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.
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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(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
+ ,362)
+ ,dimnames=list(c('Unemployment')
+ ,1:362))
> y <- array(NA,dim=c(1,362),dimnames=list(c('Unemployment'),1:362))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par3 = 'No Linear Trend'
> par2 = 'Include Monthly Dummies'
> par1 = '1'
> par3 <- 'No 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, 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
1 203.3 1 0 0 0 0 0 0 0 0 0 0
2 220.5 0 1 0 0 0 0 0 0 0 0 0
3 299.5 0 0 1 0 0 0 0 0 0 0 0
4 347.4 0 0 0 1 0 0 0 0 0 0 0
5 338.3 0 0 0 0 1 0 0 0 0 0 0
6 327.7 0 0 0 0 0 1 0 0 0 0 0
7 351.6 0 0 0 0 0 0 1 0 0 0 0
8 396.6 0 0 0 0 0 0 0 1 0 0 0
9 438.8 0 0 0 0 0 0 0 0 1 0 0
10 395.6 0 0 0 0 0 0 0 0 0 1 0
11 363.5 0 0 0 0 0 0 0 0 0 0 1
12 378.8 0 0 0 0 0 0 0 0 0 0 0
13 357.0 1 0 0 0 0 0 0 0 0 0 0
14 369.0 0 1 0 0 0 0 0 0 0 0 0
15 464.8 0 0 1 0 0 0 0 0 0 0 0
16 479.1 0 0 0 1 0 0 0 0 0 0 0
17 431.3 0 0 0 0 1 0 0 0 0 0 0
18 366.5 0 0 0 0 0 1 0 0 0 0 0
19 326.3 0 0 0 0 0 0 1 0 0 0 0
20 355.1 0 0 0 0 0 0 0 1 0 0 0
21 331.6 0 0 0 0 0 0 0 0 1 0 0
22 261.3 0 0 0 0 0 0 0 0 0 1 0
23 249.0 0 0 0 0 0 0 0 0 0 0 1
24 205.5 0 0 0 0 0 0 0 0 0 0 0
25 235.6 1 0 0 0 0 0 0 0 0 0 0
26 240.9 0 1 0 0 0 0 0 0 0 0 0
27 264.9 0 0 1 0 0 0 0 0 0 0 0
28 253.8 0 0 0 1 0 0 0 0 0 0 0
29 232.3 0 0 0 0 1 0 0 0 0 0 0
30 193.8 0 0 0 0 0 1 0 0 0 0 0
31 177.0 0 0 0 0 0 0 1 0 0 0 0
32 213.2 0 0 0 0 0 0 0 1 0 0 0
33 207.2 0 0 0 0 0 0 0 0 1 0 0
34 180.6 0 0 0 0 0 0 0 0 0 1 0
35 188.6 0 0 0 0 0 0 0 0 0 0 1
36 175.4 0 0 0 0 0 0 0 0 0 0 0
37 199.0 1 0 0 0 0 0 0 0 0 0 0
38 179.6 0 1 0 0 0 0 0 0 0 0 0
39 225.8 0 0 1 0 0 0 0 0 0 0 0
40 234.0 0 0 0 1 0 0 0 0 0 0 0
41 200.2 0 0 0 0 1 0 0 0 0 0 0
42 183.6 0 0 0 0 0 1 0 0 0 0 0
43 178.2 0 0 0 0 0 0 1 0 0 0 0
44 203.2 0 0 0 0 0 0 0 1 0 0 0
45 208.5 0 0 0 0 0 0 0 0 1 0 0
46 191.8 0 0 0 0 0 0 0 0 0 1 0
47 172.8 0 0 0 0 0 0 0 0 0 0 1
48 148.0 0 0 0 0 0 0 0 0 0 0 0
49 159.4 1 0 0 0 0 0 0 0 0 0 0
50 154.5 0 1 0 0 0 0 0 0 0 0 0
51 213.2 0 0 1 0 0 0 0 0 0 0 0
52 196.4 0 0 0 1 0 0 0 0 0 0 0
53 182.8 0 0 0 0 1 0 0 0 0 0 0
54 176.4 0 0 0 0 0 1 0 0 0 0 0
55 153.6 0 0 0 0 0 0 1 0 0 0 0
56 173.2 0 0 0 0 0 0 0 1 0 0 0
57 171.0 0 0 0 0 0 0 0 0 1 0 0
58 151.2 0 0 0 0 0 0 0 0 0 1 0
59 161.9 0 0 0 0 0 0 0 0 0 0 1
60 157.2 0 0 0 0 0 0 0 0 0 0 0
61 201.7 1 0 0 0 0 0 0 0 0 0 0
62 236.4 0 1 0 0 0 0 0 0 0 0 0
63 356.1 0 0 1 0 0 0 0 0 0 0 0
64 398.3 0 0 0 1 0 0 0 0 0 0 0
65 403.7 0 0 0 0 1 0 0 0 0 0 0
66 384.6 0 0 0 0 0 1 0 0 0 0 0
67 365.8 0 0 0 0 0 0 1 0 0 0 0
68 368.1 0 0 0 0 0 0 0 1 0 0 0
69 367.9 0 0 0 0 0 0 0 0 1 0 0
70 347.0 0 0 0 0 0 0 0 0 0 1 0
71 343.3 0 0 0 0 0 0 0 0 0 0 1
72 292.9 0 0 0 0 0 0 0 0 0 0 0
73 311.5 1 0 0 0 0 0 0 0 0 0 0
74 300.9 0 1 0 0 0 0 0 0 0 0 0
75 366.9 0 0 1 0 0 0 0 0 0 0 0
76 356.9 0 0 0 1 0 0 0 0 0 0 0
77 329.7 0 0 0 0 1 0 0 0 0 0 0
78 316.2 0 0 0 0 0 1 0 0 0 0 0
79 269.0 0 0 0 0 0 0 1 0 0 0 0
80 289.3 0 0 0 0 0 0 0 1 0 0 0
81 266.2 0 0 0 0 0 0 0 0 1 0 0
82 253.6 0 0 0 0 0 0 0 0 0 1 0
83 233.8 0 0 0 0 0 0 0 0 0 0 1
84 228.4 0 0 0 0 0 0 0 0 0 0 0
85 253.6 1 0 0 0 0 0 0 0 0 0 0
86 260.1 0 1 0 0 0 0 0 0 0 0 0
87 306.6 0 0 1 0 0 0 0 0 0 0 0
88 309.2 0 0 0 1 0 0 0 0 0 0 0
89 309.5 0 0 0 0 1 0 0 0 0 0 0
90 271.0 0 0 0 0 0 1 0 0 0 0 0
91 279.9 0 0 0 0 0 0 1 0 0 0 0
92 317.9 0 0 0 0 0 0 0 1 0 0 0
93 298.4 0 0 0 0 0 0 0 0 1 0 0
94 246.7 0 0 0 0 0 0 0 0 0 1 0
95 227.3 0 0 0 0 0 0 0 0 0 0 1
96 209.1 0 0 0 0 0 0 0 0 0 0 0
97 259.9 1 0 0 0 0 0 0 0 0 0 0
98 266.0 0 1 0 0 0 0 0 0 0 0 0
99 320.6 0 0 1 0 0 0 0 0 0 0 0
100 308.5 0 0 0 1 0 0 0 0 0 0 0
101 282.2 0 0 0 0 1 0 0 0 0 0 0
102 262.7 0 0 0 0 0 1 0 0 0 0 0
103 263.5 0 0 0 0 0 0 1 0 0 0 0
104 313.1 0 0 0 0 0 0 0 1 0 0 0
105 284.3 0 0 0 0 0 0 0 0 1 0 0
106 252.6 0 0 0 0 0 0 0 0 0 1 0
107 250.3 0 0 0 0 0 0 0 0 0 0 1
108 246.5 0 0 0 0 0 0 0 0 0 0 0
109 312.7 1 0 0 0 0 0 0 0 0 0 0
110 333.2 0 1 0 0 0 0 0 0 0 0 0
111 446.4 0 0 1 0 0 0 0 0 0 0 0
112 511.6 0 0 0 1 0 0 0 0 0 0 0
113 515.5 0 0 0 0 1 0 0 0 0 0 0
114 506.4 0 0 0 0 0 1 0 0 0 0 0
115 483.2 0 0 0 0 0 0 1 0 0 0 0
116 522.3 0 0 0 0 0 0 0 1 0 0 0
117 509.8 0 0 0 0 0 0 0 0 1 0 0
118 460.7 0 0 0 0 0 0 0 0 0 1 0
119 405.8 0 0 0 0 0 0 0 0 0 0 1
120 375.0 0 0 0 0 0 0 0 0 0 0 0
121 378.5 1 0 0 0 0 0 0 0 0 0 0
122 406.8 0 1 0 0 0 0 0 0 0 0 0
123 467.8 0 0 1 0 0 0 0 0 0 0 0
124 469.8 0 0 0 1 0 0 0 0 0 0 0
125 429.8 0 0 0 0 1 0 0 0 0 0 0
126 355.8 0 0 0 0 0 1 0 0 0 0 0
127 332.7 0 0 0 0 0 0 1 0 0 0 0
128 378.0 0 0 0 0 0 0 0 1 0 0 0
129 360.5 0 0 0 0 0 0 0 0 1 0 0
130 334.7 0 0 0 0 0 0 0 0 0 1 0
131 319.5 0 0 0 0 0 0 0 0 0 0 1
132 323.1 0 0 0 0 0 0 0 0 0 0 0
133 363.6 1 0 0 0 0 0 0 0 0 0 0
134 352.1 0 1 0 0 0 0 0 0 0 0 0
135 411.9 0 0 1 0 0 0 0 0 0 0 0
136 388.6 0 0 0 1 0 0 0 0 0 0 0
137 416.4 0 0 0 0 1 0 0 0 0 0 0
138 360.7 0 0 0 0 0 1 0 0 0 0 0
139 338.0 0 0 0 0 0 0 1 0 0 0 0
140 417.2 0 0 0 0 0 0 0 1 0 0 0
141 388.4 0 0 0 0 0 0 0 0 1 0 0
142 371.1 0 0 0 0 0 0 0 0 0 1 0
143 331.5 0 0 0 0 0 0 0 0 0 0 1
144 353.7 0 0 0 0 0 0 0 0 0 0 0
145 396.7 1 0 0 0 0 0 0 0 0 0 0
146 447.0 0 1 0 0 0 0 0 0 0 0 0
147 533.5 0 0 1 0 0 0 0 0 0 0 0
148 565.4 0 0 0 1 0 0 0 0 0 0 0
149 542.3 0 0 0 0 1 0 0 0 0 0 0
150 488.7 0 0 0 0 0 1 0 0 0 0 0
151 467.1 0 0 0 0 0 0 1 0 0 0 0
152 531.3 0 0 0 0 0 0 0 1 0 0 0
153 496.1 0 0 0 0 0 0 0 0 1 0 0
154 444.0 0 0 0 0 0 0 0 0 0 1 0
155 403.4 0 0 0 0 0 0 0 0 0 0 1
156 386.3 0 0 0 0 0 0 0 0 0 0 0
157 394.1 1 0 0 0 0 0 0 0 0 0 0
158 404.1 0 1 0 0 0 0 0 0 0 0 0
159 462.1 0 0 1 0 0 0 0 0 0 0 0
160 448.1 0 0 0 1 0 0 0 0 0 0 0
161 432.3 0 0 0 0 1 0 0 0 0 0 0
162 386.3 0 0 0 0 0 1 0 0 0 0 0
163 395.2 0 0 0 0 0 0 1 0 0 0 0
164 421.9 0 0 0 0 0 0 0 1 0 0 0
165 382.9 0 0 0 0 0 0 0 0 1 0 0
166 384.2 0 0 0 0 0 0 0 0 0 1 0
167 345.5 0 0 0 0 0 0 0 0 0 0 1
168 323.4 0 0 0 0 0 0 0 0 0 0 0
169 372.6 1 0 0 0 0 0 0 0 0 0 0
170 376.0 0 1 0 0 0 0 0 0 0 0 0
171 462.7 0 0 1 0 0 0 0 0 0 0 0
172 487.0 0 0 0 1 0 0 0 0 0 0 0
173 444.2 0 0 0 0 1 0 0 0 0 0 0
174 399.3 0 0 0 0 0 1 0 0 0 0 0
175 394.9 0 0 0 0 0 0 1 0 0 0 0
176 455.4 0 0 0 0 0 0 0 1 0 0 0
177 414.0 0 0 0 0 0 0 0 0 1 0 0
178 375.5 0 0 0 0 0 0 0 0 0 1 0
179 347.0 0 0 0 0 0 0 0 0 0 0 1
180 339.4 0 0 0 0 0 0 0 0 0 0 0
181 385.8 1 0 0 0 0 0 0 0 0 0 0
