R version 2.13.0 (2011-04-13)
Copyright (C) 2011 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-bit)
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('Unempl')
+ ,1:372))
> y <- array(NA,dim=c(1,372),dimnames=list(c('Unempl'),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 = '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
> 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
Unempl M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11
1 235.1 1 0 0 0 0 0 0 0 0 0 0
2 280.7 0 1 0 0 0 0 0 0 0 0 0
3 264.6 0 0 1 0 0 0 0 0 0 0 0
4 240.7 0 0 0 1 0 0 0 0 0 0 0
5 201.4 0 0 0 0 1 0 0 0 0 0 0
6 240.8 0 0 0 0 0 1 0 0 0 0 0
7 241.1 0 0 0 0 0 0 1 0 0 0 0
8 223.8 0 0 0 0 0 0 0 1 0 0 0
9 206.1 0 0 0 0 0 0 0 0 1 0 0
10 174.7 0 0 0 0 0 0 0 0 0 1 0
11 203.3 0 0 0 0 0 0 0 0 0 0 1
12 220.5 0 0 0 0 0 0 0 0 0 0 0
13 299.5 1 0 0 0 0 0 0 0 0 0 0
14 347.4 0 1 0 0 0 0 0 0 0 0 0
15 338.3 0 0 1 0 0 0 0 0 0 0 0
16 327.7 0 0 0 1 0 0 0 0 0 0 0
17 351.6 0 0 0 0 1 0 0 0 0 0 0
18 396.6 0 0 0 0 0 1 0 0 0 0 0
19 438.8 0 0 0 0 0 0 1 0 0 0 0
20 395.6 0 0 0 0 0 0 0 1 0 0 0
21 363.5 0 0 0 0 0 0 0 0 1 0 0
22 378.8 0 0 0 0 0 0 0 0 0 1 0
23 357.0 0 0 0 0 0 0 0 0 0 0 1
24 369.0 0 0 0 0 0 0 0 0 0 0 0
25 464.8 1 0 0 0 0 0 0 0 0 0 0
26 479.1 0 1 0 0 0 0 0 0 0 0 0
27 431.3 0 0 1 0 0 0 0 0 0 0 0
28 366.5 0 0 0 1 0 0 0 0 0 0 0
29 326.3 0 0 0 0 1 0 0 0 0 0 0
30 355.1 0 0 0 0 0 1 0 0 0 0 0
31 331.6 0 0 0 0 0 0 1 0 0 0 0
32 261.3 0 0 0 0 0 0 0 1 0 0 0
33 249.0 0 0 0 0 0 0 0 0 1 0 0
34 205.5 0 0 0 0 0 0 0 0 0 1 0
35 235.6 0 0 0 0 0 0 0 0 0 0 1
36 240.9 0 0 0 0 0 0 0 0 0 0 0
37 264.9 1 0 0 0 0 0 0 0 0 0 0
38 253.8 0 1 0 0 0 0 0 0 0 0 0
39 232.3 0 0 1 0 0 0 0 0 0 0 0
40 193.8 0 0 0 1 0 0 0 0 0 0 0
41 177.0 0 0 0 0 1 0 0 0 0 0 0
42 213.2 0 0 0 0 0 1 0 0 0 0 0
43 207.2 0 0 0 0 0 0 1 0 0 0 0
44 180.6 0 0 0 0 0 0 0 1 0 0 0
45 188.6 0 0 0 0 0 0 0 0 1 0 0
46 175.4 0 0 0 0 0 0 0 0 0 1 0
47 199.0 0 0 0 0 0 0 0 0 0 0 1
48 179.6 0 0 0 0 0 0 0 0 0 0 0
49 225.8 1 0 0 0 0 0 0 0 0 0 0
50 234.0 0 1 0 0 0 0 0 0 0 0 0
51 200.2 0 0 1 0 0 0 0 0 0 0 0
52 183.6 0 0 0 1 0 0 0 0 0 0 0
53 178.2 0 0 0 0 1 0 0 0 0 0 0
