R version 2.15.2 (2012-10-26) -- "Trick or Treat"
Copyright (C) 2012 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i686-pc-linux-gnu (32-bit)
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(255
+ ,280.2
+ ,299.9
+ ,339.2
+ ,374.2
+ ,393.5
+ ,389.2
+ ,381.7
+ ,375.2
+ ,369
+ ,357.4
+ ,352.1
+ ,346.5
+ ,342.9
+ ,340.3
+ ,328.3
+ ,322.9
+ ,314.3
+ ,308.9
+ ,294
+ ,285.6
+ ,281.2
+ ,280.3
+ ,278.8
+ ,274.5
+ ,270.4
+ ,263.4
+ ,259.9
+ ,258
+ ,262.7
+ ,284.7
+ ,311.3
+ ,322.1
+ ,327
+ ,331.3
+ ,333.3
+ ,321.4
+ ,327
+ ,320
+ ,314.7
+ ,316.7
+ ,314.4
+ ,321.3
+ ,318.2
+ ,307.2
+ ,301.3
+ ,287.5
+ ,277.7
+ ,274.4
+ ,258.8
+ ,253.3
+ ,251
+ ,248.4
+ ,249.5
+ ,246.1
+ ,244.5
+ ,243.6
+ ,244
+ ,240.8
+ ,249.8
+ ,248
+ ,259.4
+ ,260.5
+ ,260.8
+ ,261.3
+ ,259.5
+ ,256.6
+ ,257.9
+ ,256.5
+ ,254.2
+ ,253.3
+ ,253.8
+ ,255.5
+ ,257.1
+ ,257.3
+ ,253.2
+ ,252.8
+ ,252
+ ,250.7
+ ,252.2
+ ,250
+ ,251
+ ,253.4
+ ,251.2
+ ,255.6
+ ,261.1
+ ,258.9
+ ,259.9
+ ,261.2
+ ,264.7
+ ,267.1
+ ,266.4
+ ,267.7
+ ,268.6
+ ,267.5
+ ,268.5
+ ,268.5
+ ,270.5
+ ,270.9
+ ,270.1
+ ,269.3
+ ,269.8
+ ,270.1
+ ,264.9
+ ,263.7
+ ,264.8
+ ,263.7
+ ,255.9
+ ,276.2
+ ,360.1
+ ,380.5
+ ,373.7
+ ,369.8
+ ,366.6
+ ,359.3
+ ,345.8
+ ,326.2
+ ,324.5
+ ,328.1
+ ,327.5
+ ,324.4
+ ,316.5
+ ,310.9
+ ,301.5
+ ,291.7
+ ,290.4
+ ,287.4
+ ,277.7
+ ,281.6
+ ,288
+ ,276
+ ,272.9
+ ,283
+ ,283.3
+ ,276.8
+ ,284.5
+ ,282.7
+ ,281.2
+ ,287.4
+ ,283.1
+ ,284
+ ,285.5
+ ,289.2
+ ,292.5
+ ,296.4
+ ,305.2
+ ,303.9
+ ,311.5
+ ,316.3
+ ,316.7
+ ,322.5
+ ,317.1
+ ,309.8
+ ,303.8
+ ,290.3
+ ,293.7
+ ,291.7
+ ,296.5
+ ,289.1
+ ,288.5
+ ,293.8
+ ,297.7
+ ,305.4
+ ,302.7
+ ,302.5
+ ,303
+ ,294.5
+ ,294.1
+ ,294.5
+ ,297.1
+ ,289.4
+ ,292.4
+ ,287.9
+ ,286.6
+ ,280.5
+ ,272.4
+ ,269.2
+ ,270.6
+ ,267.3
+ ,262.5
+ ,266.8
+ ,268.8
+ ,263.1
+ ,261.2
+ ,266
+ ,262.5
+ ,265.2
+ ,261.3
+ ,253.7
+ ,249.2
+ ,239.1
+ ,236.4
+ ,235.2
+ ,245.2
+ ,246.2
+ ,247.7
+ ,251.4
+ ,253.3
+ ,254.8
+ ,250
+ ,249.3
+ ,241.5
+ ,243.3
+ ,248
+ ,253
+ ,252.9
+ ,251.5
+ ,251.6
+ ,253.5
+ ,259.8
+ ,334.1
+ ,448
+ ,445.8
+ ,445
+ ,448.2
+ ,438.2
+ ,439.8
+ ,423.4
+ ,410.8
+ ,408.4
+ ,406.7
+ ,405.9
+ ,402.7
+ ,405.1
+ ,399.6
+ ,386.5
+ ,381.4
+ ,375.2
+ ,357.7
+ ,359
+ ,355
+ ,352.7
+ ,344.4
+ ,343.8
+ ,338
+ ,339
+ ,333.3
+ ,334.4
+ ,328.3
+ ,330.7
+ ,330
+ ,331.6
+ ,351.2
+ ,389.4
+ ,410.9
+ ,442.8
+ ,462.8
+ ,466.9
+ ,461.7
+ ,439.2
+ ,430.3
+ ,416.1
+ ,402.5
+ ,397.3
+ ,403.3
+ ,395.9
+ ,387.8
+ ,378.6
+ ,377.1
+ ,370.4
+ ,362
+ ,350.3
+ ,348.2
+ ,344.6
+ ,343.5
+ ,342.8
+ ,347.6
+ ,346.6
+ ,349.5
+ ,342.1
+ ,342
+ ,342.8
+ ,339.3
+ ,348.2
+ ,333.7
+ ,334.7
+ ,354
+ ,367.7
+ ,363.3
+ ,358.4
+ ,353.1
+ ,343.1
+ ,344.6
+ ,344.4
+ ,333.9
+ ,331.7
+ ,324.3
+ ,321.2
+ ,322.4
+ ,321.7
+ ,320.5
+ ,312.8
+ ,309.7
+ ,315.6
+ ,309.7
+ ,304.6
+ ,302.5
+ ,301.5
+ ,298.8
+ ,291.3
+ ,293.6
+ ,294.6
+ ,285.9
+ ,297.6
+ ,301.1
+ ,293.8
+ ,297.7
+ ,292.9
+ ,292.1
+ ,287.2
+ ,288.2
+ ,283.8
+ ,299.9
+ ,292.4
+ ,293.3
+ ,300.8
+ ,293.7
+ ,293.1
+ ,294.4
+ ,292.1
+ ,291.9
+ ,282.5
+ ,277.9
+ ,287.5
+ ,289.2
+ ,285.6
+ ,293.2
+ ,290.8
+ ,283.1
+ ,275
+ ,287.8
+ ,287.8
+ ,287.4
+ ,284
+ ,277.8
+ ,277.6
+ ,304.9
+ ,294
+ ,300.9
+ ,324
+ ,332.9
+ ,341.6
+ ,333.4
+ ,348.2
+ ,344.7
+ ,344.7
+ ,329.3
+ ,323.5
+ ,323.2
+ ,317.4
+ ,330.1
+ ,329.2
+ ,334.9
+ ,315.8
+ ,315.4
+ ,319.6
+ ,317.3
+ ,313.8
+ ,315.8
+ ,311.3)
+ ,dim=c(1
+ ,360)
+ ,dimnames=list(c('USrtCoffee')
+ ,1:360))
> y <- array(NA,dim=c(1,360),dimnames=list(c('USrtCoffee'),1:360))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par3 = 'Linear Trend'
> par2 = 'Include Monthly Dummies'
> par1 = '1'
> library(lattice)
> library(lmtest)
Loading required package: zoo
Attaching package: 'zoo'
The following object(s) are masked from 'package:base':
as.Date, as.Date.numeric
> n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
> par1 <- as.numeric(par1)
> x <- t(y)
> k <- length(x[1,])
> n <- length(x[,1])
> x1 <- cbind(x[,par1], x[,1:k!=par1])
> mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
> colnames(x1) <- mycolnames #colnames(x)[par1]
> x <- x1
> if (par3 == 'First Differences'){
+ x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
+ for (i in 1:n-1) {
+ for (j in 1:k) {
+ x2[i,j] <- x[i+1,j] - x[i,j]
+ }
+ }
+ x <- x2
+ }
> if (par2 == 'Include Monthly Dummies'){
+ x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
+ for (i in 1:11){
+ x2[seq(i,n,12),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> if (par2 == 'Include Quarterly Dummies'){
+ x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
+ for (i in 1:3){
+ x2[seq(i,n,4),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> k <- length(x[1,])
> if (par3 == 'Linear Trend'){
+ x <- cbind(x, c(1:n))
+ colnames(x)[k+1] <- 't'
+ }
> x
USrtCoffee M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 255.0 1 0 0 0 0 0 0 0 0 0 0 1
2 280.2 0 1 0 0 0 0 0 0 0 0 0 2
3 299.9 0 0 1 0 0 0 0 0 0 0 0 3
4 339.2 0 0 0 1 0 0 0 0 0 0 0 4
5 374.2 0 0 0 0 1 0 0 0 0 0 0 5
6 393.5 0 0 0 0 0 1 0 0 0 0 0 6
7 389.2 0 0 0 0 0 0 1 0 0 0 0 7
8 381.7 0 0 0 0 0 0 0 1 0 0 0 8
9 375.2 0 0 0 0 0 0 0 0 1 0 0 9
10 369.0 0 0 0 0 0 0 0 0 0 1 0 10
11 357.4 0 0 0 0 0 0 0 0 0 0 1 11
12 352.1 0 0 0 0 0 0 0 0 0 0 0 12
13 346.5 1 0 0 0 0 0 0 0 0 0 0 13
14 342.9 0 1 0 0 0 0 0 0 0 0 0 14
15 340.3 0 0 1 0 0 0 0 0 0 0 0 15
16 328.3 0 0 0 1 0 0 0 0 0 0 0 16
17 322.9 0 0 0 0 1 0 0 0 0 0 0 17
18 314.3 0 0 0 0 0 1 0 0 0 0 0 18
19 308.9 0 0 0 0 0 0 1 0 0 0 0 19
20 294.0 0 0 0 0 0 0 0 1 0 0 0 20
21 285.6 0 0 0 0 0 0 0 0 1 0 0 21
22 281.2 0 0 0 0 0 0 0 0 0 1 0 22
23 280.3 0 0 0 0 0 0 0 0 0 0 1 23
24 278.8 0 0 0 0 0 0 0 0 0 0 0 24
25 274.5 1 0 0 0 0 0 0 0 0 0 0 25
26 270.4 0 1 0 0 0 0 0 0 0 0 0 26
27 263.4 0 0 1 0 0 0 0 0 0 0 0 27
28 259.9 0 0 0 1 0 0 0 0 0 0 0 28
29 258.0 0 0 0 0 1 0 0 0 0 0 0 29
30 262.7 0 0 0 0 0 1 0 0 0 0 0 30
31 284.7 0 0 0 0 0 0 1 0 0 0 0 31
32 311.3 0 0 0 0 0 0 0 1 0 0 0 32
33 322.1 0 0 0 0 0 0 0 0 1 0 0 33
34 327.0 0 0 0 0 0 0 0 0 0 1 0 34
35 331.3 0 0 0 0 0 0 0 0 0 0 1 35
36 333.3 0 0 0 0 0 0 0 0 0 0 0 36
37 321.4 1 0 0 0 0 0 0 0 0 0 0 37
38 327.0 0 1 0 0 0 0 0 0 0 0 0 38
39 320.0 0 0 1 0 0 0 0 0 0 0 0 39
40 314.7 0 0 0 1 0 0 0 0 0 0 0 40
41 316.7 0 0 0 0 1 0 0 0 0 0 0 41
42 314.4 0 0 0 0 0 1 0 0 0 0 0 42
43 321.3 0 0 0 0 0 0 1 0 0 0 0 43
44 318.2 0 0 0 0 0 0 0 1 0 0 0 44
45 307.2 0 0 0 0 0 0 0 0 1 0 0 45
46 301.3 0 0 0 0 0 0 0 0 0 1 0 46
47 287.5 0 0 0 0 0 0 0 0 0 0 1 47
48 277.7 0 0 0 0 0 0 0 0 0 0 0 48
49 274.4 1 0 0 0 0 0 0 0 0 0 0 49
50 258.8 0 1 0 0 0 0 0 0 0 0 0 50
51 253.3 0 0 1 0 0 0 0 0 0 0 0 51
52 251.0 0 0 0 1 0 0 0 0 0 0 0 52
53 248.4 0 0 0 0 1 0 0 0 0 0 0 53
54 249.5 0 0 0 0 0 1 0 0 0 0 0 54
55 246.1 0 0 0 0 0 0 1 0 0 0 0 55
56 244.5 0 0 0 0 0 0 0 1 0 0 0 56
57 243.6 0 0 0 0 0 0 0 0 1 0 0 57
58 244.0 0 0 0 0 0 0 0 0 0 1 0 58
59 240.8 0 0 0 0 0 0 0 0 0 0 1 59
60 249.8 0 0 0 0 0 0 0 0 0 0 0 60
61 248.0 1 0 0 0 0 0 0 0 0 0 0 61
62 259.4 0 1 0 0 0 0 0 0 0 0 0 62
63 260.5 0 0 1 0 0 0 0 0 0 0 0 63
64 260.8 0 0 0 1 0 0 0 0 0 0 0 64
65 261.3 0 0 0 0 1 0 0 0 0 0 0 65
66 259.5 0 0 0 0 0 1 0 0 0 0 0 66
67 256.6 0 0 0 0 0 0 1 0 0 0 0 67
68 257.9 0 0 0 0 0 0 0 1 0 0 0 68
69 256.5 0 0 0 0 0 0 0 0 1 0 0 69
70 254.2 0 0 0 0 0 0 0 0 0 1 0 70
71 253.3 0 0 0 0 0 0 0 0 0 0 1 71
72 253.8 0 0 0 0 0 0 0 0 0 0 0 72
73 255.5 1 0 0 0 0 0 0 0 0 0 0 73
74 257.1 0 1 0 0 0 0 0 0 0 0 0 74
75 257.3 0 0 1 0 0 0 0 0 0 0 0 75
76 253.2 0 0 0 1 0 0 0 0 0 0 0 76
77 252.8 0 0 0 0 1 0 0 0 0 0 0 77
78 252.0 0 0 0 0 0 1 0 0 0 0 0 78
79 250.7 0 0 0 0 0 0 1 0 0 0 0 79
80 252.2 0 0 0 0 0 0 0 1 0 0 0 80
81 250.0 0 0 0 0 0 0 0 0 1 0 0 81
82 251.0 0 0 0 0 0 0 0 0 0 1 0 82
83 253.4 0 0 0 0 0 0 0 0 0 0 1 83
84 251.2 0 0 0 0 0 0 0 0 0 0 0 84
85 255.6 1 0 0 0 0 0 0 0 0 0 0 85
86 261.1 0 1 0 0 0 0 0 0 0 0 0 86
87 258.9 0 0 1 0 0 0 0 0 0 0 0 87
88 259.9 0 0 0 1 0 0 0 0 0 0 0 88
89 261.2 0 0 0 0 1 0 0 0 0 0 0 89
90 264.7 0 0 0 0 0 1 0 0 0 0 0 90
91 267.1 0 0 0 0 0 0 1 0 0 0 0 91
92 266.4 0 0 0 0 0 0 0 1 0 0 0 92
93 267.7 0 0 0 0 0 0 0 0 1 0 0 93
94 268.6 0 0 0 0 0 0 0 0 0 1 0 94
95 267.5 0 0 0 0 0 0 0 0 0 0 1 95
96 268.5 0 0 0 0 0 0 0 0 0 0 0 96
97 268.5 1 0 0 0 0 0 0 0 0 0 0 97
98 270.5 0 1 0 0 0 0 0 0 0 0 0 98
99 270.9 0 0 1 0 0 0 0 0 0 0 0 99
100 270.1 0 0 0 1 0 0 0 0 0 0 0 100
101 269.3 0 0 0 0 1 0 0 0 0 0 0 101
102 269.8 0 0 0 0 0 1 0 0 0 0 0 102
103 270.1 0 0 0 0 0 0 1 0 0 0 0 103
104 264.9 0 0 0 0 0 0 0 1 0 0 0 104
105 263.7 0 0 0 0 0 0 0 0 1 0 0 105
106 264.8 0 0 0 0 0 0 0 0 0 1 0 106
107 263.7 0 0 0 0 0 0 0 0 0 0 1 107
108 255.9 0 0 0 0 0 0 0 0 0 0 0 108
109 276.2 1 0 0 0 0 0 0 0 0 0 0 109
110 360.1 0 1 0 0 0 0 0 0 0 0 0 110
111 380.5 0 0 1 0 0 0 0 0 0 0 0 111
112 373.7 0 0 0 1 0 0 0 0 0 0 0 112
113 369.8 0 0 0 0 1 0 0 0 0 0 0 113
114 366.6 0 0 0 0 0 1 0 0 0 0 0 114
115 359.3 0 0 0 0 0 0 1 0 0 0 0 115
116 345.8 0 0 0 0 0 0 0 1 0 0 0 116
117 326.2 0 0 0 0 0 0 0 0 1 0 0 117
118 324.5 0 0 0 0 0 0 0 0 0 1 0 118
119 328.1 0 0 0 0 0 0 0 0 0 0 1 119
120 327.5 0 0 0 0 0 0 0 0 0 0 0 120
121 324.4 1 0 0 0 0 0 0 0 0 0 0 121
122 316.5 0 1 0 0 0 0 0 0 0 0 0 122
123 310.9 0 0 1 0 0 0 0 0 0 0 0 123
124 301.5 0 0 0 1 0 0 0 0 0 0 0 124
125 291.7 0 0 0 0 1 0 0 0 0 0 0 125
126 290.4 0 0 0 0 0 1 0 0 0 0 0 126
127 287.4 0 0 0 0 0 0 1 0 0 0 0 127
128 277.7 0 0 0 0 0 0 0 1 0 0 0 128
129 281.6 0 0 0 0 0 0 0 0 1 0 0 129
130 288.0 0 0 0 0 0 0 0 0 0 1 0 130
131 276.0 0 0 0 0 0 0 0 0 0 0 1 131
132 272.9 0 0 0 0 0 0 0 0 0 0 0 132
133 283.0 1 0 0 0 0 0 0 0 0 0 0 133
