.999999617
[223,] 2.864495e-07 5.728990e-07 0.999999714
[224,] 2.034147e-07 4.068294e-07 0.999999797
[225,] 1.588637e-07 3.177273e-07 0.999999841
[226,] 1.101676e-07 2.203351e-07 0.999999890
[227,] 7.875622e-08 1.575124e-07 0.999999921
[228,] 7.257595e-08 1.451519e-07 0.999999927
[229,] 4.968797e-08 9.937595e-08 0.999999950
[230,] 3.340113e-08 6.680226e-08 0.999999967
[231,] 2.231174e-08 4.462348e-08 0.999999978
[232,] 2.621409e-08 5.242817e-08 0.999999974
[233,] 2.134263e-08 4.268527e-08 0.999999979
[234,] 1.764576e-08 3.529152e-08 0.999999982
[235,] 1.319559e-08 2.639119e-08 0.999999987
[236,] 9.659400e-09 1.931880e-08 0.999999990
[237,] 7.865556e-09 1.573111e-08 0.999999992
[238,] 7.125131e-09 1.425026e-08 0.999999993
[239,] 7.491566e-09 1.498313e-08 0.999999993
[240,] 8.460433e-09 1.692087e-08 0.999999992
[241,] 1.207489e-08 2.414979e-08 0.999999988
[242,] 1.166242e-08 2.332485e-08 0.999999988
[243,] 1.010808e-08 2.021616e-08 0.999999990
[244,] 6.883698e-09 1.376740e-08 0.999999993
[245,] 4.881737e-09 9.763474e-09 0.999999995
[246,] 3.178712e-09 6.357424e-09 0.999999997
[247,] 2.128976e-09 4.257951e-09 0.999999998
[248,] 1.464315e-09 2.928630e-09 0.999999999
[249,] 9.930307e-10 1.986061e-09 0.999999999
[250,] 6.879159e-10 1.375832e-09 0.999999999
[251,] 7.835643e-10 1.567129e-09 0.999999999
[252,] 6.883471e-10 1.376694e-09 0.999999999
[253,] 4.392309e-10 8.784617e-10 1.000000000
[254,] 3.027314e-10 6.054627e-10 1.000000000
[255,] 1.914771e-10 3.829542e-10 1.000000000
[256,] 1.229127e-10 2.458255e-10 1.000000000
[257,] 1.060052e-10 2.120103e-10 1.000000000
[258,] 1.364309e-10 2.728617e-10 1.000000000
[259,] 8.655466e-11 1.731093e-10 1.000000000
[260,] 5.387230e-11 1.077446e-10 1.000000000
[261,] 3.391281e-11 6.782561e-11 1.000000000
[262,] 3.995324e-11 7.990648e-11 1.000000000
[263,] 4.149234e-11 8.298468e-11 1.000000000
[264,] 2.651321e-11 5.302642e-11 1.000000000
[265,] 1.684936e-11 3.369871e-11 1.000000000
[266,] 1.101148e-11 2.202296e-11 1.000000000
[267,] 7.262880e-12 1.452576e-11 1.000000000
[268,] 4.491007e-12 8.982014e-12 1.000000000
[269,] 2.727981e-12 5.455963e-12 1.000000000
[270,] 1.697491e-12 3.394983e-12 1.000000000
[271,] 1.380668e-12 2.761337e-12 1.000000000
[272,] 1.140829e-12 2.281657e-12 1.000000000
[273,] 9.271152e-13 1.854230e-12 1.000000000
[274,] 7.622964e-13 1.524593e-12 1.000000000
[275,] 1.395043e-12 2.790086e-12 1.000000000
[276,] 1.417626e-12 2.835252e-12 1.000000000
[277,] 1.182142e-12 2.364283e-12 1.000000000
[278,] 1.223007e-12 2.446013e-12 1.000000000
[279,] 1.165877e-12 2.331754e-12 1.000000000
[280,] 1.197782e-12 2.395565e-12 1.000000000
[281,] 1.410647e-12 2.821293e-12 1.000000000
[282,] 3.271717e-12 6.543433e-12 1.000000000
[283,] 1.293500e-11 2.587001e-11 1.000000000
[284,] 1.170226e-10 2.340451e-10 1.000000000
[285,] 2.478758e-10 4.957516e-10 1.000000000
[286,] 4.914733e-10 9.829466e-10 1.000000000
[287,] 9.203281e-10 1.840656e-09 0.999999999
[288,] 1.408037e-09 2.816074e-09 0.999999999
[289,] 2.053399e-09 4.106799e-09 0.999999998
[290,] 3.634088e-09 7.268176e-09 0.999999996
[291,] 1.517060e-08 3.034121e-08 0.999999985
[292,] 1.431954e-07 2.863908e-07 0.999999857
[293,] 1.506816e-06 3.013633e-06 0.999998493
[294,] 4.242373e-06 8.484746e-06 0.999995758
[295,] 8.774718e-06 1.754944e-05 0.999991225
[296,] 3.720338e-05 7.440677e-05 0.999962797
[297,] 2.058830e-04 4.117660e-04 0.999794117
[298,] 1.149979e-03 2.299957e-03 0.998850021
[299,] 2.309877e-03 4.619754e-03 0.997690123
[300,] 4.743175e-03 9.486349e-03 0.995256825
[301,] 1.163812e-02 2.327623e-02 0.988361884
[302,] 1.869336e-02 3.738673e-02 0.981306636
[303,] 2.861529e-02 5.723058e-02 0.971384710
[304,] 4.179406e-02 8.358812e-02 0.958205942
[305,] 5.872495e-02 1.174499e-01 0.941275052
[306,] 7.989419e-02 1.597884e-01 0.920105805
[307,] 1.128165e-01 2.256329e-01 0.887183533
[308,] 1.369939e-01 2.739878e-01 0.863006105
[309,] 1.617596e-01 3.235192e-01 0.838240387
[310,] 1.888909e-01 3.777818e-01 0.811109105
[311,] 2.117878e-01 4.235756e-01 0.788212192
[312,] 2.404282e-01 4.808564e-01 0.759571822
[313,] 2.593914e-01 5.187829e-01 0.740608561
[314,] 2.838997e-01 5.677993e-01 0.716100331
[315,] 3.103059e-01 6.206119e-01 0.689694073
[316,] 3.598904e-01 7.197808e-01 0.640109621
[317,] 3.847634e-01 7.695267e-01 0.615236626
[318,] 3.971825e-01 7.943649e-01 0.602817547
[319,] 4.260624e-01 8.521248e-01 0.573937584
[320,] 4.474930e-01 8.949860e-01 0.552507017
[321,] 4.411088e-01 8.822175e-01 0.558891231
[322,] 4.407691e-01 8.815383e-01 0.559230862
[323,] 5.331584e-01 9.336831e-01 0.466841561
[324,] 5.222713e-01 9.554574e-01 0.477728714
[325,] 5.418822e-01 9.162356e-01 0.458117806
[326,] 6.285756e-01 7.428488e-01 0.371424380
[327,] 6.925611e-01 6.148778e-01 0.307438882
[328,] 6.685521e-01 6.628958e-01 0.331447876
[329,] 7.049825e-01 5.900349e-01 0.295017458
[330,] 6.744918e-01 6.510165e-01 0.325508241
[331,] 6.641757e-01 6.716486e-01 0.335824324
[332,] 8.140927e-01 3.718146e-01 0.185907289
[333,] 8.049499e-01 3.901003e-01 0.195050133
[334,] 7.761859e-01 4.476283e-01 0.223814127
[335,] 7.447330e-01 5.105341e-01 0.255267044
[336,] 7.304697e-01 5.390606e-01 0.269530316
[337,] 7.285807e-01 5.428386e-01 0.271419305
[338,] 7.116288e-01 5.767424e-01 0.288371201
[339,] 7.111703e-01 5.776594e-01 0.288829713
[340,] 7.885082e-01 4.229836e-01 0.211491785
[341,] 8.135472e-01 3.729056e-01 0.186452801
[342,] 8.485988e-01 3.028024e-01 0.151401206
[343,] 8.636739e-01 2.726522e-01 0.136326100
[344,] 8.399780e-01 3.200440e-01 0.160021976
[345,] 8.135404e-01 3.729193e-01 0.186459628
[346,] 8.547385e-01 2.905230e-01 0.145261483
[347,] 9.108956e-01 1.782087e-01 0.089104368
[348,] 8.946866e-01 2.106268e-01 0.105313424
[349,] 8.707411e-01 2.585178e-01 0.129258892
[350,] 9.274177e-01 1.451645e-01 0.072582254
[351,] 9.325960e-01 1.348080e-01 0.067404005
[352,] 9.251499e-01 1.497001e-01 0.074850066
[353,] 9.105409e-01 1.789182e-01 0.089459108
[354,] 8.872449e-01 2.255102e-01 0.112755125
[355,] 8.871890e-01 2.256220e-01 0.112810999
[356,] 8.747811e-01 2.504377e-01 0.125218857
[357,] 8.753232e-01 2.493535e-01 0.124676774
[358,] 9.096352e-01 1.807296e-01 0.090364803
[359,] 8.939850e-01 2.120300e-01 0.106015015
[360,] 8.641898e-01 2.716203e-01 0.135810169
[361,] 8.586213e-01 2.827573e-01 0.141378670
[362,] 8.328449e-01 3.343101e-01 0.167155063
[363,] 8.776027e-01 2.447946e-01 0.122397309
[364,] 9.916361e-01 1.672772e-02 0.008363859
[365,] 9.873479e-01 2.530417e-02 0.012652083
[366,] 9.803342e-01 3.933154e-02 0.019665768
[367,] 9.733775e-01 5.324492e-02 0.026622460
[368,] 9.624346e-01 7.513071e-02 0.037565357
[369,] 9.586137e-01 8.277257e-02 0.041386283
[370,] 9.403138e-01 1.193725e-01 0.059686248