54 203.2 0 0 0 0 0 1 0 0 0 0 0
55 208.5 0 0 0 0 0 0 1 0 0 0 0
56 191.8 0 0 0 0 0 0 0 1 0 0 0
57 172.8 0 0 0 0 0 0 0 0 1 0 0
58 148.0 0 0 0 0 0 0 0 0 0 1 0
59 159.4 0 0 0 0 0 0 0 0 0 0 1
60 154.5 0 0 0 0 0 0 0 0 0 0 0
61 213.2 1 0 0 0 0 0 0 0 0 0 0
62 196.4 0 1 0 0 0 0 0 0 0 0 0
63 182.8 0 0 1 0 0 0 0 0 0 0 0
64 176.4 0 0 0 1 0 0 0 0 0 0 0
65 153.6 0 0 0 0 1 0 0 0 0 0 0
66 173.2 0 0 0 0 0 1 0 0 0 0 0
67 171.0 0 0 0 0 0 0 1 0 0 0 0
68 151.2 0 0 0 0 0 0 0 1 0 0 0
69 161.9 0 0 0 0 0 0 0 0 1 0 0
70 157.2 0 0 0 0 0 0 0 0 0 1 0
71 201.7 0 0 0 0 0 0 0 0 0 0 1
72 236.4 0 0 0 0 0 0 0 0 0 0 0
73 356.1 1 0 0 0 0 0 0 0 0 0 0
74 398.3 0 1 0 0 0 0 0 0 0 0 0
75 403.7 0 0 1 0 0 0 0 0 0 0 0
76 384.6 0 0 0 1 0 0 0 0 0 0 0
77 365.8 0 0 0 0 1 0 0 0 0 0 0
78 368.1 0 0 0 0 0 1 0 0 0 0 0
79 367.9 0 0 0 0 0 0 1 0 0 0 0
80 347.0 0 0 0 0 0 0 0 1 0 0 0
81 343.3 0 0 0 0 0 0 0 0 1 0 0
82 292.9 0 0 0 0 0 0 0 0 0 1 0
83 311.5 0 0 0 0 0 0 0 0 0 0 1
84 300.9 0 0 0 0 0 0 0 0 0 0 0
85 366.9 1 0 0 0 0 0 0 0 0 0 0
86 356.9 0 1 0 0 0 0 0 0 0 0 0
87 329.7 0 0 1 0 0 0 0 0 0 0 0
88 316.2 0 0 0 1 0 0 0 0 0 0 0
89 269.0 0 0 0 0 1 0 0 0 0 0 0
90 289.3 0 0 0 0 0 1 0 0 0 0 0
91 266.2 0 0 0 0 0 0 1 0 0 0 0
92 253.6 0 0 0 0 0 0 0 1 0 0 0
93 233.8 0 0 0 0 0 0 0 0 1 0 0
94 228.4 0 0 0 0 0 0 0 0 0 1 0
95 253.6 0 0 0 0 0 0 0 0 0 0 1
96 260.1 0 0 0 0 0 0 0 0 0 0 0
97 306.6 1 0 0 0 0 0 0 0 0 0 0
98 309.2 0 1 0 0 0 0 0 0 0 0 0
99 309.5 0 0 1 0 0 0 0 0 0 0 0
100 271.0 0 0 0 1 0 0 0 0 0 0 0
101 279.9 0 0 0 0 1 0 0 0 0 0 0
102 317.9 0 0 0 0 0 1 0 0 0 0 0
103 298.4 0 0 0 0 0 0 1 0 0 0 0
104 246.7 0 0 0 0 0 0 0 1 0 0 0
105 227.3 0 0 0 0 0 0 0 0 1 0 0
106 209.1 0 0 0 0 0 0 0 0 0 1 0
107 259.9 0 0 0 0 0 0 0 0 0 0 1
108 266.0 0 0 0 0 0 0 0 0 0 0 0
109 320.6 1 0 0 0 0 0 0 0 0 0 0
110 308.5 0 1 0 0 0 0 0 0 0 0 0
111 282.2 0 0 1 0 0 0 0 0 0 0 0
112 262.7 0 0 0 1 0 0 0 0 0 0 0
113 263.5 0 0 0 0 1 0 0 0 0 0 0
114 313.1 0 0 0 0 0 1 0 0 0 0 0
115 284.3 0 0 0 0 0 0 1 0 0 0 0
116 252.6 0 0 0 0 0 0 0 1 0 0 0
117 250.3 0 0 0 0 0 0 0 0 1 0 0
118 246.5 0 0 0 0 0 0 0 0 0 1 0
119 312.7 0 0 0 0 0 0 0 0 0 0 1
120 333.2 0 0 0 0 0 0 0 0 0 0 0
