R version 2.9.0 (2009-04-17)
Copyright (C) 2009 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(235.1
+ ,280.7
+ ,264.6
+ ,240.7
+ ,201.4
+ ,240.8
+ ,241.1
+ ,223.8
+ ,206.1
+ ,174.7
+ ,203.3
+ ,220.5
+ ,299.5
+ ,347.4
+ ,338.3
+ ,327.7
+ ,351.6
+ ,396.6
+ ,438.8
+ ,395.6
+ ,363.5
+ ,378.8
+ ,357
+ ,369
+ ,464.8
+ ,479.1
+ ,431.3
+ ,366.5
+ ,326.3
+ ,355.1
+ ,331.6
+ ,261.3
+ ,249
+ ,205.5
+ ,235.6
+ ,240.9
+ ,264.9
+ ,253.8
+ ,232.3
+ ,193.8
+ ,177
+ ,213.2
+ ,207.2
+ ,180.6
+ ,188.6
+ ,175.4
+ ,199
+ ,179.6
+ ,225.8
+ ,234
+ ,200.2
+ ,183.6
+ ,178.2
+ ,203.2
+ ,208.5
+ ,191.8
+ ,172.8
+ ,148
+ ,159.4
+ ,154.5
+ ,213.2
+ ,196.4
+ ,182.8
+ ,176.4
+ ,153.6
+ ,173.2
+ ,171
+ ,151.2
+ ,161.9
+ ,157.2
+ ,201.7
+ ,236.4
+ ,356.1
+ ,398.3
+ ,403.7
+ ,384.6
+ ,365.8
+ ,368.1
+ ,367.9
+ ,347
+ ,343.3
+ ,292.9
+ ,311.5
+ ,300.9
+ ,366.9
+ ,356.9
+ ,329.7
+ ,316.2
+ ,269
+ ,289.3
+ ,266.2
+ ,253.6
+ ,233.8
+ ,228.4
+ ,253.6
+ ,260.1
+ ,306.6
+ ,309.2
+ ,309.5
+ ,271
+ ,279.9
+ ,317.9
+ ,298.4
+ ,246.7
+ ,227.3
+ ,209.1
+ ,259.9
+ ,266
+ ,320.6
+ ,308.5
+ ,282.2
+ ,262.7
+ ,263.5
+ ,313.1
+ ,284.3
+ ,252.6
+ ,250.3
+ ,246.5
+ ,312.7
+ ,333.2
+ ,446.4
+ ,511.6
+ ,515.5
+ ,506.4
+ ,483.2
+ ,522.3
+ ,509.8
+ ,460.7
+ ,405.8
+ ,375
+ ,378.5
+ ,406.8
+ ,467.8
+ ,469.8
+ ,429.8
+ ,355.8
+ ,332.7
+ ,378
+ ,360.5
+ ,334.7
+ ,319.5
+ ,323.1
+ ,363.6
+ ,352.1
+ ,411.9
+ ,388.6
+ ,416.4
+ ,360.7
+ ,338
+ ,417.2
+ ,388.4
+ ,371.1
+ ,331.5
+ ,353.7
+ ,396.7
+ ,447
+ ,533.5
+ ,565.4
+ ,542.3
+ ,488.7
+ ,467.1
+ ,531.3
+ ,496.1
+ ,444
+ ,403.4
+ ,386.3
+ ,394.1
+ ,404.1
+ ,462.1
+ ,448.1
+ ,432.3
+ ,386.3
+ ,395.2
+ ,421.9
+ ,382.9
+ ,384.2
+ ,345.5
+ ,323.4
+ ,372.6
+ ,376
+ ,462.7
+ ,487
+ ,444.2
+ ,399.3
+ ,394.9
+ ,455.4
+ ,414
+ ,375.5
+ ,347
+ ,339.4
+ ,385.8
+ ,378.8
+ ,451.8
+ ,446.1
+ ,422.5
+ ,383.1
+ ,352.8
+ ,445.3
+ ,367.5
+ ,355.1
+ ,326.2
+ ,319.8
+ ,331.8
+ ,340.9
+ ,394.1
+ ,417.2
+ ,369.9
+ ,349.2
+ ,321.4
+ ,405.7
+ ,342.9
+ ,316.5
+ ,284.2
+ ,270.9
+ ,288.8
+ ,278.8
+ ,324.4
+ ,310.9
+ ,299
+ ,273
+ ,279.3
+ ,359.2
+ ,305
+ ,282.1
+ ,250.3
+ ,246.5
+ ,257.9
+ ,266.5
+ ,315.9
+ ,318.4
+ ,295.4
+ ,266.4
+ ,245.8
+ ,362.8
+ ,324.9
+ ,294.2
+ ,289.5
+ ,295.2
+ ,290.3
+ ,272
+ ,307.4
+ ,328.7
+ ,292.9
+ ,249.1
+ ,230.4
+ ,361.5
+ ,321.7
+ ,277.2
+ ,260.7
+ ,251
+ ,257.6
+ ,241.8
+ ,287.5
+ ,292.3
+ ,274.7
+ ,254.2
+ ,230
+ ,339
+ ,318.2
+ ,287
+ ,295.8
+ ,284
+ ,271
+ ,262.7
+ ,340.6
+ ,379.4
+ ,373.3
+ ,355.2
+ ,338.4
+ ,466.9
+ ,451
+ ,422
+ ,429.2
+ ,425.9
+ ,460.7
+ ,463.6
+ ,541.4
+ ,544.2
+ ,517.5
+ ,469.4
+ ,439.4
+ ,549
+ ,533
+ ,506.1
+ ,484
+ ,457
+ ,481.5
+ ,469.5
+ ,544.7
+ ,541.2
+ ,521.5
+ ,469.7
+ ,434.4
+ ,542.6
+ ,517.3
+ ,485.7
+ ,465.8
+ ,447
+ ,426.6
+ ,411.6
+ ,467.5
+ ,484.5
+ ,451.2
+ ,417.4
+ ,379.9
+ ,484.7
+ ,455
+ ,420.8
+ ,416.5
+ ,376.3
+ ,405.6
+ ,405.8
+ ,500.8
+ ,514
+ ,475.5
+ ,430.1
+ ,414.4
+ ,538
+ ,526
+ ,488.5
+ ,520.2
+ ,504.4
+ ,568.5
+ ,610.6
+ ,818
+ ,830.9
+ ,835.9
+ ,782
+ ,762.3
+ ,856.9
+ ,820.9
+ ,769.6
+ ,752.2
+ ,724.4
+ ,723.1
+ ,719.5
+ ,817.4
+ ,803.3
+ ,752.5
+ ,689
+ ,630.4
+ ,765.5
+ ,757.7
+ ,732.2
+ ,702.6
+ ,683.3
+ ,709.5
+ ,702.2
+ ,784.8
+ ,810.9
+ ,755.6
+ ,656.8
+ ,615.1
+ ,745.3
+ ,694.1
+ ,675.7
+ ,643.7
+ ,622.1
+ ,634.6
+ ,588
+ ,689.7
+ ,673.9
+ ,647.9
+ ,568.8
+ ,545.7
+ ,632.6
+ ,643.8
+ ,593.1
+ ,579.7
+ ,546
+ ,562.9
+ ,572.5)
+ ,dim=c(1
+ ,372)
+ ,dimnames=list(c('Unemployment')
+ ,1:372))
> y <- array(NA,dim=c(1,372),dimnames=list(c('Unemployment'),1:372))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par3 = 'Linear Trend'
> par2 = 'Include Monthly Dummies'
> par1 = '1'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: Write here your technical program description (don't use hard returns!)
> library(lattice)
> library(lmtest)
Loading required package: zoo
Attaching package: 'zoo'
The following object(s) are masked from package:base :
as.Date.numeric
> n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
> par1 <- as.numeric(par1)
> x <- t(y)
> k <- length(x[1,])
> n <- length(x[,1])
> x1 <- cbind(x[,par1], x[,1:k!=par1])
> mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
> colnames(x1) <- mycolnames #colnames(x)[par1]
> x <- x1
> if (par3 == 'First Differences'){
+ x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
+ for (i in 1:n-1) {
+ for (j in 1:k) {
+ x2[i,j] <- x[i+1,j] - x[i,j]
+ }
+ }
+ x <- x2
+ }
> if (par2 == 'Include Monthly Dummies'){
+ x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
+ for (i in 1:11){
+ x2[seq(i,n,12),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> if (par2 == 'Include Quarterly Dummies'){
+ x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
+ for (i in 1:3){
+ x2[seq(i,n,4),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> k <- length(x[1,])
> if (par3 == 'Linear Trend'){
+ x <- cbind(x, c(1:n))
+ colnames(x)[k+1] <- 't'
+ }
> x
Unemployment M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 235.1 1 0 0 0 0 0 0 0 0 0 0 1
2 280.7 0 1 0 0 0 0 0 0 0 0 0 2
3 264.6 0 0 1 0 0 0 0 0 0 0 0 3
4 240.7 0 0 0 1 0 0 0 0 0 0 0 4
5 201.4 0 0 0 0 1 0 0 0 0 0 0 5
6 240.8 0 0 0 0 0 1 0 0 0 0 0 6
7 241.1 0 0 0 0 0 0 1 0 0 0 0 7
8 223.8 0 0 0 0 0 0 0 1 0 0 0 8
9 206.1 0 0 0 0 0 0 0 0 1 0 0 9
10 174.7 0 0 0 0 0 0 0 0 0 1 0 10
11 203.3 0 0 0 0 0 0 0 0 0 0 1 11
12 220.5 0 0 0 0 0 0 0 0 0 0 0 12
13 299.5 1 0 0 0 0 0 0 0 0 0 0 13
14 347.4 0 1 0 0 0 0 0 0 0 0 0 14
15 338.3 0 0 1 0 0 0 0 0 0 0 0 15
16 327.7 0 0 0 1 0 0 0 0 0 0 0 16
17 351.6 0 0 0 0 1 0 0 0 0 0 0 17
18 396.6 0 0 0 0 0 1 0 0 0 0 0 18
19 438.8 0 0 0 0 0 0 1 0 0 0 0 19
20 395.6 0 0 0 0 0 0 0 1 0 0 0 20
21 363.5 0 0 0 0 0 0 0 0 1 0 0 21
22 378.8 0 0 0 0 0 0 0 0 0 1 0 22
23 357.0 0 0 0 0 0 0 0 0 0 0 1 23
24 369.0 0 0 0 0 0 0 0 0 0 0 0 24
25 464.8 1 0 0 0 0 0 0 0 0 0 0 25
26 479.1 0 1 0 0 0 0 0 0 0 0 0 26
27 431.3 0 0 1 0 0 0 0 0 0 0 0 27
28 366.5 0 0 0 1 0 0 0 0 0 0 0 28
29 326.3 0 0 0 0 1 0 0 0 0 0 0 29
30 355.1 0 0 0 0 0 1 0 0 0 0 0 30
31 331.6 0 0 0 0 0 0 1 0 0 0 0 31
32 261.3 0 0 0 0 0 0 0 1 0 0 0 32
33 249.0 0 0 0 0 0 0 0 0 1 0 0 33
34 205.5 0 0 0 0 0 0 0 0 0 1 0 34
35 235.6 0 0 0 0 0 0 0 0 0 0 1 35
36 240.9 0 0 0 0 0 0 0 0 0 0 0 36
37 264.9 1 0 0 0 0 0 0 0 0 0 0 37
38 253.8 0 1 0 0 0 0 0 0 0 0 0 38
39 232.3 0 0 1 0 0 0 0 0 0 0 0 39
40 193.8 0 0 0 1 0 0 0 0 0 0 0 40
41 177.0 0 0 0 0 1 0 0 0 0 0 0 41
42 213.2 0 0 0 0 0 1 0 0 0 0 0 42
43 207.2 0 0 0 0 0 0 1 0 0 0 0 43
44 180.6 0 0 0 0 0 0 0 1 0 0 0 44
45 188.6 0 0 0 0 0 0 0 0 1 0 0 45
46 175.4 0 0 0 0 0 0 0 0 0 1 0 46
47 199.0 0 0 0 0 0 0 0 0 0 0 1 47
48 179.6 0 0 0 0 0 0 0 0 0 0 0 48
49 225.8 1 0 0 0 0 0 0 0 0 0 0 49
50 234.0 0 1 0 0 0 0 0 0 0 0 0 50
51 200.2 0 0 1 0 0 0 0 0 0 0 0 51
52 183.6 0 0 0 1 0 0 0 0 0 0 0 52
53 178.2 0 0 0 0 1 0 0 0 0 0 0 53
54 203.2 0 0 0 0 0 1 0 0 0 0 0 54
55 208.5 0 0 0 0 0 0 1 0 0 0 0 55
56 191.8 0 0 0 0 0 0 0 1 0 0 0 56
57 172.8 0 0 0 0 0 0 0 0 1 0 0 57
58 148.0 0 0 0 0 0 0 0 0 0 1 0 58
59 159.4 0 0 0 0 0 0 0 0 0 0 1 59
60 154.5 0 0 0 0 0 0 0 0 0 0 0 60
61 213.2 1 0 0 0 0 0 0 0 0 0 0 61
62 196.4 0 1 0 0 0 0 0 0 0 0 0 62
63 182.8 0 0 1 0 0 0 0 0 0 0 0 63
64 176.4 0 0 0 1 0 0 0 0 0 0 0 64
65 153.6 0 0 0 0 1 0 0 0 0 0 0 65
66 173.2 0 0 0 0 0 1 0 0 0 0 0 66
67 171.0 0 0 0 0 0 0 1 0 0 0 0 67
68 151.2 0 0 0 0 0 0 0 1 0 0 0 68
69 161.9 0 0 0 0 0 0 0 0 1 0 0 69
70 157.2 0 0 0 0 0 0 0 0 0 1 0 70
71 201.7 0 0 0 0 0 0 0 0 0 0 1 71
72 236.4 0 0 0 0 0 0 0 0 0 0 0 72
73 356.1 1 0 0 0 0 0 0 0 0 0 0 73
74 398.3 0 1 0 0 0 0 0 0 0 0 0 74
75 403.7 0 0 1 0 0 0 0 0 0 0 0 75
76 384.6 0 0 0 1 0 0 0 0 0 0 0 76
77 365.8 0 0 0 0 1 0 0 0 0 0 0 77
78 368.1 0 0 0 0 0 1 0 0 0 0 0 78
79 367.9 0 0 0 0 0 0 1 0 0 0 0 79
80 347.0 0 0 0 0 0 0 0 1 0 0 0 80
81 343.3 0 0 0 0 0 0 0 0 1 0 0 81
82 292.9 0 0 0 0 0 0 0 0 0 1 0 82
83 311.5 0 0 0 0 0 0 0 0 0 0 1 83
84 300.9 0 0 0 0 0 0 0 0 0 0 0 84
85 366.9 1 0 0 0 0 0 0 0 0 0 0 85
86 356.9 0 1 0 0 0 0 0 0 0 0 0 86
87 329.7 0 0 1 0 0 0 0 0 0 0 0 87
88 316.2 0 0 0 1 0 0 0 0 0 0 0 88
89 269.0 0 0 0 0 1 0 0 0 0 0 0 89
90 289.3 0 0 0 0 0 1 0 0 0 0 0 90
91 266.2 0 0 0 0 0 0 1 0 0 0 0 91
92 253.6 0 0 0 0 0 0 0 1 0 0 0 92
93 233.8 0 0 0 0 0 0 0 0 1 0 0 93
94 228.4 0 0 0 0 0 0 0 0 0 1 0 94
95 253.6 0 0 0 0 0 0 0 0 0 0 1 95
96 260.1 0 0 0 0 0 0 0 0 0 0 0 96
97 306.6 1 0 0 0 0 0 0 0 0 0 0 97
98 309.2 0 1 0 0 0 0 0 0 0 0 0 98
99 309.5 0 0 1 0 0 0 0 0 0 0 0 99
100 271.0 0 0 0 1 0 0 0 0 0 0 0 100
101 279.9 0 0 0 0 1 0 0 0 0 0 0 101
102 317.9 0 0 0 0 0 1 0 0 0 0 0 102
103 298.4 0 0 0 0 0 0 1 0 0 0 0 103
104 246.7 0 0 0 0 0 0 0 1 0 0 0 104
105 227.3 0 0 0 0 0 0 0 0 1 0 0 105
106 209.1 0 0 0 0 0 0 0 0 0 1 0 106
107 259.9 0 0 0 0 0 0 0 0 0 0 1 107
108 266.0 0 0 0 0 0 0 0 0 0 0 0 108
109 320.6 1 0 0 0 0 0 0 0 0 0 0 109
110 308.5 0 1 0 0 0 0 0 0 0 0 0 110
111 282.2 0 0 1 0 0 0 0 0 0 0 0 111
112 262.7 0 0 0 1 0 0 0 0 0 0 0 112
113 263.5 0 0 0 0 1 0 0 0 0 0 0 113
114 313.1 0 0 0 0 0 1 0 0 0 0 0 114
115 284.3 0 0 0 0 0 0 1 0 0 0 0 115
116 252.6 0 0 0 0 0 0 0 1 0 0 0 116
117 250.3 0 0 0 0 0 0 0 0 1 0 0 117
118 246.5 0 0 0 0 0 0 0 0 0 1 0 118
119 312.7 0 0 0 0 0 0 0 0 0 0 1 119
120 333.2 0 0 0 0 0 0 0 0 0 0 0 120
121 446.4 1 0 0 0 0 0 0 0 0 0 0 121
122 511.6 0 1 0 0 0 0 0 0 0 0 0 122
123 515.5 0 0 1 0 0 0 0 0 0 0 0 123
124 506.4 0 0 0 1 0 0 0 0 0 0 0 124
125 483.2 0 0 0 0 1 0 0 0 0 0 0 125
126 522.3 0 0 0 0 0 1 0 0 0 0 0 126
127 509.8 0 0 0 0 0 0 1 0 0 0 0 127