134 283.3 0 1 0 0 0 0 0 0 0 0 0 134
135 276.8 0 0 1 0 0 0 0 0 0 0 0 135
136 284.5 0 0 0 1 0 0 0 0 0 0 0 136
137 282.7 0 0 0 0 1 0 0 0 0 0 0 137
138 281.2 0 0 0 0 0 1 0 0 0 0 0 138
139 287.4 0 0 0 0 0 0 1 0 0 0 0 139
140 283.1 0 0 0 0 0 0 0 1 0 0 0 140
141 284.0 0 0 0 0 0 0 0 0 1 0 0 141
142 285.5 0 0 0 0 0 0 0 0 0 1 0 142
143 289.2 0 0 0 0 0 0 0 0 0 0 1 143
144 292.5 0 0 0 0 0 0 0 0 0 0 0 144
145 296.4 1 0 0 0 0 0 0 0 0 0 0 145
146 305.2 0 1 0 0 0 0 0 0 0 0 0 146
147 303.9 0 0 1 0 0 0 0 0 0 0 0 147
148 311.5 0 0 0 1 0 0 0 0 0 0 0 148
149 316.3 0 0 0 0 1 0 0 0 0 0 0 149
150 316.7 0 0 0 0 0 1 0 0 0 0 0 150
151 322.5 0 0 0 0 0 0 1 0 0 0 0 151
152 317.1 0 0 0 0 0 0 0 1 0 0 0 152
153 309.8 0 0 0 0 0 0 0 0 1 0 0 153
154 303.8 0 0 0 0 0 0 0 0 0 1 0 154
155 290.3 0 0 0 0 0 0 0 0 0 0 1 155
156 293.7 0 0 0 0 0 0 0 0 0 0 0 156
157 291.7 1 0 0 0 0 0 0 0 0 0 0 157
158 296.5 0 1 0 0 0 0 0 0 0 0 0 158
159 289.1 0 0 1 0 0 0 0 0 0 0 0 159
160 288.5 0 0 0 1 0 0 0 0 0 0 0 160
161 293.8 0 0 0 0 1 0 0 0 0 0 0 161
162 297.7 0 0 0 0 0 1 0 0 0 0 0 162
163 305.4 0 0 0 0 0 0 1 0 0 0 0 163
164 302.7 0 0 0 0 0 0 0 1 0 0 0 164
165 302.5 0 0 0 0 0 0 0 0 1 0 0 165
166 303.0 0 0 0 0 0 0 0 0 0 1 0 166
167 294.5 0 0 0 0 0 0 0 0 0 0 1 167
168 294.1 0 0 0 0 0 0 0 0 0 0 0 168
169 294.5 1 0 0 0 0 0 0 0 0 0 0 169
170 297.1 0 1 0 0 0 0 0 0 0 0 0 170
171 289.4 0 0 1 0 0 0 0 0 0 0 0 171
172 292.4 0 0 0 1 0 0 0 0 0 0 0 172
173 287.9 0 0 0 0 1 0 0 0 0 0 0 173
174 286.6 0 0 0 0 0 1 0 0 0 0 0 174
175 280.5 0 0 0 0 0 0 1 0 0 0 0 175
176 272.4 0 0 0 0 0 0 0 1 0 0 0 176
177 269.2 0 0 0 0 0 0 0 0 1 0 0 177
178 270.6 0 0 0 0 0 0 0 0 0 1 0 178
179 267.3 0 0 0 0 0 0 0 0 0 0 1 179
180 262.5 0 0 0 0 0 0 0 0 0 0 0 180
181 266.8 1 0 0 0 0 0 0 0 0 0 0 181
182 268.8 0 1 0 0 0 0 0 0 0 0 0 182
183 263.1 0 0 1 0 0 0 0 0 0 0 0 183
184 261.2 0 0 0 1 0 0 0 0 0 0 0 184
185 266.0 0 0 0 0 1 0 0 0 0 0 0 185
186 262.5 0 0 0 0 0 1 0 0 0 0 0 186
187 265.2 0 0 0 0 0 0 1 0 0 0 0 187
188 261.3 0 0 0 0 0 0 0 1 0 0 0 188
189 253.7 0 0 0 0 0 0 0 0 1 0 0 189
190 249.2 0 0 0 0 0 0 0 0 0 1 0 190
191 239.1 0 0 0 0 0 0 0 0 0 0 1 191
192 236.4 0 0 0 0 0 0 0 0 0 0 0 192
193 235.2 1 0 0 0 0 0 0 0 0 0 0 193
194 245.2 0 1 0 0 0 0 0 0 0 0 0 194
195 246.2 0 0 1 0 0 0 0 0 0 0 0 195
196 247.7 0 0 0 1 0 0 0 0 0 0 0 196
197 251.4 0 0 0 0 1 0 0 0 0 0 0 197
198 253.3 0 0 0 0 0 1 0 0 0 0 0 198
199 254.8 0 0 0 0 0 0 1 0 0 0 0 199
200 250.0 0 0 0 0 0 0 0 1 0 0 0 200
201 249.3 0 0 0 0 0 0 0 0 1 0 0 201
202 241.5 0 0 0 0 0 0 0 0 0 1 0 202
203 243.3 0 0 0 0 0 0 0 0 0 0 1 203
204 248.0 0 0 0 0 0 0 0 0 0 0 0 204
205 253.0 1 0 0 0 0 0 0 0 0 0 0 205
206 252.9 0 1 0 0 0 0 0 0 0 0 0 206
207 251.5 0 0 1 0 0 0 0 0 0 0 0 207
208 251.6 0 0 0 1 0 0 0 0 0 0 0 208
209 253.5 0 0 0 0 1 0 0 0 0 0 0 209
210 259.8 0 0 0 0 0 1 0 0 0 0 0 210
211 334.1 0 0 0 0 0 0 1 0 0 0 0 211
212 448.0 0 0 0 0 0 0 0 1 0 0 0 212
213 445.8 0 0 0 0 0 0 0 0 1 0 0 213
214 445.0 0 0 0 0 0 0 0 0 0 1 0 214
215 448.2 0 0 0 0 0 0 0 0 0 0 1 215
216 438.2 0 0 0 0 0 0 0 0 0 0 0 216
217 439.8 1 0 0 0 0 0 0 0 0 0 0 217
218 423.4 0 1 0 0 0 0 0 0 0 0 0 218
219 410.8 0 0 1 0 0 0 0 0 0 0 0 219
220 408.4 0 0 0 1 0 0 0 0 0 0 0 220
221 406.7 0 0 0 0 1 0 0 0 0 0 0 221
222 405.9 0 0 0 0 0 1 0 0 0 0 0 222
223 402.7 0 0 0 0 0 0 1 0 0 0 0 223
224 405.1 0 0 0 0 0 0 0 1 0 0 0 224
225 399.6 0 0 0 0 0 0 0 0 1 0 0 225
226 386.5 0 0 0 0 0 0 0 0 0 1 0 226
227 381.4 0 0 0 0 0 0 0 0 0 0 1 227
228 375.2 0 0 0 0 0 0 0 0 0 0 0 228
229 357.7 1 0 0 0 0 0 0 0 0 0 0 229
230 359.0 0 1 0 0 0 0 0 0 0 0 0 230
231 355.0 0 0 1 0 0 0 0 0 0 0 0 231
232 352.7 0 0 0 1 0 0 0 0 0 0 0 232
233 344.4 0 0 0 0 1 0 0 0 0 0 0 233
234 343.8 0 0 0 0 0 1 0 0 0 0 0 234
235 338.0 0 0 0 0 0 0 1 0 0 0 0 235
236 339.0 0 0 0 0 0 0 0 1 0 0 0 236
237 333.3 0 0 0 0 0 0 0 0 1 0 0 237
238 334.4 0 0 0 0 0 0 0 0 0 1 0 238
239 328.3 0 0 0 0 0 0 0 0 0 0 1 239
240 330.7 0 0 0 0 0 0 0 0 0 0 0 240
241 330.0 1 0 0 0 0 0 0 0 0 0 0 241
242 331.6 0 1 0 0 0 0 0 0 0 0 0 242
243 351.2 0 0 1 0 0 0 0 0 0 0 0 243
244 389.4 0 0 0 1 0 0 0 0 0 0 0 244
245 410.9 0 0 0 0 1 0 0 0 0 0 0 245
246 442.8 0 0 0 0 0 1 0 0 0 0 0 246
247 462.8 0 0 0 0 0 0 1 0 0 0 0 247
248 466.9 0 0 0 0 0 0 0 1 0 0 0 248
249 461.7 0 0 0 0 0 0 0 0 1 0 0 249
250 439.2 0 0 0 0 0 0 0 0 0 1 0 250
251 430.3 0 0 0 0 0 0 0 0 0 0 1 251
252 416.1 0 0 0 0 0 0 0 0 0 0 0 252
253 402.5 1 0 0 0 0 0 0 0 0 0 0 253
254 397.3 0 1 0 0 0 0 0 0 0 0 0 254
255 403.3 0 0 1 0 0 0 0 0 0 0 0 255
256 395.9 0 0 0 1 0 0 0 0 0 0 0 256
257 387.8 0 0 0 0 1 0 0 0 0 0 0 257
258 378.6 0 0 0 0 0 1 0 0 0 0 0 258
259 377.1 0 0 0 0 0 0 1 0 0 0 0 259
260 370.4 0 0 0 0 0 0 0 1 0 0 0 260
261 362.0 0 0 0 0 0 0 0 0 1 0 0 261
262 350.3 0 0 0 0 0 0 0 0 0 1 0 262
263 348.2 0 0 0 0 0 0 0 0 0 0 1 263
264 344.6 0 0 0 0 0 0 0 0 0 0 0 264
265 343.5 1 0 0 0 0 0 0 0 0 0 0 265
266 342.8 0 1 0 0 0 0 0 0 0 0 0 266
267 347.6 0 0 1 0 0 0 0 0 0 0 0 267
268 346.6 0 0 0 1 0 0 0 0 0 0 0 268
269 349.5 0 0 0 0 1 0 0 0 0 0 0 269
270 342.1 0 0 0 0 0 1 0 0 0 0 0 270
271 342.0 0 0 0 0 0 0 1 0 0 0 0 271
272 342.8 0 0 0 0 0 0 0 1 0 0 0 272
273 339.3 0 0 0 0 0 0 0 0 1 0 0 273
274 348.2 0 0 0 0 0 0 0 0 0 1 0 274
275 333.7 0 0 0 0 0 0 0 0 0 0 1 275
276 334.7 0 0 0 0 0 0 0 0 0 0 0 276
277 354.0 1 0 0 0 0 0 0 0 0 0 0 277
278 367.7 0 1 0 0 0 0 0 0 0 0 0 278
279 363.3 0 0 1 0 0 0 0 0 0 0 0 279
280 358.4 0 0 0 1 0 0 0 0 0 0 0 280
281 353.1 0 0 0 0 1 0 0 0 0 0 0 281
282 343.1 0 0 0 0 0 1 0 0 0 0 0 282
283 344.6 0 0 0 0 0 0 1 0 0 0 0 283
284 344.4 0 0 0 0 0 0 0 1 0 0 0 284
285 333.9 0 0 0 0 0 0 0 0 1 0 0 285
286 331.7 0 0 0 0 0 0 0 0 0 1 0 286
287 324.3 0 0 0 0 0 0 0 0 0 0 1 287
288 321.2 0 0 0 0 0 0 0 0 0 0 0 288
289 322.4 1 0 0 0 0 0 0 0 0 0 0 289
290 321.7 0 1 0 0 0 0 0 0 0 0 0 290
291 320.5 0 0 1 0 0 0 0 0 0 0 0 291
292 312.8 0 0 0 1 0 0 0 0 0 0 0 292
293 309.7 0 0 0 0 1 0 0 0 0 0 0 293
294 315.6 0 0 0 0 0 1 0 0 0 0 0 294
295 309.7 0 0 0 0 0 0 1 0 0 0 0 295
296 304.6 0 0 0 0 0 0 0 1 0 0 0 296
297 302.5 0 0 0 0 0 0 0 0 1 0 0 297
298 301.5 0 0 0 0 0 0 0 0 0 1 0 298
299 298.8 0 0 0 0 0 0 0 0 0 0 1 299
300 291.3 0 0 0 0 0 0 0 0 0 0 0 300
301 293.6 1 0 0 0 0 0 0 0 0 0 0 301
302 294.6 0 1 0 0 0 0 0 0 0 0 0 302
303 285.9 0 0 1 0 0 0 0 0 0 0 0 303
304 297.6 0 0 0 1 0 0 0 0 0 0 0 304
305 301.1 0 0 0 0 1 0 0 0 0 0 0 305
306 293.8 0 0 0 0 0 1 0 0 0 0 0 306
307 297.7 0 0 0 0 0 0 1 0 0 0 0 307
308 292.9 0 0 0 0 0 0 0 1 0 0 0 308
309 292.1 0 0 0 0 0 0 0 0 1 0 0 309
310 287.2 0 0 0 0 0 0 0 0 0 1 0 310
311 288.2 0 0 0 0 0 0 0 0 0 0 1 311
312 283.8 0 0 0 0 0 0 0 0 0 0 0 312
313 299.9 1 0 0 0 0 0 0 0 0 0 0 313
314 292.4 0 1 0 0 0 0 0 0 0 0 0 314
315 293.3 0 0 1 0 0 0 0 0 0 0 0 315
316 300.8 0 0 0 1 0 0 0 0 0 0 0 316
317 293.7 0 0 0 0 1 0 0 0 0 0 0 317
318 293.1 0 0 0 0 0 1 0 0 0 0 0 318
319 294.4 0 0 0 0 0 0 1 0 0 0 0 319
320 292.1 0 0 0 0 0 0 0 1 0 0 0 320
321 291.9 0 0 0 0 0 0 0 0 1 0 0 321
322 282.5 0 0 0 0 0 0 0 0 0 1 0 322
323 277.9 0 0 0 0 0 0 0 0 0 0 1 323
324 287.5 0 0 0 0 0 0 0 0 0 0 0 324
325 289.2 1 0 0 0 0 0 0 0 0 0 0 325
326 285.6 0 1 0 0 0 0 0 0 0 0 0 326
327 293.2 0 0 1 0 0 0 0 0 0 0 0 327
328 290.8 0 0 0 1 0 0 0 0 0 0 0 328
329 283.1 0 0 0 0 1 0 0 0 0 0 0 329
330 275.0 0 0 0 0 0 1 0 0 0 0 0 330
331 287.8 0 0 0 0 0 0 1 0 0 0 0 331
332 287.8 0 0 0 0 0 0 0 1 0 0 0 332
333 287.4 0 0 0 0 0 0 0 0 1 0 0 333
334 284.0 0 0 0 0 0 0 0 0 0 1 0 334
335 277.8 0 0 0 0 0 0 0 0 0 0 1 335
336 277.6 0 0 0 0 0 0 0 0 0 0 0 336
337 304.9 1 0 0 0 0 0 0 0 0 0 0 337
338 294.0 0 1 0 0 0 0 0 0 0 0 0 338
339 300.9 0 0 1 0 0 0 0 0 0 0 0 339
340 324.0 0 0 0 1 0 0 0 0 0 0 0 340
341 332.9 0 0 0 0 1 0 0 0 0 0 0 341
342 341.6 0 0 0 0 0 1 0 0 0 0 0 342
343 333.4 0 0 0 0 0 0 1 0 0 0 0 343
344 348.2 0 0 0 0 0 0 0 1 0 0 0 344
345 344.7 0 0 0 0 0 0 0 0 1 0 0 345
346 344.7 0 0 0 0 0 0 0 0 0 1 0 346
347 329.3 0 0 0 0 0 0 0 0 0 0 1 347
348 323.5 0 0 0 0 0 0 0 0 0 0 0 348
349 323.2 1 0 0 0 0 0 0 0 0 0 0 349
350 317.4 0 1 0 0 0 0 0 0 0 0 0 350
351 330.1 0 0 1 0 0 0 0 0 0 0 0 351
352 329.2 0 0 0 1 0 0 0 0 0 0 0 352
353 334.9 0 0 0 0 1 0 0 0 0 0 0 353
354 315.8 0 0 0 0 0 1 0 0 0 0 0 354
355 315.4 0 0 0 0 0 0 1 0 0 0 0 355
356 319.6 0 0 0 0 0 0 0 1 0 0 0 356
357 317.3 0 0 0 0 0 0 0 0 1 0 0 357
358 313.8 0 0 0 0 0 0 0 0 0 1 0 358
359 315.8 0 0 0 0 0 0 0 0 0 0 1 359
360 311.3 0 0 0 0 0 0 0 0 0 0 0 360
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) M1 M2 M3 M4 M5
278.270 1.348 4.523 4.741 6.786 7.634
M6 M7 M8 M9 M10 M11
7.525 11.076 13.148 9.563 6.657 2.159
t
0.132
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-70.08 -35.06 -11.63 24.50 142.76
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 278.26957 9.80471 28.381 < 2e-16 ***
M1 1.34818 12.32030 0.109 0.913
M2 4.52289 12.31980 0.367 0.714
M3 4.74093 12.31935 0.385 0.701
M4 6.78565 12.31895 0.551 0.582
M5 7.63369 12.31859 0.620 0.536
M6 7.52507 12.31828 0.611 0.542
M7 11.07645 12.31802 0.899 0.369
M8 13.14782 12.31781 1.067 0.287
M9 9.56253 12.31764 0.776 0.438
M10 6.65724 12.31752 0.540 0.589
M11 2.15862 12.31745 0.175 0.861
t 0.13196 0.02421 5.451 9.52e-08 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 47.71 on 347 degrees of freedom
Multiple R-squared: 0.08448, Adjusted R-squared: 0.05282
F-statistic: 2.668 on 12 and 347 DF, p-value: 0.001926
> 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,] 2.774425e-01 5.548851e-01 7.225575e-01
[2,] 4.607027e-01 9.214055e-01 5.392973e-01
[3,] 6.190931e-01 7.618137e-01 3.809069e-01
[4,] 6.681124e-01 6.637751e-01 3.318876e-01
[5,] 6.929066e-01 6.141869e-01 3.070934e-01