121 446.4 1 0 0 0 0 0 0 0 0 0 0
122 511.6 0 1 0 0 0 0 0 0 0 0 0
123 515.5 0 0 1 0 0 0 0 0 0 0 0
124 506.4 0 0 0 1 0 0 0 0 0 0 0
125 483.2 0 0 0 0 1 0 0 0 0 0 0
126 522.3 0 0 0 0 0 1 0 0 0 0 0
127 509.8 0 0 0 0 0 0 1 0 0 0 0
128 460.7 0 0 0 0 0 0 0 1 0 0 0
129 405.8 0 0 0 0 0 0 0 0 1 0 0
130 375.0 0 0 0 0 0 0 0 0 0 1 0
131 378.5 0 0 0 0 0 0 0 0 0 0 1
132 406.8 0 0 0 0 0 0 0 0 0 0 0
133 467.8 1 0 0 0 0 0 0 0 0 0 0
134 469.8 0 1 0 0 0 0 0 0 0 0 0
135 429.8 0 0 1 0 0 0 0 0 0 0 0
136 355.8 0 0 0 1 0 0 0 0 0 0 0
137 332.7 0 0 0 0 1 0 0 0 0 0 0
138 378.0 0 0 0 0 0 1 0 0 0 0 0
139 360.5 0 0 0 0 0 0 1 0 0 0 0
140 334.7 0 0 0 0 0 0 0 1 0 0 0
141 319.5 0 0 0 0 0 0 0 0 1 0 0
142 323.1 0 0 0 0 0 0 0 0 0 1 0
143 363.6 0 0 0 0 0 0 0 0 0 0 1
144 352.1 0 0 0 0 0 0 0 0 0 0 0
145 411.9 1 0 0 0 0 0 0 0 0 0 0
146 388.6 0 1 0 0 0 0 0 0 0 0 0
147 416.4 0 0 1 0 0 0 0 0 0 0 0
148 360.7 0 0 0 1 0 0 0 0 0 0 0
149 338.0 0 0 0 0 1 0 0 0 0 0 0
150 417.2 0 0 0 0 0 1 0 0 0 0 0
151 388.4 0 0 0 0 0 0 1 0 0 0 0
152 371.1 0 0 0 0 0 0 0 1 0 0 0
153 331.5 0 0 0 0 0 0 0 0 1 0 0
154 353.7 0 0 0 0 0 0 0 0 0 1 0
155 396.7 0 0 0 0 0 0 0 0 0 0 1
156 447.0 0 0 0 0 0 0 0 0 0 0 0
157 533.5 1 0 0 0 0 0 0 0 0 0 0
158 565.4 0 1 0 0 0 0 0 0 0 0 0
159 542.3 0 0 1 0 0 0 0 0 0 0 0
160 488.7 0 0 0 1 0 0 0 0 0 0 0
161 467.1 0 0 0 0 1 0 0 0 0 0 0
162 531.3 0 0 0 0 0 1 0 0 0 0 0
163 496.1 0 0 0 0 0 0 1 0 0 0 0
164 444.0 0 0 0 0 0 0 0 1 0 0 0
165 403.4 0 0 0 0 0 0 0 0 1 0 0
166 386.3 0 0 0 0 0 0 0 0 0 1 0
167 394.1 0 0 0 0 0 0 0 0 0 0 1
168 404.1 0 0 0 0 0 0 0 0 0 0 0
169 462.1 1 0 0 0 0 0 0 0 0 0 0
170 448.1 0 1 0 0 0 0 0 0 0 0 0
171 432.3 0 0 1 0 0 0 0 0 0 0 0
172 386.3 0 0 0 1 0 0 0 0 0 0 0
173 395.2 0 0 0 0 1 0 0 0 0 0 0
174 421.9 0 0 0 0 0 1 0 0 0 0 0
175 382.9 0 0 0 0 0 0 1 0 0 0 0
176 384.2 0 0 0 0 0 0 0 1 0 0 0
177 345.5 0 0 0 0 0 0 0 0 1 0 0
178 323.4 0 0 0 0 0 0 0 0 0 1 0
179 372.6 0 0 0 0 0 0 0 0 0 0 1
180 376.0 0 0 0 0 0 0 0 0 0 0 0
181 462.7 1 0 0 0 0 0 0 0 0 0 0
182 487.0 0 1 0 0 0 0 0 0 0 0 0
183 444.2 0 0 1 0 0 0 0 0 0 0 0
184 399.3 0 0 0 1 0 0 0 0 0 0 0
185 394.9 0 0 0 0 1 0 0 0 0 0 0
186 455.4 0 0 0 0 0 1 0 0 0 0 0