182 378.8 0 1 0 0 0 0 0 0 0 0 0
183 451.8 0 0 1 0 0 0 0 0 0 0 0
184 446.1 0 0 0 1 0 0 0 0 0 0 0
185 422.5 0 0 0 0 1 0 0 0 0 0 0
186 383.1 0 0 0 0 0 1 0 0 0 0 0
187 352.8 0 0 0 0 0 0 1 0 0 0 0
188 445.3 0 0 0 0 0 0 0 1 0 0 0
189 367.5 0 0 0 0 0 0 0 0 1 0 0
190 355.1 0 0 0 0 0 0 0 0 0 1 0
191 326.2 0 0 0 0 0 0 0 0 0 0 1
192 319.8 0 0 0 0 0 0 0 0 0 0 0
193 331.8 1 0 0 0 0 0 0 0 0 0 0
194 340.9 0 1 0 0 0 0 0 0 0 0 0
195 394.1 0 0 1 0 0 0 0 0 0 0 0
196 417.2 0 0 0 1 0 0 0 0 0 0 0
197 369.9 0 0 0 0 1 0 0 0 0 0 0
198 349.2 0 0 0 0 0 1 0 0 0 0 0
199 321.4 0 0 0 0 0 0 1 0 0 0 0
200 405.7 0 0 0 0 0 0 0 1 0 0 0
201 342.9 0 0 0 0 0 0 0 0 1 0 0
202 316.5 0 0 0 0 0 0 0 0 0 1 0
203 284.2 0 0 0 0 0 0 0 0 0 0 1
204 270.9 0 0 0 0 0 0 0 0 0 0 0
205 288.8 1 0 0 0 0 0 0 0 0 0 0
206 278.8 0 1 0 0 0 0 0 0 0 0 0
207 324.4 0 0 1 0 0 0 0 0 0 0 0
208 310.9 0 0 0 1 0 0 0 0 0 0 0
209 299.0 0 0 0 0 1 0 0 0 0 0 0
210 273.0 0 0 0 0 0 1 0 0 0 0 0
211 279.3 0 0 0 0 0 0 1 0 0 0 0
212 359.2 0 0 0 0 0 0 0 1 0 0 0
213 305.0 0 0 0 0 0 0 0 0 1 0 0
214 282.1 0 0 0 0 0 0 0 0 0 1 0
215 250.3 0 0 0 0 0 0 0 0 0 0 1
216 246.5 0 0 0 0 0 0 0 0 0 0 0
217 257.9 1 0 0 0 0 0 0 0 0 0 0
218 266.5 0 1 0 0 0 0 0 0 0 0 0
219 315.9 0 0 1 0 0 0 0 0 0 0 0
220 318.4 0 0 0 1 0 0 0 0 0 0 0
221 295.4 0 0 0 0 1 0 0 0 0 0 0
222 266.4 0 0 0 0 0 1 0 0 0 0 0
223 245.8 0 0 0 0 0 0 1 0 0 0 0
224 362.8 0 0 0 0 0 0 0 1 0 0 0
225 324.9 0 0 0 0 0 0 0 0 1 0 0
226 294.2 0 0 0 0 0 0 0 0 0 1 0
227 289.5 0 0 0 0 0 0 0 0 0 0 1
228 295.2 0 0 0 0 0 0 0 0 0 0 0
229 290.3 1 0 0 0 0 0 0 0 0 0 0
230 272.0 0 1 0 0 0 0 0 0 0 0 0
231 307.4 0 0 1 0 0 0 0 0 0 0 0
232 328.7 0 0 0 1 0 0 0 0 0 0 0
233 292.9 0 0 0 0 1 0 0 0 0 0 0
234 249.1 0 0 0 0 0 1 0 0 0 0 0
235 230.4 0 0 0 0 0 0 1 0 0 0 0
236 361.5 0 0 0 0 0 0 0 1 0 0 0
237 321.7 0 0 0 0 0 0 0 0 1 0 0
238 277.2 0 0 0 0 0 0 0 0 0 1 0
239 260.7 0 0 0 0 0 0 0 0 0 0 1
240 251.0 0 0 0 0 0 0 0 0 0 0 0
241 257.6 1 0 0 0 0 0 0 0 0 0 0
242 241.8 0 1 0 0 0 0 0 0 0 0 0
243 287.5 0 0 1 0 0 0 0 0 0 0 0
244 292.3 0 0 0 1 0 0 0 0 0 0 0
245 274.7 0 0 0 0 1 0 0 0 0 0 0
246 254.2 0 0 0 0 0 1 0 0 0 0 0
247 230.0 0 0 0 0 0 0 1 0 0 0 0
248 339.0 0 0 0 0 0 0 0 1 0 0 0
249 318.2 0 0 0 0 0 0 0 0 1 0 0
250 287.0 0 0 0 0 0 0 0 0 0 1 0
251 295.8 0 0 0 0 0 0 0 0 0 0 1
252 284.0 0 0 0 0 0 0 0 0 0 0 0
253 271.0 1 0 0 0 0 0 0 0 0 0 0
254 262.7 0 1 0 0 0 0 0 0 0 0 0
255 340.6 0 0 1 0 0 0 0 0 0 0 0
256 379.4 0 0 0 1 0 0 0 0 0 0 0
257 373.3 0 0 0 0 1 0 0 0 0 0 0
258 355.2 0 0 0 0 0 1 0 0 0 0 0
259 338.4 0 0 0 0 0 0 1 0 0 0 0
260 466.9 0 0 0 0 0 0 0 1 0 0 0
261 451.0 0 0 0 0 0 0 0 0 1 0 0
262 422.0 0 0 0 0 0 0 0 0 0 1 0
263 429.2 0 0 0 0 0 0 0 0 0 0 1
264 425.9 0 0 0 0 0 0 0 0 0 0 0
265 460.7 1 0 0 0 0 0 0 0 0 0 0
266 463.6 0 1 0 0 0 0 0 0 0 0 0
267 541.4 0 0 1 0 0 0 0 0 0 0 0
268 544.2 0 0 0 1 0 0 0 0 0 0 0
269 517.5 0 0 0 0 1 0 0 0 0 0 0
270 469.4 0 0 0 0 0 1 0 0 0 0 0
271 439.4 0 0 0 0 0 0 1 0 0 0 0
272 549.0 0 0 0 0 0 0 0 1 0 0 0
273 533.0 0 0 0 0 0 0 0 0 1 0 0
274 506.1 0 0 0 0 0 0 0 0 0 1 0
275 484.0 0 0 0 0 0 0 0 0 0 0 1
276 457.0 0 0 0 0 0 0 0 0 0 0 0
277 481.5 1 0 0 0 0 0 0 0 0 0 0
278 469.5 0 1 0 0 0 0 0 0 0 0 0
279 544.7 0 0 1 0 0 0 0 0 0 0 0
280 541.2 0 0 0 1 0 0 0 0 0 0 0
281 521.5 0 0 0 0 1 0 0 0 0 0 0
282 469.7 0 0 0 0 0 1 0 0 0 0 0
283 434.4 0 0 0 0 0 0 1 0 0 0 0
284 542.6 0 0 0 0 0 0 0 1 0 0 0
285 517.3 0 0 0 0 0 0 0 0 1 0 0
286 485.7 0 0 0 0 0 0 0 0 0 1 0
287 465.8 0 0 0 0 0 0 0 0 0 0 1
288 447.0 0 0 0 0 0 0 0 0 0 0 0
289 426.6 1 0 0 0 0 0 0 0 0 0 0
290 411.6 0 1 0 0 0 0 0 0 0 0 0
291 467.5 0 0 1 0 0 0 0 0 0 0 0
292 484.5 0 0 0 1 0 0 0 0 0 0 0
293 451.2 0 0 0 0 1 0 0 0 0 0 0
294 417.4 0 0 0 0 0 1 0 0 0 0 0
295 379.9 0 0 0 0 0 0 1 0 0 0 0
296 484.7 0 0 0 0 0 0 0 1 0 0 0
297 455.0 0 0 0 0 0 0 0 0 1 0 0
298 420.8 0 0 0 0 0 0 0 0 0 1 0
299 416.5 0 0 0 0 0 0 0 0 0 0 1
300 376.3 0 0 0 0 0 0 0 0 0 0 0
301 405.6 1 0 0 0 0 0 0 0 0 0 0
302 405.8 0 1 0 0 0 0 0 0 0 0 0
303 500.8 0 0 1 0 0 0 0 0 0 0 0
304 514.0 0 0 0 1 0 0 0 0 0 0 0
305 475.5 0 0 0 0 1 0 0 0 0 0 0
306 430.1 0 0 0 0 0 1 0 0 0 0 0
307 414.4 0 0 0 0 0 0 1 0 0 0 0
308 538.0 0 0 0 0 0 0 0 1 0 0 0
309 526.0 0 0 0 0 0 0 0 0 1 0 0
310 488.5 0 0 0 0 0 0 0 0 0 1 0
311 520.2 0 0 0 0 0 0 0 0 0 0 1
312 504.4 0 0 0 0 0 0 0 0 0 0 0
313 568.5 1 0 0 0 0 0 0 0 0 0 0
314 610.6 0 1 0 0 0 0 0 0 0 0 0
315 818.0 0 0 1 0 0 0 0 0 0 0 0
316 830.9 0 0 0 1 0 0 0 0 0 0 0
317 835.9 0 0 0 0 1 0 0 0 0 0 0
318 782.0 0 0 0 0 0 1 0 0 0 0 0
319 762.3 0 0 0 0 0 0 1 0 0 0 0
320 856.9 0 0 0 0 0 0 0 1 0 0 0
321 820.9 0 0 0 0 0 0 0 0 1 0 0
322 769.6 0 0 0 0 0 0 0 0 0 1 0
323 752.2 0 0 0 0 0 0 0 0 0 0 1
324 724.4 0 0 0 0 0 0 0 0 0 0 0
325 723.1 1 0 0 0 0 0 0 0 0 0 0
326 719.5 0 1 0 0 0 0 0 0 0 0 0
327 817.4 0 0 1 0 0 0 0 0 0 0 0
328 803.3 0 0 0 1 0 0 0 0 0 0 0
329 752.5 0 0 0 0 1 0 0 0 0 0 0
330 689.0 0 0 0 0 0 1 0 0 0 0 0
331 630.4 0 0 0 0 0 0 1 0 0 0 0
332 765.5 0 0 0 0 0 0 0 1 0 0 0
333 757.7 0 0 0 0 0 0 0 0 1 0 0
334 732.2 0 0 0 0 0 0 0 0 0 1 0
335 702.6 0 0 0 0 0 0 0 0 0 0 1
336 683.3 0 0 0 0 0 0 0 0 0 0 0
337 709.5 1 0 0 0 0 0 0 0 0 0 0
338 702.2 0 1 0 0 0 0 0 0 0 0 0
339 784.8 0 0 1 0 0 0 0 0 0 0 0
340 810.9 0 0 0 1 0 0 0 0 0 0 0
341 755.6 0 0 0 0 1 0 0 0 0 0 0
342 656.8 0 0 0 0 0 1 0 0 0 0 0
343 615.1 0 0 0 0 0 0 1 0 0 0 0
344 745.3 0 0 0 0 0 0 0 1 0 0 0
345 694.1 0 0 0 0 0 0 0 0 1 0 0
346 675.7 0 0 0 0 0 0 0 0 0 1 0
347 643.7 0 0 0 0 0 0 0 0 0 0 1
348 622.1 0 0 0 0 0 0 0 0 0 0 0
349 634.6 1 0 0 0 0 0 0 0 0 0 0
350 588.0 0 1 0 0 0 0 0 0 0 0 0
351 689.7 0 0 1 0 0 0 0 0 0 0 0
352 673.9 0 0 0 1 0 0 0 0 0 0 0
353 647.9 0 0 0 0 1 0 0 0 0 0 0
354 568.8 0 0 0 0 0 1 0 0 0 0 0
355 545.7 0 0 0 0 0 0 1 0 0 0 0
356 632.6 0 0 0 0 0 0 0 1 0 0 0
357 643.8 0 0 0 0 0 0 0 0 1 0 0
358 593.1 0 0 0 0 0 0 0 0 0 1 0
359 579.7 0 0 0 0 0 0 0 0 0 0 1
360 546.0 0 0 0 0 0 0 0 0 0 0 0
361 562.9 1 0 0 0 0 0 0 0 0 0 0
362 572.5 0 1 0 0 0 0 0 0 0 0 0
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) M1 M2 M3 M4 M5
353.22 16.31 18.78 86.41 95.12 72.64
M6 M7 M8 M9 M10 M11
33.22 13.31 87.14 63.60 32.00 14.91
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-267.16 -111.77 -25.28 74.47 416.54
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 353.22 28.04 12.599 <2e-16 ***
M1 16.31 39.33 0.415 0.6786
M2 18.78 39.33 0.478 0.6333
M3 86.41 39.65 2.179 0.0300 *
M4 95.12 39.65 2.399 0.0170 *
M5 72.64 39.65 1.832 0.0678 .