[371,] 9.572166e-01 8.556686e-02 0.042783430
[372,] 9.667222e-01 6.655552e-02 0.033277758
[373,] 9.636209e-01 7.275815e-02 0.036379075
[374,] 9.756524e-01 4.869521e-02 0.024347605
[375,] 9.597831e-01 8.043371e-02 0.040216855
[376,] 9.915857e-01 1.682869e-02 0.008414347
[377,] 9.926446e-01 1.471088e-02 0.007355442
[378,] 9.873524e-01 2.529527e-02 0.012647633
[379,] 9.796069e-01 4.078615e-02 0.020393074
[380,] 9.596944e-01 8.061116e-02 0.040305582
[381,] 9.284786e-01 1.430428e-01 0.071521380
[382,] 9.971874e-01 5.625171e-03 0.002812585
[383,] 9.958612e-01 8.277572e-03 0.004138786
[384,] 9.803376e-01 3.932488e-02 0.019662442
> postscript(file="/var/www/html/rcomp/tmp/138ka1228923785.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
> points(x[,1]-mysum$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2j2ze1228923785.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/3yuft1228923785.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4im281228923785.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5gfh41228923785.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
> qqline(mysum$resid)
> grid()
> dev.off()
null device
1
> (myerror <- as.ts(mysum$resid))
Time Series:
Start = 1
End = 395
Frequency = 1
1 2 3 4 5 6
-0.77663612 2.84258982 2.82724926 4.10010583 2.79386383 -0.68384802
7 8 9 10 11 12
-3.69070246 -9.00996264 -2.69546971 0.88650457 -2.22667522 4.12153637
13 14 15 16 17 18
7.47077189 8.40612224 7.60722953 6.20922868 1.45315319 4.30315808
19 20 21 22 23 24
-0.80781693 -1.85617567 -2.50575929 1.02824369 1.96858161 -0.79235896
25 26 27 28 29 30
-0.37676363 0.39074748 0.33124233 1.57443191 2.29455929 3.07640151
31 32 33 34 35 36
-3.75077637 -5.34649397 4.76037983 6.53479430 3.90115899 3.95287872
37 38 39 40 41 42
3.90133529 6.49567129 1.98224652 3.80114902 -4.68403461 -0.58966416
43 44 45 46 47 48
-7.67251094 -9.09543618 -7.00278057 -10.15322161 -8.35093346 -2.74854770
49 50 51 52 53 54
-13.68707294 -9.20303552 -4.14853301 0.24759629 -6.59896915 -8.34958628
55 56 57 58 59 60
-2.95279094 -7.85107121 -11.17294766 -6.75783271 -0.90476562 7.15791872
61 62 63 64 65 66
4.86350447 5.87239740 6.06273531 5.87187321 3.73959485 -5.10142418
67 68 69 70 71 72
1.00510703 4.11288227 7.53333309 5.28622411 10.16186345 5.96411715
73 74 75 76 77 78
7.52612588 0.69115278 -2.21027774 5.08272047 4.52578757 7.73664988
79 80 81 82 83 84
9.48037343 6.59310751 16.38311241 19.90709052 10.55442554 10.92838450
85 86 87 88 89 90
11.43129466 10.44652252 10.62594942 12.43428351 7.27072667 10.34885022
91 92 93 94 95 96
13.32318622 10.40249063 11.02428883 15.33127554 17.03997709 19.19802217
97 98 99 100 101 102
17.37133425 14.23342144 18.04636605 14.07747333 13.76090789 15.70406303
103 104 105 106 107 108
15.35244114 5.54721349 9.19795331 13.51690941 12.89470952 11.04471441
109 110 111 112 113 114
15.45125520 14.33419023 13.02165732 13.88264212 6.09031974 6.09142703
115 116 117 118 119 120
5.18184341 9.52377367 -1.63095445 -3.49258592 -5.00105758 -6.47509479
121 122 123 124 125 126
2.89904026 1.15146047 -5.19491359 -4.14397282 -9.70286553 -8.56187116
127 128 129 130 131 132
-15.19264521 -14.16855419 -8.58271389 -15.33499225 -14.98749071 -3.11866667
133 134 135 136 137 138
-1.42869623 -0.33776502 -1.60874003 -6.14277725 1.54543435 7.65095121
139 140 141 142 143 144
5.32209294 6.00487104 -0.93605995 -0.27798042 4.24338142 7.29515474
145 146 147 148 149 150
6.16259696 9.15415976 10.44469863 14.38731979 19.12438497 10.71009321
151 152 153 154 155 156
8.95365026 9.31186185 2.30463995 0.49781996 -8.41315505 -2.52256259
157 158 159 160 161 162
-5.22414046 -1.57760925 -1.11360627 -3.39930472 -2.12162710 -9.63603178
163 164 165 166 167 168
-7.83977999 -11.93441049 -15.15102953 -13.47445430 -15.11941782 -0.93158898
169 170 171 172 173 174
-2.52889892 -8.70816868 -11.04369490 -3.73538568 -8.17992242 -3.96077495
175 176 177 178 179 180
-1.77085809 -3.42860439 -11.67505692 -13.46770274 -3.42037343 -3.12412165
181 182 183 184 185 186
0.54609378 0.17997427 5.42610357 1.44676492 -3.92406273 -3.09344539
187 188 189 190 191 192
-4.11621370 -0.93151982 -3.41619434 -4.76514065 0.60931784 -0.01480742
193 194 195 196 197 198
-4.59651736 -10.08211247 -17.88247504 -18.15075531 -14.49754657 -12.89264216
199 200 201 202 203 204
-19.69406310 -25.13276443 -24.90165714 -24.67054986 -24.43944257 -22.91216686
205 206 207 208 209 210
-19.42043755 -30.75288242 -15.13184403 -20.56015874 -15.75368113 -13.44796332
211 212 213 214 215 216
-15.09686561 -20.55494493 -21.94007496 -25.77836480 -8.25985464 -11.61769855
217 218 219 220 221 222
-11.54136830 -14.26973662 -12.85654703 -14.40327898 -15.28424442 -12.75235818
223 224 225 226 227 228
-17.65802218 -21.71635605 -16.72242196 -12.62253956 -13.11907055 -6.03204939
229 230 231 232 233 234
-8.76555263 -14.91057932 -11.35318112 -6.17766426 -1.66867372 -6.03109372
235 236 237 238 239 240
-7.03366107 -6.83500355 3.87753915 0.01917084 0.82427621 -0.90657631
241 242 243 244 245 246
-0.55502309 -0.02672346 1.89242402 3.20247294 4.48745582 7.29366358
247 248 249 250 251 252
5.06113068 5.02717193 0.26313472 -6.98041254 -3.32725740 -7.19051566
253 254 255 256 257 258
-7.63590024 -2.34000635 -0.06359763 5.44261971 4.38241408 -0.43734563
259 260 261 262 263 264
-3.10526801 -0.83794828 1.63184608 -8.42989830 -9.99316614 -1.86742917
265 266 267 268 269 270
-4.52765968 -3.05149594 6.35235969 5.92636266 -0.04351953 -2.79461703
271 272 273 274 275 276
-2.25281883 -6.94619001 -2.74356884 -4.51690557 -2.27763560 -12.51199626
277 278 279 280 281 282
-12.63598945 -11.92328982 -11.15426483 -18.09315754 -13.79612680 -12.09995349
283 284 285 286 287 288
-13.91921366 -10.74925279 -14.25556368 -13.74352051 -18.15400556 -19.95767531
289 290 291 292 293 294
-23.60215845 -14.34990475 -12.40855249 -11.08997343 -8.89951303 -5.94440766
295 296 297 298 299 300
-5.07024775 -11.26636725 -12.61029155 -14.78888569 -5.00707792 0.62329444
301 302 303 304 305 306
-5.27580881 -6.18739626 -7.22995404 3.84361259 5.12659164 1.82210850
307 308 309 310 311 312
14.77779186 15.84358814 14.98739017 15.56604769 19.48120666 24.29513118
313 314 315 316 317 318
18.93823272 16.64848259 20.88714969 18.75858042 23.05189249 18.39091748
319 320 321 322 323 324
23.19488602 24.66427847 29.16200011 25.65384233 24.22583190 27.42470953
325 326 327 328 329 330
26.97369050 20.06259300 23.36855579 33.95478271 21.47738472 27.30809010
331 332 333 334 335 336
34.16176964 31.46279846 17.09447416 26.78114701 13.31776626 19.72429747
337 338 339 340 341 342
34.88472342 17.60761443 8.77768822 10.03418498 16.79758510 17.91954980
343 344 345 346 347 348
-1.80566827 17.64102944 22.86668794 14.72926509 14.33650635 8.84989689
349 350 351 352 353 354