128 460.7 0 0 0 0 0 0 0 1 0 0 0 128
129 405.8 0 0 0 0 0 0 0 0 1 0 0 129
130 375.0 0 0 0 0 0 0 0 0 0 1 0 130
131 378.5 0 0 0 0 0 0 0 0 0 0 1 131
132 406.8 0 0 0 0 0 0 0 0 0 0 0 132
133 467.8 1 0 0 0 0 0 0 0 0 0 0 133
134 469.8 0 1 0 0 0 0 0 0 0 0 0 134
135 429.8 0 0 1 0 0 0 0 0 0 0 0 135
136 355.8 0 0 0 1 0 0 0 0 0 0 0 136
137 332.7 0 0 0 0 1 0 0 0 0 0 0 137
138 378.0 0 0 0 0 0 1 0 0 0 0 0 138
139 360.5 0 0 0 0 0 0 1 0 0 0 0 139
140 334.7 0 0 0 0 0 0 0 1 0 0 0 140
141 319.5 0 0 0 0 0 0 0 0 1 0 0 141
142 323.1 0 0 0 0 0 0 0 0 0 1 0 142
143 363.6 0 0 0 0 0 0 0 0 0 0 1 143
144 352.1 0 0 0 0 0 0 0 0 0 0 0 144
145 411.9 1 0 0 0 0 0 0 0 0 0 0 145
146 388.6 0 1 0 0 0 0 0 0 0 0 0 146
147 416.4 0 0 1 0 0 0 0 0 0 0 0 147
148 360.7 0 0 0 1 0 0 0 0 0 0 0 148
149 338.0 0 0 0 0 1 0 0 0 0 0 0 149
150 417.2 0 0 0 0 0 1 0 0 0 0 0 150
151 388.4 0 0 0 0 0 0 1 0 0 0 0 151
152 371.1 0 0 0 0 0 0 0 1 0 0 0 152
153 331.5 0 0 0 0 0 0 0 0 1 0 0 153
154 353.7 0 0 0 0 0 0 0 0 0 1 0 154
155 396.7 0 0 0 0 0 0 0 0 0 0 1 155
156 447.0 0 0 0 0 0 0 0 0 0 0 0 156
157 533.5 1 0 0 0 0 0 0 0 0 0 0 157
158 565.4 0 1 0 0 0 0 0 0 0 0 0 158
159 542.3 0 0 1 0 0 0 0 0 0 0 0 159
160 488.7 0 0 0 1 0 0 0 0 0 0 0 160
161 467.1 0 0 0 0 1 0 0 0 0 0 0 161
162 531.3 0 0 0 0 0 1 0 0 0 0 0 162
163 496.1 0 0 0 0 0 0 1 0 0 0 0 163
164 444.0 0 0 0 0 0 0 0 1 0 0 0 164
165 403.4 0 0 0 0 0 0 0 0 1 0 0 165
166 386.3 0 0 0 0 0 0 0 0 0 1 0 166
167 394.1 0 0 0 0 0 0 0 0 0 0 1 167
168 404.1 0 0 0 0 0 0 0 0 0 0 0 168
169 462.1 1 0 0 0 0 0 0 0 0 0 0 169
170 448.1 0 1 0 0 0 0 0 0 0 0 0 170
171 432.3 0 0 1 0 0 0 0 0 0 0 0 171
172 386.3 0 0 0 1 0 0 0 0 0 0 0 172
173 395.2 0 0 0 0 1 0 0 0 0 0 0 173
174 421.9 0 0 0 0 0 1 0 0 0 0 0 174
175 382.9 0 0 0 0 0 0 1 0 0 0 0 175
176 384.2 0 0 0 0 0 0 0 1 0 0 0 176
177 345.5 0 0 0 0 0 0 0 0 1 0 0 177
178 323.4 0 0 0 0 0 0 0 0 0 1 0 178
179 372.6 0 0 0 0 0 0 0 0 0 0 1 179
180 376.0 0 0 0 0 0 0 0 0 0 0 0 180
181 462.7 1 0 0 0 0 0 0 0 0 0 0 181
182 487.0 0 1 0 0 0 0 0 0 0 0 0 182
183 444.2 0 0 1 0 0 0 0 0 0 0 0 183
184 399.3 0 0 0 1 0 0 0 0 0 0 0 184
185 394.9 0 0 0 0 1 0 0 0 0 0 0 185
186 455.4 0 0 0 0 0 1 0 0 0 0 0 186
187 414.0 0 0 0 0 0 0 1 0 0 0 0 187
188 375.5 0 0 0 0 0 0 0 1 0 0 0 188
189 347.0 0 0 0 0 0 0 0 0 1 0 0 189
190 339.4 0 0 0 0 0 0 0 0 0 1 0 190
191 385.8 0 0 0 0 0 0 0 0 0 0 1 191
192 378.8 0 0 0 0 0 0 0 0 0 0 0 192
193 451.8 1 0 0 0 0 0 0 0 0 0 0 193
194 446.1 0 1 0 0 0 0 0 0 0 0 0 194
195 422.5 0 0 1 0 0 0 0 0 0 0 0 195
196 383.1 0 0 0 1 0 0 0 0 0 0 0 196
197 352.8 0 0 0 0 1 0 0 0 0 0 0 197
198 445.3 0 0 0 0 0 1 0 0 0 0 0 198
199 367.5 0 0 0 0 0 0 1 0 0 0 0 199
200 355.1 0 0 0 0 0 0 0 1 0 0 0 200
201 326.2 0 0 0 0 0 0 0 0 1 0 0 201
202 319.8 0 0 0 0 0 0 0 0 0 1 0 202
203 331.8 0 0 0 0 0 0 0 0 0 0 1 203
204 340.9 0 0 0 0 0 0 0 0 0 0 0 204
205 394.1 1 0 0 0 0 0 0 0 0 0 0 205
206 417.2 0 1 0 0 0 0 0 0 0 0 0 206
207 369.9 0 0 1 0 0 0 0 0 0 0 0 207
208 349.2 0 0 0 1 0 0 0 0 0 0 0 208
209 321.4 0 0 0 0 1 0 0 0 0 0 0 209
210 405.7 0 0 0 0 0 1 0 0 0 0 0 210
211 342.9 0 0 0 0 0 0 1 0 0 0 0 211
212 316.5 0 0 0 0 0 0 0 1 0 0 0 212
213 284.2 0 0 0 0 0 0 0 0 1 0 0 213
214 270.9 0 0 0 0 0 0 0 0 0 1 0 214
215 288.8 0 0 0 0 0 0 0 0 0 0 1 215
216 278.8 0 0 0 0 0 0 0 0 0 0 0 216
217 324.4 1 0 0 0 0 0 0 0 0 0 0 217
218 310.9 0 1 0 0 0 0 0 0 0 0 0 218
219 299.0 0 0 1 0 0 0 0 0 0 0 0 219
220 273.0 0 0 0 1 0 0 0 0 0 0 0 220
221 279.3 0 0 0 0 1 0 0 0 0 0 0 221
222 359.2 0 0 0 0 0 1 0 0 0 0 0 222
223 305.0 0 0 0 0 0 0 1 0 0 0 0 223
224 282.1 0 0 0 0 0 0 0 1 0 0 0 224
225 250.3 0 0 0 0 0 0 0 0 1 0 0 225
226 246.5 0 0 0 0 0 0 0 0 0 1 0 226
227 257.9 0 0 0 0 0 0 0 0 0 0 1 227
228 266.5 0 0 0 0 0 0 0 0 0 0 0 228
229 315.9 1 0 0 0 0 0 0 0 0 0 0 229
230 318.4 0 1 0 0 0 0 0 0 0 0 0 230
231 295.4 0 0 1 0 0 0 0 0 0 0 0 231
232 266.4 0 0 0 1 0 0 0 0 0 0 0 232
233 245.8 0 0 0 0 1 0 0 0 0 0 0 233
234 362.8 0 0 0 0 0 1 0 0 0 0 0 234
235 324.9 0 0 0 0 0 0 1 0 0 0 0 235
236 294.2 0 0 0 0 0 0 0 1 0 0 0 236
237 289.5 0 0 0 0 0 0 0 0 1 0 0 237
238 295.2 0 0 0 0 0 0 0 0 0 1 0 238
239 290.3 0 0 0 0 0 0 0 0 0 0 1 239
240 272.0 0 0 0 0 0 0 0 0 0 0 0 240
241 307.4 1 0 0 0 0 0 0 0 0 0 0 241
242 328.7 0 1 0 0 0 0 0 0 0 0 0 242
243 292.9 0 0 1 0 0 0 0 0 0 0 0 243
244 249.1 0 0 0 1 0 0 0 0 0 0 0 244
245 230.4 0 0 0 0 1 0 0 0 0 0 0 245
246 361.5 0 0 0 0 0 1 0 0 0 0 0 246
247 321.7 0 0 0 0 0 0 1 0 0 0 0 247
248 277.2 0 0 0 0 0 0 0 1 0 0 0 248
249 260.7 0 0 0 0 0 0 0 0 1 0 0 249
250 251.0 0 0 0 0 0 0 0 0 0 1 0 250
251 257.6 0 0 0 0 0 0 0 0 0 0 1 251
252 241.8 0 0 0 0 0 0 0 0 0 0 0 252
253 287.5 1 0 0 0 0 0 0 0 0 0 0 253
254 292.3 0 1 0 0 0 0 0 0 0 0 0 254
255 274.7 0 0 1 0 0 0 0 0 0 0 0 255
256 254.2 0 0 0 1 0 0 0 0 0 0 0 256
257 230.0 0 0 0 0 1 0 0 0 0 0 0 257
258 339.0 0 0 0 0 0 1 0 0 0 0 0 258
259 318.2 0 0 0 0 0 0 1 0 0 0 0 259
260 287.0 0 0 0 0 0 0 0 1 0 0 0 260
261 295.8 0 0 0 0 0 0 0 0 1 0 0 261
262 284.0 0 0 0 0 0 0 0 0 0 1 0 262
263 271.0 0 0 0 0 0 0 0 0 0 0 1 263
264 262.7 0 0 0 0 0 0 0 0 0 0 0 264
265 340.6 1 0 0 0 0 0 0 0 0 0 0 265
266 379.4 0 1 0 0 0 0 0 0 0 0 0 266
267 373.3 0 0 1 0 0 0 0 0 0 0 0 267
268 355.2 0 0 0 1 0 0 0 0 0 0 0 268
269 338.4 0 0 0 0 1 0 0 0 0 0 0 269
270 466.9 0 0 0 0 0 1 0 0 0 0 0 270
271 451.0 0 0 0 0 0 0 1 0 0 0 0 271
272 422.0 0 0 0 0 0 0 0 1 0 0 0 272
273 429.2 0 0 0 0 0 0 0 0 1 0 0 273
274 425.9 0 0 0 0 0 0 0 0 0 1 0 274
275 460.7 0 0 0 0 0 0 0 0 0 0 1 275
276 463.6 0 0 0 0 0 0 0 0 0 0 0 276
277 541.4 1 0 0 0 0 0 0 0 0 0 0 277
278 544.2 0 1 0 0 0 0 0 0 0 0 0 278
279 517.5 0 0 1 0 0 0 0 0 0 0 0 279
280 469.4 0 0 0 1 0 0 0 0 0 0 0 280
281 439.4 0 0 0 0 1 0 0 0 0 0 0 281
282 549.0 0 0 0 0 0 1 0 0 0 0 0 282
283 533.0 0 0 0 0 0 0 1 0 0 0 0 283
284 506.1 0 0 0 0 0 0 0 1 0 0 0 284
285 484.0 0 0 0 0 0 0 0 0 1 0 0 285
286 457.0 0 0 0 0 0 0 0 0 0 1 0 286
287 481.5 0 0 0 0 0 0 0 0 0 0 1 287
288 469.5 0 0 0 0 0 0 0 0 0 0 0 288
289 544.7 1 0 0 0 0 0 0 0 0 0 0 289
290 541.2 0 1 0 0 0 0 0 0 0 0 0 290
291 521.5 0 0 1 0 0 0 0 0 0 0 0 291
292 469.7 0 0 0 1 0 0 0 0 0 0 0 292
293 434.4 0 0 0 0 1 0 0 0 0 0 0 293
294 542.6 0 0 0 0 0 1 0 0 0 0 0 294
295 517.3 0 0 0 0 0 0 1 0 0 0 0 295
296 485.7 0 0 0 0 0 0 0 1 0 0 0 296
297 465.8 0 0 0 0 0 0 0 0 1 0 0 297
298 447.0 0 0 0 0 0 0 0 0 0 1 0 298
299 426.6 0 0 0 0 0 0 0 0 0 0 1 299
300 411.6 0 0 0 0 0 0 0 0 0 0 0 300
301 467.5 1 0 0 0 0 0 0 0 0 0 0 301
302 484.5 0 1 0 0 0 0 0 0 0 0 0 302
303 451.2 0 0 1 0 0 0 0 0 0 0 0 303
304 417.4 0 0 0 1 0 0 0 0 0 0 0 304
305 379.9 0 0 0 0 1 0 0 0 0 0 0 305
306 484.7 0 0 0 0 0 1 0 0 0 0 0 306
307 455.0 0 0 0 0 0 0 1 0 0 0 0 307
308 420.8 0 0 0 0 0 0 0 1 0 0 0 308
309 416.5 0 0 0 0 0 0 0 0 1 0 0 309
310 376.3 0 0 0 0 0 0 0 0 0 1 0 310
311 405.6 0 0 0 0 0 0 0 0 0 0 1 311
312 405.8 0 0 0 0 0 0 0 0 0 0 0 312
313 500.8 1 0 0 0 0 0 0 0 0 0 0 313
314 514.0 0 1 0 0 0 0 0 0 0 0 0 314
315 475.5 0 0 1 0 0 0 0 0 0 0 0 315
316 430.1 0 0 0 1 0 0 0 0 0 0 0 316
317 414.4 0 0 0 0 1 0 0 0 0 0 0 317
318 538.0 0 0 0 0 0 1 0 0 0 0 0 318
319 526.0 0 0 0 0 0 0 1 0 0 0 0 319
320 488.5 0 0 0 0 0 0 0 1 0 0 0 320
321 520.2 0 0 0 0 0 0 0 0 1 0 0 321
322 504.4 0 0 0 0 0 0 0 0 0 1 0 322
323 568.5 0 0 0 0 0 0 0 0 0 0 1 323
324 610.6 0 0 0 0 0 0 0 0 0 0 0 324
325 818.0 1 0 0 0 0 0 0 0 0 0 0 325
326 830.9 0 1 0 0 0 0 0 0 0 0 0 326
327 835.9 0 0 1 0 0 0 0 0 0 0 0 327
328 782.0 0 0 0 1 0 0 0 0 0 0 0 328
329 762.3 0 0 0 0 1 0 0 0 0 0 0 329
330 856.9 0 0 0 0 0 1 0 0 0 0 0 330
331 820.9 0 0 0 0 0 0 1 0 0 0 0 331
332 769.6 0 0 0 0 0 0 0 1 0 0 0 332
333 752.2 0 0 0 0 0 0 0 0 1 0 0 333
334 724.4 0 0 0 0 0 0 0 0 0 1 0 334
335 723.1 0 0 0 0 0 0 0 0 0 0 1 335
336 719.5 0 0 0 0 0 0 0 0 0 0 0 336
337 817.4 1 0 0 0 0 0 0 0 0 0 0 337
338 803.3 0 1 0 0 0 0 0 0 0 0 0 338
339 752.5 0 0 1 0 0 0 0 0 0 0 0 339
340 689.0 0 0 0 1 0 0 0 0 0 0 0 340
341 630.4 0 0 0 0 1 0 0 0 0 0 0 341
342 765.5 0 0 0 0 0 1 0 0 0 0 0 342
343 757.7 0 0 0 0 0 0 1 0 0 0 0 343
344 732.2 0 0 0 0 0 0 0 1 0 0 0 344
345 702.6 0 0 0 0 0 0 0 0 1 0 0 345
346 683.3 0 0 0 0 0 0 0 0 0 1 0 346
347 709.5 0 0 0 0 0 0 0 0 0 0 1 347
348 702.2 0 0 0 0 0 0 0 0 0 0 0 348
349 784.8 1 0 0 0 0 0 0 0 0 0 0 349
350 810.9 0 1 0 0 0 0 0 0 0 0 0 350
351 755.6 0 0 1 0 0 0 0 0 0 0 0 351
352 656.8 0 0 0 1 0 0 0 0 0 0 0 352
353 615.1 0 0 0 0 1 0 0 0 0 0 0 353
354 745.3 0 0 0 0 0 1 0 0 0 0 0 354
355 694.1 0 0 0 0 0 0 1 0 0 0 0 355
356 675.7 0 0 0 0 0 0 0 1 0 0 0 356
357 643.7 0 0 0 0 0 0 0 0 1 0 0 357
358 622.1 0 0 0 0 0 0 0 0 0 1 0 358
359 634.6 0 0 0 0 0 0 0 0 0 0 1 359
360 588.0 0 0 0 0 0 0 0 0 0 0 0 360
361 689.7 1 0 0 0 0 0 0 0 0 0 0 361
362 673.9 0 1 0 0 0 0 0 0 0 0 0 362
363 647.9 0 0 1 0 0 0 0 0 0 0 0 363
364 568.8 0 0 0 1 0 0 0 0 0 0 0 364
365 545.7 0 0 0 0 1 0 0 0 0 0 0 365
366 632.6 0 0 0 0 0 1 0 0 0 0 0 366
367 643.8 0 0 0 0 0 0 1 0 0 0 0 367
368 593.1 0 0 0 0 0 0 0 1 0 0 0 368
369 579.7 0 0 0 0 0 0 0 0 1 0 0 369
370 546.0 0 0 0 0 0 0 0 0 0 1 0 370
371 562.9 0 0 0 0 0 0 0 0 0 0 1 371
372 572.5 0 0 0 0 0 0 0 0 0 0 0 372
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) M1 M2 M3 M4 M5
176.343 72.242 81.119 57.833 17.891 -3.667
M6 M7 M8 M9 M10 M11
68.040 44.250 12.086 -6.040 -22.501 -1.449
t
1.019
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-223.996 -68.016 -2.822 49.924 276.237
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 176.34312 21.58250 8.171 5.3e-15 ***
M1 72.24158 27.12567 2.663 0.00809 **
M2 81.11933 27.12464 2.991 0.00298 **
M3 57.83256 27.12371 2.132 0.03367 *