187 414.0 0 0 0 0 0 0 1 0 0 0 0
188 375.5 0 0 0 0 0 0 0 1 0 0 0
189 347.0 0 0 0 0 0 0 0 0 1 0 0
190 339.4 0 0 0 0 0 0 0 0 0 1 0
191 385.8 0 0 0 0 0 0 0 0 0 0 1
192 378.8 0 0 0 0 0 0 0 0 0 0 0
193 451.8 1 0 0 0 0 0 0 0 0 0 0
194 446.1 0 1 0 0 0 0 0 0 0 0 0
195 422.5 0 0 1 0 0 0 0 0 0 0 0
196 383.1 0 0 0 1 0 0 0 0 0 0 0
197 352.8 0 0 0 0 1 0 0 0 0 0 0
198 445.3 0 0 0 0 0 1 0 0 0 0 0
199 367.5 0 0 0 0 0 0 1 0 0 0 0
200 355.1 0 0 0 0 0 0 0 1 0 0 0
201 326.2 0 0 0 0 0 0 0 0 1 0 0
202 319.8 0 0 0 0 0 0 0 0 0 1 0
203 331.8 0 0 0 0 0 0 0 0 0 0 1
204 340.9 0 0 0 0 0 0 0 0 0 0 0
205 394.1 1 0 0 0 0 0 0 0 0 0 0
206 417.2 0 1 0 0 0 0 0 0 0 0 0
207 369.9 0 0 1 0 0 0 0 0 0 0 0
208 349.2 0 0 0 1 0 0 0 0 0 0 0
209 321.4 0 0 0 0 1 0 0 0 0 0 0
210 405.7 0 0 0 0 0 1 0 0 0 0 0
211 342.9 0 0 0 0 0 0 1 0 0 0 0
212 316.5 0 0 0 0 0 0 0 1 0 0 0
213 284.2 0 0 0 0 0 0 0 0 1 0 0
214 270.9 0 0 0 0 0 0 0 0 0 1 0
215 288.8 0 0 0 0 0 0 0 0 0 0 1
216 278.8 0 0 0 0 0 0 0 0 0 0 0
217 324.4 1 0 0 0 0 0 0 0 0 0 0
218 310.9 0 1 0 0 0 0 0 0 0 0 0
219 299.0 0 0 1 0 0 0 0 0 0 0 0
220 273.0 0 0 0 1 0 0 0 0 0 0 0
221 279.3 0 0 0 0 1 0 0 0 0 0 0
222 359.2 0 0 0 0 0 1 0 0 0 0 0
223 305.0 0 0 0 0 0 0 1 0 0 0 0
224 282.1 0 0 0 0 0 0 0 1 0 0 0
225 250.3 0 0 0 0 0 0 0 0 1 0 0
226 246.5 0 0 0 0 0 0 0 0 0 1 0
227 257.9 0 0 0 0 0 0 0 0 0 0 1
228 266.5 0 0 0 0 0 0 0 0 0 0 0
229 315.9 1 0 0 0 0 0 0 0 0 0 0
230 318.4 0 1 0 0 0 0 0 0 0 0 0
231 295.4 0 0 1 0 0 0 0 0 0 0 0
232 266.4 0 0 0 1 0 0 0 0 0 0 0
233 245.8 0 0 0 0 1 0 0 0 0 0 0
234 362.8 0 0 0 0 0 1 0 0 0 0 0
235 324.9 0 0 0 0 0 0 1 0 0 0 0
236 294.2 0 0 0 0 0 0 0 1 0 0 0
237 289.5 0 0 0 0 0 0 0 0 1 0 0
238 295.2 0 0 0 0 0 0 0 0 0 1 0
239 290.3 0 0 0 0 0 0 0 0 0 0 1
240 272.0 0 0 0 0 0 0 0 0 0 0 0
241 307.4 1 0 0 0 0 0 0 0 0 0 0
242 328.7 0 1 0 0 0 0 0 0 0 0 0
243 292.9 0 0 1 0 0 0 0 0 0 0 0
244 249.1 0 0 0 1 0 0 0 0 0 0 0
245 230.4 0 0 0 0 1 0 0 0 0 0 0
246 361.5 0 0 0 0 0 1 0 0 0 0 0
247 321.7 0 0 0 0 0 0 1 0 0 0 0
248 277.2 0 0 0 0 0 0 0 1 0 0 0
249 260.7 0 0 0 0 0 0 0 0 1 0 0
250 251.0 0 0 0 0 0 0 0 0 0 1 0
251 257.6 0 0 0 0 0 0 0 0 0 0 1
252 241.8 0 0 0 0 0 0 0 0 0 0 0