-6.52772692 -6.24212202 -17.86303386 -20.37319547 8.97936638 -0.25609095
355 356 357 358 359 360
-21.33306788 -11.27714911 -5.37274994 8.63019467 0.46006750 -8.39853621
361 362 363 364 365 366
-4.81044711 -6.74761541 -10.85508229 13.46160013 4.56844521 12.95894006
367 368 369 370 371 372
8.00378130 15.45212496 22.77107148 -0.23659063 -2.81342592 3.16143448
373 374 375 376 377 378
0.42707382 1.70728925 -9.84976614 3.33909234 -2.06961472 -8.87116772
379 380 381 382 383 384
-4.61666521 -18.19119238 -30.71824777 -15.08076153 -7.48761596 -11.55288763
385 386 387 388 389 390
-1.41075642 -0.45585200 4.59055672 -15.27193217 -5.92685167 -0.50831663
391 392 393 394 395
-8.75945815 0.02740608 5.58500523 -1.13279467 -2.03168738
> postscript(file="/var/www/html/rcomp/tmp/6d8cc1228923785.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> dum <- cbind(lag(myerror,k=1),myerror)
> dum
Time Series:
Start = 0
End = 395
Frequency = 1
lag(myerror, k = 1) myerror
0 -0.77663612 NA
1 2.84258982 -0.77663612
2 2.82724926 2.84258982
3 4.10010583 2.82724926
4 2.79386383 4.10010583
5 -0.68384802 2.79386383
6 -3.69070246 -0.68384802
7 -9.00996264 -3.69070246
8 -2.69546971 -9.00996264
9 0.88650457 -2.69546971
10 -2.22667522 0.88650457
11 4.12153637 -2.22667522
12 7.47077189 4.12153637
13 8.40612224 7.47077189
14 7.60722953 8.40612224
15 6.20922868 7.60722953
16 1.45315319 6.20922868
17 4.30315808 1.45315319
18 -0.80781693 4.30315808
19 -1.85617567 -0.80781693
20 -2.50575929 -1.85617567
21 1.02824369 -2.50575929
22 1.96858161 1.02824369
23 -0.79235896 1.96858161
24 -0.37676363 -0.79235896
25 0.39074748 -0.37676363
26 0.33124233 0.39074748
27 1.57443191 0.33124233
28 2.29455929 1.57443191
29 3.07640151 2.29455929
30 -3.75077637 3.07640151
31 -5.34649397 -3.75077637
32 4.76037983 -5.34649397
33 6.53479430 4.76037983
34 3.90115899 6.53479430
35 3.95287872 3.90115899
36 3.90133529 3.95287872
37 6.49567129 3.90133529
38 1.98224652 6.49567129
39 3.80114902 1.98224652
40 -4.68403461 3.80114902
41 -0.58966416 -4.68403461
42 -7.67251094 -0.58966416
43 -9.09543618 -7.67251094
44 -7.00278057 -9.09543618
45 -10.15322161 -7.00278057
46 -8.35093346 -10.15322161
47 -2.74854770 -8.35093346
48 -13.68707294 -2.74854770
49 -9.20303552 -13.68707294
50 -4.14853301 -9.20303552
51 0.24759629 -4.14853301
52 -6.59896915 0.24759629
53 -8.34958628 -6.59896915
54 -2.95279094 -8.34958628
55 -7.85107121 -2.95279094
56 -11.17294766 -7.85107121
57 -6.75783271 -11.17294766
58 -0.90476562 -6.75783271
59 7.15791872 -0.90476562
60 4.86350447 7.15791872
61 5.87239740 4.86350447
62 6.06273531 5.87239740
63 5.87187321 6.06273531
64 3.73959485 5.87187321
65 -5.10142418 3.73959485
66 1.00510703 -5.10142418
67 4.11288227 1.00510703
68 7.53333309 4.11288227
69 5.28622411 7.53333309
70 10.16186345 5.28622411
71 5.96411715 10.16186345
72 7.52612588 5.96411715
73 0.69115278 7.52612588
74 -2.21027774 0.69115278
75 5.08272047 -2.21027774
76 4.52578757 5.08272047
77 7.73664988 4.52578757
78 9.48037343 7.73664988
79 6.59310751 9.48037343
80 16.38311241 6.59310751
81 19.90709052 16.38311241
82 10.55442554 19.90709052
83 10.92838450 10.55442554
84 11.43129466 10.92838450
85 10.44652252 11.43129466
86 10.62594942 10.44652252
87 12.43428351 10.62594942
88 7.27072667 12.43428351
89 10.34885022 7.27072667
90 13.32318622 10.34885022
91 10.40249063 13.32318622
92 11.02428883 10.40249063
93 15.33127554 11.02428883
94 17.03997709 15.33127554
95 19.19802217 17.03997709
96 17.37133425 19.19802217
97 14.23342144 17.37133425
98 18.04636605 14.23342144
99 14.07747333 18.04636605
100 13.76090789 14.07747333
101 15.70406303 13.76090789
102 15.35244114 15.70406303
103 5.54721349 15.35244114
104 9.19795331 5.54721349
105 13.51690941 9.19795331
106 12.89470952 13.51690941
107 11.04471441 12.89470952
108 15.45125520 11.04471441
109 14.33419023 15.45125520
110 13.02165732 14.33419023
111 13.88264212 13.02165732
112 6.09031974 13.88264212
113 6.09142703 6.09031974
114 5.18184341 6.09142703
115 9.52377367 5.18184341
116 -1.63095445 9.52377367
117 -3.49258592 -1.63095445
118 -5.00105758 -3.49258592
119 -6.47509479 -5.00105758
120 2.89904026 -6.47509479
121 1.15146047 2.89904026
122 -5.19491359 1.15146047
123 -4.14397282 -5.19491359
124 -9.70286553 -4.14397282
125 -8.56187116 -9.70286553
126 -15.19264521 -8.56187116
127 -14.16855419 -15.19264521
128 -8.58271389 -14.16855419
129 -15.33499225 -8.58271389
130 -14.98749071 -15.33499225
131 -3.11866667 -14.98749071
132 -1.42869623 -3.11866667
133 -0.33776502 -1.42869623
134 -1.60874003 -0.33776502
135 -6.14277725 -1.60874003
136 1.54543435 -6.14277725
137 7.65095121 1.54543435
138 5.32209294 7.65095121
139 6.00487104 5.32209294
140 -0.93605995 6.00487104
141 -0.27798042 -0.93605995
142 4.24338142 -0.27798042
143 7.29515474 4.24338142
144 6.16259696 7.29515474
145 9.15415976 6.16259696
146 10.44469863 9.15415976
147 14.38731979 10.44469863
148 19.12438497 14.38731979
149 10.71009321 19.12438497
150 8.95365026 10.71009321
151 9.31186185 8.95365026
152 2.30463995 9.31186185
153 0.49781996 2.30463995
154 -8.41315505 0.49781996
155 -2.52256259 -8.41315505
156 -5.22414046 -2.52256259
157 -1.57760925 -5.22414046
158 -1.11360627 -1.57760925
159 -3.39930472 -1.11360627
160 -2.12162710 -3.39930472
161 -9.63603178 -2.12162710
162 -7.83977999 -9.63603178
163 -11.93441049 -7.83977999
164 -15.15102953 -11.93441049
165 -13.47445430 -15.15102953
166 -15.11941782 -13.47445430
167 -0.93158898 -15.11941782
168 -2.52889892 -0.93158898
169 -8.70816868 -2.52889892
170 -11.04369490 -8.70816868
171 -3.73538568 -11.04369490
172 -8.17992242 -3.73538568
173 -3.96077495 -8.17992242
174 -1.77085809 -3.96077495
175 -3.42860439 -1.77085809
176 -11.67505692 -3.42860439
177 -13.46770274 -11.67505692
178 -3.42037343 -13.46770274
179 -3.12412165 -3.42037343
180 0.54609378 -3.12412165
181 0.17997427 0.54609378
182 5.42610357 0.17997427
183 1.44676492 5.42610357
184 -3.92406273 1.44676492
185 -3.09344539 -3.92406273
186 -4.11621370 -3.09344539
187 -0.93151982 -4.11621370
188 -3.41619434 -0.93151982
189 -4.76514065 -3.41619434
190 0.60931784 -4.76514065
191 -0.01480742 0.60931784
192 -4.59651736 -0.01480742
193 -10.08211247 -4.59651736
194 -17.88247504 -10.08211247
195 -18.15075531 -17.88247504
196 -14.49754657 -18.15075531
197 -12.89264216 -14.49754657
198 -19.69406310 -12.89264216
199 -25.13276443 -19.69406310
200 -24.90165714 -25.13276443
201 -24.67054986 -24.90165714
202 -24.43944257 -24.67054986
203 -22.91216686 -24.43944257
204 -19.42043755 -22.91216686
205 -30.75288242 -19.42043755
206 -15.13184403 -30.75288242
207 -20.56015874 -15.13184403
208 -15.75368113 -20.56015874
209 -13.44796332 -15.75368113
210 -15.09686561 -13.44796332
211 -20.55494493 -15.09686561