M6 33.22 39.65 0.838 0.4027
M7 13.31 39.65 0.336 0.7374
M8 87.14 39.65 2.198 0.0286 *
M9 63.60 39.65 1.604 0.1096
M10 32.00 39.65 0.807 0.4202
M11 14.91 39.65 0.376 0.7071
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 153.6 on 350 degrees of freedom
Multiple R-squared: 0.04483, Adjusted R-squared: 0.01481
F-statistic: 1.493 on 11 and 350 DF, p-value: 0.1319
> 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,] 3.173716e-01 6.347433e-01 0.6826283602
[2,] 2.368432e-01 4.736864e-01 0.7631567854
[3,] 1.542596e-01 3.085191e-01 0.8457404434
[4,] 8.517067e-02 1.703413e-01 0.9148293262
[5,] 4.370720e-02 8.741440e-02 0.9562927990
[6,] 2.208975e-02 4.417949e-02 0.9779102541
[7,] 1.485371e-02 2.970742e-02 0.9851462878
[8,] 1.228766e-02 2.457532e-02 0.9877123405
[9,] 8.781212e-03 1.756242e-02 0.9912187884
[10,] 1.004936e-02 2.009872e-02 0.9899506416
[11,] 5.483767e-03 1.096753e-02 0.9945162334
[12,] 3.041203e-03 6.082406e-03 0.9969587972
[13,] 2.591501e-03 5.183003e-03 0.9974084986
[14,] 3.337255e-03 6.674510e-03 0.9966627448
[15,] 3.809582e-03 7.619164e-03 0.9961904180
[16,] 4.256156e-03 8.512313e-03 0.9957438437
[17,] 4.988970e-03 9.977941e-03 0.9950110297
[18,] 5.813035e-03 1.162607e-02 0.9941869653
[19,] 7.390226e-03 1.478045e-02 0.9926097740
[20,] 7.428507e-03 1.485701e-02 0.9925714926
[21,] 6.253031e-03 1.250606e-02 0.9937469686
[22,] 5.248828e-03 1.049766e-02 0.9947511720
[23,] 3.667041e-03 7.334083e-03 0.9963329586
[24,] 2.920503e-03 5.841007e-03 0.9970794967
[25,] 2.622095e-03 5.244190e-03 0.9973779048
[26,] 2.487045e-03 4.974090e-03 0.9975129551
[27,] 2.493135e-03 4.986271e-03 0.9975068645
[28,] 2.185132e-03 4.370264e-03 0.9978148681
[29,] 1.850776e-03 3.701551e-03 0.9981492244
[30,] 1.726307e-03 3.452615e-03 0.9982736926
[31,] 1.573749e-03 3.147499e-03 0.9984262506
[32,] 1.238754e-03 2.477508e-03 0.9987612458
[33,] 1.006494e-03 2.012988e-03 0.9989935060
[34,] 8.690297e-04 1.738059e-03 0.9991309703
[35,] 7.145528e-04 1.429106e-03 0.9992854472
[36,] 6.179284e-04 1.235857e-03 0.9993820716
[37,] 5.485498e-04 1.097100e-03 0.9994514502
[38,] 6.020744e-04 1.204149e-03 0.9993979256
[39,] 6.013411e-04 1.202682e-03 0.9993986589
[40,] 5.115338e-04 1.023068e-03 0.9994884662
[41,] 4.659582e-04 9.319163e-04 0.9995340418
[42,] 4.898807e-04 9.797615e-04 0.9995101193
[43,] 5.230117e-04 1.046023e-03 0.9994769883
[44,] 4.986606e-04 9.973212e-04 0.9995013394
[45,] 4.165304e-04 8.330608e-04 0.9995834696
[46,] 3.310921e-04 6.621841e-04 0.9996689079
[47,] 2.343733e-04 4.687466e-04 0.9997656267
[48,] 1.573027e-04 3.146054e-04 0.9998426973
[49,] 1.127668e-04 2.255337e-04 0.9998872332
[50,] 9.180150e-05 1.836030e-04 0.9999081985
[51,] 8.896808e-05 1.779362e-04 0.9999110319
[52,] 9.054348e-05 1.810870e-04 0.9999094565
[53,] 8.764860e-05 1.752972e-04 0.9999123514
[54,] 7.356332e-05 1.471266e-04 0.9999264367
[55,] 5.981403e-05 1.196281e-04 0.9999401860
[56,] 5.230269e-05 1.046054e-04 0.9999476973
[57,] 4.686700e-05 9.373400e-05 0.9999531330
[58,] 3.542709e-05 7.085418e-05 0.9999645729
[59,] 2.759569e-05 5.519138e-05 0.9999724043
[60,] 2.005240e-05 4.010481e-05 0.9999799476
[61,] 1.431901e-05 2.863802e-05 0.9999856810
[62,] 9.634456e-06 1.926891e-05 0.9999903655
[63,] 6.381009e-06 1.276202e-05 0.9999936190
[64,] 4.230378e-06 8.460756e-06 0.9999957696
[65,] 2.692341e-06 5.384682e-06 0.9999973077
[66,] 1.825084e-06 3.650168e-06 0.9999981749
[67,] 1.239614e-06 2.479228e-06 0.9999987604
[68,] 8.085063e-07 1.617013e-06 0.9999991915
[69,] 5.283850e-07 1.056770e-06 0.9999994716
[70,] 3.388597e-07 6.777194e-07 0.9999996611
[71,] 2.175689e-07 4.351377e-07 0.9999997824
[72,] 1.386106e-07 2.772212e-07 0.9999998614
[73,] 8.979945e-08 1.795989e-07 0.9999999102
[74,] 5.885595e-08 1.177119e-07 0.9999999411
[75,] 3.700835e-08 7.401669e-08 0.9999999630
[76,] 2.302029e-08 4.604059e-08 0.9999999770
[77,] 1.394411e-08 2.788821e-08 0.9999999861
[78,] 9.229764e-09 1.845953e-08 0.9999999908
[79,] 5.799380e-09 1.159876e-08 0.9999999942
[80,] 3.731273e-09 7.462546e-09 0.9999999963
[81,] 2.421465e-09 4.842930e-09 0.9999999976
[82,] 1.582187e-09 3.164374e-09 0.9999999984
[83,] 9.878671e-10 1.975734e-09 0.9999999990
[84,] 6.119279e-10 1.223856e-09 0.9999999994
[85,] 3.819087e-10 7.638174e-10 0.9999999996
[86,] 2.486529e-10 4.973058e-10 0.9999999998
[87,] 1.647121e-10 3.294241e-10 0.9999999998
[88,] 1.027576e-10 2.055153e-10 0.9999999999
[89,] 6.088007e-11 1.217601e-10 0.9999999999
[90,] 3.993615e-11 7.987231e-11 1.0000000000
[91,] 2.541077e-11 5.082154e-11 1.0000000000
[92,] 1.617978e-11 3.235957e-11 1.0000000000
[93,] 9.958791e-12 1.991758e-11 1.0000000000
[94,] 6.129076e-12 1.225815e-11 1.0000000000
[95,] 4.384036e-12 8.768073e-12 1.0000000000
[96,] 3.451319e-12 6.902638e-12 1.0000000000
[97,] 4.397067e-12 8.794134e-12 1.0000000000
[98,] 1.323546e-11 2.647092e-11 1.0000000000
[99,] 5.524579e-11 1.104916e-10 0.9999999999
[100,] 2.753329e-10 5.506658e-10 0.9999999997
[101,] 9.934722e-10 1.986944e-09 0.9999999990
[102,] 3.599287e-09 7.198574e-09 0.9999999964
[103,] 1.066752e-08 2.133503e-08 0.9999999893
[104,] 2.332749e-08 4.665498e-08 0.9999999767
[105,] 3.025399e-08 6.050799e-08 0.9999999697
[106,] 3.435585e-08 6.871169e-08 0.9999999656
[107,] 3.390099e-08 6.780199e-08 0.9999999661
[108,] 3.887779e-08 7.775559e-08 0.9999999611
[109,] 4.117797e-08 8.235593e-08 0.9999999588
[110,] 4.012313e-08 8.024627e-08 0.9999999599
[111,] 3.396423e-08 6.792847e-08 0.9999999660
[112,] 2.349787e-08 4.699574e-08 0.9999999765
[113,] 1.580152e-08 3.160304e-08 0.9999999842
[114,] 1.179600e-08 2.359201e-08 0.9999999882
[115,] 8.324390e-09 1.664878e-08 0.9999999917
[116,] 5.982363e-09 1.196473e-08 0.9999999940
[117,] 4.262674e-09 8.525348e-09 0.9999999957
[118,] 3.234138e-09 6.468275e-09 0.9999999968
[119,] 2.684448e-09 5.368896e-09 0.9999999973
[120,] 2.021421e-09 4.042842e-09 0.9999999980
[121,] 1.471611e-09 2.943222e-09 0.9999999985
[122,] 9.972036e-10 1.994407e-09 0.9999999990
[123,] 7.448322e-10 1.489664e-09 0.9999999993
[124,] 5.007470e-10 1.001494e-09 0.9999999995
[125,] 3.275426e-10 6.550851e-10 0.9999999997
[126,] 2.682007e-10 5.364014e-10 0.9999999997
[127,] 1.961435e-10 3.922869e-10 0.9999999998
[128,] 1.527735e-10 3.055470e-10 0.9999999998
[129,] 1.084707e-10 2.169414e-10 0.9999999999
[130,] 8.960087e-11 1.792017e-10 0.9999999999
[131,] 8.504106e-11 1.700821e-10 0.9999999999
[132,] 1.163954e-10 2.327908e-10 0.9999999999
[133,] 1.887585e-10 3.775170e-10 0.9999999998
[134,] 3.874655e-10 7.749310e-10 0.9999999996
[135,] 7.026995e-10 1.405399e-09 0.9999999993
[136,] 9.822485e-10 1.964497e-09 0.9999999990
[137,] 1.282727e-09 2.565453e-09 0.9999999987
[138,] 2.097473e-09 4.194946e-09 0.9999999979
[139,] 2.668368e-09 5.336736e-09 0.9999999973
[140,] 2.878960e-09 5.757920e-09 0.9999999971
[141,] 2.655886e-09 5.311771e-09 0.9999999973
[142,] 2.383029e-09 4.766058e-09 0.9999999976
[143,] 1.991819e-09 3.983638e-09 0.9999999980
[144,] 1.647414e-09 3.294828e-09 0.9999999984
[145,] 1.288996e-09 2.577992e-09 0.9999999987
[146,] 9.240791e-10 1.848158e-09 0.9999999991
[147,] 6.542521e-10 1.308504e-09 0.9999999993
[148,] 4.421874e-10 8.843748e-10 0.9999999996
[149,] 3.199200e-10 6.398399e-10 0.9999999997
[150,] 2.359505e-10 4.719011e-10 0.9999999998
[151,] 1.615765e-10 3.231531e-10 0.9999999998
[152,] 1.182681e-10 2.365362e-10 0.9999999999
[153,] 8.278802e-11 1.655760e-10 0.9999999999
[154,] 5.685348e-11 1.137070e-10 0.9999999999
[155,] 4.129115e-11 8.258231e-11 1.0000000000
[156,] 2.889106e-11 5.778212e-11 1.0000000000
[157,] 2.141297e-11 4.282594e-11 1.0000000000
[158,] 1.694241e-11 3.388481e-11 1.0000000000
[159,] 1.185874e-11 2.371748e-11 1.0000000000
[160,] 7.917842e-12 1.583568e-11 1.0000000000
[161,] 5.413808e-12 1.082762e-11 1.0000000000
[162,] 4.256490e-12 8.512980e-12 1.0000000000
[163,] 2.976525e-12 5.953051e-12 1.0000000000
[164,] 2.039843e-12 4.079686e-12 1.0000000000
[165,] 1.386058e-12 2.772117e-12 1.0000000000
[166,] 9.455402e-13 1.891080e-12 1.0000000000
[167,] 6.846612e-13 1.369322e-12 1.0000000000
[168,] 4.612883e-13 9.225766e-13 1.0000000000
[169,] 3.119097e-13 6.238194e-13 1.0000000000
[170,] 2.016462e-13 4.032924e-13 1.0000000000
[171,] 1.269285e-13 2.538570e-13 1.0000000000
[172,] 7.791365e-14 1.558273e-13 1.0000000000
[173,] 4.609423e-14 9.218847e-14 1.0000000000
[174,] 3.315229e-14 6.630458e-14 1.0000000000
[175,] 2.165165e-14 4.330330e-14 1.0000000000
[176,] 1.398741e-14 2.797481e-14 1.0000000000
[177,] 9.172107e-15 1.834421e-14 1.0000000000
[178,] 5.946819e-15 1.189364e-14 1.0000000000
[179,] 3.782297e-15 7.564594e-15 1.0000000000
[180,] 2.328013e-15 4.656027e-15 1.0000000000
[181,] 1.449555e-15 2.899109e-15 1.0000000000
[182,] 8.843405e-16 1.768681e-15 1.0000000000
[183,] 5.507453e-16 1.101491e-15 1.0000000000
[184,] 3.239665e-16 6.479330e-16 1.0000000000
[185,] 1.895653e-16 3.791306e-16 1.0000000000
[186,] 1.247259e-16 2.494519e-16 1.0000000000
[187,] 8.692057e-17 1.738411e-16 1.0000000000
[188,] 5.918201e-17 1.183640e-16 1.0000000000
[189,] 4.355147e-17 8.710293e-17 1.0000000000
[190,] 3.160005e-17 6.320011e-17 1.0000000000
[191,] 2.271128e-17 4.542256e-17 1.0000000000
[192,] 1.708236e-17 3.416471e-17 1.0000000000