253 287.5 1 0 0 0 0 0 0 0 0 0 0
254 292.3 0 1 0 0 0 0 0 0 0 0 0
255 274.7 0 0 1 0 0 0 0 0 0 0 0
256 254.2 0 0 0 1 0 0 0 0 0 0 0
257 230.0 0 0 0 0 1 0 0 0 0 0 0
258 339.0 0 0 0 0 0 1 0 0 0 0 0
259 318.2 0 0 0 0 0 0 1 0 0 0 0
260 287.0 0 0 0 0 0 0 0 1 0 0 0
261 295.8 0 0 0 0 0 0 0 0 1 0 0
262 284.0 0 0 0 0 0 0 0 0 0 1 0
263 271.0 0 0 0 0 0 0 0 0 0 0 1
264 262.7 0 0 0 0 0 0 0 0 0 0 0
265 340.6 1 0 0 0 0 0 0 0 0 0 0
266 379.4 0 1 0 0 0 0 0 0 0 0 0
267 373.3 0 0 1 0 0 0 0 0 0 0 0
268 355.2 0 0 0 1 0 0 0 0 0 0 0
269 338.4 0 0 0 0 1 0 0 0 0 0 0
270 466.9 0 0 0 0 0 1 0 0 0 0 0
271 451.0 0 0 0 0 0 0 1 0 0 0 0
272 422.0 0 0 0 0 0 0 0 1 0 0 0
273 429.2 0 0 0 0 0 0 0 0 1 0 0
274 425.9 0 0 0 0 0 0 0 0 0 1 0
275 460.7 0 0 0 0 0 0 0 0 0 0 1
276 463.6 0 0 0 0 0 0 0 0 0 0 0
277 541.4 1 0 0 0 0 0 0 0 0 0 0
278 544.2 0 1 0 0 0 0 0 0 0 0 0
279 517.5 0 0 1 0 0 0 0 0 0 0 0
280 469.4 0 0 0 1 0 0 0 0 0 0 0
281 439.4 0 0 0 0 1 0 0 0 0 0 0
282 549.0 0 0 0 0 0 1 0 0 0 0 0
283 533.0 0 0 0 0 0 0 1 0 0 0 0
284 506.1 0 0 0 0 0 0 0 1 0 0 0
285 484.0 0 0 0 0 0 0 0 0 1 0 0
286 457.0 0 0 0 0 0 0 0 0 0 1 0
287 481.5 0 0 0 0 0 0 0 0 0 0 1
288 469.5 0 0 0 0 0 0 0 0 0 0 0
289 544.7 1 0 0 0 0 0 0 0 0 0 0
290 541.2 0 1 0 0 0 0 0 0 0 0 0
291 521.5 0 0 1 0 0 0 0 0 0 0 0
292 469.7 0 0 0 1 0 0 0 0 0 0 0
293 434.4 0 0 0 0 1 0 0 0 0 0 0
294 542.6 0 0 0 0 0 1 0 0 0 0 0
295 517.3 0 0 0 0 0 0 1 0 0 0 0
296 485.7 0 0 0 0 0 0 0 1 0 0 0
297 465.8 0 0 0 0 0 0 0 0 1 0 0
298 447.0 0 0 0 0 0 0 0 0 0 1 0
299 426.6 0 0 0 0 0 0 0 0 0 0 1
300 411.6 0 0 0 0 0 0 0 0 0 0 0
301 467.5 1 0 0 0 0 0 0 0 0 0 0
302 484.5 0 1 0 0 0 0 0 0 0 0 0
303 451.2 0 0 1 0 0 0 0 0 0 0 0
304 417.4 0 0 0 1 0 0 0 0 0 0 0
305 379.9 0 0 0 0 1 0 0 0 0 0 0
306 484.7 0 0 0 0 0 1 0 0 0 0 0
307 455.0 0 0 0 0 0 0 1 0 0 0 0
308 420.8 0 0 0 0 0 0 0 1 0 0 0
309 416.5 0 0 0 0 0 0 0 0 1 0 0
310 376.3 0 0 0 0 0 0 0 0 0 1 0
311 405.6 0 0 0 0 0 0 0 0 0 0 1
312 405.8 0 0 0 0 0 0 0 0 0 0 0
313 500.8 1 0 0 0 0 0 0 0 0 0 0
314 514.0 0 1 0 0 0 0 0 0 0 0 0
315 475.5 0 0 1 0 0 0 0 0 0 0 0
316 430.1 0 0 0 1 0 0 0 0 0 0 0
317 414.4 0 0 0 0 1 0 0 0 0 0 0
318 538.0 0 0 0 0 0 1 0 0 0 0 0