212 -21.94007496 -20.55494493
213 -25.77836480 -21.94007496
214 -8.25985464 -25.77836480
215 -11.61769855 -8.25985464
216 -11.54136830 -11.61769855
217 -14.26973662 -11.54136830
218 -12.85654703 -14.26973662
219 -14.40327898 -12.85654703
220 -15.28424442 -14.40327898
221 -12.75235818 -15.28424442
222 -17.65802218 -12.75235818
223 -21.71635605 -17.65802218
224 -16.72242196 -21.71635605
225 -12.62253956 -16.72242196
226 -13.11907055 -12.62253956
227 -6.03204939 -13.11907055
228 -8.76555263 -6.03204939
229 -14.91057932 -8.76555263
230 -11.35318112 -14.91057932
231 -6.17766426 -11.35318112
232 -1.66867372 -6.17766426
233 -6.03109372 -1.66867372
234 -7.03366107 -6.03109372
235 -6.83500355 -7.03366107
236 3.87753915 -6.83500355
237 0.01917084 3.87753915
238 0.82427621 0.01917084
239 -0.90657631 0.82427621
240 -0.55502309 -0.90657631
241 -0.02672346 -0.55502309
242 1.89242402 -0.02672346
243 3.20247294 1.89242402
244 4.48745582 3.20247294
245 7.29366358 4.48745582
246 5.06113068 7.29366358
247 5.02717193 5.06113068
248 0.26313472 5.02717193
249 -6.98041254 0.26313472
250 -3.32725740 -6.98041254
251 -7.19051566 -3.32725740
252 -7.63590024 -7.19051566
253 -2.34000635 -7.63590024
254 -0.06359763 -2.34000635
255 5.44261971 -0.06359763
256 4.38241408 5.44261971
257 -0.43734563 4.38241408
258 -3.10526801 -0.43734563
259 -0.83794828 -3.10526801
260 1.63184608 -0.83794828
261 -8.42989830 1.63184608
262 -9.99316614 -8.42989830
263 -1.86742917 -9.99316614
264 -4.52765968 -1.86742917
265 -3.05149594 -4.52765968
266 6.35235969 -3.05149594
267 5.92636266 6.35235969
268 -0.04351953 5.92636266
269 -2.79461703 -0.04351953
270 -2.25281883 -2.79461703
271 -6.94619001 -2.25281883
272 -2.74356884 -6.94619001
273 -4.51690557 -2.74356884
274 -2.27763560 -4.51690557
275 -12.51199626 -2.27763560
276 -12.63598945 -12.51199626
277 -11.92328982 -12.63598945
278 -11.15426483 -11.92328982
279 -18.09315754 -11.15426483
280 -13.79612680 -18.09315754
281 -12.09995349 -13.79612680
282 -13.91921366 -12.09995349
283 -10.74925279 -13.91921366
284 -14.25556368 -10.74925279
285 -13.74352051 -14.25556368
286 -18.15400556 -13.74352051
287 -19.95767531 -18.15400556
288 -23.60215845 -19.95767531
289 -14.34990475 -23.60215845
290 -12.40855249 -14.34990475
291 -11.08997343 -12.40855249
292 -8.89951303 -11.08997343
293 -5.94440766 -8.89951303
294 -5.07024775 -5.94440766
295 -11.26636725 -5.07024775
296 -12.61029155 -11.26636725
297 -14.78888569 -12.61029155
298 -5.00707792 -14.78888569
299 0.62329444 -5.00707792
300 -5.27580881 0.62329444
301 -6.18739626 -5.27580881
302 -7.22995404 -6.18739626
303 3.84361259 -7.22995404
304 5.12659164 3.84361259
305 1.82210850 5.12659164
306 14.77779186 1.82210850
307 15.84358814 14.77779186
308 14.98739017 15.84358814
309 15.56604769 14.98739017
310 19.48120666 15.56604769
311 24.29513118 19.48120666
312 18.93823272 24.29513118
313 16.64848259 18.93823272
314 20.88714969 16.64848259
315 18.75858042 20.88714969
316 23.05189249 18.75858042
317 18.39091748 23.05189249
318 23.19488602 18.39091748
319 24.66427847 23.19488602
320 29.16200011 24.66427847
321 25.65384233 29.16200011
322 24.22583190 25.65384233
323 27.42470953 24.22583190
324 26.97369050 27.42470953
325 20.06259300 26.97369050
326 23.36855579 20.06259300
327 33.95478271 23.36855579
328 21.47738472 33.95478271
329 27.30809010 21.47738472
330 34.16176964 27.30809010
331 31.46279846 34.16176964
332 17.09447416 31.46279846
333 26.78114701 17.09447416
334 13.31776626 26.78114701
335 19.72429747 13.31776626
336 34.88472342 19.72429747
337 17.60761443 34.88472342
338 8.77768822 17.60761443
339 10.03418498 8.77768822
340 16.79758510 10.03418498
341 17.91954980 16.79758510
342 -1.80566827 17.91954980
343 17.64102944 -1.80566827
344 22.86668794 17.64102944
345 14.72926509 22.86668794
346 14.33650635 14.72926509
347 8.84989689 14.33650635
348 -6.52772692 8.84989689
349 -6.24212202 -6.52772692
350 -17.86303386 -6.24212202
351 -20.37319547 -17.86303386
352 8.97936638 -20.37319547
353 -0.25609095 8.97936638
354 -21.33306788 -0.25609095
355 -11.27714911 -21.33306788
356 -5.37274994 -11.27714911
357 8.63019467 -5.37274994
358 0.46006750 8.63019467
359 -8.39853621 0.46006750
360 -4.81044711 -8.39853621
361 -6.74761541 -4.81044711
362 -10.85508229 -6.74761541
363 13.46160013 -10.85508229
364 4.56844521 13.46160013
365 12.95894006 4.56844521
366 8.00378130 12.95894006
367 15.45212496 8.00378130
368 22.77107148 15.45212496
369 -0.23659063 22.77107148
370 -2.81342592 -0.23659063
371 3.16143448 -2.81342592
372 0.42707382 3.16143448
373 1.70728925 0.42707382
374 -9.84976614 1.70728925
375 3.33909234 -9.84976614
376 -2.06961472 3.33909234
377 -8.87116772 -2.06961472
378 -4.61666521 -8.87116772
379 -18.19119238 -4.61666521
380 -30.71824777 -18.19119238
381 -15.08076153 -30.71824777
382 -7.48761596 -15.08076153
383 -11.55288763 -7.48761596
384 -1.41075642 -11.55288763
385 -0.45585200 -1.41075642
386 4.59055672 -0.45585200
387 -15.27193217 4.59055672
388 -5.92685167 -15.27193217
389 -0.50831663 -5.92685167
390 -8.75945815 -0.50831663
391 0.02740608 -8.75945815
392 5.58500523 0.02740608
393 -1.13279467 5.58500523
394 -2.03168738 -1.13279467
395 NA -2.03168738
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 2.84258982 -0.77663612
[2,] 2.82724926 2.84258982
[3,] 4.10010583 2.82724926
[4,] 2.79386383 4.10010583
[5,] -0.68384802 2.79386383
[6,] -3.69070246 -0.68384802
[7,] -9.00996264 -3.69070246
[8,] -2.69546971 -9.00996264
[9,] 0.88650457 -2.69546971
[10,] -2.22667522 0.88650457
[11,] 4.12153637 -2.22667522
[12,] 7.47077189 4.12153637
[13,] 8.40612224 7.47077189
[14,] 7.60722953 8.40612224
[15,] 6.20922868 7.60722953
[16,] 1.45315319 6.20922868
[17,] 4.30315808 1.45315319
[18,] -0.80781693 4.30315808
[19,] -1.85617567 -0.80781693
[20,] -2.50575929 -1.85617567
[21,] 1.02824369 -2.50575929
[22,] 1.96858161 1.02824369
[23,] -0.79235896 1.96858161
[24,] -0.37676363 -0.79235896
[25,] 0.39074748 -0.37676363
[26,] 0.33124233 0.39074748
[27,] 1.57443191 0.33124233
[28,] 2.29455929 1.57443191
[29,] 3.07640151 2.29455929
[30,] -3.75077637 3.07640151
[31,] -5.34649397 -3.75077637
[32,] 4.76037983 -5.34649397
[33,] 6.53479430 4.76037983
[34,] 3.90115899 6.53479430
[35,] 3.95287872 3.90115899
[36,] 3.90133529 3.95287872
[37,] 6.49567129 3.90133529
[38,] 1.98224652 6.49567129
[39,] 3.80114902 1.98224652
[40,] -4.68403461 3.80114902
[41,] -0.58966416 -4.68403461
[42,] -7.67251094 -0.58966416
[43,] -9.09543618 -7.67251094
[44,] -7.00278057 -9.09543618
[45,] -10.15322161 -7.00278057
[46,] -8.35093346 -10.15322161
[47,] -2.74854770 -8.35093346
[48,] -13.68707294 -2.74854770
[49,] -9.20303552 -13.68707294
[50,] -4.14853301 -9.20303552
[51,] 0.24759629 -4.14853301