M4 17.89095 27.12288 0.660 0.50992
M5 -3.66679 27.12214 -0.135 0.89253
M6 68.03998 27.12150 2.509 0.01256 *
M7 44.24999 27.12096 1.632 0.10365
M8 12.08580 27.12052 0.446 0.65613
M9 -6.03969 27.12018 -0.223 0.82390
M10 -22.50065 27.11993 -0.830 0.40728
M11 -1.44871 27.11979 -0.053 0.95743
t 1.01903 0.05158 19.758 < 2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 106.8 on 359 degrees of freedom
Multiple R-squared: 0.5411, Adjusted R-squared: 0.5258
F-statistic: 35.28 on 12 and 359 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,] 3.991785e-04 7.983570e-04 9.996008e-01
[2,] 5.459917e-03 1.091983e-02 9.945401e-01
[3,] 4.117538e-03 8.235076e-03 9.958825e-01
[4,] 6.375702e-03 1.275140e-02 9.936243e-01
[5,] 3.381282e-03 6.762564e-03 9.966187e-01
[6,] 1.357249e-03 2.714499e-03 9.986428e-01
[7,] 1.146449e-03 2.292899e-03 9.988536e-01
[8,] 4.207208e-04 8.414415e-04 9.995793e-01
[9,] 1.456653e-04 2.913306e-04 9.998543e-01
[10,] 4.856151e-05 9.712302e-05 9.999514e-01
[11,] 2.187073e-05 4.374147e-05 9.999781e-01
[12,] 1.938237e-05 3.876475e-05 9.999806e-01
[13,] 5.353466e-05 1.070693e-04 9.999465e-01
[14,] 1.894436e-04 3.788872e-04 9.998106e-01
[15,] 4.447664e-04 8.895327e-04 9.995552e-01
[16,] 1.680611e-03 3.361221e-03 9.983194e-01
[17,] 6.762854e-03 1.352571e-02 9.932371e-01
[18,] 1.221292e-02 2.442584e-02 9.877871e-01
[19,] 2.547334e-02 5.094667e-02 9.745267e-01
[20,] 3.140855e-02 6.281710e-02 9.685914e-01
[21,] 3.771295e-02 7.542591e-02 9.622870e-01
[22,] 5.800570e-02 1.160114e-01 9.419943e-01
[23,] 1.024910e-01 2.049820e-01 8.975090e-01
[24,] 1.387263e-01 2.774525e-01 8.612737e-01
[25,] 1.695035e-01 3.390069e-01 8.304965e-01
[26,] 1.886705e-01 3.773410e-01 8.113295e-01
[27,] 2.005142e-01 4.010284e-01 7.994858e-01
[28,] 2.135317e-01 4.270635e-01 7.864683e-01
[29,] 2.082083e-01 4.164167e-01 7.917917e-01
[30,] 1.857450e-01 3.714900e-01 8.142550e-01
[31,] 1.615205e-01 3.230411e-01 8.384795e-01
[32,] 1.361637e-01 2.723274e-01 8.638363e-01
[33,] 1.206461e-01 2.412923e-01 8.793539e-01
[34,] 1.033167e-01 2.066333e-01 8.966833e-01
[35,] 9.043246e-02 1.808649e-01 9.095675e-01
[36,] 8.017690e-02 1.603538e-01 9.198231e-01
[37,] 6.677307e-02 1.335461e-01 9.332269e-01
[38,] 5.357611e-02 1.071522e-01 9.464239e-01
[39,] 4.385962e-02 8.771924e-02 9.561404e-01
[40,] 3.508238e-02 7.016475e-02 9.649176e-01
[41,] 2.681128e-02 5.362256e-02 9.731887e-01
[42,] 2.038222e-02 4.076444e-02 9.796178e-01
[43,] 1.548414e-02 3.096829e-02 9.845159e-01
[44,] 1.173797e-02 2.347594e-02 9.882620e-01
[45,] 8.971493e-03 1.794299e-02 9.910285e-01
[46,] 6.598154e-03 1.319631e-02 9.934018e-01
[47,] 5.225848e-03 1.045170e-02 9.947742e-01
[48,] 3.953849e-03 7.907699e-03 9.960462e-01
[49,] 2.817605e-03 5.635211e-03 9.971824e-01
[50,] 2.002056e-03 4.004113e-03 9.979979e-01
[51,] 1.505017e-03 3.010033e-03 9.984950e-01
[52,] 1.114071e-03 2.228142e-03 9.988859e-01
[53,] 7.896167e-04 1.579233e-03 9.992104e-01
[54,] 5.406139e-04 1.081228e-03 9.994594e-01
[55,] 3.712143e-04 7.424287e-04 9.996288e-01
[56,] 2.727382e-04 5.454765e-04 9.997273e-01
[57,] 2.331913e-04 4.663825e-04 9.997668e-01
[58,] 4.118396e-04 8.236793e-04 9.995882e-01
[59,] 8.765142e-04 1.753028e-03 9.991235e-01
[60,] 2.194295e-03 4.388590e-03 9.978057e-01
[61,] 4.899728e-03 9.799456e-03 9.951003e-01
[62,] 9.050974e-03 1.810195e-02 9.909490e-01
[63,] 1.137394e-02 2.274787e-02 9.886261e-01
[64,] 1.358488e-02 2.716976e-02 9.864151e-01
[65,] 1.672882e-02 3.345763e-02 9.832712e-01
[66,] 2.073804e-02 4.147608e-02 9.792620e-01
[67,] 2.082970e-02 4.165940e-02 9.791703e-01
[68,] 2.050928e-02 4.101855e-02 9.794907e-01
[69,] 1.866329e-02 3.732658e-02 9.813367e-01
[70,] 1.718755e-02 3.437509e-02 9.828125e-01
[71,] 1.440515e-02 2.881031e-02 9.855948e-01
[72,] 1.177998e-02 2.355996e-02 9.882200e-01
[73,] 9.928386e-03 1.985677e-02 9.900716e-01
[74,] 7.809531e-03 1.561906e-02 9.921905e-01
[75,] 6.022653e-03 1.204531e-02 9.939773e-01
[76,] 4.580369e-03 9.160739e-03 9.954196e-01
[77,] 3.458107e-03 6.916213e-03 9.965419e-01
[78,] 2.585248e-03 5.170496e-03 9.974148e-01
[79,] 1.931430e-03 3.862860e-03 9.980686e-01
[80,] 1.440476e-03 2.880951e-03 9.985595e-01
[81,] 1.069195e-03 2.138391e-03 9.989308e-01
[82,] 7.791116e-04 1.558223e-03 9.992209e-01
[83,] 5.631928e-04 1.126386e-03 9.994368e-01
[84,] 4.067110e-04 8.134219e-04 9.995933e-01
[85,] 2.895536e-04 5.791072e-04 9.997104e-01
[86,] 2.126651e-04 4.253303e-04 9.997873e-01
[87,] 1.571402e-04 3.142804e-04 9.998429e-01
[88,] 1.112534e-04 2.225067e-04 9.998887e-01
[89,] 7.728686e-05 1.545737e-04 9.999227e-01
[90,] 5.349691e-05 1.069938e-04 9.999465e-01
[91,] 3.678746e-05 7.357491e-05 9.999632e-01
[92,] 2.539373e-05 5.078747e-05 9.999746e-01
[93,] 1.743979e-05 3.487957e-05 9.999826e-01
[94,] 1.184134e-05 2.368269e-05 9.999882e-01
[95,] 7.966191e-06 1.593238e-05 9.999920e-01
[96,] 5.367555e-06 1.073511e-05 9.999946e-01
[97,] 3.541271e-06 7.082543e-06 9.999965e-01
[98,] 2.321893e-06 4.643787e-06 9.999977e-01
[99,] 1.571963e-06 3.143926e-06 9.999984e-01
[100,] 1.021049e-06 2.042098e-06 9.999990e-01
[101,] 6.591092e-07 1.318218e-06 9.999993e-01
[102,] 4.227043e-07 8.454087e-07 9.999996e-01
[103,] 2.759551e-07 5.519102e-07 9.999997e-01
[104,] 2.153307e-07 4.306614e-07 9.999998e-01
[105,] 1.860487e-07 3.720973e-07 9.999998e-01
[106,] 2.706025e-07 5.412050e-07 9.999997e-01
[107,] 8.081169e-07 1.616234e-06 9.999992e-01
[108,] 3.062428e-06 6.124856e-06 9.999969e-01
[109,] 1.343201e-05 2.686403e-05 9.999866e-01
[110,] 4.466555e-05 8.933110e-05 9.999553e-01
[111,] 1.197760e-04 2.395520e-04 9.998802e-01
[112,] 2.800730e-04 5.601461e-04 9.997199e-01
[113,] 4.963992e-04 9.927983e-04 9.995036e-01
[114,] 5.936114e-04 1.187223e-03 9.994064e-01
[115,] 6.388656e-04 1.277731e-03 9.993611e-01
[116,] 6.048981e-04 1.209796e-03 9.993951e-01
[117,] 6.531668e-04 1.306334e-03 9.993468e-01
[118,] 6.652422e-04 1.330484e-03 9.993348e-01
[119,] 6.376682e-04 1.275336e-03 9.993623e-01
[120,] 5.591770e-04 1.118354e-03 9.994408e-01
[121,] 4.445372e-04 8.890744e-04 9.995555e-01
[122,] 3.529306e-04 7.058612e-04 9.996471e-01
[123,] 2.651718e-04 5.303437e-04 9.997348e-01
[124,] 2.003351e-04 4.006703e-04 9.997997e-01
[125,] 1.514782e-04 3.029564e-04 9.998485e-01
[126,] 1.145221e-04 2.290443e-04 9.998855e-01
[127,] 8.970276e-05 1.794055e-04 9.999103e-01
[128,] 7.435573e-05 1.487115e-04 9.999256e-01
[129,] 5.874408e-05 1.174882e-04 9.999413e-01
[130,] 4.476399e-05 8.952797e-05 9.999552e-01
[131,] 3.316804e-05 6.633608e-05 9.999668e-01
[132,] 2.636723e-05 5.273446e-05 9.999736e-01
[133,] 2.035122e-05 4.070245e-05 9.999796e-01
[134,] 1.574965e-05 3.149931e-05 9.999843e-01
[135,] 1.212650e-05 2.425301e-05 9.999879e-01
[136,] 9.126001e-06 1.825200e-05 9.999909e-01
[137,] 7.147853e-06 1.429571e-05 9.999929e-01
[138,] 5.277628e-06 1.055526e-05 9.999947e-01
[139,] 4.406404e-06 8.812808e-06 9.999956e-01
[140,] 4.124997e-06 8.249994e-06 9.999959e-01
[141,] 5.641322e-06 1.128264e-05 9.999944e-01
[142,] 8.984986e-06 1.796997e-05 9.999910e-01
[143,] 1.810134e-05 3.620267e-05 9.999819e-01
[144,] 3.498359e-05 6.996718e-05 9.999650e-01
[145,] 5.713911e-05 1.142782e-04 9.999429e-01
[146,] 9.318572e-05 1.863714e-04 9.999068e-01
[147,] 1.478827e-04 2.957654e-04 9.998521e-01
[148,] 2.063180e-04 4.126359e-04 9.997937e-01
[149,] 2.480518e-04 4.961036e-04 9.997519e-01
[150,] 2.612049e-04 5.224098e-04 9.997388e-01
[151,] 2.764528e-04 5.529056e-04 9.997235e-01
[152,] 2.789449e-04 5.578898e-04 9.997211e-01
[153,] 3.004060e-04 6.008119e-04 9.996996e-01
[154,] 2.990310e-04 5.980620e-04 9.997010e-01
[155,] 2.819456e-04 5.638913e-04 9.997181e-01
[156,] 2.794314e-04 5.588627e-04 9.997206e-01
[157,] 2.834838e-04 5.669676e-04 9.997165e-01
[158,] 3.253320e-04 6.506640e-04 9.996747e-01
[159,] 2.889902e-04 5.779804e-04 9.997110e-01
[160,] 2.632399e-04 5.264798e-04 9.997368e-01
[161,] 2.561812e-04 5.123623e-04 9.997438e-01
[162,] 2.373335e-04 4.746671e-04 9.997627e-01
[163,] 2.198351e-04 4.396702e-04 9.997802e-01
[164,] 2.234738e-04 4.469476e-04 9.997765e-01
[165,] 2.391894e-04 4.783787e-04 9.997608e-01
[166,] 2.615803e-04 5.231607e-04 9.997384e-01
[167,] 3.157300e-04 6.314599e-04 9.996843e-01
[168,] 3.633020e-04 7.266040e-04 9.996367e-01
[169,] 4.309606e-04 8.619211e-04 9.995690e-01
[170,] 5.763478e-04 1.152696e-03 9.994237e-01
[171,] 6.240925e-04 1.248185e-03 9.993759e-01
[172,] 6.654463e-04 1.330893e-03 9.993346e-01
[173,] 7.061806e-04 1.412361e-03 9.992938e-01
[174,] 7.257548e-04 1.451510e-03 9.992742e-01
[175,] 7.739410e-04 1.547882e-03 9.992261e-01
[176,] 9.562546e-04 1.912509e-03 9.990437e-01
[177,] 1.208457e-03 2.416913e-03 9.987915e-01
[178,] 1.461129e-03 2.922259e-03 9.985389e-01
[179,] 1.722647e-03 3.445295e-03 9.982774e-01
[180,] 2.124320e-03 4.248639e-03 9.978757e-01
[181,] 2.769511e-03 5.539023e-03 9.972305e-01
[182,] 3.707169e-03 7.414338e-03 9.962928e-01
[183,] 4.329541e-03 8.659083e-03 9.956705e-01
[184,] 4.633960e-03 9.267920e-03 9.953660e-01
[185,] 5.170571e-03 1.034114e-02 9.948294e-01
[186,] 5.579033e-03 1.115807e-02 9.944210e-01
[187,] 6.232205e-03 1.246441e-02 9.937678e-01
[188,] 7.210617e-03 1.442123e-02 9.927894e-01
[189,] 8.943801e-03 1.788760e-02 9.910562e-01
[190,] 1.006952e-02 2.013905e-02 9.899305e-01
[191,] 1.177567e-02 2.355133e-02 9.882243e-01
[192,] 1.378540e-02 2.757079e-02 9.862146e-01
[193,] 1.728738e-02 3.457476e-02 9.827126e-01