[6,] 6.938572e-01 6.122856e-01 3.061428e-01
[7,] 6.736880e-01 6.526240e-01 3.263120e-01
[8,] 6.240787e-01 7.518425e-01 3.759213e-01
[9,] 5.635937e-01 8.728125e-01 4.364063e-01
[10,] 4.940889e-01 9.881779e-01 5.059111e-01
[11,] 4.118553e-01 8.237106e-01 5.881447e-01
[12,] 3.356473e-01 6.712946e-01 6.643527e-01
[13,] 2.776954e-01 5.553907e-01 7.223046e-01
[14,] 2.421757e-01 4.843513e-01 7.578243e-01
[15,] 2.062409e-01 4.124817e-01 7.937591e-01
[16,] 1.574986e-01 3.149973e-01 8.425014e-01
[17,] 1.322858e-01 2.645717e-01 8.677142e-01
[18,] 1.264646e-01 2.529293e-01 8.735354e-01
[19,] 1.296003e-01 2.592005e-01 8.703997e-01
[20,] 1.428708e-01 2.857415e-01 8.571292e-01
[21,] 1.588205e-01 3.176409e-01 8.411795e-01
[22,] 2.227233e-01 4.454465e-01 7.772767e-01
[23,] 2.677295e-01 5.354590e-01 7.322705e-01
[24,] 2.741294e-01 5.482588e-01 7.258706e-01
[25,] 2.519687e-01 5.039374e-01 7.480313e-01
[26,] 2.215324e-01 4.430647e-01 7.784676e-01
[27,] 1.877457e-01 3.754913e-01 8.122543e-01
[28,] 1.588831e-01 3.177661e-01 8.411169e-01
[29,] 1.308846e-01 2.617693e-01 8.691154e-01
[30,] 1.045563e-01 2.091126e-01 8.954437e-01
[31,] 8.226208e-02 1.645242e-01 9.177379e-01
[32,] 6.443682e-02 1.288736e-01 9.355632e-01
[33,] 5.098617e-02 1.019723e-01 9.490138e-01
[34,] 3.860906e-02 7.721812e-02 9.613909e-01
[35,] 2.951795e-02 5.903591e-02 9.704820e-01
[36,] 2.292876e-02 4.585751e-02 9.770712e-01
[37,] 1.833501e-02 3.667001e-02 9.816650e-01
[38,] 1.565585e-02 3.131170e-02 9.843441e-01
[39,] 1.336501e-02 2.673001e-02 9.866350e-01
[40,] 1.223899e-02 2.447799e-02 9.877610e-01
[41,] 1.123301e-02 2.246601e-02 9.887670e-01
[42,] 9.778614e-03 1.955723e-02 9.902214e-01
[43,] 8.102296e-03 1.620459e-02 9.918977e-01
[44,] 6.496760e-03 1.299352e-02 9.935032e-01
[45,] 4.740671e-03 9.481342e-03 9.952593e-01
[46,] 3.434021e-03 6.868042e-03 9.965660e-01
[47,] 2.576579e-03 5.153159e-03 9.974234e-01
[48,] 1.928289e-03 3.856579e-03 9.980717e-01
[49,] 1.398961e-03 2.797922e-03 9.986010e-01
[50,] 9.783207e-04 1.956641e-03 9.990217e-01
[51,] 6.678218e-04 1.335644e-03 9.993322e-01
[52,] 4.518170e-04 9.036340e-04 9.995482e-01
[53,] 3.037584e-04 6.075169e-04 9.996962e-01
[54,] 2.022684e-04 4.045367e-04 9.997977e-01
[55,] 1.334491e-04 2.668981e-04 9.998666e-01
[56,] 8.770281e-05 1.754056e-04 9.999123e-01
[57,] 5.726521e-05 1.145304e-04 9.999427e-01
[58,] 4.542274e-05 9.084548e-05 9.999546e-01
[59,] 3.467567e-05 6.935134e-05 9.999653e-01
[60,] 2.618226e-05 5.236451e-05 9.999738e-01
[61,] 1.830097e-05 3.660195e-05 9.999817e-01
[62,] 1.221039e-05 2.442077e-05 9.999878e-01
[63,] 7.964296e-06 1.592859e-05 9.999920e-01
[64,] 5.160749e-06 1.032150e-05 9.999948e-01
[65,] 3.352639e-06 6.705278e-06 9.999966e-01
[66,] 2.164616e-06 4.329232e-06 9.999978e-01
[67,] 1.397206e-06 2.794412e-06 9.999986e-01
[68,] 9.275784e-07 1.855157e-06 9.999991e-01
[69,] 6.034091e-07 1.206818e-06 9.999994e-01
[70,] 5.280321e-07 1.056064e-06 9.999995e-01
[71,] 4.714904e-07 9.429808e-07 9.999995e-01
[72,] 3.956192e-07 7.912384e-07 9.999996e-01
[73,] 3.213805e-07 6.427611e-07 9.999997e-01
[74,] 2.447167e-07 4.894333e-07 9.999998e-01
[75,] 1.873072e-07 3.746144e-07 9.999998e-01
[76,] 1.436636e-07 2.873272e-07 9.999999e-01
[77,] 1.079696e-07 2.159392e-07 9.999999e-01
[78,] 8.455587e-08 1.691117e-07 9.999999e-01
[79,] 6.776799e-08 1.355360e-07 9.999999e-01
[80,] 5.531619e-08 1.106324e-07 9.999999e-01
[81,] 4.584380e-08 9.168760e-08 1.000000e+00
[82,] 5.050545e-08 1.010109e-07 9.999999e-01
[83,] 5.167163e-08 1.033433e-07 9.999999e-01
[84,] 5.198902e-08 1.039780e-07 9.999999e-01
[85,] 4.825098e-08 9.650196e-08 1.000000e+00
[86,] 4.015328e-08 8.030655e-08 1.000000e+00
[87,] 3.194661e-08 6.389322e-08 1.000000e+00
[88,] 2.480103e-08 4.960206e-08 1.000000e+00
[89,] 1.822330e-08 3.644659e-08 1.000000e+00
[90,] 1.334978e-08 2.669956e-08 1.000000e+00
[91,] 9.884828e-09 1.976966e-08 1.000000e+00
[92,] 7.373944e-09 1.474789e-08 1.000000e+00
[93,] 5.096589e-09 1.019318e-08 1.000000e+00
[94,] 6.054535e-09 1.210907e-08 1.000000e+00
[95,] 2.948985e-07 5.897970e-07 9.999997e-01
[96,] 1.561781e-05 3.123563e-05 9.999844e-01
[97,] 1.827509e-04 3.655017e-04 9.998172e-01
[98,] 9.332019e-04 1.866404e-03 9.990668e-01
[99,] 2.960550e-03 5.921100e-03 9.970394e-01
[100,] 6.162055e-03 1.232411e-02 9.938379e-01
[101,] 9.047130e-03 1.809426e-02 9.909529e-01
[102,] 1.011154e-02 2.022308e-02 9.898885e-01
[103,] 1.102807e-02 2.205614e-02 9.889719e-01
[104,] 1.269560e-02 2.539120e-02 9.873044e-01
[105,] 1.446700e-02 2.893399e-02 9.855330e-01
[106,] 1.622816e-02 3.245632e-02 9.837718e-01
[107,] 1.532614e-02 3.065227e-02 9.846739e-01
[108,] 1.370846e-02 2.741692e-02 9.862915e-01
[109,] 1.160013e-02 2.320026e-02 9.883999e-01
[110,] 9.444112e-03 1.888822e-02 9.905559e-01
[111,] 7.612216e-03 1.522443e-02 9.923878e-01
[112,] 6.115364e-03 1.223073e-02 9.938846e-01
[113,] 4.980996e-03 9.961991e-03 9.950190e-01
[114,] 4.004840e-03 8.009679e-03 9.959952e-01
[115,] 3.203180e-03 6.406361e-03 9.967968e-01
[116,] 2.532960e-03 5.065920e-03 9.974670e-01
[117,] 1.994707e-03 3.989414e-03 9.980053e-01
[118,] 1.588474e-03 3.176947e-03 9.984115e-01
[119,] 1.232448e-03 2.464896e-03 9.987676e-01
[120,] 9.565416e-04 1.913083e-03 9.990435e-01
[121,] 7.382720e-04 1.476544e-03 9.992617e-01
[122,] 5.677355e-04 1.135471e-03 9.994323e-01
[123,] 4.348414e-04 8.696828e-04 9.995652e-01
[124,] 3.332290e-04 6.664579e-04 9.996668e-01
[125,] 2.596727e-04 5.193454e-04 9.997403e-01
[126,] 2.006444e-04 4.012887e-04 9.997994e-01
[127,] 1.531165e-04 3.062330e-04 9.998469e-01
[128,] 1.169268e-04 2.338536e-04 9.998831e-01
[129,] 9.010980e-05 1.802196e-04 9.999099e-01
[130,] 7.177791e-05 1.435558e-04 9.999282e-01
[131,] 5.647552e-05 1.129510e-04 9.999435e-01
[132,] 4.367639e-05 8.735279e-05 9.999563e-01
[133,] 3.519332e-05 7.038664e-05 9.999648e-01
[134,] 2.900827e-05 5.801654e-05 9.999710e-01
[135,] 2.364695e-05 4.729389e-05 9.999764e-01
[136,] 1.995247e-05 3.990494e-05 9.999800e-01
[137,] 1.629796e-05 3.259592e-05 9.999837e-01
[138,] 1.280024e-05 2.560048e-05 9.999872e-01
[139,] 9.645407e-06 1.929081e-05 9.999904e-01
[140,] 6.970113e-06 1.394023e-05 9.999930e-01
[141,] 5.045565e-06 1.009113e-05 9.999950e-01
[142,] 3.668258e-06 7.336516e-06 9.999963e-01
[143,] 2.588456e-06 5.176912e-06 9.999974e-01
[144,] 1.813401e-06 3.626802e-06 9.999982e-01
[145,] 1.276054e-06 2.552109e-06 9.999987e-01
[146,] 8.884662e-07 1.776932e-06 9.999991e-01
[147,] 6.141506e-07 1.228301e-06 9.999994e-01
[148,] 4.306587e-07 8.613173e-07 9.999996e-01
[149,] 3.070531e-07 6.141062e-07 9.999997e-01
[150,] 2.191342e-07 4.382684e-07 9.999998e-01
[151,] 1.549783e-07 3.099565e-07 9.999998e-01
[152,] 1.072218e-07 2.144435e-07 9.999999e-01
[153,] 7.352848e-08 1.470570e-07 9.999999e-01
[154,] 5.113681e-08 1.022736e-07 9.999999e-01
[155,] 3.423215e-08 6.846430e-08 1.000000e+00
[156,] 2.306099e-08 4.612199e-08 1.000000e+00
[157,] 1.555620e-08 3.111239e-08 1.000000e+00
[158,] 1.064727e-08 2.129455e-08 1.000000e+00
[159,] 7.306386e-09 1.461277e-08 1.000000e+00
[160,] 5.449457e-09 1.089891e-08 1.000000e+00
[161,] 4.681752e-09 9.363505e-09 1.000000e+00
[162,] 4.044161e-09 8.088323e-09 1.000000e+00
[163,] 3.314988e-09 6.629976e-09 1.000000e+00
[164,] 2.698702e-09 5.397403e-09 1.000000e+00
[165,] 2.294499e-09 4.588997e-09 1.000000e+00
[166,] 1.897195e-09 3.794389e-09 1.000000e+00
[167,] 1.576159e-09 3.152318e-09 1.000000e+00
[168,] 1.458434e-09 2.916868e-09 1.000000e+00
[169,] 1.478756e-09 2.957511e-09 1.000000e+00
[170,] 1.419329e-09 2.838657e-09 1.000000e+00
[171,] 1.472624e-09 2.945247e-09 1.000000e+00
[172,] 1.607664e-09 3.215329e-09 1.000000e+00
[173,] 2.124243e-09 4.248486e-09 1.000000e+00
[174,] 3.193563e-09 6.387126e-09 1.000000e+00
[175,] 5.127847e-09 1.025569e-08 1.000000e+00
[176,] 9.994541e-09 1.998908e-08 1.000000e+00
[177,] 2.060566e-08 4.121132e-08 1.000000e+00
[178,] 4.716540e-08 9.433081e-08 1.000000e+00
[179,] 8.845467e-08 1.769093e-07 9.999999e-01
[180,] 1.725165e-07 3.450329e-07 9.999998e-01
[181,] 3.655627e-07 7.311254e-07 9.999996e-01
[182,] 7.514823e-07 1.502965e-06 9.999992e-01
[183,] 1.533530e-06 3.067060e-06 9.999985e-01
[184,] 3.637682e-06 7.275364e-06 9.999964e-01
[185,] 1.239901e-05 2.479802e-05 9.999876e-01
[186,] 4.152958e-05 8.305915e-05 9.999585e-01
[187,] 1.638409e-04 3.276819e-04 9.998362e-01
[188,] 5.655009e-04 1.131002e-03 9.994345e-01
[189,] 1.681337e-03 3.362675e-03 9.983187e-01
[190,] 4.690818e-03 9.381636e-03 9.953092e-01
[191,] 1.281718e-02 2.563436e-02 9.871828e-01
[192,] 3.693071e-02 7.386141e-02 9.630693e-01
[193,] 1.075015e-01 2.150031e-01 8.924985e-01
[194,] 2.676631e-01 5.353261e-01 7.323369e-01
[195,] 5.087243e-01 9.825513e-01 4.912757e-01
[196,] 5.928099e-01 8.143802e-01 4.071901e-01
[197,] 8.391862e-01 3.216275e-01 1.608138e-01
[198,] 9.509814e-01 9.803712e-02 4.901856e-02
[199,] 9.878797e-01 2.424059e-02 1.212030e-02
[200,] 9.979240e-01 4.151986e-03 2.075993e-03
[201,] 9.995843e-01 8.314095e-04 4.157047e-04
[202,] 9.999267e-01 1.466434e-04 7.332172e-05
[203,] 9.999755e-01 4.899850e-05 2.449925e-05
[204,] 9.999878e-01 2.449809e-05 1.224904e-05
[205,] 9.999929e-01 1.418180e-05 7.090900e-06
[206,] 9.999955e-01 9.038625e-06 4.519312e-06
[207,] 9.999970e-01 6.070555e-06 3.035278e-06
[208,] 9.999976e-01 4.804745e-06 2.402373e-06
[209,] 9.999981e-01 3.890025e-06 1.945012e-06
[210,] 9.999983e-01 3.343384e-06 1.671692e-06
[211,] 9.999983e-01 3.423958e-06 1.711979e-06