[52,] -6.59896915 0.24759629
[53,] -8.34958628 -6.59896915
[54,] -2.95279094 -8.34958628
[55,] -7.85107121 -2.95279094
[56,] -11.17294766 -7.85107121
[57,] -6.75783271 -11.17294766
[58,] -0.90476562 -6.75783271
[59,] 7.15791872 -0.90476562
[60,] 4.86350447 7.15791872
[61,] 5.87239740 4.86350447
[62,] 6.06273531 5.87239740
[63,] 5.87187321 6.06273531
[64,] 3.73959485 5.87187321
[65,] -5.10142418 3.73959485
[66,] 1.00510703 -5.10142418
[67,] 4.11288227 1.00510703
[68,] 7.53333309 4.11288227
[69,] 5.28622411 7.53333309
[70,] 10.16186345 5.28622411
[71,] 5.96411715 10.16186345
[72,] 7.52612588 5.96411715
[73,] 0.69115278 7.52612588
[74,] -2.21027774 0.69115278
[75,] 5.08272047 -2.21027774
[76,] 4.52578757 5.08272047
[77,] 7.73664988 4.52578757
[78,] 9.48037343 7.73664988
[79,] 6.59310751 9.48037343
[80,] 16.38311241 6.59310751
[81,] 19.90709052 16.38311241
[82,] 10.55442554 19.90709052
[83,] 10.92838450 10.55442554
[84,] 11.43129466 10.92838450
[85,] 10.44652252 11.43129466
[86,] 10.62594942 10.44652252
[87,] 12.43428351 10.62594942
[88,] 7.27072667 12.43428351
[89,] 10.34885022 7.27072667
[90,] 13.32318622 10.34885022
[91,] 10.40249063 13.32318622
[92,] 11.02428883 10.40249063
[93,] 15.33127554 11.02428883
[94,] 17.03997709 15.33127554
[95,] 19.19802217 17.03997709
[96,] 17.37133425 19.19802217
[97,] 14.23342144 17.37133425
[98,] 18.04636605 14.23342144
[99,] 14.07747333 18.04636605
[100,] 13.76090789 14.07747333
[101,] 15.70406303 13.76090789
[102,] 15.35244114 15.70406303
[103,] 5.54721349 15.35244114
[104,] 9.19795331 5.54721349
[105,] 13.51690941 9.19795331
[106,] 12.89470952 13.51690941
[107,] 11.04471441 12.89470952
[108,] 15.45125520 11.04471441
[109,] 14.33419023 15.45125520
[110,] 13.02165732 14.33419023
[111,] 13.88264212 13.02165732
[112,] 6.09031974 13.88264212
[113,] 6.09142703 6.09031974
[114,] 5.18184341 6.09142703
[115,] 9.52377367 5.18184341
[116,] -1.63095445 9.52377367
[117,] -3.49258592 -1.63095445
[118,] -5.00105758 -3.49258592
[119,] -6.47509479 -5.00105758
[120,] 2.89904026 -6.47509479
[121,] 1.15146047 2.89904026
[122,] -5.19491359 1.15146047
[123,] -4.14397282 -5.19491359
[124,] -9.70286553 -4.14397282
[125,] -8.56187116 -9.70286553
[126,] -15.19264521 -8.56187116
[127,] -14.16855419 -15.19264521
[128,] -8.58271389 -14.16855419
[129,] -15.33499225 -8.58271389
[130,] -14.98749071 -15.33499225
[131,] -3.11866667 -14.98749071
[132,] -1.42869623 -3.11866667
[133,] -0.33776502 -1.42869623
[134,] -1.60874003 -0.33776502
[135,] -6.14277725 -1.60874003
[136,] 1.54543435 -6.14277725
[137,] 7.65095121 1.54543435
[138,] 5.32209294 7.65095121
[139,] 6.00487104 5.32209294
[140,] -0.93605995 6.00487104
[141,] -0.27798042 -0.93605995
[142,] 4.24338142 -0.27798042
[143,] 7.29515474 4.24338142
[144,] 6.16259696 7.29515474
[145,] 9.15415976 6.16259696
[146,] 10.44469863 9.15415976
[147,] 14.38731979 10.44469863
[148,] 19.12438497 14.38731979
[149,] 10.71009321 19.12438497
[150,] 8.95365026 10.71009321
[151,] 9.31186185 8.95365026
[152,] 2.30463995 9.31186185
[153,] 0.49781996 2.30463995
[154,] -8.41315505 0.49781996
[155,] -2.52256259 -8.41315505
[156,] -5.22414046 -2.52256259
[157,] -1.57760925 -5.22414046
[158,] -1.11360627 -1.57760925
[159,] -3.39930472 -1.11360627
[160,] -2.12162710 -3.39930472
[161,] -9.63603178 -2.12162710
[162,] -7.83977999 -9.63603178
[163,] -11.93441049 -7.83977999
[164,] -15.15102953 -11.93441049
[165,] -13.47445430 -15.15102953
[166,] -15.11941782 -13.47445430
[167,] -0.93158898 -15.11941782
[168,] -2.52889892 -0.93158898
[169,] -8.70816868 -2.52889892
[170,] -11.04369490 -8.70816868
[171,] -3.73538568 -11.04369490
[172,] -8.17992242 -3.73538568
[173,] -3.96077495 -8.17992242
[174,] -1.77085809 -3.96077495
[175,] -3.42860439 -1.77085809
[176,] -11.67505692 -3.42860439
[177,] -13.46770274 -11.67505692
[178,] -3.42037343 -13.46770274
[179,] -3.12412165 -3.42037343
[180,] 0.54609378 -3.12412165
[181,] 0.17997427 0.54609378
[182,] 5.42610357 0.17997427
[183,] 1.44676492 5.42610357
[184,] -3.92406273 1.44676492
[185,] -3.09344539 -3.92406273
[186,] -4.11621370 -3.09344539
[187,] -0.93151982 -4.11621370
[188,] -3.41619434 -0.93151982
[189,] -4.76514065 -3.41619434
[190,] 0.60931784 -4.76514065
[191,] -0.01480742 0.60931784
[192,] -4.59651736 -0.01480742
[193,] -10.08211247 -4.59651736
[194,] -17.88247504 -10.08211247
[195,] -18.15075531 -17.88247504
[196,] -14.49754657 -18.15075531
[197,] -12.89264216 -14.49754657
[198,] -19.69406310 -12.89264216
[199,] -25.13276443 -19.69406310
[200,] -24.90165714 -25.13276443
[201,] -24.67054986 -24.90165714
[202,] -24.43944257 -24.67054986
[203,] -22.91216686 -24.43944257
[204,] -19.42043755 -22.91216686
[205,] -30.75288242 -19.42043755
[206,] -15.13184403 -30.75288242
[207,] -20.56015874 -15.13184403
[208,] -15.75368113 -20.56015874
[209,] -13.44796332 -15.75368113
[210,] -15.09686561 -13.44796332
[211,] -20.55494493 -15.09686561
[212,] -21.94007496 -20.55494493
[213,] -25.77836480 -21.94007496
[214,] -8.25985464 -25.77836480
[215,] -11.61769855 -8.25985464
[216,] -11.54136830 -11.61769855
[217,] -14.26973662 -11.54136830
[218,] -12.85654703 -14.26973662
[219,] -14.40327898 -12.85654703
[220,] -15.28424442 -14.40327898
[221,] -12.75235818 -15.28424442
[222,] -17.65802218 -12.75235818
[223,] -21.71635605 -17.65802218
[224,] -16.72242196 -21.71635605
[225,] -12.62253956 -16.72242196
[226,] -13.11907055 -12.62253956
[227,] -6.03204939 -13.11907055
[228,] -8.76555263 -6.03204939
[229,] -14.91057932 -8.76555263
[230,] -11.35318112 -14.91057932
[231,] -6.17766426 -11.35318112
[232,] -1.66867372 -6.17766426
[233,] -6.03109372 -1.66867372
[234,] -7.03366107 -6.03109372
[235,] -6.83500355 -7.03366107
[236,] 3.87753915 -6.83500355
[237,] 0.01917084 3.87753915
[238,] 0.82427621 0.01917084
[239,] -0.90657631 0.82427621
[240,] -0.55502309 -0.90657631
[241,] -0.02672346 -0.55502309
[242,] 1.89242402 -0.02672346
[243,] 3.20247294 1.89242402
[244,] 4.48745582 3.20247294
[245,] 7.29366358 4.48745582
[246,] 5.06113068 7.29366358
[247,] 5.02717193 5.06113068
[248,] 0.26313472 5.02717193
[249,] -6.98041254 0.26313472
[250,] -3.32725740 -6.98041254
[251,] -7.19051566 -3.32725740
[252,] -7.63590024 -7.19051566
[253,] -2.34000635 -7.63590024
[254,] -0.06359763 -2.34000635
[255,] 5.44261971 -0.06359763
[256,] 4.38241408 5.44261971
[257,] -0.43734563 4.38241408
[258,] -3.10526801 -0.43734563
[259,] -0.83794828 -3.10526801
[260,] 1.63184608 -0.83794828
[261,] -8.42989830 1.63184608
[262,] -9.99316614 -8.42989830
[263,] -1.86742917 -9.99316614
[264,] -4.52765968 -1.86742917
[265,] -3.05149594 -4.52765968
[266,] 6.35235969 -3.05149594
[267,] 5.92636266 6.35235969
[268,] -0.04351953 5.92636266
[269,] -2.79461703 -0.04351953