[194,] 2.225002e-02 4.450004e-02 9.777500e-01
[195,] 2.400416e-02 4.800832e-02 9.759958e-01
[196,] 2.538656e-02 5.077312e-02 9.746134e-01
[197,] 2.718012e-02 5.436024e-02 9.728199e-01
[198,] 2.840620e-02 5.681240e-02 9.715938e-01
[199,] 2.992221e-02 5.984441e-02 9.700778e-01
[200,] 3.261960e-02 6.523920e-02 9.673804e-01
[201,] 3.688957e-02 7.377913e-02 9.631104e-01
[202,] 4.047083e-02 8.094166e-02 9.595292e-01
[203,] 4.674818e-02 9.349636e-02 9.532518e-01
[204,] 5.242855e-02 1.048571e-01 9.475714e-01
[205,] 5.852309e-02 1.170462e-01 9.414769e-01
[206,] 6.533498e-02 1.306700e-01 9.346650e-01
[207,] 6.350399e-02 1.270080e-01 9.364960e-01
[208,] 6.317009e-02 1.263402e-01 9.368299e-01
[209,] 6.250530e-02 1.250106e-01 9.374947e-01
[210,] 6.163108e-02 1.232622e-01 9.383689e-01
[211,] 6.008987e-02 1.201797e-01 9.399101e-01
[212,] 6.019417e-02 1.203883e-01 9.398058e-01
[213,] 6.105813e-02 1.221163e-01 9.389419e-01
[214,] 6.122306e-02 1.224461e-01 9.387769e-01
[215,] 6.207116e-02 1.241423e-01 9.379288e-01
[216,] 6.313280e-02 1.262656e-01 9.368672e-01
[217,] 6.391184e-02 1.278237e-01 9.360882e-01
[218,] 6.554641e-02 1.310928e-01 9.344536e-01
[219,] 5.957510e-02 1.191502e-01 9.404249e-01
[220,] 5.429652e-02 1.085930e-01 9.457035e-01
[221,] 4.958568e-02 9.917136e-02 9.504143e-01
[222,] 4.440197e-02 8.880395e-02 9.555980e-01
[223,] 4.041149e-02 8.082298e-02 9.595885e-01
[224,] 3.683753e-02 7.367506e-02 9.631625e-01
[225,] 3.439921e-02 6.879842e-02 9.656008e-01
[226,] 3.376874e-02 6.753748e-02 9.662313e-01
[227,] 3.191627e-02 6.383254e-02 9.680837e-01
[228,] 3.129901e-02 6.259801e-02 9.687010e-01
[229,] 3.118696e-02 6.237391e-02 9.688130e-01
[230,] 3.092925e-02 6.185850e-02 9.690708e-01
[231,] 2.649853e-02 5.299706e-02 9.735015e-01
[232,] 2.307740e-02 4.615480e-02 9.769226e-01
[233,] 2.057541e-02 4.115083e-02 9.794246e-01
[234,] 1.825318e-02 3.650637e-02 9.817468e-01
[235,] 1.591503e-02 3.183005e-02 9.840850e-01
[236,] 1.436821e-02 2.873641e-02 9.856318e-01
[237,] 1.371028e-02 2.742055e-02 9.862897e-01
[238,] 1.579632e-02 3.159264e-02 9.842037e-01
[239,] 1.871673e-02 3.743347e-02 9.812833e-01
[240,] 2.134093e-02 4.268185e-02 9.786591e-01
[241,] 2.162516e-02 4.325033e-02 9.783748e-01
[242,] 2.196176e-02 4.392352e-02 9.780382e-01
[243,] 2.064392e-02 4.128785e-02 9.793561e-01
[244,] 1.943660e-02 3.887319e-02 9.805634e-01
[245,] 1.828244e-02 3.656489e-02 9.817176e-01
[246,] 1.609857e-02 3.219713e-02 9.839014e-01
[247,] 1.387793e-02 2.775586e-02 9.861221e-01
[248,] 1.341528e-02 2.683057e-02 9.865847e-01
[249,] 1.351774e-02 2.703549e-02 9.864823e-01
[250,] 1.542953e-02 3.085905e-02 9.845705e-01
[251,] 1.528939e-02 3.057878e-02 9.847106e-01
[252,] 1.406685e-02 2.813370e-02 9.859332e-01
[253,] 1.180037e-02 2.360073e-02 9.881996e-01
[254,] 9.648984e-03 1.929797e-02 9.903510e-01
[255,] 8.042767e-03 1.608553e-02 9.919572e-01
[256,] 6.716032e-03 1.343206e-02 9.932840e-01
[257,] 5.570381e-03 1.114076e-02 9.944296e-01
[258,] 4.800452e-03 9.600903e-03 9.951995e-01
[259,] 4.261380e-03 8.522760e-03 9.957386e-01
[260,] 3.963536e-03 7.927073e-03 9.960365e-01
[261,] 3.714751e-03 7.429502e-03 9.962852e-01
[262,] 3.401003e-03 6.802005e-03 9.965990e-01
[263,] 3.023063e-03 6.046127e-03 9.969769e-01
[264,] 2.636437e-03 5.272874e-03 9.973636e-01
[265,] 2.246715e-03 4.493430e-03 9.977533e-01
[266,] 1.871998e-03 3.743995e-03 9.981280e-01
[267,] 1.717296e-03 3.434591e-03 9.982827e-01
[268,] 1.613667e-03 3.227333e-03 9.983863e-01
[269,] 1.550378e-03 3.100755e-03 9.984496e-01
[270,] 1.440428e-03 2.880856e-03 9.985596e-01
[271,] 1.283115e-03 2.566229e-03 9.987169e-01
[272,] 1.160336e-03 2.320672e-03 9.988397e-01
[273,] 9.930998e-04 1.986200e-03 9.990069e-01
[274,] 8.204625e-04 1.640925e-03 9.991795e-01
[275,] 6.542974e-04 1.308595e-03 9.993457e-01
[276,] 5.173314e-04 1.034663e-03 9.994827e-01
[277,] 3.951390e-04 7.902781e-04 9.996049e-01
[278,] 2.921534e-04 5.843068e-04 9.997078e-01
[279,] 2.301754e-04 4.603507e-04 9.997698e-01
[280,] 1.788453e-04 3.576906e-04 9.998212e-01
[281,] 1.376029e-04 2.752057e-04 9.998624e-01
[282,] 1.044486e-04 2.088971e-04 9.998956e-01
[283,] 7.786110e-05 1.557222e-04 9.999221e-01
[284,] 5.577358e-05 1.115472e-04 9.999442e-01
[285,] 4.046887e-05 8.093775e-05 9.999595e-01
[286,] 4.359779e-05 8.719557e-05 9.999564e-01
[287,] 4.502371e-05 9.004742e-05 9.999550e-01
[288,] 4.818289e-05 9.636578e-05 9.999518e-01
[289,] 4.334471e-05 8.668942e-05 9.999567e-01
[290,] 4.151292e-05 8.302584e-05 9.999585e-01
[291,] 4.393757e-05 8.787514e-05 9.999561e-01
[292,] 5.266076e-05 1.053215e-04 9.999473e-01
[293,] 6.590620e-05 1.318124e-04 9.999341e-01
[294,] 8.359803e-05 1.671961e-04 9.999164e-01
[295,] 1.323852e-04 2.647704e-04 9.998676e-01
[296,] 2.213325e-04 4.426651e-04 9.997787e-01
[297,] 4.115827e-04 8.231654e-04 9.995884e-01
[298,] 1.448473e-03 2.896945e-03 9.985515e-01
[299,] 4.973331e-03 9.946661e-03 9.950267e-01
[300,] 1.999962e-02 3.999924e-02 9.800004e-01
[301,] 6.113288e-02 1.222658e-01 9.388671e-01
[302,] 1.558521e-01 3.117042e-01 8.441479e-01
[303,] 3.496115e-01 6.992229e-01 6.503885e-01
[304,] 6.476623e-01 7.046753e-01 3.523377e-01
[305,] 9.266567e-01 1.466867e-01 7.334334e-02
[306,] 9.926918e-01 1.461647e-02 7.308237e-03
[307,] 9.999403e-01 1.194157e-04 5.970783e-05
[308,] 1.000000e+00 6.978411e-08 3.489206e-08
[309,] 1.000000e+00 1.348629e-12 6.743144e-13
[310,] 1.000000e+00 1.914665e-13 9.573327e-14
[311,] 1.000000e+00 5.485826e-14 2.742913e-14
[312,] 1.000000e+00 9.928580e-14 4.964290e-14
[313,] 1.000000e+00 1.500807e-13 7.504033e-14
[314,] 1.000000e+00 7.532327e-14 3.766164e-14
[315,] 1.000000e+00 1.074530e-13 5.372652e-14
[316,] 1.000000e+00 2.732003e-13 1.366001e-13
[317,] 1.000000e+00 7.028229e-13 3.514115e-13
[318,] 1.000000e+00 2.070062e-12 1.035031e-12
[319,] 1.000000e+00 6.205439e-12 3.102719e-12
[320,] 1.000000e+00 1.072870e-11 5.364350e-12
[321,] 1.000000e+00 2.631817e-11 1.315908e-11
[322,] 1.000000e+00 8.387342e-11 4.193671e-11
[323,] 1.000000e+00 1.583714e-10 7.918569e-11
[324,] 1.000000e+00 1.597947e-10 7.989736e-11
[325,] 1.000000e+00 4.743065e-10 2.371532e-10
[326,] 1.000000e+00 2.755718e-10 1.377859e-10
[327,] 1.000000e+00 6.016100e-10 3.008050e-10
[328,] 1.000000e+00 1.990300e-09 9.951502e-10
[329,] 1.000000e+00 8.176300e-09 4.088150e-09
[330,] 1.000000e+00 2.572813e-08 1.286406e-08
[331,] 1.000000e+00 9.823422e-08 4.911711e-08
[332,] 9.999998e-01 4.549432e-07 2.274716e-07
[333,] 9.999989e-01 2.218635e-06 1.109318e-06
[334,] 9.999953e-01 9.449539e-06 4.724770e-06
[335,] 9.999965e-01 7.035547e-06 3.517774e-06
[336,] 9.999912e-01 1.760145e-05 8.800727e-06
[337,] 9.999588e-01 8.237983e-05 4.118992e-05
[338,] 9.997652e-01 4.696085e-04 2.348043e-04
[339,] 9.997013e-01 5.974102e-04 2.987051e-04
[340,] 9.981847e-01 3.630615e-03 1.815308e-03
[341,] 9.918338e-01 1.633231e-02 8.166154e-03
> postscript(file="/var/www/html/rcomp/tmp/148781291150235.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/248781291150235.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/3ezot1291150235.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4ezot1291150235.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5ezot1291150235.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 = 372
Frequency = 1
1 2 3 4 5 6
-14.5037298 21.1994960 27.3672379 42.3898185 23.6285282 -9.6972782
7 8 9 10 11 12
13.3736895 27.2188508 26.6253024 10.6672379 17.1962702 31.9285282
13 14 15 16 17 18
37.6679167 75.6711425 88.8388844 117.1614651 161.6001747 133.8743683
19 20 21 22 23 24
198.8453360 186.7904973 171.7969489 202.5388844 158.6679167 168.2001747
25 26 27 28 29 30
190.7395632 195.1427890 169.6105309 143.7331116 124.0718212 80.1460148
31 32 33 34 35 36
79.4169825 40.2621438 45.0685954 17.0105309 25.0395632 27.8718212
37 38 39 40 41 42
-21.3887903 -42.3855645 -41.6178226 -41.1952419 -37.4565323 -73.9823387
43 44 45 46 47 48
-57.2113710 -52.6662097 -27.5597581 -25.3178226 -23.7887903 -45.6565323
49 50 51 52 53 54
-72.7171438 -74.4139180 -85.9461761 -63.6235954 -48.4848858 -96.2106922
55 56 57 58 59 60
-68.1397245 -53.6945632 -55.5881116 -64.9461761 -75.6171438 -82.9848858
61 62 63 64 65 66
-97.5454973 -124.2422715 -115.5745296 -83.0519489 -85.3132392 -138.4390457
67 68 69 70 71 72
-117.8680780 -106.5229167 -78.7164651 -67.9745296 -45.5454973 -13.3132392
73 74 75 76 77 78
33.1261492 65.4293750 93.0971169 112.9196976 114.6584073 44.2326008
79 80 81 82 83 84
66.8035685 77.0487298 90.4551815 55.4971169 52.0261492 38.9584073
85 86 87 88 89 90
31.6977957 11.8010215 6.8687634 32.2913441 5.6300538 -46.7957527
91 92 93 94 95 96
-47.1247849 -28.5796237 -31.2731720 -21.2312366 -18.1022043 -14.0699462
97 98 99 100 101 102
-40.8305578 -48.1273320 -25.5595901 -25.1370094 4.3017003 -30.4241062
103 104 105 106 107 108
-27.1531384 -47.7079772 -50.0015255 -52.7595901 -24.0305578 -20.3982997
109 110 111 112 113 114
-39.0589113 -61.0556855 -65.0879435 -45.6653629 -24.3266532 -47.4524597
115 116 117 118 119 120
-53.4814919 -54.0363306 -39.2298790 -27.5879435 16.5410887 34.5733468
121 122 123 124 125 126
74.5127352 129.8159610 155.9837030 185.8062836 183.1449933 149.5191868
127 128 129 130 131 132
159.7901546 141.8353159 104.0417675 88.6837030 70.1127352 95.9449933
133 134 135 136 137 138
83.6843817 75.7876075 58.0553495 22.9779301 20.4166398 -7.0091667