[193,] 1.543374e-17 3.086748e-17 1.0000000000
[194,] 1.716669e-17 3.433337e-17 1.0000000000
[195,] 1.720329e-17 3.440658e-17 1.0000000000
[196,] 1.514197e-17 3.028394e-17 1.0000000000
[197,] 1.086620e-17 2.173240e-17 1.0000000000
[198,] 8.542977e-18 1.708595e-17 1.0000000000
[199,] 8.177446e-18 1.635489e-17 1.0000000000
[200,] 7.320571e-18 1.464114e-17 1.0000000000
[201,] 7.603005e-18 1.520601e-17 1.0000000000
[202,] 7.194848e-18 1.438970e-17 1.0000000000
[203,] 7.148584e-18 1.429717e-17 1.0000000000
[204,] 6.603510e-18 1.320702e-17 1.0000000000
[205,] 7.600495e-18 1.520099e-17 1.0000000000
[206,] 9.436374e-18 1.887275e-17 1.0000000000
[207,] 1.168502e-17 2.337004e-17 1.0000000000
[208,] 1.263958e-17 2.527916e-17 1.0000000000
[209,] 1.348349e-17 2.696697e-17 1.0000000000
[210,] 1.219077e-17 2.438155e-17 1.0000000000
[211,] 1.224742e-17 2.449484e-17 1.0000000000
[212,] 1.213434e-17 2.426867e-17 1.0000000000
[213,] 1.165620e-17 2.331240e-17 1.0000000000
[214,] 9.825455e-18 1.965091e-17 1.0000000000
[215,] 9.289707e-18 1.857941e-17 1.0000000000
[216,] 9.936505e-18 1.987301e-17 1.0000000000
[217,] 1.658451e-17 3.316901e-17 1.0000000000
[218,] 2.431951e-17 4.863903e-17 1.0000000000
[219,] 4.122318e-17 8.244635e-17 1.0000000000
[220,] 7.031771e-17 1.406354e-16 1.0000000000
[221,] 1.136933e-16 2.273865e-16 1.0000000000
[222,] 1.327287e-16 2.654573e-16 1.0000000000
[223,] 1.831086e-16 3.662172e-16 1.0000000000
[224,] 2.865029e-16 5.730058e-16 1.0000000000
[225,] 4.822359e-16 9.644719e-16 1.0000000000
[226,] 7.452042e-16 1.490408e-15 1.0000000000
[227,] 1.320598e-15 2.641196e-15 1.0000000000
[228,] 2.844234e-15 5.688467e-15 1.0000000000
[229,] 1.059360e-14 2.118720e-14 1.0000000000
[230,] 4.333434e-14 8.666868e-14 1.0000000000
[231,] 1.614090e-13 3.228180e-13 1.0000000000
[232,] 4.114495e-13 8.228990e-13 1.0000000000
[233,] 1.041464e-12 2.082928e-12 1.0000000000
[234,] 2.442515e-12 4.885030e-12 1.0000000000
[235,] 5.890091e-12 1.178018e-11 1.0000000000
[236,] 1.421753e-11 2.843506e-11 1.0000000000
[237,] 2.863596e-11 5.727191e-11 1.0000000000
[238,] 5.299642e-11 1.059928e-10 0.9999999999
[239,] 1.424915e-10 2.849830e-10 0.9999999999
[240,] 4.242283e-10 8.484566e-10 0.9999999996
[241,] 1.541669e-09 3.083338e-09 0.9999999985
[242,] 3.906461e-09 7.812923e-09 0.9999999961
[243,] 7.961120e-09 1.592224e-08 0.9999999920
[244,] 1.162089e-08 2.324177e-08 0.9999999884
[245,] 1.511074e-08 3.022148e-08 0.9999999849
[246,] 2.115751e-08 4.231501e-08 0.9999999788
[247,] 2.978320e-08 5.956639e-08 0.9999999702
[248,] 4.072214e-08 8.144428e-08 0.9999999593
[249,] 5.557812e-08 1.111562e-07 0.9999999444
[250,] 6.998875e-08 1.399775e-07 0.9999999300
[251,] 8.948550e-08 1.789710e-07 0.9999999105
[252,] 1.089421e-07 2.178842e-07 0.9999998911
[253,] 1.547411e-07 3.094823e-07 0.9999998453
[254,] 2.105403e-07 4.210806e-07 0.9999997895
[255,] 2.673708e-07 5.347415e-07 0.9999997326
[256,] 2.956473e-07 5.912946e-07 0.9999997044
[257,] 3.019408e-07 6.038817e-07 0.9999996981
[258,] 3.905661e-07 7.811322e-07 0.9999996094
[259,] 5.111252e-07 1.022250e-06 0.9999994889
[260,] 6.519754e-07 1.303951e-06 0.9999993480
[261,] 8.338271e-07 1.667654e-06 0.9999991662
[262,] 9.815611e-07 1.963122e-06 0.9999990184
[263,] 1.151549e-06 2.303098e-06 0.9999988485
[264,] 1.287071e-06 2.574141e-06 0.9999987129
[265,] 1.701071e-06 3.402141e-06 0.9999982989
[266,] 2.226194e-06 4.452389e-06 0.9999977738
[267,] 2.706142e-06 5.412284e-06 0.9999972939
[268,] 2.916858e-06 5.833715e-06 0.9999970831
[269,] 2.992503e-06 5.985007e-06 0.9999970075
[270,] 3.630606e-06 7.261212e-06 0.9999963694
[271,] 4.450667e-06 8.901335e-06 0.9999955493
[272,] 5.279491e-06 1.055898e-05 0.9999947205
[273,] 6.478721e-06 1.295744e-05 0.9999935213
[274,] 7.444139e-06 1.488828e-05 0.9999925559
[275,] 9.861928e-06 1.972386e-05 0.9999901381
[276,] 1.381593e-05 2.763186e-05 0.9999861841
[277,] 3.187313e-05 6.374627e-05 0.9999681269
[278,] 6.682525e-05 1.336505e-04 0.9999331747
[279,] 1.377868e-04 2.755735e-04 0.9998622132
[280,] 2.166638e-04 4.333276e-04 0.9997833362
[281,] 3.490995e-04 6.981991e-04 0.9996509005
[282,] 6.369367e-04 1.273873e-03 0.9993630633
[283,] 1.251205e-03 2.502409e-03 0.9987487953
[284,] 2.387304e-03 4.774608e-03 0.9976126962
[285,] 4.337108e-03 8.674216e-03 0.9956628922
[286,] 8.599560e-03 1.719912e-02 0.9914004405
[287,] 1.628883e-02 3.257765e-02 0.9837111727
[288,] 2.992753e-02 5.985506e-02 0.9700724687
[289,] 7.164045e-02 1.432809e-01 0.9283595495
[290,] 1.470807e-01 2.941614e-01 0.8529192766
[291,] 2.831506e-01 5.663013e-01 0.7168493726
[292,] 4.299567e-01 8.599134e-01 0.5700432887
[293,] 5.689255e-01 8.621489e-01 0.4310744541
[294,] 7.007198e-01 5.985605e-01 0.2992802421
[295,] 8.092367e-01 3.815266e-01 0.1907633237
[296,] 8.953673e-01 2.092655e-01 0.1046327275
[297,] 9.270812e-01 1.458375e-01 0.0729187510
[298,] 9.477388e-01 1.045225e-01 0.0522612343
[299,] 9.527856e-01 9.442882e-02 0.0472144108
[300,] 9.510985e-01 9.780300e-02 0.0489015016
[301,] 9.610414e-01 7.791727e-02 0.0389586375
[302,] 9.695653e-01 6.086947e-02 0.0304347350
[303,] 9.819879e-01 3.602427e-02 0.0180121342
[304,] 9.911289e-01 1.774212e-02 0.0088710599
[305,] 9.967608e-01 6.478392e-03 0.0032391959
[306,] 9.986420e-01 2.716062e-03 0.0013580312
[307,] 9.992782e-01 1.443513e-03 0.0007217565
[308,] 9.994991e-01 1.001763e-03 0.0005008815
[309,] 9.996757e-01 6.486652e-04 0.0003243326
[310,] 9.997754e-01 4.492229e-04 0.0002246114
[311,] 9.997953e-01 4.094345e-04 0.0002047172
[312,] 9.998310e-01 3.380775e-04 0.0001690388
[313,] 9.998221e-01 3.557511e-04 0.0001778755
[314,] 9.997684e-01 4.632233e-04 0.0002316116
[315,] 9.996610e-01 6.780586e-04 0.0003390293
[316,] 9.995668e-01 8.663464e-04 0.0004331732
[317,] 9.993073e-01 1.385450e-03 0.0006927248
[318,] 9.991101e-01 1.779701e-03 0.0008898504
[319,] 9.989678e-01 2.064333e-03 0.0010321666
[320,] 9.988940e-01 2.211901e-03 0.0011059506
[321,] 9.986947e-01 2.610555e-03 0.0013052776
[322,] 9.985700e-01 2.859987e-03 0.0014299934
[323,] 9.986545e-01 2.691031e-03 0.0013455154
[324,] 9.989711e-01 2.057730e-03 0.0010288651
[325,] 9.986104e-01 2.779279e-03 0.0013896395
[326,] 9.989998e-01 2.000308e-03 0.0010001541
[327,] 9.988909e-01 2.218198e-03 0.0011090988
[328,] 9.983166e-01 3.366717e-03 0.0016833583
[329,] 9.966716e-01 6.656879e-03 0.0033284394
[330,] 9.969315e-01 6.137087e-03 0.0030685437
[331,] 9.920010e-01 1.599797e-02 0.0079989861
[332,] 9.867870e-01 2.642604e-02 0.0132130207
[333,] 9.692333e-01 6.153340e-02 0.0307667024
> postscript(file="/var/wessaorg/rcomp/tmp/1a3q61355670569.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/293wr1355670569.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3w4gn1355670569.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/49atp1355670569.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/59w9d1355670569.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 = 362
Frequency = 1
1 2 3 4 5 6
-166.2290323 -151.4967742 -140.1266667 -100.9333333 -87.5600000 -58.7366667
7 8 9 10 11 12
-14.9233333 -43.7600000 21.9800000 10.3866667 -4.6266667 25.5833333
13 14 15 16 17 18
-12.5290323 -2.9967742 25.1733333 30.7666667 5.4400000 -19.9366667
19 20 21 22 23 24
-40.2233333 -85.2600000 -85.2200000 -123.9133333 -119.1266667 -147.7166667
25 26 27 28 29 30
-133.9290323 -131.0967742 -174.7266667 -194.5333333 -193.5600000 -192.6366667
31 32 33 34 35 36
-189.5233333 -227.1600000 -209.6200000 -204.6133333 -179.5266667 -177.8166667
37 38 39 40 41 42
-170.5290323 -192.3967742 -213.8266667 -214.3333333 -225.6600000 -202.8366667
43 44 45 46 47 48
-188.3233333 -237.1600000 -208.3200000 -193.4133333 -195.3266667 -205.2166667
49 50 51 52 53 54
-210.1290323 -217.4967742 -226.4266667 -251.9333333 -243.0600000 -210.0366667
55 56 57 58 59 60
-212.9233333 -267.1600000 -245.8200000 -234.0133333 -206.2266667 -196.0166667
61 62 63 64 65 66
-167.8290323 -135.5967742 -83.5266667 -50.0333333 -22.1600000 -1.8366667
67 68 69 70 71 72
-0.7233333 -72.2600000 -48.9200000 -38.2133333 -24.8266667 -60.3166667
73 74 75 76 77 78
-58.0290323 -71.0967742 -72.7266667 -91.4333333 -96.1600000 -70.2366667
79 80 81 82 83 84
-97.5233333 -151.0600000 -150.6200000 -131.6133333 -134.3266667 -124.8166667
85 86 87 88 89 90
-115.9290323 -111.8967742 -133.0266667 -139.1333333 -116.3600000 -115.4366667
91 92 93 94 95 96
-86.6233333 -122.4600000 -118.4200000 -138.5133333 -140.8266667 -144.1166667
97 98 99 100 101 102
-109.6290323 -105.9967742 -119.0266667 -139.8333333 -143.6600000 -123.7366667
103 104 105 106 107 108
-103.0233333 -127.2600000 -132.5200000 -132.6133333 -117.8266667 -106.7166667
109 110 111 112 113 114
-56.8290323 -38.7967742 6.7733333 63.2666667 89.6400000 119.9633333
115 116 117 118 119 120
116.6766667 81.9400000 92.9800000 75.4866667 37.6733333 21.7833333
121 122 123 124 125 126
8.9709677 34.8032258 28.1733333 21.4666667 3.9400000 -30.6366667
127 128 129 130 131 132
-33.8233333 -62.3600000 -56.3200000 -50.5133333 -48.6266667 -30.1166667
133 134 135 136 137 138
-5.9290323 -19.8967742 -27.7266667 -59.7333333 -9.4600000 -25.7366667
139 140 141 142 143 144
-28.5233333 -23.1600000 -28.4200000 -14.1133333 -36.6266667 0.4833333