[270,] -2.25281883 -2.79461703
[271,] -6.94619001 -2.25281883
[272,] -2.74356884 -6.94619001
[273,] -4.51690557 -2.74356884
[274,] -2.27763560 -4.51690557
[275,] -12.51199626 -2.27763560
[276,] -12.63598945 -12.51199626
[277,] -11.92328982 -12.63598945
[278,] -11.15426483 -11.92328982
[279,] -18.09315754 -11.15426483
[280,] -13.79612680 -18.09315754
[281,] -12.09995349 -13.79612680
[282,] -13.91921366 -12.09995349
[283,] -10.74925279 -13.91921366
[284,] -14.25556368 -10.74925279
[285,] -13.74352051 -14.25556368
[286,] -18.15400556 -13.74352051
[287,] -19.95767531 -18.15400556
[288,] -23.60215845 -19.95767531
[289,] -14.34990475 -23.60215845
[290,] -12.40855249 -14.34990475
[291,] -11.08997343 -12.40855249
[292,] -8.89951303 -11.08997343
[293,] -5.94440766 -8.89951303
[294,] -5.07024775 -5.94440766
[295,] -11.26636725 -5.07024775
[296,] -12.61029155 -11.26636725
[297,] -14.78888569 -12.61029155
[298,] -5.00707792 -14.78888569
[299,] 0.62329444 -5.00707792
[300,] -5.27580881 0.62329444
[301,] -6.18739626 -5.27580881
[302,] -7.22995404 -6.18739626
[303,] 3.84361259 -7.22995404
[304,] 5.12659164 3.84361259
[305,] 1.82210850 5.12659164
[306,] 14.77779186 1.82210850
[307,] 15.84358814 14.77779186
[308,] 14.98739017 15.84358814
[309,] 15.56604769 14.98739017
[310,] 19.48120666 15.56604769
[311,] 24.29513118 19.48120666
[312,] 18.93823272 24.29513118
[313,] 16.64848259 18.93823272
[314,] 20.88714969 16.64848259
[315,] 18.75858042 20.88714969
[316,] 23.05189249 18.75858042
[317,] 18.39091748 23.05189249
[318,] 23.19488602 18.39091748
[319,] 24.66427847 23.19488602
[320,] 29.16200011 24.66427847
[321,] 25.65384233 29.16200011
[322,] 24.22583190 25.65384233
[323,] 27.42470953 24.22583190
[324,] 26.97369050 27.42470953
[325,] 20.06259300 26.97369050
[326,] 23.36855579 20.06259300
[327,] 33.95478271 23.36855579
[328,] 21.47738472 33.95478271
[329,] 27.30809010 21.47738472
[330,] 34.16176964 27.30809010
[331,] 31.46279846 34.16176964
[332,] 17.09447416 31.46279846
[333,] 26.78114701 17.09447416
[334,] 13.31776626 26.78114701
[335,] 19.72429747 13.31776626
[336,] 34.88472342 19.72429747
[337,] 17.60761443 34.88472342
[338,] 8.77768822 17.60761443
[339,] 10.03418498 8.77768822
[340,] 16.79758510 10.03418498
[341,] 17.91954980 16.79758510
[342,] -1.80566827 17.91954980
[343,] 17.64102944 -1.80566827
[344,] 22.86668794 17.64102944
[345,] 14.72926509 22.86668794
[346,] 14.33650635 14.72926509
[347,] 8.84989689 14.33650635
[348,] -6.52772692 8.84989689
[349,] -6.24212202 -6.52772692
[350,] -17.86303386 -6.24212202
[351,] -20.37319547 -17.86303386
[352,] 8.97936638 -20.37319547
[353,] -0.25609095 8.97936638
[354,] -21.33306788 -0.25609095
[355,] -11.27714911 -21.33306788
[356,] -5.37274994 -11.27714911
[357,] 8.63019467 -5.37274994
[358,] 0.46006750 8.63019467
[359,] -8.39853621 0.46006750
[360,] -4.81044711 -8.39853621
[361,] -6.74761541 -4.81044711
[362,] -10.85508229 -6.74761541
[363,] 13.46160013 -10.85508229
[364,] 4.56844521 13.46160013
[365,] 12.95894006 4.56844521
[366,] 8.00378130 12.95894006
[367,] 15.45212496 8.00378130
[368,] 22.77107148 15.45212496
[369,] -0.23659063 22.77107148
[370,] -2.81342592 -0.23659063
[371,] 3.16143448 -2.81342592
[372,] 0.42707382 3.16143448
[373,] 1.70728925 0.42707382
[374,] -9.84976614 1.70728925
[375,] 3.33909234 -9.84976614
[376,] -2.06961472 3.33909234
[377,] -8.87116772 -2.06961472
[378,] -4.61666521 -8.87116772
[379,] -18.19119238 -4.61666521
[380,] -30.71824777 -18.19119238
[381,] -15.08076153 -30.71824777
[382,] -7.48761596 -15.08076153
[383,] -11.55288763 -7.48761596
[384,] -1.41075642 -11.55288763
[385,] -0.45585200 -1.41075642
[386,] 4.59055672 -0.45585200
[387,] -15.27193217 4.59055672
[388,] -5.92685167 -15.27193217
[389,] -0.50831663 -5.92685167
[390,] -8.75945815 -0.50831663
[391,] 0.02740608 -8.75945815
[392,] 5.58500523 0.02740608
[393,] -1.13279467 5.58500523
[394,] -2.03168738 -1.13279467
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 2.84258982 -0.77663612
2 2.82724926 2.84258982
3 4.10010583 2.82724926
4 2.79386383 4.10010583
5 -0.68384802 2.79386383
6 -3.69070246 -0.68384802
7 -9.00996264 -3.69070246
8 -2.69546971 -9.00996264
9 0.88650457 -2.69546971
10 -2.22667522 0.88650457
11 4.12153637 -2.22667522
12 7.47077189 4.12153637
13 8.40612224 7.47077189
14 7.60722953 8.40612224
15 6.20922868 7.60722953
16 1.45315319 6.20922868
17 4.30315808 1.45315319
18 -0.80781693 4.30315808
19 -1.85617567 -0.80781693
20 -2.50575929 -1.85617567
21 1.02824369 -2.50575929
22 1.96858161 1.02824369
23 -0.79235896 1.96858161
24 -0.37676363 -0.79235896
25 0.39074748 -0.37676363
26 0.33124233 0.39074748
27 1.57443191 0.33124233
28 2.29455929 1.57443191
29 3.07640151 2.29455929
30 -3.75077637 3.07640151
31 -5.34649397 -3.75077637
32 4.76037983 -5.34649397
33 6.53479430 4.76037983
34 3.90115899 6.53479430
35 3.95287872 3.90115899
36 3.90133529 3.95287872
37 6.49567129 3.90133529
38 1.98224652 6.49567129
39 3.80114902 1.98224652
40 -4.68403461 3.80114902
41 -0.58966416 -4.68403461
42 -7.67251094 -0.58966416
43 -9.09543618 -7.67251094
44 -7.00278057 -9.09543618
45 -10.15322161 -7.00278057
46 -8.35093346 -10.15322161
47 -2.74854770 -8.35093346
48 -13.68707294 -2.74854770
49 -9.20303552 -13.68707294
50 -4.14853301 -9.20303552
51 0.24759629 -4.14853301
52 -6.59896915 0.24759629
53 -8.34958628 -6.59896915
54 -2.95279094 -8.34958628
55 -7.85107121 -2.95279094
56 -11.17294766 -7.85107121
57 -6.75783271 -11.17294766
58 -0.90476562 -6.75783271
59 7.15791872 -0.90476562
60 4.86350447 7.15791872
61 5.87239740 4.86350447
62 6.06273531 5.87239740
63 5.87187321 6.06273531
64 3.73959485 5.87187321
65 -5.10142418 3.73959485
66 1.00510703 -5.10142418
67 4.11288227 1.00510703
68 7.53333309 4.11288227
69 5.28622411 7.53333309
70 10.16186345 5.28622411
71 5.96411715 10.16186345
72 7.52612588 5.96411715
73 0.69115278 7.52612588
74 -2.21027774 0.69115278
75 5.08272047 -2.21027774
76 4.52578757 5.08272047
77 7.73664988 4.52578757
78 9.48037343 7.73664988
79 6.59310751 9.48037343
80 16.38311241 6.59310751
81 19.90709052 16.38311241
82 10.55442554 19.90709052
83 10.92838450 10.55442554
84 11.43129466 10.92838450
85 10.44652252 11.43129466
86 10.62594942 10.44652252
87 12.43428351 10.62594942
88 7.27072667 12.43428351
89 10.34885022 7.27072667
90 13.32318622 10.34885022
91 10.40249063 13.32318622
92 11.02428883 10.40249063
93 15.33127554 11.02428883
94 17.03997709 15.33127554
95 19.19802217 17.03997709
96 17.37133425 19.19802217
97 14.23342144 17.37133425
98 18.04636605 14.23342144
99 14.07747333 18.04636605
100 13.76090789 14.07747333
101 15.70406303 13.76090789
102 15.35244114 15.70406303
103 5.54721349 15.35244114
104 9.19795331 5.54721349
105 13.51690941 9.19795331