139 140 141 142 143 144
-1.7381989 3.6069624 5.5134140 24.5553495 42.9843817 29.0166398
145 146 147 148 149 150
15.5560282 -17.6407460 32.4269960 15.6495766 13.4882863 19.9624798
151 152 153 154 155 156
13.9334476 27.7786089 5.2850605 42.9269960 63.8560282 111.6882863
157 158 159 160 161 162
124.9276747 146.9309005 146.0986425 131.4212231 130.3599328 121.8341263
163 164 165 166 167 168
109.4050941 88.4502554 64.9567070 63.2986425 49.0276747 56.5599328
169 170 171 172 173 174
41.2993212 17.4025470 23.8702890 16.7928696 46.2315793 0.2057728
175 176 177 178 179 180
-16.0232594 16.4219019 -5.1716465 -11.8297110 15.2993212 16.2315793
181 182 183 184 185 186
29.6709677 44.0741935 23.5419355 17.5645161 33.7032258 21.4774194
187 188 189 190 191 192
2.8483871 -4.5064516 -15.9000000 -8.0580645 16.2709677 6.8032258
193 194 195 196 197 198
6.5426142 -9.0541599 -10.3864180 -10.8638374 -20.6251277 -0.8509341
199 200 201 202 203 204
-55.8799664 -37.1348051 -48.9283535 -39.8864180 -49.9573858 -43.3251277
205 206 207 208 209 210
-63.3857392 -50.1825134 -75.2147715 -56.9921909 -64.2534812 -52.6792876
211 212 213 214 215 216
-92.7083199 -87.9631586 -103.1567070 -101.0147715 -105.1857392 -117.6534812
217 218 219 220 221 222
-145.3140927 -168.7108669 -158.3431250 -145.4205444 -118.5818347 -111.4076411
223 224 225 226 227 228
-142.8366734 -134.5915121 -149.2850605 -137.6431250 -148.3140927 -142.1818347
229 230 231 232 233 234
-166.0424462 -173.4392204 -174.1714785 -164.2488978 -164.3101882 -120.0359946
235 236 237 238 239 240
-135.1650269 -134.7198656 -122.3134140 -101.1714785 -128.1424462 -148.9101882
241 242 243 244 245 246
-186.7707997 -175.3675739 -188.8998320 -193.7772513 -191.9385417 -133.5643481
247 248 249 250 251 252
-150.5933804 -163.9482191 -163.3417675 -157.5998320 -173.0707997 -191.3385417
253 254 255 256 257 258
-218.8991532 -223.9959274 -219.3281855 -200.9056048 -204.5668952 -168.2927016
259 260 261 262 263 264
-166.3217339 -166.3765726 -140.4701210 -136.8281855 -171.8991532 -182.6668952
265 266 267 268 269 270
-178.0275067 -149.1242809 -132.9565390 -112.1339583 -108.3952487 -52.6210551
271 272 273 274 275 276
-45.7500874 -43.6049261 -19.2984745 -7.1565390 5.5724933 6.0047513
277 278 279 280 281 282
10.5441398 3.4473656 -0.9848925 -10.1623118 -19.6236022 17.2505914
283 284 285 286 287 288
24.0215591 28.2667204 23.2731720 11.7151075 14.1441398 -0.3236022
289 290 291 292 293 294
1.6157863 -11.7809879 -9.2132460 -22.0906653 -36.8519556 -1.3777621
295 296 297 298 299 300
-3.9067944 -4.3616331 -7.1551815 -10.5132460 -52.9842137 -70.4519556
301 302 303 304 305 306
-87.8125672 -80.7093414 -91.7415995 -86.6190188 -103.5803091 -71.5061156
307 308 309 310 311 312
-78.4351478 -81.4899866 -68.6835349 -93.4415995 -86.2125672 -88.4803091
313 314 315 316 317 318
-66.7409207 -63.4376949 -79.6699530 -86.1473723 -81.3086626 -30.4344691
319 320 321 322 323 324
-19.6635013 -26.0183401 22.7881116 22.4300470 64.4590793 104.0913374
325 326 327 328 329 330
238.2307258 241.2339516 268.5016935 253.5242742 254.3629839 276.2371774
331 332 333 334 335 336
263.0081452 242.8533065 242.5597581 230.2016935 206.8307258 200.7629839
337 338 339 340 341 342
225.4023723 201.4055981 172.8733401 148.2959207 110.2346304 172.6088239
343 344 345 346 347 348
187.5797917 193.2249530 180.7314046 176.8733401 181.0023723 171.2346304
349 350 351 352 353 354
180.5740188 196.7772446 163.7449866 103.8675672 82.7062769 140.1804704
355 356 357 358 359 360
111.7514382 124.4965995 109.6030511 103.4449866 93.8740188 44.8062769
361 362 363 364 365 366
73.2456653 47.5488911 43.8166331 3.6392137 1.0779234 15.2521169
367 368 369 370 371 372
49.2230847 29.6682460 33.3746976 15.1166331 9.9456653 17.0779234
> postscript(file="/var/www/html/rcomp/tmp/6p9ne1291150235.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 = 372
Frequency = 1
lag(myerror, k = 1) myerror
0 -14.5037298 NA
1 21.1994960 -14.5037298
2 27.3672379 21.1994960
3 42.3898185 27.3672379
4 23.6285282 42.3898185
5 -9.6972782 23.6285282
6 13.3736895 -9.6972782
7 27.2188508 13.3736895
8 26.6253024 27.2188508
9 10.6672379 26.6253024
10 17.1962702 10.6672379
11 31.9285282 17.1962702
12 37.6679167 31.9285282
13 75.6711425 37.6679167
14 88.8388844 75.6711425
15 117.1614651 88.8388844
16 161.6001747 117.1614651
17 133.8743683 161.6001747
18 198.8453360 133.8743683
19 186.7904973 198.8453360
20 171.7969489 186.7904973
21 202.5388844 171.7969489
22 158.6679167 202.5388844
23 168.2001747 158.6679167
24 190.7395632 168.2001747
25 195.1427890 190.7395632
26 169.6105309 195.1427890
27 143.7331116 169.6105309
28 124.0718212 143.7331116
29 80.1460148 124.0718212
30 79.4169825 80.1460148
31 40.2621438 79.4169825
32 45.0685954 40.2621438
33 17.0105309 45.0685954
34 25.0395632 17.0105309
35 27.8718212 25.0395632
36 -21.3887903 27.8718212
37 -42.3855645 -21.3887903
38 -41.6178226 -42.3855645
39 -41.1952419 -41.6178226
40 -37.4565323 -41.1952419
41 -73.9823387 -37.4565323
42 -57.2113710 -73.9823387
43 -52.6662097 -57.2113710
44 -27.5597581 -52.6662097
45 -25.3178226 -27.5597581
46 -23.7887903 -25.3178226
47 -45.6565323 -23.7887903
48 -72.7171438 -45.6565323
49 -74.4139180 -72.7171438
50 -85.9461761 -74.4139180
51 -63.6235954 -85.9461761
52 -48.4848858 -63.6235954
53 -96.2106922 -48.4848858
54 -68.1397245 -96.2106922
55 -53.6945632 -68.1397245
56 -55.5881116 -53.6945632
57 -64.9461761 -55.5881116
58 -75.6171438 -64.9461761
59 -82.9848858 -75.6171438
60 -97.5454973 -82.9848858
61 -124.2422715 -97.5454973
62 -115.5745296 -124.2422715
63 -83.0519489 -115.5745296
64 -85.3132392 -83.0519489
65 -138.4390457 -85.3132392
66 -117.8680780 -138.4390457
67 -106.5229167 -117.8680780
68 -78.7164651 -106.5229167
69 -67.9745296 -78.7164651
70 -45.5454973 -67.9745296
71 -13.3132392 -45.5454973
72 33.1261492 -13.3132392
73 65.4293750 33.1261492
74 93.0971169 65.4293750
75 112.9196976 93.0971169
76 114.6584073 112.9196976
77 44.2326008 114.6584073
78 66.8035685 44.2326008
79 77.0487298 66.8035685
80 90.4551815 77.0487298
81 55.4971169 90.4551815
82 52.0261492 55.4971169
83 38.9584073 52.0261492
84 31.6977957 38.9584073
85 11.8010215 31.6977957
86 6.8687634 11.8010215
87 32.2913441 6.8687634
88 5.6300538 32.2913441
89 -46.7957527 5.6300538
90 -47.1247849 -46.7957527
91 -28.5796237 -47.1247849
92 -31.2731720 -28.5796237
93 -21.2312366 -31.2731720
94 -18.1022043 -21.2312366
95 -14.0699462 -18.1022043
96 -40.8305578 -14.0699462
97 -48.1273320 -40.8305578
98 -25.5595901 -48.1273320
99 -25.1370094 -25.5595901
100 4.3017003 -25.1370094
101 -30.4241062 4.3017003
102 -27.1531384 -30.4241062
103 -47.7079772 -27.1531384
104 -50.0015255 -47.7079772
105 -52.7595901 -50.0015255
106 -24.0305578 -52.7595901
107 -20.3982997 -24.0305578
108 -39.0589113 -20.3982997
109 -61.0556855 -39.0589113
110 -65.0879435 -61.0556855
111 -45.6653629 -65.0879435
112 -24.3266532 -45.6653629
113 -47.4524597 -24.3266532
114 -53.4814919 -47.4524597
115 -54.0363306 -53.4814919
116 -39.2298790 -54.0363306
117 -27.5879435 -39.2298790
118 16.5410887 -27.5879435
119 34.5733468 16.5410887
120 74.5127352 34.5733468
121 129.8159610 74.5127352
122 155.9837030 129.8159610
123 185.8062836 155.9837030
124 183.1449933 185.8062836
125 149.5191868 183.1449933
126 159.7901546 149.5191868
127 141.8353159 159.7901546
128 104.0417675 141.8353159
129 88.6837030 104.0417675
130 70.1127352 88.6837030
131 95.9449933 70.1127352
132 83.6843817 95.9449933
133 75.7876075 83.6843817
134 58.0553495 75.7876075
135 22.9779301 58.0553495
136 20.4166398 22.9779301
137 -7.0091667 20.4166398
138 -1.7381989 -7.0091667
139 3.6069624 -1.7381989
140 5.5134140 3.6069624
141 24.5553495 5.5134140
142 42.9843817 24.5553495
143 29.0166398 42.9843817
144 15.5560282 29.0166398
145 -17.6407460 15.5560282
146 32.4269960 -17.6407460
147 15.6495766 32.4269960
148 13.4882863 15.6495766
149 19.9624798 13.4882863
150 13.9334476 19.9624798
151 27.7786089 13.9334476
152 5.2850605 27.7786089
153 42.9269960 5.2850605
154 63.8560282 42.9269960
155 111.6882863 63.8560282
156 124.9276747 111.6882863
157 146.9309005 124.9276747
158 146.0986425 146.9309005
159 131.4212231 146.0986425
160 130.3599328 131.4212231
161 121.8341263 130.3599328
162 109.4050941 121.8341263
163 88.4502554 109.4050941
164 64.9567070 88.4502554
165 63.2986425 64.9567070
166 49.0276747 63.2986425
167 56.5599328 49.0276747
168 41.2993212 56.5599328
169 17.4025470 41.2993212
170 23.8702890 17.4025470
171 16.7928696 23.8702890
172 46.2315793 16.7928696
173 0.2057728 46.2315793
174 -16.0232594 0.2057728
175 16.4219019 -16.0232594
176 -5.1716465 16.4219019
177 -11.8297110 -5.1716465
178 15.2993212 -11.8297110
179 16.2315793 15.2993212
180 29.6709677 16.2315793
181 44.0741935 29.6709677
182 23.5419355 44.0741935
183 17.5645161 23.5419355
184 33.7032258 17.5645161
185 21.4774194 33.7032258
186 2.8483871 21.4774194
187 -4.5064516 2.8483871
188 -15.9000000 -4.5064516
189 -8.0580645 -15.9000000
190 16.2709677 -8.0580645
191 6.8032258 16.2709677
192 6.5426142 6.8032258
193 -9.0541599 6.5426142
194 -10.3864180 -9.0541599
195 -10.8638374 -10.3864180
196 -20.6251277 -10.8638374
197 -0.8509341 -20.6251277
198 -55.8799664 -0.8509341
199 -37.1348051 -55.8799664
200 -48.9283535 -37.1348051
201 -39.8864180 -48.9283535
202 -49.9573858 -39.8864180
203 -43.3251277 -49.9573858
204 -63.3857392 -43.3251277