319 526.0 0 0 0 0 0 0 1 0 0 0 0
320 488.5 0 0 0 0 0 0 0 1 0 0 0
321 520.2 0 0 0 0 0 0 0 0 1 0 0
322 504.4 0 0 0 0 0 0 0 0 0 1 0
323 568.5 0 0 0 0 0 0 0 0 0 0 1
324 610.6 0 0 0 0 0 0 0 0 0 0 0
325 818.0 1 0 0 0 0 0 0 0 0 0 0
326 830.9 0 1 0 0 0 0 0 0 0 0 0
327 835.9 0 0 1 0 0 0 0 0 0 0 0
328 782.0 0 0 0 1 0 0 0 0 0 0 0
329 762.3 0 0 0 0 1 0 0 0 0 0 0
330 856.9 0 0 0 0 0 1 0 0 0 0 0
331 820.9 0 0 0 0 0 0 1 0 0 0 0
332 769.6 0 0 0 0 0 0 0 1 0 0 0
333 752.2 0 0 0 0 0 0 0 0 1 0 0
334 724.4 0 0 0 0 0 0 0 0 0 1 0
335 723.1 0 0 0 0 0 0 0 0 0 0 1
336 719.5 0 0 0 0 0 0 0 0 0 0 0
337 817.4 1 0 0 0 0 0 0 0 0 0 0
338 803.3 0 1 0 0 0 0 0 0 0 0 0
339 752.5 0 0 1 0 0 0 0 0 0 0 0
340 689.0 0 0 0 1 0 0 0 0 0 0 0
341 630.4 0 0 0 0 1 0 0 0 0 0 0
342 765.5 0 0 0 0 0 1 0 0 0 0 0
343 757.7 0 0 0 0 0 0 1 0 0 0 0
344 732.2 0 0 0 0 0 0 0 1 0 0 0
345 702.6 0 0 0 0 0 0 0 0 1 0 0
346 683.3 0 0 0 0 0 0 0 0 0 1 0
347 709.5 0 0 0 0 0 0 0 0 0 0 1
348 702.2 0 0 0 0 0 0 0 0 0 0 0
349 784.8 1 0 0 0 0 0 0 0 0 0 0
350 810.9 0 1 0 0 0 0 0 0 0 0 0
351 755.6 0 0 1 0 0 0 0 0 0 0 0
352 656.8 0 0 0 1 0 0 0 0 0 0 0
353 615.1 0 0 0 0 1 0 0 0 0 0 0
354 745.3 0 0 0 0 0 1 0 0 0 0 0
355 694.1 0 0 0 0 0 0 1 0 0 0 0
356 675.7 0 0 0 0 0 0 0 1 0 0 0
357 643.7 0 0 0 0 0 0 0 0 1 0 0
358 622.1 0 0 0 0 0 0 0 0 0 1 0
359 634.6 0 0 0 0 0 0 0 0 0 0 1
360 588.0 0 0 0 0 0 0 0 0 0 0 0
361 689.7 1 0 0 0 0 0 0 0 0 0 0
362 673.9 0 1 0 0 0 0 0 0 0 0 0
363 647.9 0 0 1 0 0 0 0 0 0 0 0
364 568.8 0 0 0 1 0 0 0 0 0 0 0
365 545.7 0 0 0 0 1 0 0 0 0 0 0
366 632.6 0 0 0 0 0 1 0 0 0 0 0
367 643.8 0 0 0 0 0 0 1 0 0 0 0
368 593.1 0 0 0 0 0 0 0 1 0 0 0
369 579.7 0 0 0 0 0 0 0 0 1 0 0
370 546.0 0 0 0 0 0 0 0 0 0 1 0
371 562.9 0 0 0 0 0 0 0 0 0 0 1
372 572.5 0 0 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
371.997 61.032 70.929 48.661 9.739 -10.800
M6 M7 M8 M9 M10 M11
61.926 39.155 8.010 -9.097 -24.539 -2.468
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-260.72 -112.47 -23.63 73.65 422.98
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 371.997 27.667 13.445 <2e-16 ***
M1 61.032 39.127 1.560 0.1197
M2 70.929 39.127 1.813 0.0707 .