[212,] 9.999982e-01 3.601101e-06 1.800550e-06
[213,] 9.999980e-01 4.029248e-06 2.014624e-06
[214,] 9.999975e-01 4.983604e-06 2.491802e-06
[215,] 9.999968e-01 6.424078e-06 3.212039e-06
[216,] 9.999960e-01 8.030667e-06 4.015334e-06
[217,] 9.999952e-01 9.515317e-06 4.757658e-06
[218,] 9.999948e-01 1.042511e-05 5.212553e-06
[219,] 9.999943e-01 1.149235e-05 5.746175e-06
[220,] 9.999943e-01 1.134568e-05 5.672842e-06
[221,] 9.999944e-01 1.110114e-05 5.550569e-06
[222,] 9.999949e-01 1.025746e-05 5.128729e-06
[223,] 9.999949e-01 1.024418e-05 5.122088e-06
[224,] 9.999950e-01 9.993565e-06 4.996782e-06
[225,] 9.999948e-01 1.042287e-05 5.211435e-06
[226,] 9.999949e-01 1.023377e-05 5.116884e-06
[227,] 9.999947e-01 1.058546e-05 5.292729e-06
[228,] 9.999935e-01 1.296255e-05 6.481273e-06
[229,] 9.999925e-01 1.509416e-05 7.547081e-06
[230,] 9.999936e-01 1.281431e-05 6.407157e-06
[231,] 9.999981e-01 3.751684e-06 1.875842e-06
[232,] 9.999998e-01 3.813217e-07 1.906609e-07
[233,] 1.000000e+00 2.090661e-08 1.045330e-08
[234,] 1.000000e+00 7.274247e-10 3.637123e-10
[235,] 1.000000e+00 6.355151e-11 3.177576e-11
[236,] 1.000000e+00 4.830517e-12 2.415258e-12
[237,] 1.000000e+00 6.315570e-13 3.157785e-13
[238,] 1.000000e+00 2.213899e-13 1.106950e-13
[239,] 1.000000e+00 8.864623e-14 4.432311e-14
[240,] 1.000000e+00 2.367873e-14 1.183937e-14
[241,] 1.000000e+00 1.080686e-14 5.403428e-15
[242,] 1.000000e+00 7.131759e-15 3.565880e-15
[243,] 1.000000e+00 5.699186e-15 2.849593e-15
[244,] 1.000000e+00 4.804036e-15 2.402018e-15
[245,] 1.000000e+00 5.476294e-15 2.738147e-15
[246,] 1.000000e+00 7.441229e-15 3.720614e-15
[247,] 1.000000e+00 1.326848e-14 6.634239e-15
[248,] 1.000000e+00 2.086480e-14 1.043240e-14
[249,] 1.000000e+00 3.367052e-14 1.683526e-14
[250,] 1.000000e+00 6.439866e-14 3.219933e-14
[251,] 1.000000e+00 1.186995e-13 5.934973e-14
[252,] 1.000000e+00 2.015507e-13 1.007753e-13
[253,] 1.000000e+00 3.750533e-13 1.875266e-13
[254,] 1.000000e+00 6.334600e-13 3.167300e-13
[255,] 1.000000e+00 1.127356e-12 5.636780e-13
[256,] 1.000000e+00 2.002568e-12 1.001284e-12
[257,] 1.000000e+00 3.503120e-12 1.751560e-12
[258,] 1.000000e+00 6.110342e-12 3.055171e-12
[259,] 1.000000e+00 7.266199e-12 3.633099e-12
[260,] 1.000000e+00 1.130355e-11 5.651777e-12
[261,] 1.000000e+00 1.550563e-11 7.752813e-12
[262,] 1.000000e+00 1.148500e-11 5.742501e-12
[263,] 1.000000e+00 2.200491e-12 1.100246e-12
[264,] 1.000000e+00 5.334519e-13 2.667259e-13
[265,] 1.000000e+00 2.121291e-13 1.060645e-13
[266,] 1.000000e+00 1.008863e-13 5.044316e-14
[267,] 1.000000e+00 6.351251e-14 3.175625e-14
[268,] 1.000000e+00 3.157192e-14 1.578596e-14
[269,] 1.000000e+00 1.404221e-14 7.021106e-15
[270,] 1.000000e+00 1.004153e-14 5.020765e-15
[271,] 1.000000e+00 5.405460e-15 2.702730e-15
[272,] 1.000000e+00 3.015674e-15 1.507837e-15
[273,] 1.000000e+00 1.450515e-15 7.252577e-16
[274,] 1.000000e+00 1.102638e-15 5.513191e-16
[275,] 1.000000e+00 4.636422e-16 2.318211e-16
[276,] 1.000000e+00 2.506118e-16 1.253059e-16
[277,] 1.000000e+00 3.823141e-16 1.911571e-16
[278,] 1.000000e+00 6.755058e-16 3.377529e-16
[279,] 1.000000e+00 5.220336e-16 2.610168e-16
[280,] 1.000000e+00 6.369047e-16 3.184524e-16
[281,] 1.000000e+00 1.124689e-15 5.623446e-16
[282,] 1.000000e+00 1.976590e-15 9.882951e-16
[283,] 1.000000e+00 2.699096e-15 1.349548e-15
[284,] 1.000000e+00 2.897993e-15 1.448996e-15
[285,] 1.000000e+00 4.348788e-15 2.174394e-15
[286,] 1.000000e+00 1.042898e-14 5.214491e-15
[287,] 1.000000e+00 1.633381e-14 8.166903e-15
[288,] 1.000000e+00 4.498478e-14 2.249239e-14
[289,] 1.000000e+00 1.120764e-13 5.603819e-14
[290,] 1.000000e+00 2.401353e-13 1.200676e-13
[291,] 1.000000e+00 5.419722e-13 2.709861e-13
[292,] 1.000000e+00 1.063007e-12 5.315037e-13
[293,] 1.000000e+00 2.739908e-12 1.369954e-12
[294,] 1.000000e+00 6.855993e-12 3.427997e-12
[295,] 1.000000e+00 1.708622e-11 8.543108e-12
[296,] 1.000000e+00 3.218463e-11 1.609231e-11
[297,] 1.000000e+00 6.849777e-11 3.424889e-11
[298,] 1.000000e+00 1.236335e-10 6.181674e-11
[299,] 1.000000e+00 2.152373e-10 1.076186e-10
[300,] 1.000000e+00 5.057273e-10 2.528636e-10
[301,] 1.000000e+00 1.129611e-09 5.648056e-10
[302,] 1.000000e+00 3.086332e-09 1.543166e-09
[303,] 1.000000e+00 7.313958e-09 3.656979e-09
[304,] 1.000000e+00 1.680230e-08 8.401152e-09
[305,] 1.000000e+00 4.478003e-08 2.239001e-08
[306,] 9.999999e-01 1.147362e-07 5.736808e-08
[307,] 9.999998e-01 3.054858e-07 1.527429e-07
[308,] 9.999996e-01 7.930910e-07 3.965455e-07
[309,] 9.999992e-01 1.571929e-06 7.859643e-07
[310,] 9.999980e-01 4.096355e-06 2.048177e-06
[311,] 9.999950e-01 1.005875e-05 5.029377e-06
[312,] 9.999876e-01 2.484833e-05 1.242417e-05
[313,] 9.999710e-01 5.800552e-05 2.900276e-05
[314,] 9.999537e-01 9.257767e-05 4.628883e-05
[315,] 9.999400e-01 1.199303e-04 5.996516e-05
[316,] 9.998755e-01 2.489723e-04 1.244862e-04
[317,] 9.998166e-01 3.668062e-04 1.834031e-04
[318,] 9.997391e-01 5.217132e-04 2.608566e-04
[319,] 9.997222e-01 5.555460e-04 2.777730e-04
[320,] 9.998090e-01 3.820567e-04 1.910283e-04
[321,] 9.999313e-01 1.373870e-04 6.869348e-05
[322,] 9.998804e-01 2.391970e-04 1.195985e-04
[323,] 9.998826e-01 2.348489e-04 1.174245e-04
[324,] 9.999829e-01 3.414573e-05 1.707287e-05
[325,] 9.999819e-01 3.626703e-05 1.813351e-05
[326,] 9.999920e-01 1.600230e-05 8.001151e-06
[327,] 9.999315e-01 1.370657e-04 6.853287e-05
[328,] 9.994503e-01 1.099408e-03 5.497041e-04
[329,] 9.964028e-01 7.194359e-03 3.597180e-03
> postscript(file="/var/wessaorg/rcomp/tmp/1ds1g1355853062.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/23cme1355853062.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/3x1k81355853062.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/4mk631355853062.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/5xw581355853062.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$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
-24.74970430 -2.85637097 16.49362903 53.61696237 87.63696237 106.91362903
7 8 9 10 11 12
98.93029570 89.22696237 86.18029570 82.75362903 75.52029570 72.24696237
13 14 15 16 17 18
65.16682703 58.26016036 55.31016036 41.13349370 34.75349370 26.13016036
19 20 21 22 23 24
17.04682703 -0.05650630 -5.00317297 -6.62983964 -3.16317297 -2.63650630
25 26 27 28 29 30
-8.41664164 -15.82330831 -23.17330831 -28.84997497 -31.72997497 -27.05330831
31 32 33 34 35 36
-8.73664164 15.66002503 29.91335836 37.58669169 46.25335836 50.28002503
37 38 39 40 41 42
36.89988969 39.19322303 31.84322303 24.36655636 25.38655636 23.06322303
43 44 45 46 47 48
26.27988969 20.97655636 13.42988969 10.30322303 0.86988969 -6.90344364
49 50 51 52 53 54
-11.68357898 -30.59024564 -36.44024564 -40.91691231 -44.49691231 -43.42024564
55 56 57 58 59 60
-50.50357898 -54.30691231 -51.75357898 -48.58024564 -47.41357898 -36.38691231
61 62 63 64 65 66
-39.66704765 -31.57371431 -30.82371431 -32.70038098 -33.18038098 -35.00371431
67 68 69 70 71 72
-41.58704765 -42.49038098 -40.43704765 -39.96371431 -36.49704765 -33.97038098
73 74 75 76 77 78
-33.75051631 -35.45718298 -35.60718298 -41.88384965 -43.26384965 -44.08718298
79 80 81 82 83 84
-49.07051631 -49.77384965 -48.52051631 -44.74718298 -37.98051631 -38.15384965
85 86 87 88 89 90
-35.23398498 -33.04065165 -35.59065165 -36.76731832 -36.44731832 -32.97065165
91 92 93 94 95 96
-34.25398498 -37.15731832 -32.40398498 -28.73065165 -25.46398498 -22.43731832
97 98 99 100 101 102
-23.91745365 -25.22412032 -25.17412032 -28.15078699 -29.93078699 -29.45412032
103 104 105 106 107 108
-32.83745365 -40.24078699 -37.98745365 -34.11412032 -30.84745365 -36.62078699
109 110 111 112 113 114
-17.80092232 62.79241101 82.84241101 73.86574435 68.98574435 65.76241101
115 116 117 118 119 120
54.77907768 39.07574435 22.92907768 24.00241101 31.96907768 33.39574435
121 122 123 124 125 126
28.81560901 17.60894234 11.65894234 0.08227568 -10.69772432 -12.02105766
127 128 129 130 131 132
-18.70439099 -30.60772432 -23.25439099 -14.08105766 -21.71439099 -22.78772432
133 134 135 136 137 138
-14.16785966 -17.17452633 -24.02452633 -18.50119299 -21.28119299 -22.80452633
139 140 141 142 143 144
-20.28785966 -26.79119299 -22.43785966 -18.16452633 -10.09785966 -4.77119299
145 146 147 148 149 150
-2.35132833 3.14200501 1.49200501 6.91533834 10.73533834 11.11200501
151 152 153 154 155 156
13.22867167 5.62533834 1.77867167 -1.44799499 -10.58132833 -5.15466166
157 158 159 160 161 162
-8.63479700 -7.14146366 -14.89146366 -17.66813033 -13.34813033 -9.47146366
163 164 165 166 167 168
-5.45479700 -10.35813033 -7.10479700 -3.83146366 -7.96479700 -6.33813033
169 170 171 172 173 174
-7.41826567 -8.12493233 -16.17493233 -15.35159900 -20.83159900 -22.15493233
175 176 177 178 179 180
-31.93826567 -42.24159900 -41.98826567 -37.81493233 -36.74826567 -39.52159900
181 182 183 184 185 186
-36.70173433 -38.00840100 -44.05840100 -48.13506767 -44.31506767 -47.83840100
187 188 189 190 191 192
-48.82173433 -54.92506767 -59.07173433 -60.79840100 -66.53173433 -67.20506767
193 194 195 196 197 198
-69.88520300 -63.19186967 -62.54186967 -63.21853634 -60.49853634 -58.62186967
199 200 201 202 203 204
-60.80520300 -67.80853634 -65.05520300 -70.08186967 -63.91520300 -57.18853634
205 206 207 208 209 210
-53.66867167 -57.07533834 -58.82533834 -60.90200501 -59.98200501 -53.70533834
211 212 213 214 215 216
16.91132833 128.60799499 129.86132833 131.83466166 139.40132833 131.42799499
217 218 219 220 221 222