205 -50.1825134 -63.3857392
206 -75.2147715 -50.1825134
207 -56.9921909 -75.2147715
208 -64.2534812 -56.9921909
209 -52.6792876 -64.2534812
210 -92.7083199 -52.6792876
211 -87.9631586 -92.7083199
212 -103.1567070 -87.9631586
213 -101.0147715 -103.1567070
214 -105.1857392 -101.0147715
215 -117.6534812 -105.1857392
216 -145.3140927 -117.6534812
217 -168.7108669 -145.3140927
218 -158.3431250 -168.7108669
219 -145.4205444 -158.3431250
220 -118.5818347 -145.4205444
221 -111.4076411 -118.5818347
222 -142.8366734 -111.4076411
223 -134.5915121 -142.8366734
224 -149.2850605 -134.5915121
225 -137.6431250 -149.2850605
226 -148.3140927 -137.6431250
227 -142.1818347 -148.3140927
228 -166.0424462 -142.1818347
229 -173.4392204 -166.0424462
230 -174.1714785 -173.4392204
231 -164.2488978 -174.1714785
232 -164.3101882 -164.2488978
233 -120.0359946 -164.3101882
234 -135.1650269 -120.0359946
235 -134.7198656 -135.1650269
236 -122.3134140 -134.7198656
237 -101.1714785 -122.3134140
238 -128.1424462 -101.1714785
239 -148.9101882 -128.1424462
240 -186.7707997 -148.9101882
241 -175.3675739 -186.7707997
242 -188.8998320 -175.3675739
243 -193.7772513 -188.8998320
244 -191.9385417 -193.7772513
245 -133.5643481 -191.9385417
246 -150.5933804 -133.5643481
247 -163.9482191 -150.5933804
248 -163.3417675 -163.9482191
249 -157.5998320 -163.3417675
250 -173.0707997 -157.5998320
251 -191.3385417 -173.0707997
252 -218.8991532 -191.3385417
253 -223.9959274 -218.8991532
254 -219.3281855 -223.9959274
255 -200.9056048 -219.3281855
256 -204.5668952 -200.9056048
257 -168.2927016 -204.5668952
258 -166.3217339 -168.2927016
259 -166.3765726 -166.3217339
260 -140.4701210 -166.3765726
261 -136.8281855 -140.4701210
262 -171.8991532 -136.8281855
263 -182.6668952 -171.8991532
264 -178.0275067 -182.6668952
265 -149.1242809 -178.0275067
266 -132.9565390 -149.1242809
267 -112.1339583 -132.9565390
268 -108.3952487 -112.1339583
269 -52.6210551 -108.3952487
270 -45.7500874 -52.6210551
271 -43.6049261 -45.7500874
272 -19.2984745 -43.6049261
273 -7.1565390 -19.2984745
274 5.5724933 -7.1565390
275 6.0047513 5.5724933
276 10.5441398 6.0047513
277 3.4473656 10.5441398
278 -0.9848925 3.4473656
279 -10.1623118 -0.9848925
280 -19.6236022 -10.1623118
281 17.2505914 -19.6236022
282 24.0215591 17.2505914
283 28.2667204 24.0215591
284 23.2731720 28.2667204
285 11.7151075 23.2731720
286 14.1441398 11.7151075
287 -0.3236022 14.1441398
288 1.6157863 -0.3236022
289 -11.7809879 1.6157863
290 -9.2132460 -11.7809879
291 -22.0906653 -9.2132460
292 -36.8519556 -22.0906653
293 -1.3777621 -36.8519556
294 -3.9067944 -1.3777621
295 -4.3616331 -3.9067944
296 -7.1551815 -4.3616331
297 -10.5132460 -7.1551815
298 -52.9842137 -10.5132460
299 -70.4519556 -52.9842137
300 -87.8125672 -70.4519556
301 -80.7093414 -87.8125672
302 -91.7415995 -80.7093414
303 -86.6190188 -91.7415995
304 -103.5803091 -86.6190188
305 -71.5061156 -103.5803091
306 -78.4351478 -71.5061156
307 -81.4899866 -78.4351478
308 -68.6835349 -81.4899866
309 -93.4415995 -68.6835349
310 -86.2125672 -93.4415995
311 -88.4803091 -86.2125672
312 -66.7409207 -88.4803091
313 -63.4376949 -66.7409207
314 -79.6699530 -63.4376949
315 -86.1473723 -79.6699530
316 -81.3086626 -86.1473723
317 -30.4344691 -81.3086626
318 -19.6635013 -30.4344691
319 -26.0183401 -19.6635013
320 22.7881116 -26.0183401
321 22.4300470 22.7881116
322 64.4590793 22.4300470
323 104.0913374 64.4590793
324 238.2307258 104.0913374
325 241.2339516 238.2307258
326 268.5016935 241.2339516
327 253.5242742 268.5016935
328 254.3629839 253.5242742
329 276.2371774 254.3629839
330 263.0081452 276.2371774
331 242.8533065 263.0081452
332 242.5597581 242.8533065
333 230.2016935 242.5597581
334 206.8307258 230.2016935
335 200.7629839 206.8307258
336 225.4023723 200.7629839
337 201.4055981 225.4023723
338 172.8733401 201.4055981
339 148.2959207 172.8733401
340 110.2346304 148.2959207
341 172.6088239 110.2346304
342 187.5797917 172.6088239
343 193.2249530 187.5797917
344 180.7314046 193.2249530
345 176.8733401 180.7314046
346 181.0023723 176.8733401
347 171.2346304 181.0023723
348 180.5740188 171.2346304
349 196.7772446 180.5740188
350 163.7449866 196.7772446
351 103.8675672 163.7449866
352 82.7062769 103.8675672
353 140.1804704 82.7062769
354 111.7514382 140.1804704
355 124.4965995 111.7514382
356 109.6030511 124.4965995
357 103.4449866 109.6030511
358 93.8740188 103.4449866
359 44.8062769 93.8740188
360 73.2456653 44.8062769
361 47.5488911 73.2456653
362 43.8166331 47.5488911
363 3.6392137 43.8166331
364 1.0779234 3.6392137
365 15.2521169 1.0779234
366 49.2230847 15.2521169
367 29.6682460 49.2230847
368 33.3746976 29.6682460
369 15.1166331 33.3746976
370 9.9456653 15.1166331
371 17.0779234 9.9456653
372 NA 17.0779234
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 21.1994960 -14.5037298
[2,] 27.3672379 21.1994960
[3,] 42.3898185 27.3672379
[4,] 23.6285282 42.3898185
[5,] -9.6972782 23.6285282
[6,] 13.3736895 -9.6972782
[7,] 27.2188508 13.3736895
[8,] 26.6253024 27.2188508
[9,] 10.6672379 26.6253024
[10,] 17.1962702 10.6672379
[11,] 31.9285282 17.1962702
[12,] 37.6679167 31.9285282
[13,] 75.6711425 37.6679167
[14,] 88.8388844 75.6711425
[15,] 117.1614651 88.8388844
[16,] 161.6001747 117.1614651
[17,] 133.8743683 161.6001747
[18,] 198.8453360 133.8743683
[19,] 186.7904973 198.8453360
[20,] 171.7969489 186.7904973
[21,] 202.5388844 171.7969489
[22,] 158.6679167 202.5388844
[23,] 168.2001747 158.6679167
[24,] 190.7395632 168.2001747
[25,] 195.1427890 190.7395632
[26,] 169.6105309 195.1427890
[27,] 143.7331116 169.6105309
[28,] 124.0718212 143.7331116
[29,] 80.1460148 124.0718212
[30,] 79.4169825 80.1460148
[31,] 40.2621438 79.4169825
[32,] 45.0685954 40.2621438
[33,] 17.0105309 45.0685954
[34,] 25.0395632 17.0105309
[35,] 27.8718212 25.0395632
[36,] -21.3887903 27.8718212
[37,] -42.3855645 -21.3887903
[38,] -41.6178226 -42.3855645
[39,] -41.1952419 -41.6178226
[40,] -37.4565323 -41.1952419
[41,] -73.9823387 -37.4565323
[42,] -57.2113710 -73.9823387
[43,] -52.6662097 -57.2113710
[44,] -27.5597581 -52.6662097
[45,] -25.3178226 -27.5597581
[46,] -23.7887903 -25.3178226
[47,] -45.6565323 -23.7887903
[48,] -72.7171438 -45.6565323
[49,] -74.4139180 -72.7171438
[50,] -85.9461761 -74.4139180
[51,] -63.6235954 -85.9461761
[52,] -48.4848858 -63.6235954
[53,] -96.2106922 -48.4848858
[54,] -68.1397245 -96.2106922
[55,] -53.6945632 -68.1397245
[56,] -55.5881116 -53.6945632
[57,] -64.9461761 -55.5881116
[58,] -75.6171438 -64.9461761
[59,] -82.9848858 -75.6171438
[60,] -97.5454973 -82.9848858
[61,] -124.2422715 -97.5454973
[62,] -115.5745296 -124.2422715
[63,] -83.0519489 -115.5745296
[64,] -85.3132392 -83.0519489
[65,] -138.4390457 -85.3132392
[66,] -117.8680780 -138.4390457
[67,] -106.5229167 -117.8680780
[68,] -78.7164651 -106.5229167
[69,] -67.9745296 -78.7164651
[70,] -45.5454973 -67.9745296
[71,] -13.3132392 -45.5454973
[72,] 33.1261492 -13.3132392
[73,] 65.4293750 33.1261492
[74,] 93.0971169 65.4293750
[75,] 112.9196976 93.0971169
[76,] 114.6584073 112.9196976
[77,] 44.2326008 114.6584073
[78,] 66.8035685 44.2326008
[79,] 77.0487298 66.8035685
[80,] 90.4551815 77.0487298
[81,] 55.4971169 90.4551815
[82,] 52.0261492 55.4971169
[83,] 38.9584073 52.0261492
[84,] 31.6977957 38.9584073
[85,] 11.8010215 31.6977957
[86,] 6.8687634 11.8010215
[87,] 32.2913441 6.8687634
[88,] 5.6300538 32.2913441
[89,] -46.7957527 5.6300538
[90,] -47.1247849 -46.7957527
[91,] -28.5796237 -47.1247849
[92,] -31.2731720 -28.5796237
[93,] -21.2312366 -31.2731720
[94,] -18.1022043 -21.2312366
[95,] -14.0699462 -18.1022043
[96,] -40.8305578 -14.0699462
[97,] -48.1273320 -40.8305578
[98,] -25.5595901 -48.1273320
[99,] -25.1370094 -25.5595901
[100,] 4.3017003 -25.1370094
[101,] -30.4241062 4.3017003
[102,] -27.1531384 -30.4241062
[103,] -47.7079772 -27.1531384
[104,] -50.0015255 -47.7079772
[105,] -52.7595901 -50.0015255
[106,] -24.0305578 -52.7595901
[107,] -20.3982997 -24.0305578
[108,] -39.0589113 -20.3982997
[109,] -61.0556855 -39.0589113
[110,] -65.0879435 -61.0556855
[111,] -45.6653629 -65.0879435
[112,] -24.3266532 -45.6653629
[113,] -47.4524597 -24.3266532
[114,] -53.4814919 -47.4524597
[115,] -54.0363306 -53.4814919
[116,] -39.2298790 -54.0363306
[117,] -27.5879435 -39.2298790
[118,] 16.5410887 -27.5879435
[119,] 34.5733468 16.5410887
[120,] 74.5127352 34.5733468
[121,] 129.8159610 74.5127352
[122,] 155.9837030 129.8159610
[123,] 185.8062836 155.9837030
[124,] 183.1449933 185.8062836
[125,] 149.5191868 183.1449933
[126,] 159.7901546 149.5191868
[127,] 141.8353159 159.7901546
[128,] 104.0417675 141.8353159
[129,] 88.6837030 104.0417675
[130,] 70.1127352 88.6837030
[131,] 95.9449933 70.1127352
[132,] 83.6843817 95.9449933
[133,] 75.7876075 83.6843817
[134,] 58.0553495 75.7876075
[135,] 22.9779301 58.0553495
[136,] 20.4166398 22.9779301
[137,] -7.0091667 20.4166398
[138,] -1.7381989 -7.0091667
[139,] 3.6069624 -1.7381989
[140,] 5.5134140 3.6069624
[141,] 24.5553495 5.5134140
[142,] 42.9843817 24.5553495
[143,] 29.0166398 42.9843817
[144,] 15.5560282 29.0166398
[145,] -17.6407460 15.5560282
[146,] 32.4269960 -17.6407460
[147,] 15.6495766 32.4269960
[148,] 13.4882863 15.6495766
[149,] 19.9624798 13.4882863
[150,] 13.9334476 19.9624798
[151,] 27.7786089 13.9334476
[152,] 5.2850605 27.7786089
[153,] 42.9269960 5.2850605
[154,] 63.8560282 42.9269960