145 146 147 148 149 150
27.1709677 75.0032258 93.8733333 117.0666667 116.4400000 102.2633333
151 152 153 154 155 156
100.5766667 90.9400000 79.2800000 58.7866667 35.2733333 33.0833333
157 158 159 160 161 162
24.5709677 32.1032258 22.4733333 -0.2333333 6.4400000 -0.1366667
163 164 165 166 167 168
28.6766667 -18.4600000 -33.9200000 -1.0133333 -22.6266667 -29.8166667
169 170 171 172 173 174
3.0709677 4.0032258 23.0733333 38.6666667 18.3400000 12.8633333
175 176 177 178 179 180
28.3766667 15.0400000 -2.8200000 -9.7133333 -21.1266667 -13.8166667
181 182 183 184 185 186
16.2709677 6.8032258 12.1733333 -2.2333333 -3.3600000 -3.3366667
187 188 189 190 191 192
-13.7233333 4.9400000 -49.3200000 -30.1133333 -41.9266667 -33.4166667
193 194 195 196 197 198
-37.7290323 -31.0967742 -45.5266667 -31.1333333 -55.9600000 -37.2366667
199 200 201 202 203 204
-45.1233333 -34.6600000 -73.9200000 -68.7133333 -83.9266667 -82.3166667
205 206 207 208 209 210
-80.7290323 -93.1967742 -115.2266667 -137.4333333 -126.8600000 -113.4366667
211 212 213 214 215 216
-87.2233333 -81.1600000 -111.8200000 -103.1133333 -117.8266667 -106.7166667
217 218 219 220 221 222
-111.6290323 -105.4967742 -123.7266667 -129.9333333 -130.4600000 -120.0366667
223 224 225 226 227 228
-120.7233333 -77.5600000 -91.9200000 -91.0133333 -78.6266667 -58.0166667
229 230 231 232 233 234
-79.2290323 -99.9967742 -132.2266667 -119.6333333 -132.9600000 -137.3366667
235 236 237 238 239 240
-136.1233333 -78.8600000 -95.1200000 -108.0133333 -107.4266667 -102.2166667
241 242 243 244 245 246
-111.9290323 -130.1967742 -152.1266667 -156.0333333 -151.1600000 -132.2366667
247 248 249 250 251 252
-136.5233333 -101.3600000 -98.6200000 -98.2133333 -72.3266667 -69.2166667
253 254 255 256 257 258
-98.5290323 -109.2967742 -99.0266667 -68.9333333 -52.5600000 -31.2366667
259 260 261 262 263 264
-28.1233333 26.5400000 34.1800000 36.7866667 61.0733333 72.6833333
265 266 267 268 269 270
91.1709677 91.6032258 101.7733333 95.8666667 91.6400000 82.9633333
271 272 273 274 275 276
72.8766667 108.6400000 116.1800000 120.8866667 115.8733333 103.7833333
277 278 279 280 281 282
111.9709677 97.5032258 105.0733333 92.8666667 95.6400000 83.2633333
283 284 285 286 287 288
67.8766667 102.2400000 100.4800000 100.4866667 97.6733333 93.7833333
289 290 291 292 293 294
57.0709677 39.6032258 27.8733333 36.1666667 25.3400000 30.9633333
295 296 297 298 299 300
13.3766667 44.3400000 38.1800000 35.5866667 48.3733333 23.0833333
301 302 303 304 305 306
36.0709677 33.8032258 61.1733333 65.6666667 49.6400000 43.6633333
307 308 309 310 311 312
47.8766667 97.6400000 109.1800000 103.2866667 152.0733333 151.1833333
313 314 315 316 317 318
198.9709677 238.6032258 378.3733333 382.5666667 410.0400000 395.5633333
319 320 321 322 323 324
395.7766667 416.5400000 404.0800000 384.3866667 384.0733333 371.1833333
325 326 327 328 329 330
353.5709677 347.5032258 377.7733333 354.9666667 326.6400000 302.5633333
331 332 333 334 335 336
263.8766667 325.1400000 340.8800000 346.9866667 334.4733333 330.0833333
337 338 339 340 341 342
339.9709677 330.2032258 345.1733333 362.5666667 329.7400000 270.3633333
343 344 345 346 347 348
248.5766667 304.9400000 277.2800000 290.4866667 275.5733333 268.8833333
349 350 351 352 353 354
265.0709677 216.0032258 250.0733333 225.5666667 222.0400000 182.3633333
355 356 357 358 359 360
179.1766667 192.2400000 226.9800000 207.8866667 211.5733333 192.7833333
361 362
193.3709677 200.5032258
> postscript(file="/var/wessaorg/rcomp/tmp/60icw1355670569.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 = 362
Frequency = 1
lag(myerror, k = 1) myerror
0 -166.2290323 NA
1 -151.4967742 -166.2290323
2 -140.1266667 -151.4967742
3 -100.9333333 -140.1266667
4 -87.5600000 -100.9333333
5 -58.7366667 -87.5600000
6 -14.9233333 -58.7366667
7 -43.7600000 -14.9233333
8 21.9800000 -43.7600000
9 10.3866667 21.9800000
10 -4.6266667 10.3866667
11 25.5833333 -4.6266667
12 -12.5290323 25.5833333
13 -2.9967742 -12.5290323
14 25.1733333 -2.9967742
15 30.7666667 25.1733333
16 5.4400000 30.7666667
17 -19.9366667 5.4400000
18 -40.2233333 -19.9366667
19 -85.2600000 -40.2233333
20 -85.2200000 -85.2600000
21 -123.9133333 -85.2200000
22 -119.1266667 -123.9133333
23 -147.7166667 -119.1266667
24 -133.9290323 -147.7166667
25 -131.0967742 -133.9290323
26 -174.7266667 -131.0967742
27 -194.5333333 -174.7266667
28 -193.5600000 -194.5333333
29 -192.6366667 -193.5600000
30 -189.5233333 -192.6366667
31 -227.1600000 -189.5233333
32 -209.6200000 -227.1600000
33 -204.6133333 -209.6200000
34 -179.5266667 -204.6133333
35 -177.8166667 -179.5266667
36 -170.5290323 -177.8166667
37 -192.3967742 -170.5290323
38 -213.8266667 -192.3967742
39 -214.3333333 -213.8266667
40 -225.6600000 -214.3333333
41 -202.8366667 -225.6600000
42 -188.3233333 -202.8366667
43 -237.1600000 -188.3233333
44 -208.3200000 -237.1600000
45 -193.4133333 -208.3200000
46 -195.3266667 -193.4133333
47 -205.2166667 -195.3266667
48 -210.1290323 -205.2166667
49 -217.4967742 -210.1290323
50 -226.4266667 -217.4967742
51 -251.9333333 -226.4266667
52 -243.0600000 -251.9333333
53 -210.0366667 -243.0600000
54 -212.9233333 -210.0366667
55 -267.1600000 -212.9233333
56 -245.8200000 -267.1600000
57 -234.0133333 -245.8200000
58 -206.2266667 -234.0133333
59 -196.0166667 -206.2266667
60 -167.8290323 -196.0166667
61 -135.5967742 -167.8290323
62 -83.5266667 -135.5967742
63 -50.0333333 -83.5266667
64 -22.1600000 -50.0333333
65 -1.8366667 -22.1600000
66 -0.7233333 -1.8366667
67 -72.2600000 -0.7233333
68 -48.9200000 -72.2600000
69 -38.2133333 -48.9200000
70 -24.8266667 -38.2133333
71 -60.3166667 -24.8266667
72 -58.0290323 -60.3166667
73 -71.0967742 -58.0290323
74 -72.7266667 -71.0967742
75 -91.4333333 -72.7266667
76 -96.1600000 -91.4333333
77 -70.2366667 -96.1600000
78 -97.5233333 -70.2366667
79 -151.0600000 -97.5233333
80 -150.6200000 -151.0600000
81 -131.6133333 -150.6200000
82 -134.3266667 -131.6133333
83 -124.8166667 -134.3266667
84 -115.9290323 -124.8166667
85 -111.8967742 -115.9290323
86 -133.0266667 -111.8967742
87 -139.1333333 -133.0266667
88 -116.3600000 -139.1333333
89 -115.4366667 -116.3600000
90 -86.6233333 -115.4366667
91 -122.4600000 -86.6233333
92 -118.4200000 -122.4600000
93 -138.5133333 -118.4200000
94 -140.8266667 -138.5133333
95 -144.1166667 -140.8266667
96 -109.6290323 -144.1166667
97 -105.9967742 -109.6290323
98 -119.0266667 -105.9967742
99 -139.8333333 -119.0266667
100 -143.6600000 -139.8333333
101 -123.7366667 -143.6600000
102 -103.0233333 -123.7366667
103 -127.2600000 -103.0233333
104 -132.5200000 -127.2600000
105 -132.6133333 -132.5200000
106 -117.8266667 -132.6133333
107 -106.7166667 -117.8266667
108 -56.8290323 -106.7166667
109 -38.7967742 -56.8290323
110 6.7733333 -38.7967742
111 63.2666667 6.7733333
112 89.6400000 63.2666667
113 119.9633333 89.6400000
114 116.6766667 119.9633333
115 81.9400000 116.6766667
116 92.9800000 81.9400000
117 75.4866667 92.9800000
118 37.6733333 75.4866667
119 21.7833333 37.6733333
120 8.9709677 21.7833333
121 34.8032258 8.9709677
122 28.1733333 34.8032258
123 21.4666667 28.1733333
124 3.9400000 21.4666667
125 -30.6366667 3.9400000
126 -33.8233333 -30.6366667
127 -62.3600000 -33.8233333
128 -56.3200000 -62.3600000
129 -50.5133333 -56.3200000
130 -48.6266667 -50.5133333
131 -30.1166667 -48.6266667
132 -5.9290323 -30.1166667
133 -19.8967742 -5.9290323
134 -27.7266667 -19.8967742
135 -59.7333333 -27.7266667
136 -9.4600000 -59.7333333
137 -25.7366667 -9.4600000
138 -28.5233333 -25.7366667
139 -23.1600000 -28.5233333
140 -28.4200000 -23.1600000
141 -14.1133333 -28.4200000
142 -36.6266667 -14.1133333
143 0.4833333 -36.6266667
144 27.1709677 0.4833333
145 75.0032258 27.1709677
146 93.8733333 75.0032258
147 117.0666667 93.8733333
148 116.4400000 117.0666667
149 102.2633333 116.4400000
150 100.5766667 102.2633333
151 90.9400000 100.5766667
152 79.2800000 90.9400000
153 58.7866667 79.2800000
154 35.2733333 58.7866667
155 33.0833333 35.2733333
156 24.5709677 33.0833333
157 32.1032258 24.5709677
158 22.4733333 32.1032258
159 -0.2333333 22.4733333
160 6.4400000 -0.2333333
161 -0.1366667 6.4400000
162 28.6766667 -0.1366667
163 -18.4600000 28.6766667
164 -33.9200000 -18.4600000
165 -1.0133333 -33.9200000
166 -22.6266667 -1.0133333
167 -29.8166667 -22.6266667
168 3.0709677 -29.8166667
169 4.0032258 3.0709677
170 23.0733333 4.0032258
171 38.6666667 23.0733333
172 18.3400000 38.6666667
173 12.8633333 18.3400000
174 28.3766667 12.8633333
175 15.0400000 28.3766667
176 -2.8200000 15.0400000
177 -9.7133333 -2.8200000
178 -21.1266667 -9.7133333
179 -13.8166667 -21.1266667
180 16.2709677 -13.8166667
181 6.8032258 16.2709677
182 12.1733333 6.8032258
183 -2.2333333 12.1733333
184 -3.3600000 -2.2333333
185 -3.3366667 -3.3600000
186 -13.7233333 -3.3366667
187 4.9400000 -13.7233333
188 -49.3200000 4.9400000
189 -30.1133333 -49.3200000
190 -41.9266667 -30.1133333
191 -33.4166667 -41.9266667
192 -37.7290323 -33.4166667
193 -31.0967742 -37.7290323
194 -45.5266667 -31.0967742
195 -31.1333333 -45.5266667
196 -55.9600000 -31.1333333
197 -37.2366667 -55.9600000
198 -45.1233333 -37.2366667
199 -34.6600000 -45.1233333
200 -73.9200000 -34.6600000
201 -68.7133333 -73.9200000