131.54785966 111.84119299 98.89119299 94.31452633 91.63452633 90.81119299
223 224 225 226 227 228
83.92785966 84.12452633 82.07785966 71.75119299 71.01785966 66.84452633
229 230 231 232 233 234
47.86439099 45.85772432 41.50772432 37.03105766 27.75105766 27.12772432
235 236 237 238 239 240
17.64439099 16.44105766 14.19439099 18.06772432 16.33439099 20.76105766
241 242 243 244 245 246
18.58092232 16.87425565 36.12425565 72.14758899 92.66758899 124.54425565
247 248 249 250 251 252
140.86092232 142.75758899 141.01092232 121.28425565 116.75092232 104.57758899
253 254 255 256 257 258
89.49745365 80.99078699 86.64078699 77.06412032 67.98412032 58.76078699
259 260 261 262 263 264
53.57745365 44.67412032 39.72745365 30.80078699 33.06745365 31.49412032
265 266 267 268 269 270
28.91398498 24.90731832 29.35731832 26.18065165 28.10065165 20.67731832
271 272 273 274 275 276
16.89398498 15.49065165 15.44398498 27.11731832 16.98398498 20.01065165
277 278 279 280 281 282
37.83051631 48.22384965 43.47384965 36.39718298 30.11718298 20.09384965
283 284 285 286 287 288
17.91051631 15.50718298 8.46051631 9.03384965 6.00051631 4.92718298
289 290 291 292 293 294
4.64704765 0.64038098 -0.90961902 -10.78628569 -14.86628569 -8.98961902
295 296 297 298 299 300
-18.57295235 -25.87628569 -24.52295235 -22.74961902 -21.08295235 -26.55628569
301 302 303 304 305 306
-25.73642102 -28.04308769 -37.09308769 -27.56975436 -25.04975436 -32.37308769
307 308 309 310 311 312
-32.15642102 -39.15975436 -36.50642102 -38.63308769 -33.26642102 -35.63975436
313 314 315 316 317 318
-21.01988969 -31.82655636 -31.27655636 -25.95322303 -34.03322303 -34.65655636
319 320 321 322 323 324
-37.03988969 -41.54322303 -38.28988969 -44.91655636 -45.14988969 -33.52322303
325 326 327 328 329 330
-33.30335836 -40.21002503 -32.96002503 -37.53669169 -46.21669169 -54.34002503
331 332 333 334 335 336
-45.22335836 -47.42669169 -44.37335836 -45.00002503 -46.83335836 -45.00669169
337 338 339 340 341 342
-19.18682703 -33.39349370 -26.84349370 -5.92016036 1.99983964 10.67650630
343 344 345 346 347 348
-1.20682703 11.38983964 11.34317297 14.11650630 3.08317297 -0.69016036
349 350 351 352 353 354
-2.47029570 -11.57696237 0.77303763 -2.30362903 2.41637097 -16.70696237
355 356 357 358 359 360
-20.79029570 -18.79362903 -17.64029570 -18.36696237 -12.00029570 -14.47362903
> postscript(file="/var/wessaorg/rcomp/tmp/61mni1355853062.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 -24.74970430 NA
1 -2.85637097 -24.74970430
2 16.49362903 -2.85637097
3 53.61696237 16.49362903
4 87.63696237 53.61696237
5 106.91362903 87.63696237
6 98.93029570 106.91362903
7 89.22696237 98.93029570
8 86.18029570 89.22696237
9 82.75362903 86.18029570
10 75.52029570 82.75362903
11 72.24696237 75.52029570
12 65.16682703 72.24696237
13 58.26016036 65.16682703
14 55.31016036 58.26016036
15 41.13349370 55.31016036
16 34.75349370 41.13349370
17 26.13016036 34.75349370
18 17.04682703 26.13016036
19 -0.05650630 17.04682703
20 -5.00317297 -0.05650630
21 -6.62983964 -5.00317297
22 -3.16317297 -6.62983964
23 -2.63650630 -3.16317297
24 -8.41664164 -2.63650630
25 -15.82330831 -8.41664164
26 -23.17330831 -15.82330831
27 -28.84997497 -23.17330831
28 -31.72997497 -28.84997497
29 -27.05330831 -31.72997497
30 -8.73664164 -27.05330831
31 15.66002503 -8.73664164
32 29.91335836 15.66002503
33 37.58669169 29.91335836
34 46.25335836 37.58669169
35 50.28002503 46.25335836
36 36.89988969 50.28002503
37 39.19322303 36.89988969
38 31.84322303 39.19322303
39 24.36655636 31.84322303
40 25.38655636 24.36655636
41 23.06322303 25.38655636
42 26.27988969 23.06322303
43 20.97655636 26.27988969
44 13.42988969 20.97655636
45 10.30322303 13.42988969
46 0.86988969 10.30322303
47 -6.90344364 0.86988969
48 -11.68357898 -6.90344364
49 -30.59024564 -11.68357898
50 -36.44024564 -30.59024564
51 -40.91691231 -36.44024564
52 -44.49691231 -40.91691231
53 -43.42024564 -44.49691231
54 -50.50357898 -43.42024564
55 -54.30691231 -50.50357898
56 -51.75357898 -54.30691231
57 -48.58024564 -51.75357898
58 -47.41357898 -48.58024564
59 -36.38691231 -47.41357898
60 -39.66704765 -36.38691231
61 -31.57371431 -39.66704765
62 -30.82371431 -31.57371431
63 -32.70038098 -30.82371431
64 -33.18038098 -32.70038098
65 -35.00371431 -33.18038098
66 -41.58704765 -35.00371431
67 -42.49038098 -41.58704765
68 -40.43704765 -42.49038098
69 -39.96371431 -40.43704765
70 -36.49704765 -39.96371431
71 -33.97038098 -36.49704765
72 -33.75051631 -33.97038098
73 -35.45718298 -33.75051631
74 -35.60718298 -35.45718298
75 -41.88384965 -35.60718298
76 -43.26384965 -41.88384965
77 -44.08718298 -43.26384965
78 -49.07051631 -44.08718298
79 -49.77384965 -49.07051631
80 -48.52051631 -49.77384965
81 -44.74718298 -48.52051631
82 -37.98051631 -44.74718298
83 -38.15384965 -37.98051631
84 -35.23398498 -38.15384965
85 -33.04065165 -35.23398498
86 -35.59065165 -33.04065165
87 -36.76731832 -35.59065165
88 -36.44731832 -36.76731832
89 -32.97065165 -36.44731832
90 -34.25398498 -32.97065165
91 -37.15731832 -34.25398498
92 -32.40398498 -37.15731832
93 -28.73065165 -32.40398498
94 -25.46398498 -28.73065165
95 -22.43731832 -25.46398498
96 -23.91745365 -22.43731832
97 -25.22412032 -23.91745365
98 -25.17412032 -25.22412032
99 -28.15078699 -25.17412032
100 -29.93078699 -28.15078699
101 -29.45412032 -29.93078699
102 -32.83745365 -29.45412032
103 -40.24078699 -32.83745365
104 -37.98745365 -40.24078699
105 -34.11412032 -37.98745365
106 -30.84745365 -34.11412032
107 -36.62078699 -30.84745365
108 -17.80092232 -36.62078699
109 62.79241101 -17.80092232
110 82.84241101 62.79241101
111 73.86574435 82.84241101
112 68.98574435 73.86574435
113 65.76241101 68.98574435
114 54.77907768 65.76241101
115 39.07574435 54.77907768
116 22.92907768 39.07574435
117 24.00241101 22.92907768
118 31.96907768 24.00241101
119 33.39574435 31.96907768
120 28.81560901 33.39574435
121 17.60894234 28.81560901
122 11.65894234 17.60894234
123 0.08227568 11.65894234
124 -10.69772432 0.08227568
125 -12.02105766 -10.69772432
126 -18.70439099 -12.02105766
127 -30.60772432 -18.70439099
128 -23.25439099 -30.60772432
129 -14.08105766 -23.25439099
130 -21.71439099 -14.08105766
131 -22.78772432 -21.71439099
132 -14.16785966 -22.78772432
133 -17.17452633 -14.16785966
134 -24.02452633 -17.17452633
135 -18.50119299 -24.02452633
136 -21.28119299 -18.50119299
137 -22.80452633 -21.28119299
138 -20.28785966 -22.80452633
139 -26.79119299 -20.28785966
140 -22.43785966 -26.79119299
141 -18.16452633 -22.43785966
142 -10.09785966 -18.16452633
143 -4.77119299 -10.09785966
144 -2.35132833 -4.77119299
145 3.14200501 -2.35132833
146 1.49200501 3.14200501
147 6.91533834 1.49200501
148 10.73533834 6.91533834
149 11.11200501 10.73533834
150 13.22867167 11.11200501
151 5.62533834 13.22867167
152 1.77867167 5.62533834
153 -1.44799499 1.77867167
154 -10.58132833 -1.44799499
155 -5.15466166 -10.58132833
156 -8.63479700 -5.15466166
157 -7.14146366 -8.63479700
158 -14.89146366 -7.14146366
159 -17.66813033 -14.89146366
160 -13.34813033 -17.66813033
161 -9.47146366 -13.34813033
162 -5.45479700 -9.47146366
163 -10.35813033 -5.45479700
164 -7.10479700 -10.35813033
165 -3.83146366 -7.10479700
166 -7.96479700 -3.83146366
167 -6.33813033 -7.96479700
168 -7.41826567 -6.33813033
169 -8.12493233 -7.41826567
170 -16.17493233 -8.12493233
171 -15.35159900 -16.17493233
172 -20.83159900 -15.35159900
173 -22.15493233 -20.83159900
174 -31.93826567 -22.15493233
175 -42.24159900 -31.93826567
176 -41.98826567 -42.24159900
177 -37.81493233 -41.98826567
178 -36.74826567 -37.81493233
179 -39.52159900 -36.74826567
180 -36.70173433 -39.52159900
181 -38.00840100 -36.70173433
182 -44.05840100 -38.00840100
183 -48.13506767 -44.05840100
184 -44.31506767 -48.13506767
185 -47.83840100 -44.31506767
186 -48.82173433 -47.83840100
187 -54.92506767 -48.82173433
188 -59.07173433 -54.92506767
189 -60.79840100 -59.07173433
190 -66.53173433 -60.79840100
191 -67.20506767 -66.53173433
192 -69.88520300 -67.20506767
193 -63.19186967 -69.88520300
194 -62.54186967 -63.19186967
195 -63.21853634 -62.54186967
196 -60.49853634 -63.21853634
197 -58.62186967 -60.49853634
198 -60.80520300 -58.62186967
199 -67.80853634 -60.80520300
200 -65.05520300 -67.80853634
201 -70.08186967 -65.05520300
202 -63.91520300 -70.08186967
203 -57.18853634 -63.91520300
204 -53.66867167 -57.18853634
205 -57.07533834 -53.66867167
206 -58.82533834 -57.07533834
207 -60.90200501 -58.82533834
208 -59.98200501 -60.90200501
209 -53.70533834 -59.98200501
210 16.91132833 -53.70533834
211 128.60799499 16.91132833
212 129.86132833 128.60799499
213 131.83466166 129.86132833
214 139.40132833 131.83466166
215 131.42799499 139.40132833
216 131.54785966 131.42799499
217 111.84119299 131.54785966
218 98.89119299 111.84119299
219 94.31452633 98.89119299
220 91.63452633 94.31452633
221 90.81119299 91.63452633
222 83.92785966 90.81119299
223 84.12452633 83.92785966
224 82.07785966 84.12452633
225 71.75119299 82.07785966
226 71.01785966 71.75119299
227 66.84452633 71.01785966
228 47.86439099 66.84452633
229 45.85772432 47.86439099
230 41.50772432 45.85772432
231 37.03105766 41.50772432
232 27.75105766 37.03105766
233 27.12772432 27.75105766
234 17.64439099 27.12772432
235 16.44105766 17.64439099
236 14.19439099 16.44105766
237 18.06772432 14.19439099
238 16.33439099 18.06772432
239 20.76105766 16.33439099
240 18.58092232 20.76105766
241 16.87425565 18.58092232
242 36.12425565 16.87425565