[155,] 111.6882863 63.8560282
[156,] 124.9276747 111.6882863
[157,] 146.9309005 124.9276747
[158,] 146.0986425 146.9309005
[159,] 131.4212231 146.0986425
[160,] 130.3599328 131.4212231
[161,] 121.8341263 130.3599328
[162,] 109.4050941 121.8341263
[163,] 88.4502554 109.4050941
[164,] 64.9567070 88.4502554
[165,] 63.2986425 64.9567070
[166,] 49.0276747 63.2986425
[167,] 56.5599328 49.0276747
[168,] 41.2993212 56.5599328
[169,] 17.4025470 41.2993212
[170,] 23.8702890 17.4025470
[171,] 16.7928696 23.8702890
[172,] 46.2315793 16.7928696
[173,] 0.2057728 46.2315793
[174,] -16.0232594 0.2057728
[175,] 16.4219019 -16.0232594
[176,] -5.1716465 16.4219019
[177,] -11.8297110 -5.1716465
[178,] 15.2993212 -11.8297110
[179,] 16.2315793 15.2993212
[180,] 29.6709677 16.2315793
[181,] 44.0741935 29.6709677
[182,] 23.5419355 44.0741935
[183,] 17.5645161 23.5419355
[184,] 33.7032258 17.5645161
[185,] 21.4774194 33.7032258
[186,] 2.8483871 21.4774194
[187,] -4.5064516 2.8483871
[188,] -15.9000000 -4.5064516
[189,] -8.0580645 -15.9000000
[190,] 16.2709677 -8.0580645
[191,] 6.8032258 16.2709677
[192,] 6.5426142 6.8032258
[193,] -9.0541599 6.5426142
[194,] -10.3864180 -9.0541599
[195,] -10.8638374 -10.3864180
[196,] -20.6251277 -10.8638374
[197,] -0.8509341 -20.6251277
[198,] -55.8799664 -0.8509341
[199,] -37.1348051 -55.8799664
[200,] -48.9283535 -37.1348051
[201,] -39.8864180 -48.9283535
[202,] -49.9573858 -39.8864180
[203,] -43.3251277 -49.9573858
[204,] -63.3857392 -43.3251277
[205,] -50.1825134 -63.3857392
[206,] -75.2147715 -50.1825134
[207,] -56.9921909 -75.2147715
[208,] -64.2534812 -56.9921909
[209,] -52.6792876 -64.2534812
[210,] -92.7083199 -52.6792876
[211,] -87.9631586 -92.7083199
[212,] -103.1567070 -87.9631586
[213,] -101.0147715 -103.1567070
[214,] -105.1857392 -101.0147715
[215,] -117.6534812 -105.1857392
[216,] -145.3140927 -117.6534812
[217,] -168.7108669 -145.3140927
[218,] -158.3431250 -168.7108669
[219,] -145.4205444 -158.3431250
[220,] -118.5818347 -145.4205444
[221,] -111.4076411 -118.5818347
[222,] -142.8366734 -111.4076411
[223,] -134.5915121 -142.8366734
[224,] -149.2850605 -134.5915121
[225,] -137.6431250 -149.2850605
[226,] -148.3140927 -137.6431250
[227,] -142.1818347 -148.3140927
[228,] -166.0424462 -142.1818347
[229,] -173.4392204 -166.0424462
[230,] -174.1714785 -173.4392204
[231,] -164.2488978 -174.1714785
[232,] -164.3101882 -164.2488978
[233,] -120.0359946 -164.3101882
[234,] -135.1650269 -120.0359946
[235,] -134.7198656 -135.1650269
[236,] -122.3134140 -134.7198656
[237,] -101.1714785 -122.3134140
[238,] -128.1424462 -101.1714785
[239,] -148.9101882 -128.1424462
[240,] -186.7707997 -148.9101882
[241,] -175.3675739 -186.7707997
[242,] -188.8998320 -175.3675739
[243,] -193.7772513 -188.8998320
[244,] -191.9385417 -193.7772513
[245,] -133.5643481 -191.9385417
[246,] -150.5933804 -133.5643481
[247,] -163.9482191 -150.5933804
[248,] -163.3417675 -163.9482191
[249,] -157.5998320 -163.3417675
[250,] -173.0707997 -157.5998320
[251,] -191.3385417 -173.0707997
[252,] -218.8991532 -191.3385417
[253,] -223.9959274 -218.8991532
[254,] -219.3281855 -223.9959274
[255,] -200.9056048 -219.3281855
[256,] -204.5668952 -200.9056048
[257,] -168.2927016 -204.5668952
[258,] -166.3217339 -168.2927016
[259,] -166.3765726 -166.3217339
[260,] -140.4701210 -166.3765726
[261,] -136.8281855 -140.4701210
[262,] -171.8991532 -136.8281855
[263,] -182.6668952 -171.8991532
[264,] -178.0275067 -182.6668952
[265,] -149.1242809 -178.0275067
[266,] -132.9565390 -149.1242809
[267,] -112.1339583 -132.9565390
[268,] -108.3952487 -112.1339583
[269,] -52.6210551 -108.3952487
[270,] -45.7500874 -52.6210551
[271,] -43.6049261 -45.7500874
[272,] -19.2984745 -43.6049261
[273,] -7.1565390 -19.2984745
[274,] 5.5724933 -7.1565390
[275,] 6.0047513 5.5724933
[276,] 10.5441398 6.0047513
[277,] 3.4473656 10.5441398
[278,] -0.9848925 3.4473656
[279,] -10.1623118 -0.9848925
[280,] -19.6236022 -10.1623118
[281,] 17.2505914 -19.6236022
[282,] 24.0215591 17.2505914
[283,] 28.2667204 24.0215591
[284,] 23.2731720 28.2667204
[285,] 11.7151075 23.2731720
[286,] 14.1441398 11.7151075
[287,] -0.3236022 14.1441398
[288,] 1.6157863 -0.3236022
[289,] -11.7809879 1.6157863
[290,] -9.2132460 -11.7809879
[291,] -22.0906653 -9.2132460
[292,] -36.8519556 -22.0906653
[293,] -1.3777621 -36.8519556
[294,] -3.9067944 -1.3777621
[295,] -4.3616331 -3.9067944
[296,] -7.1551815 -4.3616331
[297,] -10.5132460 -7.1551815
[298,] -52.9842137 -10.5132460
[299,] -70.4519556 -52.9842137
[300,] -87.8125672 -70.4519556
[301,] -80.7093414 -87.8125672
[302,] -91.7415995 -80.7093414
[303,] -86.6190188 -91.7415995
[304,] -103.5803091 -86.6190188
[305,] -71.5061156 -103.5803091
[306,] -78.4351478 -71.5061156
[307,] -81.4899866 -78.4351478
[308,] -68.6835349 -81.4899866
[309,] -93.4415995 -68.6835349
[310,] -86.2125672 -93.4415995
[311,] -88.4803091 -86.2125672
[312,] -66.7409207 -88.4803091
[313,] -63.4376949 -66.7409207
[314,] -79.6699530 -63.4376949
[315,] -86.1473723 -79.6699530
[316,] -81.3086626 -86.1473723
[317,] -30.4344691 -81.3086626
[318,] -19.6635013 -30.4344691
[319,] -26.0183401 -19.6635013
[320,] 22.7881116 -26.0183401
[321,] 22.4300470 22.7881116
[322,] 64.4590793 22.4300470
[323,] 104.0913374 64.4590793
[324,] 238.2307258 104.0913374
[325,] 241.2339516 238.2307258
[326,] 268.5016935 241.2339516
[327,] 253.5242742 268.5016935
[328,] 254.3629839 253.5242742
[329,] 276.2371774 254.3629839
[330,] 263.0081452 276.2371774
[331,] 242.8533065 263.0081452
[332,] 242.5597581 242.8533065
[333,] 230.2016935 242.5597581
[334,] 206.8307258 230.2016935
[335,] 200.7629839 206.8307258
[336,] 225.4023723 200.7629839
[337,] 201.4055981 225.4023723
[338,] 172.8733401 201.4055981
[339,] 148.2959207 172.8733401
[340,] 110.2346304 148.2959207
[341,] 172.6088239 110.2346304
[342,] 187.5797917 172.6088239
[343,] 193.2249530 187.5797917
[344,] 180.7314046 193.2249530
[345,] 176.8733401 180.7314046
[346,] 181.0023723 176.8733401
[347,] 171.2346304 181.0023723
[348,] 180.5740188 171.2346304
[349,] 196.7772446 180.5740188
[350,] 163.7449866 196.7772446
[351,] 103.8675672 163.7449866
[352,] 82.7062769 103.8675672
[353,] 140.1804704 82.7062769
[354,] 111.7514382 140.1804704
[355,] 124.4965995 111.7514382
[356,] 109.6030511 124.4965995
[357,] 103.4449866 109.6030511
[358,] 93.8740188 103.4449866
[359,] 44.8062769 93.8740188
[360,] 73.2456653 44.8062769
[361,] 47.5488911 73.2456653
[362,] 43.8166331 47.5488911
[363,] 3.6392137 43.8166331
[364,] 1.0779234 3.6392137
[365,] 15.2521169 1.0779234
[366,] 49.2230847 15.2521169
[367,] 29.6682460 49.2230847
[368,] 33.3746976 29.6682460
[369,] 15.1166331 33.3746976
[370,] 9.9456653 15.1166331
[371,] 17.0779234 9.9456653
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 21.1994960 -14.5037298
2 27.3672379 21.1994960
3 42.3898185 27.3672379
4 23.6285282 42.3898185
5 -9.6972782 23.6285282
6 13.3736895 -9.6972782
7 27.2188508 13.3736895
8 26.6253024 27.2188508
9 10.6672379 26.6253024
10 17.1962702 10.6672379
11 31.9285282 17.1962702
12 37.6679167 31.9285282
13 75.6711425 37.6679167
14 88.8388844 75.6711425
15 117.1614651 88.8388844
16 161.6001747 117.1614651
17 133.8743683 161.6001747
18 198.8453360 133.8743683
19 186.7904973 198.8453360
20 171.7969489 186.7904973
21 202.5388844 171.7969489
22 158.6679167 202.5388844
23 168.2001747 158.6679167
24 190.7395632 168.2001747
25 195.1427890 190.7395632
26 169.6105309 195.1427890
27 143.7331116 169.6105309
28 124.0718212 143.7331116
29 80.1460148 124.0718212
30 79.4169825 80.1460148
31 40.2621438 79.4169825
32 45.0685954 40.2621438
33 17.0105309 45.0685954
34 25.0395632 17.0105309
35 27.8718212 25.0395632
36 -21.3887903 27.8718212
37 -42.3855645 -21.3887903
38 -41.6178226 -42.3855645
39 -41.1952419 -41.6178226
40 -37.4565323 -41.1952419
41 -73.9823387 -37.4565323
42 -57.2113710 -73.9823387
43 -52.6662097 -57.2113710
44 -27.5597581 -52.6662097
45 -25.3178226 -27.5597581
46 -23.7887903 -25.3178226
47 -45.6565323 -23.7887903
48 -72.7171438 -45.6565323
49 -74.4139180 -72.7171438
50 -85.9461761 -74.4139180
51 -63.6235954 -85.9461761
52 -48.4848858 -63.6235954
53 -96.2106922 -48.4848858
54 -68.1397245 -96.2106922
55 -53.6945632 -68.1397245
56 -55.5881116 -53.6945632
57 -64.9461761 -55.5881116
58 -75.6171438 -64.9461761
59 -82.9848858 -75.6171438
60 -97.5454973 -82.9848858
61 -124.2422715 -97.5454973
62 -115.5745296 -124.2422715
63 -83.0519489 -115.5745296
64 -85.3132392 -83.0519489
65 -138.4390457 -85.3132392
66 -117.8680780 -138.4390457
67 -106.5229167 -117.8680780
68 -78.7164651 -106.5229167
69 -67.9745296 -78.7164651
70 -45.5454973 -67.9745296
71 -13.3132392 -45.5454973
72 33.1261492 -13.3132392
73 65.4293750 33.1261492
74 93.0971169 65.4293750
75 112.9196976 93.0971169
76 114.6584073 112.9196976
77 44.2326008 114.6584073
78 66.8035685 44.2326008
79 77.0487298 66.8035685
80 90.4551815 77.0487298
81 55.4971169 90.4551815
82 52.0261492 55.4971169
83 38.9584073 52.0261492
84 31.6977957 38.9584073
85 11.8010215 31.6977957
86 6.8687634 11.8010215
87 32.2913441 6.8687634
88 5.6300538 32.2913441
89 -46.7957527 5.6300538
90 -47.1247849 -46.7957527
91 -28.5796237 -47.1247849
92 -31.2731720 -28.5796237
93 -21.2312366 -31.2731720
94 -18.1022043 -21.2312366
95 -14.0699462 -18.1022043
96 -40.8305578 -14.0699462
97 -48.1273320 -40.8305578