202 -83.9266667 -68.7133333
203 -82.3166667 -83.9266667
204 -80.7290323 -82.3166667
205 -93.1967742 -80.7290323
206 -115.2266667 -93.1967742
207 -137.4333333 -115.2266667
208 -126.8600000 -137.4333333
209 -113.4366667 -126.8600000
210 -87.2233333 -113.4366667
211 -81.1600000 -87.2233333
212 -111.8200000 -81.1600000
213 -103.1133333 -111.8200000
214 -117.8266667 -103.1133333
215 -106.7166667 -117.8266667
216 -111.6290323 -106.7166667
217 -105.4967742 -111.6290323
218 -123.7266667 -105.4967742
219 -129.9333333 -123.7266667
220 -130.4600000 -129.9333333
221 -120.0366667 -130.4600000
222 -120.7233333 -120.0366667
223 -77.5600000 -120.7233333
224 -91.9200000 -77.5600000
225 -91.0133333 -91.9200000
226 -78.6266667 -91.0133333
227 -58.0166667 -78.6266667
228 -79.2290323 -58.0166667
229 -99.9967742 -79.2290323
230 -132.2266667 -99.9967742
231 -119.6333333 -132.2266667
232 -132.9600000 -119.6333333
233 -137.3366667 -132.9600000
234 -136.1233333 -137.3366667
235 -78.8600000 -136.1233333
236 -95.1200000 -78.8600000
237 -108.0133333 -95.1200000
238 -107.4266667 -108.0133333
239 -102.2166667 -107.4266667
240 -111.9290323 -102.2166667
241 -130.1967742 -111.9290323
242 -152.1266667 -130.1967742
243 -156.0333333 -152.1266667
244 -151.1600000 -156.0333333
245 -132.2366667 -151.1600000
246 -136.5233333 -132.2366667
247 -101.3600000 -136.5233333
248 -98.6200000 -101.3600000
249 -98.2133333 -98.6200000
250 -72.3266667 -98.2133333
251 -69.2166667 -72.3266667
252 -98.5290323 -69.2166667
253 -109.2967742 -98.5290323
254 -99.0266667 -109.2967742
255 -68.9333333 -99.0266667
256 -52.5600000 -68.9333333
257 -31.2366667 -52.5600000
258 -28.1233333 -31.2366667
259 26.5400000 -28.1233333
260 34.1800000 26.5400000
261 36.7866667 34.1800000
262 61.0733333 36.7866667
263 72.6833333 61.0733333
264 91.1709677 72.6833333
265 91.6032258 91.1709677
266 101.7733333 91.6032258
267 95.8666667 101.7733333
268 91.6400000 95.8666667
269 82.9633333 91.6400000
270 72.8766667 82.9633333
271 108.6400000 72.8766667
272 116.1800000 108.6400000
273 120.8866667 116.1800000
274 115.8733333 120.8866667
275 103.7833333 115.8733333
276 111.9709677 103.7833333
277 97.5032258 111.9709677
278 105.0733333 97.5032258
279 92.8666667 105.0733333
280 95.6400000 92.8666667
281 83.2633333 95.6400000
282 67.8766667 83.2633333
283 102.2400000 67.8766667
284 100.4800000 102.2400000
285 100.4866667 100.4800000
286 97.6733333 100.4866667
287 93.7833333 97.6733333
288 57.0709677 93.7833333
289 39.6032258 57.0709677
290 27.8733333 39.6032258
291 36.1666667 27.8733333
292 25.3400000 36.1666667
293 30.9633333 25.3400000
294 13.3766667 30.9633333
295 44.3400000 13.3766667
296 38.1800000 44.3400000
297 35.5866667 38.1800000
298 48.3733333 35.5866667
299 23.0833333 48.3733333
300 36.0709677 23.0833333
301 33.8032258 36.0709677
302 61.1733333 33.8032258
303 65.6666667 61.1733333
304 49.6400000 65.6666667
305 43.6633333 49.6400000
306 47.8766667 43.6633333
307 97.6400000 47.8766667
308 109.1800000 97.6400000
309 103.2866667 109.1800000
310 152.0733333 103.2866667
311 151.1833333 152.0733333
312 198.9709677 151.1833333
313 238.6032258 198.9709677
314 378.3733333 238.6032258
315 382.5666667 378.3733333
316 410.0400000 382.5666667
317 395.5633333 410.0400000
318 395.7766667 395.5633333
319 416.5400000 395.7766667
320 404.0800000 416.5400000
321 384.3866667 404.0800000
322 384.0733333 384.3866667
323 371.1833333 384.0733333
324 353.5709677 371.1833333
325 347.5032258 353.5709677
326 377.7733333 347.5032258
327 354.9666667 377.7733333
328 326.6400000 354.9666667
329 302.5633333 326.6400000
330 263.8766667 302.5633333
331 325.1400000 263.8766667
332 340.8800000 325.1400000
333 346.9866667 340.8800000
334 334.4733333 346.9866667
335 330.0833333 334.4733333
336 339.9709677 330.0833333
337 330.2032258 339.9709677
338 345.1733333 330.2032258
339 362.5666667 345.1733333
340 329.7400000 362.5666667
341 270.3633333 329.7400000
342 248.5766667 270.3633333
343 304.9400000 248.5766667
344 277.2800000 304.9400000
345 290.4866667 277.2800000
346 275.5733333 290.4866667
347 268.8833333 275.5733333
348 265.0709677 268.8833333
349 216.0032258 265.0709677
350 250.0733333 216.0032258
351 225.5666667 250.0733333
352 222.0400000 225.5666667
353 182.3633333 222.0400000
354 179.1766667 182.3633333
355 192.2400000 179.1766667
356 226.9800000 192.2400000
357 207.8866667 226.9800000
358 211.5733333 207.8866667
359 192.7833333 211.5733333
360 193.3709677 192.7833333
361 200.5032258 193.3709677
362 NA 200.5032258
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -151.4967742 -166.2290323
[2,] -140.1266667 -151.4967742
[3,] -100.9333333 -140.1266667
[4,] -87.5600000 -100.9333333
[5,] -58.7366667 -87.5600000
[6,] -14.9233333 -58.7366667
[7,] -43.7600000 -14.9233333
[8,] 21.9800000 -43.7600000
[9,] 10.3866667 21.9800000
[10,] -4.6266667 10.3866667
[11,] 25.5833333 -4.6266667
[12,] -12.5290323 25.5833333
[13,] -2.9967742 -12.5290323
[14,] 25.1733333 -2.9967742
[15,] 30.7666667 25.1733333
[16,] 5.4400000 30.7666667
[17,] -19.9366667 5.4400000
[18,] -40.2233333 -19.9366667
[19,] -85.2600000 -40.2233333
[20,] -85.2200000 -85.2600000
[21,] -123.9133333 -85.2200000
[22,] -119.1266667 -123.9133333
[23,] -147.7166667 -119.1266667
[24,] -133.9290323 -147.7166667
[25,] -131.0967742 -133.9290323
[26,] -174.7266667 -131.0967742
[27,] -194.5333333 -174.7266667
[28,] -193.5600000 -194.5333333
[29,] -192.6366667 -193.5600000
[30,] -189.5233333 -192.6366667
[31,] -227.1600000 -189.5233333
[32,] -209.6200000 -227.1600000
[33,] -204.6133333 -209.6200000
[34,] -179.5266667 -204.6133333
[35,] -177.8166667 -179.5266667
[36,] -170.5290323 -177.8166667
[37,] -192.3967742 -170.5290323
[38,] -213.8266667 -192.3967742
[39,] -214.3333333 -213.8266667
[40,] -225.6600000 -214.3333333
[41,] -202.8366667 -225.6600000
[42,] -188.3233333 -202.8366667
[43,] -237.1600000 -188.3233333
[44,] -208.3200000 -237.1600000
[45,] -193.4133333 -208.3200000
[46,] -195.3266667 -193.4133333
[47,] -205.2166667 -195.3266667
[48,] -210.1290323 -205.2166667
[49,] -217.4967742 -210.1290323
[50,] -226.4266667 -217.4967742
[51,] -251.9333333 -226.4266667
[52,] -243.0600000 -251.9333333
[53,] -210.0366667 -243.0600000
[54,] -212.9233333 -210.0366667
[55,] -267.1600000 -212.9233333
[56,] -245.8200000 -267.1600000
[57,] -234.0133333 -245.8200000
[58,] -206.2266667 -234.0133333
[59,] -196.0166667 -206.2266667
[60,] -167.8290323 -196.0166667
[61,] -135.5967742 -167.8290323
[62,] -83.5266667 -135.5967742
[63,] -50.0333333 -83.5266667
[64,] -22.1600000 -50.0333333
[65,] -1.8366667 -22.1600000
[66,] -0.7233333 -1.8366667
[67,] -72.2600000 -0.7233333
[68,] -48.9200000 -72.2600000
[69,] -38.2133333 -48.9200000
[70,] -24.8266667 -38.2133333
[71,] -60.3166667 -24.8266667
[72,] -58.0290323 -60.3166667
[73,] -71.0967742 -58.0290323
[74,] -72.7266667 -71.0967742
[75,] -91.4333333 -72.7266667
[76,] -96.1600000 -91.4333333
[77,] -70.2366667 -96.1600000
[78,] -97.5233333 -70.2366667
[79,] -151.0600000 -97.5233333
[80,] -150.6200000 -151.0600000
[81,] -131.6133333 -150.6200000
[82,] -134.3266667 -131.6133333
[83,] -124.8166667 -134.3266667
[84,] -115.9290323 -124.8166667
[85,] -111.8967742 -115.9290323
[86,] -133.0266667 -111.8967742
[87,] -139.1333333 -133.0266667
[88,] -116.3600000 -139.1333333
[89,] -115.4366667 -116.3600000
[90,] -86.6233333 -115.4366667
[91,] -122.4600000 -86.6233333
[92,] -118.4200000 -122.4600000
[93,] -138.5133333 -118.4200000
[94,] -140.8266667 -138.5133333
[95,] -144.1166667 -140.8266667
[96,] -109.6290323 -144.1166667
[97,] -105.9967742 -109.6290323
[98,] -119.0266667 -105.9967742
[99,] -139.8333333 -119.0266667
[100,] -143.6600000 -139.8333333
[101,] -123.7366667 -143.6600000
[102,] -103.0233333 -123.7366667
[103,] -127.2600000 -103.0233333
[104,] -132.5200000 -127.2600000
[105,] -132.6133333 -132.5200000
[106,] -117.8266667 -132.6133333
[107,] -106.7166667 -117.8266667
[108,] -56.8290323 -106.7166667
[109,] -38.7967742 -56.8290323
[110,] 6.7733333 -38.7967742
[111,] 63.2666667 6.7733333
[112,] 89.6400000 63.2666667
[113,] 119.9633333 89.6400000
[114,] 116.6766667 119.9633333
[115,] 81.9400000 116.6766667
[116,] 92.9800000 81.9400000
[117,] 75.4866667 92.9800000
[118,] 37.6733333 75.4866667
[119,] 21.7833333 37.6733333
[120,] 8.9709677 21.7833333
[121,] 34.8032258 8.9709677
[122,] 28.1733333 34.8032258
[123,] 21.4666667 28.1733333
[124,] 3.9400000 21.4666667
[125,] -30.6366667 3.9400000
[126,] -33.8233333 -30.6366667
[127,] -62.3600000 -33.8233333
[128,] -56.3200000 -62.3600000
[129,] -50.5133333 -56.3200000
[130,] -48.6266667 -50.5133333
[131,] -30.1166667 -48.6266667
[132,] -5.9290323 -30.1166667
[133,] -19.8967742 -5.9290323
[134,] -27.7266667 -19.8967742
[135,] -59.7333333 -27.7266667
[136,] -9.4600000 -59.7333333
[137,] -25.7366667 -9.4600000
[138,] -28.5233333 -25.7366667
[139,] -23.1600000 -28.5233333
[140,] -28.4200000 -23.1600000
[141,] -14.1133333 -28.4200000
[142,] -36.6266667 -14.1133333
[143,] 0.4833333 -36.6266667
[144,] 27.1709677 0.4833333
[145,] 75.0032258 27.1709677
[146,] 93.8733333 75.0032258
[147,] 117.0666667 93.8733333
[148,] 116.4400000 117.0666667
[149,] 102.2633333 116.4400000