M3 48.661 39.127 1.244 0.2144
M4 9.739 39.127 0.249 0.8036
M5 -10.800 39.127 -0.276 0.7827
M6 61.926 39.127 1.583 0.1144
M7 39.155 39.127 1.001 0.3176
M8 8.010 39.127 0.205 0.8379
M9 -9.097 39.127 -0.232 0.8163
M10 -24.539 39.127 -0.627 0.5310
M11 -2.468 39.127 -0.063 0.9497
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 154 on 360 degrees of freedom
Multiple R-squared: 0.04221, Adjusted R-squared: 0.01294
F-statistic: 1.442 on 11 and 360 DF, p-value: 0.152
> 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,] 3.936653e-02 7.873305e-02 0.9606334750
[2,] 2.239021e-02 4.478042e-02 0.9776097918
[3,] 3.206730e-02 6.413459e-02 0.9679327034
[4,] 3.662302e-02 7.324605e-02 0.9633769751
[5,] 5.572176e-02 1.114435e-01 0.9442782444
[6,] 5.771934e-02 1.154387e-01 0.9422806634
[7,] 5.272827e-02 1.054565e-01 0.9472717257
[8,] 6.412046e-02 1.282409e-01 0.9358795382
[9,] 5.611936e-02 1.122387e-01 0.9438806393
[10,] 4.792170e-02 9.584340e-02 0.9520782988
[11,] 6.261404e-02 1.252281e-01 0.9373859585
[12,] 6.390555e-02 1.278111e-01 0.9360944459
[13,] 5.479928e-02 1.095986e-01 0.9452007157
[14,] 3.972314e-02 7.944628e-02 0.9602768577
[15,] 2.638933e-02 5.277866e-02 0.9736106700
[16,] 1.689379e-02 3.378758e-02 0.9831062087
[17,] 1.031526e-02 2.063053e-02 0.9896847369
[18,] 6.534442e-03 1.306888e-02 0.9934655575
[19,] 3.972397e-03 7.944794e-03 0.9960276031
[20,] 2.638169e-03 5.276337e-03 0.9973618314
[21,] 1.600649e-03 3.201298e-03 0.9983993510
[22,] 9.830918e-04 1.966184e-03 0.9990169082
[23,] 6.499017e-04 1.299803e-03 0.9993500983
[24,] 5.731870e-04 1.146374e-03 0.9994268130
[25,] 4.957547e-04 9.915094e-04 0.9995042453
[26,] 4.463207e-04 8.926415e-04 0.9995536793
[27,] 3.963549e-04 7.927098e-04 0.9996036451
[28,] 3.644178e-04 7.288357e-04 0.9996355822
[29,] 3.630772e-04 7.261544e-04 0.9996369228
[30,] 3.199213e-04 6.398427e-04 0.9996800787
[31,] 2.362405e-04 4.724809e-04 0.9997637595
[32,] 1.688669e-04 3.377339e-04 0.9998311331
[33,] 1.148028e-04 2.296055e-04 0.9998851972
[34,] 9.234370e-05 1.846874e-04 0.9999076563
[35,] 7.395290e-05 1.479058e-04 0.9999260471
[36,] 6.588531e-05 1.317706e-04 0.9999341147
[37,] 6.397484e-05 1.279497e-04 0.9999360252
[38,] 5.405345e-05 1.081069e-04 0.9999459466
[39,] 4.198751e-05 8.397502e-05 0.9999580125
[40,] 3.686070e-05 7.372140e-05 0.9999631393
[41,] 3.116141e-05 6.232283e-05 0.9999688386
[42,] 2.307733e-05 4.615467e-05 0.9999769227
[43,] 1.761666e-05 3.523333e-05 0.9999823833
[44,] 1.410182e-05 2.820363e-05 0.9999858982
[45,] 1.171196e-05 2.342393e-05 0.9999882880
[46,] 1.038874e-05 2.077748e-05 0.9999896113
[47,] 8.742919e-06 1.748584e-05 0.9999912571
[48,] 9.968897e-06 1.993779e-05 0.9999900311
[49,] 1.026226e-05 2.052453e-05 0.9999897377
[50,] 8.675902e-06 1.735180e-05 0.9999913241
[51,] 7.704891e-06 1.540978e-05 0.9999922951
[52,] 8.276768e-06 1.655354e-05 0.9999917232
[53,] 8.980868e-06 1.796174e-05 0.9999910191
[54,] 8.698625e-06 1.739725e-05 0.9999913014
[55,] 7.083386e-06 1.416677e-05 0.9999929166
[56,] 5.360813e-06 1.072163e-05 0.9999946392
[57,] 3.626513e-06 7.253026e-06 0.9999963735
[58,] 2.295832e-06 4.591663e-06 0.9999977042
[59,] 1.666860e-06 3.333720e-06 0.9999983331
[60,] 1.400708e-06 2.801416e-06 0.9999985993
[61,] 1.465011e-06 2.930022e-06 0.9999985350
[62,] 1.620801e-06 3.241602e-06 0.9999983792