243 72.14758899 36.12425565
244 92.66758899 72.14758899
245 124.54425565 92.66758899
246 140.86092232 124.54425565
247 142.75758899 140.86092232
248 141.01092232 142.75758899
249 121.28425565 141.01092232
250 116.75092232 121.28425565
251 104.57758899 116.75092232
252 89.49745365 104.57758899
253 80.99078699 89.49745365
254 86.64078699 80.99078699
255 77.06412032 86.64078699
256 67.98412032 77.06412032
257 58.76078699 67.98412032
258 53.57745365 58.76078699
259 44.67412032 53.57745365
260 39.72745365 44.67412032
261 30.80078699 39.72745365
262 33.06745365 30.80078699
263 31.49412032 33.06745365
264 28.91398498 31.49412032
265 24.90731832 28.91398498
266 29.35731832 24.90731832
267 26.18065165 29.35731832
268 28.10065165 26.18065165
269 20.67731832 28.10065165
270 16.89398498 20.67731832
271 15.49065165 16.89398498
272 15.44398498 15.49065165
273 27.11731832 15.44398498
274 16.98398498 27.11731832
275 20.01065165 16.98398498
276 37.83051631 20.01065165
277 48.22384965 37.83051631
278 43.47384965 48.22384965
279 36.39718298 43.47384965
280 30.11718298 36.39718298
281 20.09384965 30.11718298
282 17.91051631 20.09384965
283 15.50718298 17.91051631
284 8.46051631 15.50718298
285 9.03384965 8.46051631
286 6.00051631 9.03384965
287 4.92718298 6.00051631
288 4.64704765 4.92718298
289 0.64038098 4.64704765
290 -0.90961902 0.64038098
291 -10.78628569 -0.90961902
292 -14.86628569 -10.78628569
293 -8.98961902 -14.86628569
294 -18.57295235 -8.98961902
295 -25.87628569 -18.57295235
296 -24.52295235 -25.87628569
297 -22.74961902 -24.52295235
298 -21.08295235 -22.74961902
299 -26.55628569 -21.08295235
300 -25.73642102 -26.55628569
301 -28.04308769 -25.73642102
302 -37.09308769 -28.04308769
303 -27.56975436 -37.09308769
304 -25.04975436 -27.56975436
305 -32.37308769 -25.04975436
306 -32.15642102 -32.37308769
307 -39.15975436 -32.15642102
308 -36.50642102 -39.15975436
309 -38.63308769 -36.50642102
310 -33.26642102 -38.63308769
311 -35.63975436 -33.26642102
312 -21.01988969 -35.63975436
313 -31.82655636 -21.01988969
314 -31.27655636 -31.82655636
315 -25.95322303 -31.27655636
316 -34.03322303 -25.95322303
317 -34.65655636 -34.03322303
318 -37.03988969 -34.65655636
319 -41.54322303 -37.03988969
320 -38.28988969 -41.54322303
321 -44.91655636 -38.28988969
322 -45.14988969 -44.91655636
323 -33.52322303 -45.14988969
324 -33.30335836 -33.52322303
325 -40.21002503 -33.30335836
326 -32.96002503 -40.21002503
327 -37.53669169 -32.96002503
328 -46.21669169 -37.53669169
329 -54.34002503 -46.21669169
330 -45.22335836 -54.34002503
331 -47.42669169 -45.22335836
332 -44.37335836 -47.42669169
333 -45.00002503 -44.37335836
334 -46.83335836 -45.00002503
335 -45.00669169 -46.83335836
336 -19.18682703 -45.00669169
337 -33.39349370 -19.18682703
338 -26.84349370 -33.39349370
339 -5.92016036 -26.84349370
340 1.99983964 -5.92016036
341 10.67650630 1.99983964
342 -1.20682703 10.67650630
343 11.38983964 -1.20682703
344 11.34317297 11.38983964
345 14.11650630 11.34317297
346 3.08317297 14.11650630
347 -0.69016036 3.08317297
348 -2.47029570 -0.69016036
349 -11.57696237 -2.47029570
350 0.77303763 -11.57696237
351 -2.30362903 0.77303763
352 2.41637097 -2.30362903
353 -16.70696237 2.41637097
354 -20.79029570 -16.70696237
355 -18.79362903 -20.79029570
356 -17.64029570 -18.79362903
357 -18.36696237 -17.64029570
358 -12.00029570 -18.36696237
359 -14.47362903 -12.00029570
360 NA -14.47362903
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -2.85637097 -24.74970430
[2,] 16.49362903 -2.85637097
[3,] 53.61696237 16.49362903
[4,] 87.63696237 53.61696237
[5,] 106.91362903 87.63696237
[6,] 98.93029570 106.91362903
[7,] 89.22696237 98.93029570
[8,] 86.18029570 89.22696237
[9,] 82.75362903 86.18029570
[10,] 75.52029570 82.75362903
[11,] 72.24696237 75.52029570
[12,] 65.16682703 72.24696237
[13,] 58.26016036 65.16682703
[14,] 55.31016036 58.26016036
[15,] 41.13349370 55.31016036
[16,] 34.75349370 41.13349370
[17,] 26.13016036 34.75349370
[18,] 17.04682703 26.13016036
[19,] -0.05650630 17.04682703
[20,] -5.00317297 -0.05650630
[21,] -6.62983964 -5.00317297
[22,] -3.16317297 -6.62983964
[23,] -2.63650630 -3.16317297
[24,] -8.41664164 -2.63650630
[25,] -15.82330831 -8.41664164
[26,] -23.17330831 -15.82330831
[27,] -28.84997497 -23.17330831
[28,] -31.72997497 -28.84997497
[29,] -27.05330831 -31.72997497
[30,] -8.73664164 -27.05330831
[31,] 15.66002503 -8.73664164
[32,] 29.91335836 15.66002503
[33,] 37.58669169 29.91335836
[34,] 46.25335836 37.58669169
[35,] 50.28002503 46.25335836
[36,] 36.89988969 50.28002503
[37,] 39.19322303 36.89988969
[38,] 31.84322303 39.19322303
[39,] 24.36655636 31.84322303
[40,] 25.38655636 24.36655636
[41,] 23.06322303 25.38655636
[42,] 26.27988969 23.06322303
[43,] 20.97655636 26.27988969
[44,] 13.42988969 20.97655636
[45,] 10.30322303 13.42988969
[46,] 0.86988969 10.30322303
[47,] -6.90344364 0.86988969
[48,] -11.68357898 -6.90344364
[49,] -30.59024564 -11.68357898
[50,] -36.44024564 -30.59024564
[51,] -40.91691231 -36.44024564
[52,] -44.49691231 -40.91691231
[53,] -43.42024564 -44.49691231
[54,] -50.50357898 -43.42024564
[55,] -54.30691231 -50.50357898
[56,] -51.75357898 -54.30691231
[57,] -48.58024564 -51.75357898
[58,] -47.41357898 -48.58024564
[59,] -36.38691231 -47.41357898
[60,] -39.66704765 -36.38691231
[61,] -31.57371431 -39.66704765
[62,] -30.82371431 -31.57371431
[63,] -32.70038098 -30.82371431
[64,] -33.18038098 -32.70038098
[65,] -35.00371431 -33.18038098
[66,] -41.58704765 -35.00371431
[67,] -42.49038098 -41.58704765
[68,] -40.43704765 -42.49038098
[69,] -39.96371431 -40.43704765
[70,] -36.49704765 -39.96371431
[71,] -33.97038098 -36.49704765
[72,] -33.75051631 -33.97038098
[73,] -35.45718298 -33.75051631
[74,] -35.60718298 -35.45718298
[75,] -41.88384965 -35.60718298
[76,] -43.26384965 -41.88384965
[77,] -44.08718298 -43.26384965
[78,] -49.07051631 -44.08718298
[79,] -49.77384965 -49.07051631
[80,] -48.52051631 -49.77384965
[81,] -44.74718298 -48.52051631
[82,] -37.98051631 -44.74718298
[83,] -38.15384965 -37.98051631
[84,] -35.23398498 -38.15384965
[85,] -33.04065165 -35.23398498
[86,] -35.59065165 -33.04065165
[87,] -36.76731832 -35.59065165
[88,] -36.44731832 -36.76731832
[89,] -32.97065165 -36.44731832
[90,] -34.25398498 -32.97065165
[91,] -37.15731832 -34.25398498
[92,] -32.40398498 -37.15731832
[93,] -28.73065165 -32.40398498
[94,] -25.46398498 -28.73065165
[95,] -22.43731832 -25.46398498
[96,] -23.91745365 -22.43731832
[97,] -25.22412032 -23.91745365
[98,] -25.17412032 -25.22412032
[99,] -28.15078699 -25.17412032
[100,] -29.93078699 -28.15078699
[101,] -29.45412032 -29.93078699
[102,] -32.83745365 -29.45412032
[103,] -40.24078699 -32.83745365
[104,] -37.98745365 -40.24078699
[105,] -34.11412032 -37.98745365
[106,] -30.84745365 -34.11412032
[107,] -36.62078699 -30.84745365
[108,] -17.80092232 -36.62078699
[109,] 62.79241101 -17.80092232
[110,] 82.84241101 62.79241101
[111,] 73.86574435 82.84241101
[112,] 68.98574435 73.86574435
[113,] 65.76241101 68.98574435
[114,] 54.77907768 65.76241101
[115,] 39.07574435 54.77907768
[116,] 22.92907768 39.07574435
[117,] 24.00241101 22.92907768
[118,] 31.96907768 24.00241101
[119,] 33.39574435 31.96907768
[120,] 28.81560901 33.39574435
[121,] 17.60894234 28.81560901
[122,] 11.65894234 17.60894234
[123,] 0.08227568 11.65894234
[124,] -10.69772432 0.08227568
[125,] -12.02105766 -10.69772432
[126,] -18.70439099 -12.02105766
[127,] -30.60772432 -18.70439099
[128,] -23.25439099 -30.60772432
[129,] -14.08105766 -23.25439099
[130,] -21.71439099 -14.08105766
[131,] -22.78772432 -21.71439099
[132,] -14.16785966 -22.78772432
[133,] -17.17452633 -14.16785966
[134,] -24.02452633 -17.17452633
[135,] -18.50119299 -24.02452633
[136,] -21.28119299 -18.50119299
[137,] -22.80452633 -21.28119299
[138,] -20.28785966 -22.80452633
[139,] -26.79119299 -20.28785966
[140,] -22.43785966 -26.79119299
[141,] -18.16452633 -22.43785966
[142,] -10.09785966 -18.16452633
[143,] -4.77119299 -10.09785966
[144,] -2.35132833 -4.77119299
[145,] 3.14200501 -2.35132833
[146,] 1.49200501 3.14200501
[147,] 6.91533834 1.49200501
[148,] 10.73533834 6.91533834
[149,] 11.11200501 10.73533834
[150,] 13.22867167 11.11200501
[151,] 5.62533834 13.22867167
[152,] 1.77867167 5.62533834
[153,] -1.44799499 1.77867167
[154,] -10.58132833 -1.44799499
[155,] -5.15466166 -10.58132833
[156,] -8.63479700 -5.15466166
[157,] -7.14146366 -8.63479700
[158,] -14.89146366 -7.14146366
[159,] -17.66813033 -14.89146366
[160,] -13.34813033 -17.66813033
[161,] -9.47146366 -13.34813033
[162,] -5.45479700 -9.47146366
[163,] -10.35813033 -5.45479700
[164,] -7.10479700 -10.35813033
[165,] -3.83146366 -7.10479700
[166,] -7.96479700 -3.83146366
[167,] -6.33813033 -7.96479700
[168,] -7.41826567 -6.33813033
[169,] -8.12493233 -7.41826567
[170,] -16.17493233 -8.12493233
[171,] -15.35159900 -16.17493233
[172,] -20.83159900 -15.35159900
[173,] -22.15493233 -20.83159900
[174,] -31.93826567 -22.15493233
[175,] -42.24159900 -31.93826567
[176,] -41.98826567 -42.24159900
[177,] -37.81493233 -41.98826567
[178,] -36.74826567 -37.81493233
[179,] -39.52159900 -36.74826567
[180,] -36.70173433 -39.52159900
[181,] -38.00840100 -36.70173433
[182,] -44.05840100 -38.00840100
[183,] -48.13506767 -44.05840100
[184,] -44.31506767 -48.13506767
[185,] -47.83840100 -44.31506767
[186,] -48.82173433 -47.83840100
[187,] -54.92506767 -48.82173433
[188,] -59.07173433 -54.92506767
[189,] -60.79840100 -59.07173433