106 12.89470952 13.51690941
107 11.04471441 12.89470952
108 15.45125520 11.04471441
109 14.33419023 15.45125520
110 13.02165732 14.33419023
111 13.88264212 13.02165732
112 6.09031974 13.88264212
113 6.09142703 6.09031974
114 5.18184341 6.09142703
115 9.52377367 5.18184341
116 -1.63095445 9.52377367
117 -3.49258592 -1.63095445
118 -5.00105758 -3.49258592
119 -6.47509479 -5.00105758
120 2.89904026 -6.47509479
121 1.15146047 2.89904026
122 -5.19491359 1.15146047
123 -4.14397282 -5.19491359
124 -9.70286553 -4.14397282
125 -8.56187116 -9.70286553
126 -15.19264521 -8.56187116
127 -14.16855419 -15.19264521
128 -8.58271389 -14.16855419
129 -15.33499225 -8.58271389
130 -14.98749071 -15.33499225
131 -3.11866667 -14.98749071
132 -1.42869623 -3.11866667
133 -0.33776502 -1.42869623
134 -1.60874003 -0.33776502
135 -6.14277725 -1.60874003
136 1.54543435 -6.14277725
137 7.65095121 1.54543435
138 5.32209294 7.65095121
139 6.00487104 5.32209294
140 -0.93605995 6.00487104
141 -0.27798042 -0.93605995
142 4.24338142 -0.27798042
143 7.29515474 4.24338142
144 6.16259696 7.29515474
145 9.15415976 6.16259696
146 10.44469863 9.15415976
147 14.38731979 10.44469863
148 19.12438497 14.38731979
149 10.71009321 19.12438497
150 8.95365026 10.71009321
151 9.31186185 8.95365026
152 2.30463995 9.31186185
153 0.49781996 2.30463995
154 -8.41315505 0.49781996
155 -2.52256259 -8.41315505
156 -5.22414046 -2.52256259
157 -1.57760925 -5.22414046
158 -1.11360627 -1.57760925
159 -3.39930472 -1.11360627
160 -2.12162710 -3.39930472
161 -9.63603178 -2.12162710
162 -7.83977999 -9.63603178
163 -11.93441049 -7.83977999
164 -15.15102953 -11.93441049
165 -13.47445430 -15.15102953
166 -15.11941782 -13.47445430
167 -0.93158898 -15.11941782
168 -2.52889892 -0.93158898
169 -8.70816868 -2.52889892
170 -11.04369490 -8.70816868
171 -3.73538568 -11.04369490
172 -8.17992242 -3.73538568
173 -3.96077495 -8.17992242
174 -1.77085809 -3.96077495
175 -3.42860439 -1.77085809
176 -11.67505692 -3.42860439
177 -13.46770274 -11.67505692
178 -3.42037343 -13.46770274
179 -3.12412165 -3.42037343
180 0.54609378 -3.12412165
181 0.17997427 0.54609378
182 5.42610357 0.17997427
183 1.44676492 5.42610357
184 -3.92406273 1.44676492
185 -3.09344539 -3.92406273
186 -4.11621370 -3.09344539
187 -0.93151982 -4.11621370
188 -3.41619434 -0.93151982
189 -4.76514065 -3.41619434
190 0.60931784 -4.76514065
191 -0.01480742 0.60931784
192 -4.59651736 -0.01480742
193 -10.08211247 -4.59651736
194 -17.88247504 -10.08211247
195 -18.15075531 -17.88247504
196 -14.49754657 -18.15075531
197 -12.89264216 -14.49754657
198 -19.69406310 -12.89264216
199 -25.13276443 -19.69406310
200 -24.90165714 -25.13276443
201 -24.67054986 -24.90165714
202 -24.43944257 -24.67054986
203 -22.91216686 -24.43944257
204 -19.42043755 -22.91216686
205 -30.75288242 -19.42043755
206 -15.13184403 -30.75288242
207 -20.56015874 -15.13184403
208 -15.75368113 -20.56015874
209 -13.44796332 -15.75368113
210 -15.09686561 -13.44796332
211 -20.55494493 -15.09686561
212 -21.94007496 -20.55494493
213 -25.77836480 -21.94007496
214 -8.25985464 -25.77836480
215 -11.61769855 -8.25985464
216 -11.54136830 -11.61769855
217 -14.26973662 -11.54136830
218 -12.85654703 -14.26973662
219 -14.40327898 -12.85654703
220 -15.28424442 -14.40327898
221 -12.75235818 -15.28424442
222 -17.65802218 -12.75235818
223 -21.71635605 -17.65802218
224 -16.72242196 -21.71635605
225 -12.62253956 -16.72242196
226 -13.11907055 -12.62253956
227 -6.03204939 -13.11907055
228 -8.76555263 -6.03204939
229 -14.91057932 -8.76555263
230 -11.35318112 -14.91057932
231 -6.17766426 -11.35318112
232 -1.66867372 -6.17766426
233 -6.03109372 -1.66867372
234 -7.03366107 -6.03109372
235 -6.83500355 -7.03366107
236 3.87753915 -6.83500355
237 0.01917084 3.87753915
238 0.82427621 0.01917084
239 -0.90657631 0.82427621
240 -0.55502309 -0.90657631
241 -0.02672346 -0.55502309
242 1.89242402 -0.02672346
243 3.20247294 1.89242402
244 4.48745582 3.20247294
245 7.29366358 4.48745582
246 5.06113068 7.29366358
247 5.02717193 5.06113068
248 0.26313472 5.02717193
249 -6.98041254 0.26313472
250 -3.32725740 -6.98041254
251 -7.19051566 -3.32725740
252 -7.63590024 -7.19051566
253 -2.34000635 -7.63590024
254 -0.06359763 -2.34000635
255 5.44261971 -0.06359763
256 4.38241408 5.44261971
257 -0.43734563 4.38241408
258 -3.10526801 -0.43734563
259 -0.83794828 -3.10526801
260 1.63184608 -0.83794828
261 -8.42989830 1.63184608
262 -9.99316614 -8.42989830
263 -1.86742917 -9.99316614
264 -4.52765968 -1.86742917
265 -3.05149594 -4.52765968
266 6.35235969 -3.05149594
267 5.92636266 6.35235969
268 -0.04351953 5.92636266
269 -2.79461703 -0.04351953
270 -2.25281883 -2.79461703
271 -6.94619001 -2.25281883
272 -2.74356884 -6.94619001
273 -4.51690557 -2.74356884
274 -2.27763560 -4.51690557
275 -12.51199626 -2.27763560
276 -12.63598945 -12.51199626
277 -11.92328982 -12.63598945
278 -11.15426483 -11.92328982
279 -18.09315754 -11.15426483
280 -13.79612680 -18.09315754
281 -12.09995349 -13.79612680
282 -13.91921366 -12.09995349
283 -10.74925279 -13.91921366
284 -14.25556368 -10.74925279
285 -13.74352051 -14.25556368
286 -18.15400556 -13.74352051
287 -19.95767531 -18.15400556
288 -23.60215845 -19.95767531
289 -14.34990475 -23.60215845
290 -12.40855249 -14.34990475
291 -11.08997343 -12.40855249
292 -8.89951303 -11.08997343
293 -5.94440766 -8.89951303
294 -5.07024775 -5.94440766
295 -11.26636725 -5.07024775
296 -12.61029155 -11.26636725
297 -14.78888569 -12.61029155
298 -5.00707792 -14.78888569
299 0.62329444 -5.00707792
300 -5.27580881 0.62329444
301 -6.18739626 -5.27580881
302 -7.22995404 -6.18739626
303 3.84361259 -7.22995404
304 5.12659164 3.84361259
305 1.82210850 5.12659164
306 14.77779186 1.82210850
307 15.84358814 14.77779186
308 14.98739017 15.84358814
309 15.56604769 14.98739017
310 19.48120666 15.56604769
311 24.29513118 19.48120666
312 18.93823272 24.29513118
313 16.64848259 18.93823272
314 20.88714969 16.64848259
315 18.75858042 20.88714969
316 23.05189249 18.75858042
317 18.39091748 23.05189249
318 23.19488602 18.39091748
319 24.66427847 23.19488602
320 29.16200011 24.66427847
321 25.65384233 29.16200011
322 24.22583190 25.65384233
323 27.42470953 24.22583190
324 26.97369050 27.42470953
325 20.06259300 26.97369050
326 23.36855579 20.06259300
327 33.95478271 23.36855579
328 21.47738472 33.95478271
329 27.30809010 21.47738472
330 34.16176964 27.30809010
331 31.46279846 34.16176964
332 17.09447416 31.46279846
333 26.78114701 17.09447416
334 13.31776626 26.78114701
335 19.72429747 13.31776626
336 34.88472342 19.72429747
337 17.60761443 34.88472342
338 8.77768822 17.60761443
339 10.03418498 8.77768822
340 16.79758510 10.03418498
341 17.91954980 16.79758510
342 -1.80566827 17.91954980