[150,] 100.5766667 102.2633333
[151,] 90.9400000 100.5766667
[152,] 79.2800000 90.9400000
[153,] 58.7866667 79.2800000
[154,] 35.2733333 58.7866667
[155,] 33.0833333 35.2733333
[156,] 24.5709677 33.0833333
[157,] 32.1032258 24.5709677
[158,] 22.4733333 32.1032258
[159,] -0.2333333 22.4733333
[160,] 6.4400000 -0.2333333
[161,] -0.1366667 6.4400000
[162,] 28.6766667 -0.1366667
[163,] -18.4600000 28.6766667
[164,] -33.9200000 -18.4600000
[165,] -1.0133333 -33.9200000
[166,] -22.6266667 -1.0133333
[167,] -29.8166667 -22.6266667
[168,] 3.0709677 -29.8166667
[169,] 4.0032258 3.0709677
[170,] 23.0733333 4.0032258
[171,] 38.6666667 23.0733333
[172,] 18.3400000 38.6666667
[173,] 12.8633333 18.3400000
[174,] 28.3766667 12.8633333
[175,] 15.0400000 28.3766667
[176,] -2.8200000 15.0400000
[177,] -9.7133333 -2.8200000
[178,] -21.1266667 -9.7133333
[179,] -13.8166667 -21.1266667
[180,] 16.2709677 -13.8166667
[181,] 6.8032258 16.2709677
[182,] 12.1733333 6.8032258
[183,] -2.2333333 12.1733333
[184,] -3.3600000 -2.2333333
[185,] -3.3366667 -3.3600000
[186,] -13.7233333 -3.3366667
[187,] 4.9400000 -13.7233333
[188,] -49.3200000 4.9400000
[189,] -30.1133333 -49.3200000
[190,] -41.9266667 -30.1133333
[191,] -33.4166667 -41.9266667
[192,] -37.7290323 -33.4166667
[193,] -31.0967742 -37.7290323
[194,] -45.5266667 -31.0967742
[195,] -31.1333333 -45.5266667
[196,] -55.9600000 -31.1333333
[197,] -37.2366667 -55.9600000
[198,] -45.1233333 -37.2366667
[199,] -34.6600000 -45.1233333
[200,] -73.9200000 -34.6600000
[201,] -68.7133333 -73.9200000
[202,] -83.9266667 -68.7133333
[203,] -82.3166667 -83.9266667
[204,] -80.7290323 -82.3166667
[205,] -93.1967742 -80.7290323
[206,] -115.2266667 -93.1967742
[207,] -137.4333333 -115.2266667
[208,] -126.8600000 -137.4333333
[209,] -113.4366667 -126.8600000
[210,] -87.2233333 -113.4366667
[211,] -81.1600000 -87.2233333
[212,] -111.8200000 -81.1600000
[213,] -103.1133333 -111.8200000
[214,] -117.8266667 -103.1133333
[215,] -106.7166667 -117.8266667
[216,] -111.6290323 -106.7166667
[217,] -105.4967742 -111.6290323
[218,] -123.7266667 -105.4967742
[219,] -129.9333333 -123.7266667
[220,] -130.4600000 -129.9333333
[221,] -120.0366667 -130.4600000
[222,] -120.7233333 -120.0366667
[223,] -77.5600000 -120.7233333
[224,] -91.9200000 -77.5600000
[225,] -91.0133333 -91.9200000
[226,] -78.6266667 -91.0133333
[227,] -58.0166667 -78.6266667
[228,] -79.2290323 -58.0166667
[229,] -99.9967742 -79.2290323
[230,] -132.2266667 -99.9967742
[231,] -119.6333333 -132.2266667
[232,] -132.9600000 -119.6333333
[233,] -137.3366667 -132.9600000
[234,] -136.1233333 -137.3366667
[235,] -78.8600000 -136.1233333
[236,] -95.1200000 -78.8600000
[237,] -108.0133333 -95.1200000
[238,] -107.4266667 -108.0133333
[239,] -102.2166667 -107.4266667
[240,] -111.9290323 -102.2166667
[241,] -130.1967742 -111.9290323
[242,] -152.1266667 -130.1967742
[243,] -156.0333333 -152.1266667
[244,] -151.1600000 -156.0333333
[245,] -132.2366667 -151.1600000
[246,] -136.5233333 -132.2366667
[247,] -101.3600000 -136.5233333
[248,] -98.6200000 -101.3600000
[249,] -98.2133333 -98.6200000
[250,] -72.3266667 -98.2133333
[251,] -69.2166667 -72.3266667
[252,] -98.5290323 -69.2166667
[253,] -109.2967742 -98.5290323
[254,] -99.0266667 -109.2967742
[255,] -68.9333333 -99.0266667
[256,] -52.5600000 -68.9333333
[257,] -31.2366667 -52.5600000
[258,] -28.1233333 -31.2366667
[259,] 26.5400000 -28.1233333
[260,] 34.1800000 26.5400000
[261,] 36.7866667 34.1800000
[262,] 61.0733333 36.7866667
[263,] 72.6833333 61.0733333
[264,] 91.1709677 72.6833333
[265,] 91.6032258 91.1709677
[266,] 101.7733333 91.6032258
[267,] 95.8666667 101.7733333
[268,] 91.6400000 95.8666667
[269,] 82.9633333 91.6400000
[270,] 72.8766667 82.9633333
[271,] 108.6400000 72.8766667
[272,] 116.1800000 108.6400000
[273,] 120.8866667 116.1800000
[274,] 115.8733333 120.8866667
[275,] 103.7833333 115.8733333
[276,] 111.9709677 103.7833333
[277,] 97.5032258 111.9709677
[278,] 105.0733333 97.5032258
[279,] 92.8666667 105.0733333
[280,] 95.6400000 92.8666667
[281,] 83.2633333 95.6400000
[282,] 67.8766667 83.2633333
[283,] 102.2400000 67.8766667
[284,] 100.4800000 102.2400000
[285,] 100.4866667 100.4800000
[286,] 97.6733333 100.4866667
[287,] 93.7833333 97.6733333
[288,] 57.0709677 93.7833333
[289,] 39.6032258 57.0709677
[290,] 27.8733333 39.6032258
[291,] 36.1666667 27.8733333
[292,] 25.3400000 36.1666667
[293,] 30.9633333 25.3400000
[294,] 13.3766667 30.9633333
[295,] 44.3400000 13.3766667
[296,] 38.1800000 44.3400000
[297,] 35.5866667 38.1800000
[298,] 48.3733333 35.5866667
[299,] 23.0833333 48.3733333
[300,] 36.0709677 23.0833333
[301,] 33.8032258 36.0709677
[302,] 61.1733333 33.8032258
[303,] 65.6666667 61.1733333
[304,] 49.6400000 65.6666667
[305,] 43.6633333 49.6400000
[306,] 47.8766667 43.6633333
[307,] 97.6400000 47.8766667
[308,] 109.1800000 97.6400000
[309,] 103.2866667 109.1800000
[310,] 152.0733333 103.2866667
[311,] 151.1833333 152.0733333
[312,] 198.9709677 151.1833333
[313,] 238.6032258 198.9709677
[314,] 378.3733333 238.6032258
[315,] 382.5666667 378.3733333
[316,] 410.0400000 382.5666667
[317,] 395.5633333 410.0400000
[318,] 395.7766667 395.5633333
[319,] 416.5400000 395.7766667
[320,] 404.0800000 416.5400000
[321,] 384.3866667 404.0800000
[322,] 384.0733333 384.3866667
[323,] 371.1833333 384.0733333
[324,] 353.5709677 371.1833333
[325,] 347.5032258 353.5709677
[326,] 377.7733333 347.5032258
[327,] 354.9666667 377.7733333
[328,] 326.6400000 354.9666667
[329,] 302.5633333 326.6400000
[330,] 263.8766667 302.5633333
[331,] 325.1400000 263.8766667
[332,] 340.8800000 325.1400000
[333,] 346.9866667 340.8800000
[334,] 334.4733333 346.9866667
[335,] 330.0833333 334.4733333
[336,] 339.9709677 330.0833333
[337,] 330.2032258 339.9709677
[338,] 345.1733333 330.2032258
[339,] 362.5666667 345.1733333
[340,] 329.7400000 362.5666667
[341,] 270.3633333 329.7400000
[342,] 248.5766667 270.3633333
[343,] 304.9400000 248.5766667
[344,] 277.2800000 304.9400000
[345,] 290.4866667 277.2800000
[346,] 275.5733333 290.4866667
[347,] 268.8833333 275.5733333
[348,] 265.0709677 268.8833333
[349,] 216.0032258 265.0709677
[350,] 250.0733333 216.0032258
[351,] 225.5666667 250.0733333
[352,] 222.0400000 225.5666667
[353,] 182.3633333 222.0400000
[354,] 179.1766667 182.3633333
[355,] 192.2400000 179.1766667
[356,] 226.9800000 192.2400000
[357,] 207.8866667 226.9800000
[358,] 211.5733333 207.8866667
[359,] 192.7833333 211.5733333
[360,] 193.3709677 192.7833333
[361,] 200.5032258 193.3709677
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -151.4967742 -166.2290323
2 -140.1266667 -151.4967742
3 -100.9333333 -140.1266667
4 -87.5600000 -100.9333333
5 -58.7366667 -87.5600000
6 -14.9233333 -58.7366667
7 -43.7600000 -14.9233333
8 21.9800000 -43.7600000
9 10.3866667 21.9800000
10 -4.6266667 10.3866667
11 25.5833333 -4.6266667
12 -12.5290323 25.5833333
13 -2.9967742 -12.5290323
14 25.1733333 -2.9967742
15 30.7666667 25.1733333
16 5.4400000 30.7666667
17 -19.9366667 5.4400000
18 -40.2233333 -19.9366667
19 -85.2600000 -40.2233333
20 -85.2200000 -85.2600000
21 -123.9133333 -85.2200000
22 -119.1266667 -123.9133333
23 -147.7166667 -119.1266667
24 -133.9290323 -147.7166667
25 -131.0967742 -133.9290323
26 -174.7266667 -131.0967742
27 -194.5333333 -174.7266667
28 -193.5600000 -194.5333333
29 -192.6366667 -193.5600000
30 -189.5233333 -192.6366667
31 -227.1600000 -189.5233333
32 -209.6200000 -227.1600000
33 -204.6133333 -209.6200000
34 -179.5266667 -204.6133333
35 -177.8166667 -179.5266667
36 -170.5290323 -177.8166667
37 -192.3967742 -170.5290323
38 -213.8266667 -192.3967742
39 -214.3333333 -213.8266667
40 -225.6600000 -214.3333333
41 -202.8366667 -225.6600000
42 -188.3233333 -202.8366667
43 -237.1600000 -188.3233333
44 -208.3200000 -237.1600000
45 -193.4133333 -208.3200000
46 -195.3266667 -193.4133333
47 -205.2166667 -195.3266667
48 -210.1290323 -205.2166667
49 -217.4967742 -210.1290323
50 -226.4266667 -217.4967742
51 -251.9333333 -226.4266667
52 -243.0600000 -251.9333333
53 -210.0366667 -243.0600000
54 -212.9233333 -210.0366667
55 -267.1600000 -212.9233333
56 -245.8200000 -267.1600000
57 -234.0133333 -245.8200000
58 -206.2266667 -234.0133333
59 -196.0166667 -206.2266667
60 -167.8290323 -196.0166667
61 -135.5967742 -167.8290323
62 -83.5266667 -135.5967742
63 -50.0333333 -83.5266667
64 -22.1600000 -50.0333333
65 -1.8366667 -22.1600000
66 -0.7233333 -1.8366667
67 -72.2600000 -0.7233333
68 -48.9200000 -72.2600000
69 -38.2133333 -48.9200000
70 -24.8266667 -38.2133333
71 -60.3166667 -24.8266667
72 -58.0290323 -60.3166667
73 -71.0967742 -58.0290323
74 -72.7266667 -71.0967742
75 -91.4333333 -72.7266667
76 -96.1600000 -91.4333333
77 -70.2366667 -96.1600000
78 -97.5233333 -70.2366667
79 -151.0600000 -97.5233333
80 -150.6200000 -151.0600000
81 -131.6133333 -150.6200000
82 -134.3266667 -131.6133333
83 -124.8166667 -134.3266667
84 -115.9290323 -124.8166667
85 -111.8967742 -115.9290323
86 -133.0266667 -111.8967742
87 -139.1333333 -133.0266667
88 -116.3600000 -139.1333333
89 -115.4366667 -116.3600000
90 -86.6233333 -115.4366667
91 -122.4600000 -86.6233333
92 -118.4200000 -122.4600000
93 -138.5133333 -118.4200000