[190,] -66.53173433 -60.79840100
[191,] -67.20506767 -66.53173433
[192,] -69.88520300 -67.20506767
[193,] -63.19186967 -69.88520300
[194,] -62.54186967 -63.19186967
[195,] -63.21853634 -62.54186967
[196,] -60.49853634 -63.21853634
[197,] -58.62186967 -60.49853634
[198,] -60.80520300 -58.62186967
[199,] -67.80853634 -60.80520300
[200,] -65.05520300 -67.80853634
[201,] -70.08186967 -65.05520300
[202,] -63.91520300 -70.08186967
[203,] -57.18853634 -63.91520300
[204,] -53.66867167 -57.18853634
[205,] -57.07533834 -53.66867167
[206,] -58.82533834 -57.07533834
[207,] -60.90200501 -58.82533834
[208,] -59.98200501 -60.90200501
[209,] -53.70533834 -59.98200501
[210,] 16.91132833 -53.70533834
[211,] 128.60799499 16.91132833
[212,] 129.86132833 128.60799499
[213,] 131.83466166 129.86132833
[214,] 139.40132833 131.83466166
[215,] 131.42799499 139.40132833
[216,] 131.54785966 131.42799499
[217,] 111.84119299 131.54785966
[218,] 98.89119299 111.84119299
[219,] 94.31452633 98.89119299
[220,] 91.63452633 94.31452633
[221,] 90.81119299 91.63452633
[222,] 83.92785966 90.81119299
[223,] 84.12452633 83.92785966
[224,] 82.07785966 84.12452633
[225,] 71.75119299 82.07785966
[226,] 71.01785966 71.75119299
[227,] 66.84452633 71.01785966
[228,] 47.86439099 66.84452633
[229,] 45.85772432 47.86439099
[230,] 41.50772432 45.85772432
[231,] 37.03105766 41.50772432
[232,] 27.75105766 37.03105766
[233,] 27.12772432 27.75105766
[234,] 17.64439099 27.12772432
[235,] 16.44105766 17.64439099
[236,] 14.19439099 16.44105766
[237,] 18.06772432 14.19439099
[238,] 16.33439099 18.06772432
[239,] 20.76105766 16.33439099
[240,] 18.58092232 20.76105766
[241,] 16.87425565 18.58092232
[242,] 36.12425565 16.87425565
[243,] 72.14758899 36.12425565
[244,] 92.66758899 72.14758899
[245,] 124.54425565 92.66758899
[246,] 140.86092232 124.54425565
[247,] 142.75758899 140.86092232
[248,] 141.01092232 142.75758899
[249,] 121.28425565 141.01092232
[250,] 116.75092232 121.28425565
[251,] 104.57758899 116.75092232
[252,] 89.49745365 104.57758899
[253,] 80.99078699 89.49745365
[254,] 86.64078699 80.99078699
[255,] 77.06412032 86.64078699
[256,] 67.98412032 77.06412032
[257,] 58.76078699 67.98412032
[258,] 53.57745365 58.76078699
[259,] 44.67412032 53.57745365
[260,] 39.72745365 44.67412032
[261,] 30.80078699 39.72745365
[262,] 33.06745365 30.80078699
[263,] 31.49412032 33.06745365
[264,] 28.91398498 31.49412032
[265,] 24.90731832 28.91398498
[266,] 29.35731832 24.90731832
[267,] 26.18065165 29.35731832
[268,] 28.10065165 26.18065165
[269,] 20.67731832 28.10065165
[270,] 16.89398498 20.67731832
[271,] 15.49065165 16.89398498
[272,] 15.44398498 15.49065165
[273,] 27.11731832 15.44398498
[274,] 16.98398498 27.11731832
[275,] 20.01065165 16.98398498
[276,] 37.83051631 20.01065165
[277,] 48.22384965 37.83051631
[278,] 43.47384965 48.22384965
[279,] 36.39718298 43.47384965
[280,] 30.11718298 36.39718298
[281,] 20.09384965 30.11718298
[282,] 17.91051631 20.09384965
[283,] 15.50718298 17.91051631
[284,] 8.46051631 15.50718298
[285,] 9.03384965 8.46051631
[286,] 6.00051631 9.03384965
[287,] 4.92718298 6.00051631
[288,] 4.64704765 4.92718298
[289,] 0.64038098 4.64704765
[290,] -0.90961902 0.64038098
[291,] -10.78628569 -0.90961902
[292,] -14.86628569 -10.78628569
[293,] -8.98961902 -14.86628569
[294,] -18.57295235 -8.98961902
[295,] -25.87628569 -18.57295235
[296,] -24.52295235 -25.87628569
[297,] -22.74961902 -24.52295235
[298,] -21.08295235 -22.74961902
[299,] -26.55628569 -21.08295235
[300,] -25.73642102 -26.55628569
[301,] -28.04308769 -25.73642102
[302,] -37.09308769 -28.04308769
[303,] -27.56975436 -37.09308769
[304,] -25.04975436 -27.56975436
[305,] -32.37308769 -25.04975436
[306,] -32.15642102 -32.37308769
[307,] -39.15975436 -32.15642102
[308,] -36.50642102 -39.15975436
[309,] -38.63308769 -36.50642102
[310,] -33.26642102 -38.63308769
[311,] -35.63975436 -33.26642102
[312,] -21.01988969 -35.63975436
[313,] -31.82655636 -21.01988969
[314,] -31.27655636 -31.82655636
[315,] -25.95322303 -31.27655636
[316,] -34.03322303 -25.95322303
[317,] -34.65655636 -34.03322303
[318,] -37.03988969 -34.65655636
[319,] -41.54322303 -37.03988969
[320,] -38.28988969 -41.54322303
[321,] -44.91655636 -38.28988969
[322,] -45.14988969 -44.91655636
[323,] -33.52322303 -45.14988969
[324,] -33.30335836 -33.52322303
[325,] -40.21002503 -33.30335836
[326,] -32.96002503 -40.21002503
[327,] -37.53669169 -32.96002503
[328,] -46.21669169 -37.53669169
[329,] -54.34002503 -46.21669169
[330,] -45.22335836 -54.34002503
[331,] -47.42669169 -45.22335836
[332,] -44.37335836 -47.42669169
[333,] -45.00002503 -44.37335836
[334,] -46.83335836 -45.00002503
[335,] -45.00669169 -46.83335836
[336,] -19.18682703 -45.00669169
[337,] -33.39349370 -19.18682703
[338,] -26.84349370 -33.39349370
[339,] -5.92016036 -26.84349370
[340,] 1.99983964 -5.92016036
[341,] 10.67650630 1.99983964
[342,] -1.20682703 10.67650630
[343,] 11.38983964 -1.20682703
[344,] 11.34317297 11.38983964
[345,] 14.11650630 11.34317297
[346,] 3.08317297 14.11650630
[347,] -0.69016036 3.08317297
[348,] -2.47029570 -0.69016036
[349,] -11.57696237 -2.47029570
[350,] 0.77303763 -11.57696237
[351,] -2.30362903 0.77303763
[352,] 2.41637097 -2.30362903
[353,] -16.70696237 2.41637097
[354,] -20.79029570 -16.70696237
[355,] -18.79362903 -20.79029570
[356,] -17.64029570 -18.79362903
[357,] -18.36696237 -17.64029570
[358,] -12.00029570 -18.36696237
[359,] -14.47362903 -12.00029570
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -2.85637097 -24.74970430
2 16.49362903 -2.85637097
3 53.61696237 16.49362903
4 87.63696237 53.61696237
5 106.91362903 87.63696237
6 98.93029570 106.91362903
7 89.22696237 98.93029570
8 86.18029570 89.22696237
9 82.75362903 86.18029570
10 75.52029570 82.75362903
11 72.24696237 75.52029570
12 65.16682703 72.24696237
13 58.26016036 65.16682703
14 55.31016036 58.26016036
15 41.13349370 55.31016036
16 34.75349370 41.13349370
17 26.13016036 34.75349370
18 17.04682703 26.13016036
19 -0.05650630 17.04682703
20 -5.00317297 -0.05650630
21 -6.62983964 -5.00317297
22 -3.16317297 -6.62983964
23 -2.63650630 -3.16317297
24 -8.41664164 -2.63650630
25 -15.82330831 -8.41664164
26 -23.17330831 -15.82330831
27 -28.84997497 -23.17330831
28 -31.72997497 -28.84997497
29 -27.05330831 -31.72997497
30 -8.73664164 -27.05330831
31 15.66002503 -8.73664164
32 29.91335836 15.66002503
33 37.58669169 29.91335836
34 46.25335836 37.58669169
35 50.28002503 46.25335836
36 36.89988969 50.28002503
37 39.19322303 36.89988969
38 31.84322303 39.19322303
39 24.36655636 31.84322303
40 25.38655636 24.36655636
41 23.06322303 25.38655636
42 26.27988969 23.06322303
43 20.97655636 26.27988969
44 13.42988969 20.97655636
45 10.30322303 13.42988969
46 0.86988969 10.30322303
47 -6.90344364 0.86988969
48 -11.68357898 -6.90344364
49 -30.59024564 -11.68357898
50 -36.44024564 -30.59024564
51 -40.91691231 -36.44024564
52 -44.49691231 -40.91691231
53 -43.42024564 -44.49691231
54 -50.50357898 -43.42024564
55 -54.30691231 -50.50357898
56 -51.75357898 -54.30691231
57 -48.58024564 -51.75357898
58 -47.41357898 -48.58024564
59 -36.38691231 -47.41357898
60 -39.66704765 -36.38691231
61 -31.57371431 -39.66704765
62 -30.82371431 -31.57371431
63 -32.70038098 -30.82371431
64 -33.18038098 -32.70038098
65 -35.00371431 -33.18038098
66 -41.58704765 -35.00371431
67 -42.49038098 -41.58704765
68 -40.43704765 -42.49038098
69 -39.96371431 -40.43704765
70 -36.49704765 -39.96371431
71 -33.97038098 -36.49704765
72 -33.75051631 -33.97038098
73 -35.45718298 -33.75051631
74 -35.60718298 -35.45718298
75 -41.88384965 -35.60718298
76 -43.26384965 -41.88384965
77 -44.08718298 -43.26384965
78 -49.07051631 -44.08718298
79 -49.77384965 -49.07051631
80 -48.52051631 -49.77384965
81 -44.74718298 -48.52051631
82 -37.98051631 -44.74718298
83 -38.15384965 -37.98051631
84 -35.23398498 -38.15384965
85 -33.04065165 -35.23398498
86 -35.59065165 -33.04065165
87 -36.76731832 -35.59065165
88 -36.44731832 -36.76731832
89 -32.97065165 -36.44731832
90 -34.25398498 -32.97065165
91 -37.15731832 -34.25398498
92 -32.40398498 -37.15731832
93 -28.73065165 -32.40398498
94 -25.46398498 -28.73065165
95 -22.43731832 -25.46398498
96 -23.91745365 -22.43731832
97 -25.22412032 -23.91745365
98 -25.17412032 -25.22412032
99 -28.15078699 -25.17412032
100 -29.93078699 -28.15078699
101 -29.45412032 -29.93078699
102 -32.83745365 -29.45412032
103 -40.24078699 -32.83745365
104 -37.98745365 -40.24078699
105 -34.11412032 -37.98745365
106 -30.84745365 -34.11412032
107 -36.62078699 -30.84745365
108 -17.80092232 -36.62078699
109 62.79241101 -17.80092232
110 82.84241101 62.79241101
111 73.86574435 82.84241101
112 68.98574435 73.86574435
113 65.76241101 68.98574435
114 54.77907768 65.76241101
115 39.07574435 54.77907768
116 22.92907768 39.07574435
117 24.00241101 22.92907768
118 31.96907768 24.00241101
119 33.39574435 31.96907768
120 28.81560901 33.39574435
121 17.60894234 28.81560901
122 11.65894234 17.60894234
123 0.08227568 11.65894234
124 -10.69772432 0.08227568
125 -12.02105766 -10.69772432
126 -18.70439099 -12.02105766
127 -30.60772432 -18.70439099
128 -23.25439099 -30.60772432
129 -14.08105766 -23.25439099
130 -21.71439099 -14.08105766
131 -22.78772432 -21.71439099
132 -14.16785966 -22.78772432
133 -17.17452633 -14.16785966
134 -24.02452633 -17.17452633
135 -18.50119299 -24.02452633
136 -21.28119299 -18.50119299
137 -22.80452633 -21.28119299