98 -25.5595901 -48.1273320
99 -25.1370094 -25.5595901
100 4.3017003 -25.1370094
101 -30.4241062 4.3017003
102 -27.1531384 -30.4241062
103 -47.7079772 -27.1531384
104 -50.0015255 -47.7079772
105 -52.7595901 -50.0015255
106 -24.0305578 -52.7595901
107 -20.3982997 -24.0305578
108 -39.0589113 -20.3982997
109 -61.0556855 -39.0589113
110 -65.0879435 -61.0556855
111 -45.6653629 -65.0879435
112 -24.3266532 -45.6653629
113 -47.4524597 -24.3266532
114 -53.4814919 -47.4524597
115 -54.0363306 -53.4814919
116 -39.2298790 -54.0363306
117 -27.5879435 -39.2298790
118 16.5410887 -27.5879435
119 34.5733468 16.5410887
120 74.5127352 34.5733468
121 129.8159610 74.5127352
122 155.9837030 129.8159610
123 185.8062836 155.9837030
124 183.1449933 185.8062836
125 149.5191868 183.1449933
126 159.7901546 149.5191868
127 141.8353159 159.7901546
128 104.0417675 141.8353159
129 88.6837030 104.0417675
130 70.1127352 88.6837030
131 95.9449933 70.1127352
132 83.6843817 95.9449933
133 75.7876075 83.6843817
134 58.0553495 75.7876075
135 22.9779301 58.0553495
136 20.4166398 22.9779301
137 -7.0091667 20.4166398
138 -1.7381989 -7.0091667
139 3.6069624 -1.7381989
140 5.5134140 3.6069624
141 24.5553495 5.5134140
142 42.9843817 24.5553495
143 29.0166398 42.9843817
144 15.5560282 29.0166398
145 -17.6407460 15.5560282
146 32.4269960 -17.6407460
147 15.6495766 32.4269960
148 13.4882863 15.6495766
149 19.9624798 13.4882863
150 13.9334476 19.9624798
151 27.7786089 13.9334476
152 5.2850605 27.7786089
153 42.9269960 5.2850605
154 63.8560282 42.9269960
155 111.6882863 63.8560282
156 124.9276747 111.6882863
157 146.9309005 124.9276747
158 146.0986425 146.9309005
159 131.4212231 146.0986425
160 130.3599328 131.4212231
161 121.8341263 130.3599328
162 109.4050941 121.8341263
163 88.4502554 109.4050941
164 64.9567070 88.4502554
165 63.2986425 64.9567070
166 49.0276747 63.2986425
167 56.5599328 49.0276747
168 41.2993212 56.5599328
169 17.4025470 41.2993212
170 23.8702890 17.4025470
171 16.7928696 23.8702890
172 46.2315793 16.7928696
173 0.2057728 46.2315793
174 -16.0232594 0.2057728
175 16.4219019 -16.0232594
176 -5.1716465 16.4219019
177 -11.8297110 -5.1716465
178 15.2993212 -11.8297110
179 16.2315793 15.2993212
180 29.6709677 16.2315793
181 44.0741935 29.6709677
182 23.5419355 44.0741935
183 17.5645161 23.5419355
184 33.7032258 17.5645161
185 21.4774194 33.7032258
186 2.8483871 21.4774194
187 -4.5064516 2.8483871
188 -15.9000000 -4.5064516
189 -8.0580645 -15.9000000
190 16.2709677 -8.0580645
191 6.8032258 16.2709677
192 6.5426142 6.8032258
193 -9.0541599 6.5426142
194 -10.3864180 -9.0541599
195 -10.8638374 -10.3864180
196 -20.6251277 -10.8638374
197 -0.8509341 -20.6251277
198 -55.8799664 -0.8509341
199 -37.1348051 -55.8799664
200 -48.9283535 -37.1348051
201 -39.8864180 -48.9283535
202 -49.9573858 -39.8864180
203 -43.3251277 -49.9573858
204 -63.3857392 -43.3251277
205 -50.1825134 -63.3857392
206 -75.2147715 -50.1825134
207 -56.9921909 -75.2147715
208 -64.2534812 -56.9921909
209 -52.6792876 -64.2534812
210 -92.7083199 -52.6792876
211 -87.9631586 -92.7083199
212 -103.1567070 -87.9631586
213 -101.0147715 -103.1567070
214 -105.1857392 -101.0147715
215 -117.6534812 -105.1857392
216 -145.3140927 -117.6534812
217 -168.7108669 -145.3140927
218 -158.3431250 -168.7108669
219 -145.4205444 -158.3431250
220 -118.5818347 -145.4205444
221 -111.4076411 -118.5818347
222 -142.8366734 -111.4076411
223 -134.5915121 -142.8366734
224 -149.2850605 -134.5915121
225 -137.6431250 -149.2850605
226 -148.3140927 -137.6431250
227 -142.1818347 -148.3140927
228 -166.0424462 -142.1818347
229 -173.4392204 -166.0424462
230 -174.1714785 -173.4392204
231 -164.2488978 -174.1714785
232 -164.3101882 -164.2488978
233 -120.0359946 -164.3101882
234 -135.1650269 -120.0359946
235 -134.7198656 -135.1650269
236 -122.3134140 -134.7198656
237 -101.1714785 -122.3134140
238 -128.1424462 -101.1714785
239 -148.9101882 -128.1424462
240 -186.7707997 -148.9101882
241 -175.3675739 -186.7707997
242 -188.8998320 -175.3675739
243 -193.7772513 -188.8998320
244 -191.9385417 -193.7772513
245 -133.5643481 -191.9385417
246 -150.5933804 -133.5643481
247 -163.9482191 -150.5933804
248 -163.3417675 -163.9482191
249 -157.5998320 -163.3417675
250 -173.0707997 -157.5998320
251 -191.3385417 -173.0707997
252 -218.8991532 -191.3385417
253 -223.9959274 -218.8991532
254 -219.3281855 -223.9959274
255 -200.9056048 -219.3281855
256 -204.5668952 -200.9056048
257 -168.2927016 -204.5668952
258 -166.3217339 -168.2927016
259 -166.3765726 -166.3217339
260 -140.4701210 -166.3765726
261 -136.8281855 -140.4701210
262 -171.8991532 -136.8281855
263 -182.6668952 -171.8991532
264 -178.0275067 -182.6668952
265 -149.1242809 -178.0275067
266 -132.9565390 -149.1242809
267 -112.1339583 -132.9565390
268 -108.3952487 -112.1339583
269 -52.6210551 -108.3952487
270 -45.7500874 -52.6210551
271 -43.6049261 -45.7500874
272 -19.2984745 -43.6049261
273 -7.1565390 -19.2984745
274 5.5724933 -7.1565390
275 6.0047513 5.5724933
276 10.5441398 6.0047513
277 3.4473656 10.5441398
278 -0.9848925 3.4473656
279 -10.1623118 -0.9848925
280 -19.6236022 -10.1623118
281 17.2505914 -19.6236022
282 24.0215591 17.2505914
283 28.2667204 24.0215591
284 23.2731720 28.2667204
285 11.7151075 23.2731720
286 14.1441398 11.7151075
287 -0.3236022 14.1441398
288 1.6157863 -0.3236022
289 -11.7809879 1.6157863
290 -9.2132460 -11.7809879
291 -22.0906653 -9.2132460
292 -36.8519556 -22.0906653
293 -1.3777621 -36.8519556
294 -3.9067944 -1.3777621
295 -4.3616331 -3.9067944
296 -7.1551815 -4.3616331
297 -10.5132460 -7.1551815
298 -52.9842137 -10.5132460
299 -70.4519556 -52.9842137
300 -87.8125672 -70.4519556
301 -80.7093414 -87.8125672
302 -91.7415995 -80.7093414
303 -86.6190188 -91.7415995
304 -103.5803091 -86.6190188
305 -71.5061156 -103.5803091
306 -78.4351478 -71.5061156
307 -81.4899866 -78.4351478
308 -68.6835349 -81.4899866
309 -93.4415995 -68.6835349
310 -86.2125672 -93.4415995
311 -88.4803091 -86.2125672
312 -66.7409207 -88.4803091
313 -63.4376949 -66.7409207
314 -79.6699530 -63.4376949
315 -86.1473723 -79.6699530
316 -81.3086626 -86.1473723
317 -30.4344691 -81.3086626
318 -19.6635013 -30.4344691
319 -26.0183401 -19.6635013
320 22.7881116 -26.0183401
321 22.4300470 22.7881116
322 64.4590793 22.4300470
323 104.0913374 64.4590793
324 238.2307258 104.0913374
325 241.2339516 238.2307258
326 268.5016935 241.2339516
327 253.5242742 268.5016935
328 254.3629839 253.5242742
329 276.2371774 254.3629839
330 263.0081452 276.2371774
331 242.8533065 263.0081452
332 242.5597581 242.8533065
333 230.2016935 242.5597581
334 206.8307258 230.2016935
335 200.7629839 206.8307258
336 225.4023723 200.7629839
337 201.4055981 225.4023723
338 172.8733401 201.4055981
339 148.2959207 172.8733401
340 110.2346304 148.2959207
341 172.6088239 110.2346304
342 187.5797917 172.6088239
343 193.2249530 187.5797917
344 180.7314046 193.2249530
345 176.8733401 180.7314046
346 181.0023723 176.8733401
347 171.2346304 181.0023723
348 180.5740188 171.2346304
349 196.7772446 180.5740188
350 163.7449866 196.7772446
351 103.8675672 163.7449866
352 82.7062769 103.8675672
353 140.1804704 82.7062769
354 111.7514382 140.1804704
355 124.4965995 111.7514382
356 109.6030511 124.4965995
357 103.4449866 109.6030511
358 93.8740188 103.4449866
359 44.8062769 93.8740188
360 73.2456653 44.8062769
361 47.5488911 73.2456653
362 43.8166331 47.5488911
363 3.6392137 43.8166331
364 1.0779234 3.6392137
365 15.2521169 1.0779234
366 49.2230847 15.2521169
367 29.6682460 49.2230847
368 33.3746976 29.6682460
369 15.1166331 33.3746976
370 9.9456653 15.1166331
371 17.0779234 9.9456653
> 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/7iinz1291150235.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8iinz1291150235.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9iinz1291150235.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10srm21291150235.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11es281291150235.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/12za1w1291150235.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/13d2ym1291150235.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/14h2fs1291150235.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/15k3eg1291150235.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/16n3cm1291150235.tab")
+ }
>
> try(system("convert tmp/148781291150235.ps tmp/148781291150235.png",intern=TRUE))
character(0)
> try(system("convert tmp/248781291150235.ps tmp/248781291150235.png",intern=TRUE))
character(0)
> try(system("convert tmp/3ezot1291150235.ps tmp/3ezot1291150235.png",intern=TRUE))
character(0)
> try(system("convert tmp/4ezot1291150235.ps tmp/4ezot1291150235.png",intern=TRUE))
character(0)
> try(system("convert tmp/5ezot1291150235.ps tmp/5ezot1291150235.png",intern=TRUE))
character(0)
> try(system("convert tmp/6p9ne1291150235.ps tmp/6p9ne1291150235.png",intern=TRUE))
character(0)
> try(system("convert tmp/7iinz1291150235.ps tmp/7iinz1291150235.png",intern=TRUE))
character(0)
> try(system("convert tmp/8iinz1291150235.ps tmp/8iinz1291150235.png",intern=TRUE))
character(0)
> try(system("convert tmp/9iinz1291150235.ps tmp/9iinz1291150235.png",intern=TRUE))
character(0)
> try(system("convert tmp/10srm21291150235.ps tmp/10srm21291150235.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
10.044 2.037 26.467