94 -140.8266667 -138.5133333
95 -144.1166667 -140.8266667
96 -109.6290323 -144.1166667
97 -105.9967742 -109.6290323
98 -119.0266667 -105.9967742
99 -139.8333333 -119.0266667
100 -143.6600000 -139.8333333
101 -123.7366667 -143.6600000
102 -103.0233333 -123.7366667
103 -127.2600000 -103.0233333
104 -132.5200000 -127.2600000
105 -132.6133333 -132.5200000
106 -117.8266667 -132.6133333
107 -106.7166667 -117.8266667
108 -56.8290323 -106.7166667
109 -38.7967742 -56.8290323
110 6.7733333 -38.7967742
111 63.2666667 6.7733333
112 89.6400000 63.2666667
113 119.9633333 89.6400000
114 116.6766667 119.9633333
115 81.9400000 116.6766667
116 92.9800000 81.9400000
117 75.4866667 92.9800000
118 37.6733333 75.4866667
119 21.7833333 37.6733333
120 8.9709677 21.7833333
121 34.8032258 8.9709677
122 28.1733333 34.8032258
123 21.4666667 28.1733333
124 3.9400000 21.4666667
125 -30.6366667 3.9400000
126 -33.8233333 -30.6366667
127 -62.3600000 -33.8233333
128 -56.3200000 -62.3600000
129 -50.5133333 -56.3200000
130 -48.6266667 -50.5133333
131 -30.1166667 -48.6266667
132 -5.9290323 -30.1166667
133 -19.8967742 -5.9290323
134 -27.7266667 -19.8967742
135 -59.7333333 -27.7266667
136 -9.4600000 -59.7333333
137 -25.7366667 -9.4600000
138 -28.5233333 -25.7366667
139 -23.1600000 -28.5233333
140 -28.4200000 -23.1600000
141 -14.1133333 -28.4200000
142 -36.6266667 -14.1133333
143 0.4833333 -36.6266667
144 27.1709677 0.4833333
145 75.0032258 27.1709677
146 93.8733333 75.0032258
147 117.0666667 93.8733333
148 116.4400000 117.0666667
149 102.2633333 116.4400000
150 100.5766667 102.2633333
151 90.9400000 100.5766667
152 79.2800000 90.9400000
153 58.7866667 79.2800000
154 35.2733333 58.7866667
155 33.0833333 35.2733333
156 24.5709677 33.0833333
157 32.1032258 24.5709677
158 22.4733333 32.1032258
159 -0.2333333 22.4733333
160 6.4400000 -0.2333333
161 -0.1366667 6.4400000
162 28.6766667 -0.1366667
163 -18.4600000 28.6766667
164 -33.9200000 -18.4600000
165 -1.0133333 -33.9200000
166 -22.6266667 -1.0133333
167 -29.8166667 -22.6266667
168 3.0709677 -29.8166667
169 4.0032258 3.0709677
170 23.0733333 4.0032258
171 38.6666667 23.0733333
172 18.3400000 38.6666667
173 12.8633333 18.3400000
174 28.3766667 12.8633333
175 15.0400000 28.3766667
176 -2.8200000 15.0400000
177 -9.7133333 -2.8200000
178 -21.1266667 -9.7133333
179 -13.8166667 -21.1266667
180 16.2709677 -13.8166667
181 6.8032258 16.2709677
182 12.1733333 6.8032258
183 -2.2333333 12.1733333
184 -3.3600000 -2.2333333
185 -3.3366667 -3.3600000
186 -13.7233333 -3.3366667
187 4.9400000 -13.7233333
188 -49.3200000 4.9400000
189 -30.1133333 -49.3200000
190 -41.9266667 -30.1133333
191 -33.4166667 -41.9266667
192 -37.7290323 -33.4166667
193 -31.0967742 -37.7290323
194 -45.5266667 -31.0967742
195 -31.1333333 -45.5266667
196 -55.9600000 -31.1333333
197 -37.2366667 -55.9600000
198 -45.1233333 -37.2366667
199 -34.6600000 -45.1233333
200 -73.9200000 -34.6600000
201 -68.7133333 -73.9200000
202 -83.9266667 -68.7133333
203 -82.3166667 -83.9266667
204 -80.7290323 -82.3166667
205 -93.1967742 -80.7290323
206 -115.2266667 -93.1967742
207 -137.4333333 -115.2266667
208 -126.8600000 -137.4333333
209 -113.4366667 -126.8600000
210 -87.2233333 -113.4366667
211 -81.1600000 -87.2233333
212 -111.8200000 -81.1600000
213 -103.1133333 -111.8200000
214 -117.8266667 -103.1133333
215 -106.7166667 -117.8266667
216 -111.6290323 -106.7166667
217 -105.4967742 -111.6290323
218 -123.7266667 -105.4967742
219 -129.9333333 -123.7266667
220 -130.4600000 -129.9333333
221 -120.0366667 -130.4600000
222 -120.7233333 -120.0366667
223 -77.5600000 -120.7233333
224 -91.9200000 -77.5600000
225 -91.0133333 -91.9200000
226 -78.6266667 -91.0133333
227 -58.0166667 -78.6266667
228 -79.2290323 -58.0166667
229 -99.9967742 -79.2290323
230 -132.2266667 -99.9967742
231 -119.6333333 -132.2266667
232 -132.9600000 -119.6333333
233 -137.3366667 -132.9600000
234 -136.1233333 -137.3366667
235 -78.8600000 -136.1233333
236 -95.1200000 -78.8600000
237 -108.0133333 -95.1200000
238 -107.4266667 -108.0133333
239 -102.2166667 -107.4266667
240 -111.9290323 -102.2166667
241 -130.1967742 -111.9290323
242 -152.1266667 -130.1967742
243 -156.0333333 -152.1266667
244 -151.1600000 -156.0333333
245 -132.2366667 -151.1600000
246 -136.5233333 -132.2366667
247 -101.3600000 -136.5233333
248 -98.6200000 -101.3600000
249 -98.2133333 -98.6200000
250 -72.3266667 -98.2133333
251 -69.2166667 -72.3266667
252 -98.5290323 -69.2166667
253 -109.2967742 -98.5290323
254 -99.0266667 -109.2967742
255 -68.9333333 -99.0266667
256 -52.5600000 -68.9333333
257 -31.2366667 -52.5600000
258 -28.1233333 -31.2366667
259 26.5400000 -28.1233333
260 34.1800000 26.5400000
261 36.7866667 34.1800000
262 61.0733333 36.7866667
263 72.6833333 61.0733333
264 91.1709677 72.6833333
265 91.6032258 91.1709677
266 101.7733333 91.6032258
267 95.8666667 101.7733333
268 91.6400000 95.8666667
269 82.9633333 91.6400000
270 72.8766667 82.9633333
271 108.6400000 72.8766667
272 116.1800000 108.6400000
273 120.8866667 116.1800000
274 115.8733333 120.8866667
275 103.7833333 115.8733333
276 111.9709677 103.7833333
277 97.5032258 111.9709677
278 105.0733333 97.5032258
279 92.8666667 105.0733333
280 95.6400000 92.8666667
281 83.2633333 95.6400000
282 67.8766667 83.2633333
283 102.2400000 67.8766667
284 100.4800000 102.2400000
285 100.4866667 100.4800000
286 97.6733333 100.4866667
287 93.7833333 97.6733333
288 57.0709677 93.7833333
289 39.6032258 57.0709677
290 27.8733333 39.6032258
291 36.1666667 27.8733333
292 25.3400000 36.1666667
293 30.9633333 25.3400000
294 13.3766667 30.9633333
295 44.3400000 13.3766667
296 38.1800000 44.3400000
297 35.5866667 38.1800000
298 48.3733333 35.5866667
299 23.0833333 48.3733333
300 36.0709677 23.0833333
301 33.8032258 36.0709677
302 61.1733333 33.8032258
303 65.6666667 61.1733333
304 49.6400000 65.6666667
305 43.6633333 49.6400000
306 47.8766667 43.6633333
307 97.6400000 47.8766667
308 109.1800000 97.6400000
309 103.2866667 109.1800000
310 152.0733333 103.2866667
311 151.1833333 152.0733333
312 198.9709677 151.1833333
313 238.6032258 198.9709677
314 378.3733333 238.6032258
315 382.5666667 378.3733333
316 410.0400000 382.5666667
317 395.5633333 410.0400000
318 395.7766667 395.5633333
319 416.5400000 395.7766667
320 404.0800000 416.5400000
321 384.3866667 404.0800000
322 384.0733333 384.3866667
323 371.1833333 384.0733333
324 353.5709677 371.1833333
325 347.5032258 353.5709677
326 377.7733333 347.5032258
327 354.9666667 377.7733333
328 326.6400000 354.9666667
329 302.5633333 326.6400000
330 263.8766667 302.5633333
331 325.1400000 263.8766667
332 340.8800000 325.1400000
333 346.9866667 340.8800000
334 334.4733333 346.9866667
335 330.0833333 334.4733333
336 339.9709677 330.0833333
337 330.2032258 339.9709677
338 345.1733333 330.2032258
339 362.5666667 345.1733333
340 329.7400000 362.5666667
341 270.3633333 329.7400000
342 248.5766667 270.3633333
343 304.9400000 248.5766667
344 277.2800000 304.9400000
345 290.4866667 277.2800000
346 275.5733333 290.4866667
347 268.8833333 275.5733333
348 265.0709677 268.8833333
349 216.0032258 265.0709677
350 250.0733333 216.0032258
351 225.5666667 250.0733333
352 222.0400000 225.5666667
353 182.3633333 222.0400000
354 179.1766667 182.3633333
355 192.2400000 179.1766667
356 226.9800000 192.2400000
357 207.8866667 226.9800000
358 211.5733333 207.8866667
359 192.7833333 211.5733333
360 193.3709677 192.7833333
361 200.5032258 193.3709677
> 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/7xnno1355670569.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/8rw9h1355670569.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/9cwm91355670569.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/wessaorg/rcomp/tmp/10fnoe1355670569.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/118cqf1355670569.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/128qr31355670569.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/13sq671355670569.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/148gv51355670569.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/15fss91355670569.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/16pjx71355670569.tab")
+ }
>
> try(system("convert tmp/1a3q61355670569.ps tmp/1a3q61355670569.png",intern=TRUE))
character(0)
> try(system("convert tmp/293wr1355670569.ps tmp/293wr1355670569.png",intern=TRUE))
character(0)
> try(system("convert tmp/3w4gn1355670569.ps tmp/3w4gn1355670569.png",intern=TRUE))
character(0)
> try(system("convert tmp/49atp1355670569.ps tmp/49atp1355670569.png",intern=TRUE))
character(0)
> try(system("convert tmp/59w9d1355670569.ps tmp/59w9d1355670569.png",intern=TRUE))
character(0)
> try(system("convert tmp/60icw1355670569.ps tmp/60icw1355670569.png",intern=TRUE))
character(0)
> try(system("convert tmp/7xnno1355670569.ps tmp/7xnno1355670569.png",intern=TRUE))
character(0)
> try(system("convert tmp/8rw9h1355670569.ps tmp/8rw9h1355670569.png",intern=TRUE))
character(0)
> try(system("convert tmp/9cwm91355670569.ps tmp/9cwm91355670569.png",intern=TRUE))
character(0)
> try(system("convert tmp/10fnoe1355670569.ps tmp/10fnoe1355670569.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
13.757 0.874 14.632