138 -20.28785966 -22.80452633
139 -26.79119299 -20.28785966
140 -22.43785966 -26.79119299
141 -18.16452633 -22.43785966
142 -10.09785966 -18.16452633
143 -4.77119299 -10.09785966
144 -2.35132833 -4.77119299
145 3.14200501 -2.35132833
146 1.49200501 3.14200501
147 6.91533834 1.49200501
148 10.73533834 6.91533834
149 11.11200501 10.73533834
150 13.22867167 11.11200501
151 5.62533834 13.22867167
152 1.77867167 5.62533834
153 -1.44799499 1.77867167
154 -10.58132833 -1.44799499
155 -5.15466166 -10.58132833
156 -8.63479700 -5.15466166
157 -7.14146366 -8.63479700
158 -14.89146366 -7.14146366
159 -17.66813033 -14.89146366
160 -13.34813033 -17.66813033
161 -9.47146366 -13.34813033
162 -5.45479700 -9.47146366
163 -10.35813033 -5.45479700
164 -7.10479700 -10.35813033
165 -3.83146366 -7.10479700
166 -7.96479700 -3.83146366
167 -6.33813033 -7.96479700
168 -7.41826567 -6.33813033
169 -8.12493233 -7.41826567
170 -16.17493233 -8.12493233
171 -15.35159900 -16.17493233
172 -20.83159900 -15.35159900
173 -22.15493233 -20.83159900
174 -31.93826567 -22.15493233
175 -42.24159900 -31.93826567
176 -41.98826567 -42.24159900
177 -37.81493233 -41.98826567
178 -36.74826567 -37.81493233
179 -39.52159900 -36.74826567
180 -36.70173433 -39.52159900
181 -38.00840100 -36.70173433
182 -44.05840100 -38.00840100
183 -48.13506767 -44.05840100
184 -44.31506767 -48.13506767
185 -47.83840100 -44.31506767
186 -48.82173433 -47.83840100
187 -54.92506767 -48.82173433
188 -59.07173433 -54.92506767
189 -60.79840100 -59.07173433
190 -66.53173433 -60.79840100
191 -67.20506767 -66.53173433
192 -69.88520300 -67.20506767
193 -63.19186967 -69.88520300
194 -62.54186967 -63.19186967
195 -63.21853634 -62.54186967
196 -60.49853634 -63.21853634
197 -58.62186967 -60.49853634
198 -60.80520300 -58.62186967
199 -67.80853634 -60.80520300
200 -65.05520300 -67.80853634
201 -70.08186967 -65.05520300
202 -63.91520300 -70.08186967
203 -57.18853634 -63.91520300
204 -53.66867167 -57.18853634
205 -57.07533834 -53.66867167
206 -58.82533834 -57.07533834
207 -60.90200501 -58.82533834
208 -59.98200501 -60.90200501
209 -53.70533834 -59.98200501
210 16.91132833 -53.70533834
211 128.60799499 16.91132833
212 129.86132833 128.60799499
213 131.83466166 129.86132833
214 139.40132833 131.83466166
215 131.42799499 139.40132833
216 131.54785966 131.42799499
217 111.84119299 131.54785966
218 98.89119299 111.84119299
219 94.31452633 98.89119299
220 91.63452633 94.31452633
221 90.81119299 91.63452633
222 83.92785966 90.81119299
223 84.12452633 83.92785966
224 82.07785966 84.12452633
225 71.75119299 82.07785966
226 71.01785966 71.75119299
227 66.84452633 71.01785966
228 47.86439099 66.84452633
229 45.85772432 47.86439099
230 41.50772432 45.85772432
231 37.03105766 41.50772432
232 27.75105766 37.03105766
233 27.12772432 27.75105766
234 17.64439099 27.12772432
235 16.44105766 17.64439099
236 14.19439099 16.44105766
237 18.06772432 14.19439099
238 16.33439099 18.06772432
239 20.76105766 16.33439099
240 18.58092232 20.76105766
241 16.87425565 18.58092232
242 36.12425565 16.87425565
243 72.14758899 36.12425565
244 92.66758899 72.14758899
245 124.54425565 92.66758899
246 140.86092232 124.54425565
247 142.75758899 140.86092232
248 141.01092232 142.75758899
249 121.28425565 141.01092232
250 116.75092232 121.28425565
251 104.57758899 116.75092232
252 89.49745365 104.57758899
253 80.99078699 89.49745365
254 86.64078699 80.99078699
255 77.06412032 86.64078699
256 67.98412032 77.06412032
257 58.76078699 67.98412032
258 53.57745365 58.76078699
259 44.67412032 53.57745365
260 39.72745365 44.67412032
261 30.80078699 39.72745365
262 33.06745365 30.80078699
263 31.49412032 33.06745365
264 28.91398498 31.49412032
265 24.90731832 28.91398498
266 29.35731832 24.90731832
267 26.18065165 29.35731832
268 28.10065165 26.18065165
269 20.67731832 28.10065165
270 16.89398498 20.67731832
271 15.49065165 16.89398498
272 15.44398498 15.49065165
273 27.11731832 15.44398498
274 16.98398498 27.11731832
275 20.01065165 16.98398498
276 37.83051631 20.01065165
277 48.22384965 37.83051631
278 43.47384965 48.22384965
279 36.39718298 43.47384965
280 30.11718298 36.39718298
281 20.09384965 30.11718298
282 17.91051631 20.09384965
283 15.50718298 17.91051631
284 8.46051631 15.50718298
285 9.03384965 8.46051631
286 6.00051631 9.03384965
287 4.92718298 6.00051631
288 4.64704765 4.92718298
289 0.64038098 4.64704765
290 -0.90961902 0.64038098
291 -10.78628569 -0.90961902
292 -14.86628569 -10.78628569
293 -8.98961902 -14.86628569
294 -18.57295235 -8.98961902
295 -25.87628569 -18.57295235
296 -24.52295235 -25.87628569
297 -22.74961902 -24.52295235
298 -21.08295235 -22.74961902
299 -26.55628569 -21.08295235
300 -25.73642102 -26.55628569
301 -28.04308769 -25.73642102
302 -37.09308769 -28.04308769
303 -27.56975436 -37.09308769
304 -25.04975436 -27.56975436
305 -32.37308769 -25.04975436
306 -32.15642102 -32.37308769
307 -39.15975436 -32.15642102
308 -36.50642102 -39.15975436
309 -38.63308769 -36.50642102
310 -33.26642102 -38.63308769
311 -35.63975436 -33.26642102
312 -21.01988969 -35.63975436
313 -31.82655636 -21.01988969
314 -31.27655636 -31.82655636
315 -25.95322303 -31.27655636
316 -34.03322303 -25.95322303
317 -34.65655636 -34.03322303
318 -37.03988969 -34.65655636
319 -41.54322303 -37.03988969
320 -38.28988969 -41.54322303
321 -44.91655636 -38.28988969
322 -45.14988969 -44.91655636
323 -33.52322303 -45.14988969
324 -33.30335836 -33.52322303
325 -40.21002503 -33.30335836
326 -32.96002503 -40.21002503
327 -37.53669169 -32.96002503
328 -46.21669169 -37.53669169
329 -54.34002503 -46.21669169
330 -45.22335836 -54.34002503
331 -47.42669169 -45.22335836
332 -44.37335836 -47.42669169
333 -45.00002503 -44.37335836
334 -46.83335836 -45.00002503
335 -45.00669169 -46.83335836
336 -19.18682703 -45.00669169
337 -33.39349370 -19.18682703
338 -26.84349370 -33.39349370
339 -5.92016036 -26.84349370
340 1.99983964 -5.92016036
341 10.67650630 1.99983964
342 -1.20682703 10.67650630
343 11.38983964 -1.20682703
344 11.34317297 11.38983964
345 14.11650630 11.34317297
346 3.08317297 14.11650630
347 -0.69016036 3.08317297
348 -2.47029570 -0.69016036
349 -11.57696237 -2.47029570
350 0.77303763 -11.57696237
351 -2.30362903 0.77303763
352 2.41637097 -2.30362903
353 -16.70696237 2.41637097
354 -20.79029570 -16.70696237
355 -18.79362903 -20.79029570
356 -17.64029570 -18.79362903
357 -18.36696237 -17.64029570
358 -12.00029570 -18.36696237
359 -14.47362903 -12.00029570
> 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/7k8ik1355853062.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/8bten1355853062.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/9b9nu1355853062.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/102rau1355853062.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$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
+ }
+ }
> myeq <- paste(myeq, ' + e[t]')
> a<-table.row.start(a)
> a<-table.element(a, myeq)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/11zl821355853062.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Variable',header=TRUE)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
> a<-table.element(a,'2-tail p-value',header=TRUE)
> a<-table.element(a,'1-tail p-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:k){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(mysum$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$coefficients[i,4]/2,6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/12kl9j1355853062.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple R',1,TRUE)
> a<-table.element(a, sqrt(mysum$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$sigma)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a, sum(myerror*myerror))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/13byw91355853062.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Time or Index', 1, TRUE)
> a<-table.element(a, 'Actuals', 1, TRUE)
> a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
> a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
> a<-table.row.end(a)
> for (i in 1:n) {
+ a<-table.row.start(a)
+ a<-table.element(a,i, 1, TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]-mysum$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/14rtt11355853062.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/15nc2w1355853062.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/16e1vh1355853062.tab")
+ }
>
> try(system("convert tmp/1ds1g1355853062.ps tmp/1ds1g1355853062.png",intern=TRUE))
character(0)
> try(system("convert tmp/23cme1355853062.ps tmp/23cme1355853062.png",intern=TRUE))
character(0)
> try(system("convert tmp/3x1k81355853062.ps tmp/3x1k81355853062.png",intern=TRUE))
character(0)
> try(system("convert tmp/4mk631355853062.ps tmp/4mk631355853062.png",intern=TRUE))
character(0)
> try(system("convert tmp/5xw581355853062.ps tmp/5xw581355853062.png",intern=TRUE))
character(0)
> try(system("convert tmp/61mni1355853062.ps tmp/61mni1355853062.png",intern=TRUE))
character(0)
> try(system("convert tmp/7k8ik1355853062.ps tmp/7k8ik1355853062.png",intern=TRUE))
character(0)
> try(system("convert tmp/8bten1355853062.ps tmp/8bten1355853062.png",intern=TRUE))
character(0)
> try(system("convert tmp/9b9nu1355853062.ps tmp/9b9nu1355853062.png",intern=TRUE))
character(0)
> try(system("convert tmp/102rau1355853062.ps tmp/102rau1355853062.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
21.699 1.426 23.112