343 17.64102944 -1.80566827
344 22.86668794 17.64102944
345 14.72926509 22.86668794
346 14.33650635 14.72926509
347 8.84989689 14.33650635
348 -6.52772692 8.84989689
349 -6.24212202 -6.52772692
350 -17.86303386 -6.24212202
351 -20.37319547 -17.86303386
352 8.97936638 -20.37319547
353 -0.25609095 8.97936638
354 -21.33306788 -0.25609095
355 -11.27714911 -21.33306788
356 -5.37274994 -11.27714911
357 8.63019467 -5.37274994
358 0.46006750 8.63019467
359 -8.39853621 0.46006750
360 -4.81044711 -8.39853621
361 -6.74761541 -4.81044711
362 -10.85508229 -6.74761541
363 13.46160013 -10.85508229
364 4.56844521 13.46160013
365 12.95894006 4.56844521
366 8.00378130 12.95894006
367 15.45212496 8.00378130
368 22.77107148 15.45212496
369 -0.23659063 22.77107148
370 -2.81342592 -0.23659063
371 3.16143448 -2.81342592
372 0.42707382 3.16143448
373 1.70728925 0.42707382
374 -9.84976614 1.70728925
375 3.33909234 -9.84976614
376 -2.06961472 3.33909234
377 -8.87116772 -2.06961472
378 -4.61666521 -8.87116772
379 -18.19119238 -4.61666521
380 -30.71824777 -18.19119238
381 -15.08076153 -30.71824777
382 -7.48761596 -15.08076153
383 -11.55288763 -7.48761596
384 -1.41075642 -11.55288763
385 -0.45585200 -1.41075642
386 4.59055672 -0.45585200
387 -15.27193217 4.59055672
388 -5.92685167 -15.27193217
389 -0.50831663 -5.92685167
390 -8.75945815 -0.50831663
391 0.02740608 -8.75945815
392 5.58500523 0.02740608
393 -1.13279467 5.58500523
394 -2.03168738 -1.13279467
> plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
> lines(lowess(z))
> abline(lm(z))
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/7ntvx1228923785.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8gst91228923785.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9ixmd1228923785.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10h6601228923785.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
+ myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ')
+ if (rownames(mysum$coefficients)[i] != '(Intercept)') {
+ myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
+ if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
+ }
+ }
> myeq <- paste(myeq, ' + e[t]')
> a<-table.row.start(a)
> a<-table.element(a, myeq)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/1176oc1228923785.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Variable',header=TRUE)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
> a<-table.element(a,'2-tail p-value',header=TRUE)
> a<-table.element(a,'1-tail p-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:k){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
+ a<-table.element(a,mysum$coefficients[i,1])
+ a<-table.element(a, round(mysum$coefficients[i,2],6))
+ a<-table.element(a, round(mysum$coefficients[i,3],4))
+ a<-table.element(a, round(mysum$coefficients[i,4],6))
+ a<-table.element(a, round(mysum$coefficients[i,4]/2,6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/12td4h1228923785.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple R',1,TRUE)
> a<-table.element(a, sqrt(mysum$r.squared))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'R-squared',1,TRUE)
> a<-table.element(a, mysum$r.squared)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Adjusted R-squared',1,TRUE)
> a<-table.element(a, mysum$adj.r.squared)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (value)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[1])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[2])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[3])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'p-value',1,TRUE)
> a<-table.element(a, 1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
> a<-table.element(a, mysum$sigma)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a, sum(myerror*myerror))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/13tg2s1228923785.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Time or Index', 1, TRUE)
> a<-table.element(a, 'Actuals', 1, TRUE)
> a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
> a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
> a<-table.row.end(a)
> for (i in 1:n) {
+ a<-table.row.start(a)
+ a<-table.element(a,i, 1, TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]-mysum$resid[i])
+ a<-table.element(a,mysum$resid[i])
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/14wv9u1228923785.tab")
> if (n > n25) {
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'p-values',header=TRUE)
+ a<-table.element(a,'Alternative Hypothesis',3,header=TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'breakpoint index',header=TRUE)
+ a<-table.element(a,'greater',header=TRUE)
+ a<-table.element(a,'2-sided',header=TRUE)
+ a<-table.element(a,'less',header=TRUE)
+ a<-table.row.end(a)
+ for (mypoint in kp3:nmkm3) {
+ a<-table.row.start(a)
+ a<-table.element(a,mypoint,header=TRUE)
+ a<-table.element(a,gqarr[mypoint-kp3+1,1])
+ a<-table.element(a,gqarr[mypoint-kp3+1,2])
+ a<-table.element(a,gqarr[mypoint-kp3+1,3])
+ a<-table.row.end(a)
+ }
+ a<-table.end(a)
+ table.save(a,file="/var/www/html/rcomp/tmp/152oct1228923785.tab")
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'Description',header=TRUE)
+ a<-table.element(a,'# significant tests',header=TRUE)
+ a<-table.element(a,'% significant tests',header=TRUE)
+ a<-table.element(a,'OK/NOK',header=TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'1% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant1)
+ a<-table.element(a,numsignificant1/numgqtests)
+ if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'5% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant5)
+ a<-table.element(a,numsignificant5/numgqtests)
+ if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'10% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant10)
+ a<-table.element(a,numsignificant10/numgqtests)
+ if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.end(a)
+ table.save(a,file="/var/www/html/rcomp/tmp/16azh21228923785.tab")
+ }
>
> system("convert tmp/138ka1228923785.ps tmp/138ka1228923785.png")
> system("convert tmp/2j2ze1228923785.ps tmp/2j2ze1228923785.png")
> system("convert tmp/3yuft1228923785.ps tmp/3yuft1228923785.png")
> system("convert tmp/4im281228923785.ps tmp/4im281228923785.png")
> system("convert tmp/5gfh41228923785.ps tmp/5gfh41228923785.png")
> system("convert tmp/6d8cc1228923785.ps tmp/6d8cc1228923785.png")
> system("convert tmp/7ntvx1228923785.ps tmp/7ntvx1228923785.png")
> system("convert tmp/8gst91228923785.ps tmp/8gst91228923785.png")
> system("convert tmp/9ixmd1228923785.ps tmp/9ixmd1228923785.png")
> system("convert tmp/10h6601228923785.ps tmp/10h6601228923785.png")
>
>
> proc.time()
user system elapsed
10.044 2.069 11.580