[63,] 1.743553e-06 3.487106e-06 0.9999982564
[64,] 1.528095e-06 3.056190e-06 0.9999984719
[65,] 1.289361e-06 2.578721e-06 0.9999987106
[66,] 1.170874e-06 2.341749e-06 0.9999988291
[67,] 1.108419e-06 2.216839e-06 0.9999988916
[68,] 8.557207e-07 1.711441e-06 0.9999991443
[69,] 6.589051e-07 1.317810e-06 0.9999993411
[70,] 4.674052e-07 9.348104e-07 0.9999995326
[71,] 3.409802e-07 6.819604e-07 0.9999996590
[72,] 2.252452e-07 4.504904e-07 0.9999997748
[73,] 1.457573e-07 2.915145e-07 0.9999998542
[74,] 9.490447e-08 1.898089e-07 0.9999999051
[75,] 5.864137e-08 1.172827e-07 0.9999999414
[76,] 3.897652e-08 7.795303e-08 0.9999999610
[77,] 2.568167e-08 5.136333e-08 0.9999999743
[78,] 1.629725e-08 3.259449e-08 0.9999999837
[79,] 1.033303e-08 2.066606e-08 0.9999999897
[80,] 6.465833e-09 1.293167e-08 0.9999999935
[81,] 4.043237e-09 8.086473e-09 0.9999999960
[82,] 2.508771e-09 5.017542e-09 0.9999999975
[83,] 1.588449e-09 3.176899e-09 0.9999999984
[84,] 1.016453e-09 2.032906e-09 0.9999999990
[85,] 6.261296e-10 1.252259e-09 0.9999999994
[86,] 3.791811e-10 7.583621e-10 0.9999999996
[87,] 2.267517e-10 4.535033e-10 0.9999999998
[88,] 1.507763e-10 3.015527e-10 0.9999999998
[89,] 9.370344e-11 1.874069e-10 0.9999999999
[90,] 5.931805e-11 1.186361e-10 0.9999999999
[91,] 3.777427e-11 7.554854e-11 1.0000000000
[92,] 2.421442e-11 4.842883e-11 1.0000000000
[93,] 1.486803e-11 2.973605e-11 1.0000000000
[94,] 9.055005e-12 1.811001e-11 1.0000000000
[95,] 5.631259e-12 1.126252e-11 1.0000000000
[96,] 3.620504e-12 7.241008e-12 1.0000000000
[97,] 2.366785e-12 4.733571e-12 1.0000000000
[98,] 1.450970e-12 2.901939e-12 1.0000000000
[99,] 8.468533e-13 1.693707e-12 1.0000000000
[100,] 5.613916e-13 1.122783e-12 1.0000000000
[101,] 3.548690e-13 7.097381e-13 1.0000000000
[102,] 2.246348e-13 4.492696e-13 1.0000000000
[103,] 1.375044e-13 2.750089e-13 1.0000000000
[104,] 8.508511e-14 1.701702e-13 1.0000000000
[105,] 6.085449e-14 1.217090e-13 1.0000000000
[106,] 4.823134e-14 9.646268e-14 1.0000000000
[107,] 7.272052e-14 1.454410e-13 1.0000000000
[108,] 2.678437e-13 5.356874e-13 1.0000000000
[109,] 1.397621e-12 2.795242e-12 1.0000000000
[110,] 8.791313e-12 1.758263e-11 1.0000000000
[111,] 4.037540e-11 8.075080e-11 1.0000000000
[112,] 1.812102e-10 3.624204e-10 0.9999999998
[113,] 6.404286e-10 1.280857e-09 0.9999999994
[114,] 1.578653e-09 3.157305e-09 0.9999999984
[115,] 2.207480e-09 4.414959e-09 0.9999999978
[116,] 2.698160e-09 5.396319e-09 0.9999999973
[117,] 2.689455e-09 5.378910e-09 0.9999999973
[118,] 3.144128e-09 6.288256e-09 0.9999999969
[119,] 3.637946e-09 7.275891e-09 0.9999999964
[120,] 3.735009e-09 7.470018e-09 0.9999999963
[121,] 3.274279e-09 6.548558e-09 0.9999999967
[122,] 2.283672e-09 4.567345e-09 0.9999999977
[123,] 1.553481e-09 3.106962e-09 0.9999999984
[124,] 1.188105e-09 2.376210e-09 0.9999999988
[125,] 8.505709e-10 1.701142e-09 0.9999999991
[126,] 6.191432e-10 1.238286e-09 0.9999999994
[127,] 4.472112e-10 8.944223e-10 0.9999999996
[128,] 3.492280e-10 6.984561e-10 0.9999999997
[129,] 2.897442e-10 5.794884e-10 0.9999999997
[130,] 2.173644e-10 4.347287e-10 0.9999999998
[131,] 1.641592e-10 3.283185e-10 0.9999999998
[132,] 1.123761e-10 2.247522e-10 0.9999999999
[133,] 8.624375e-11 1.724875e-10 0.9999999999
[134,] 5.874233e-11 1.174847e-10 0.9999999999
[135,] 3.908092e-11 7.816185e-11 1.0000000000
[136,] 3.342906e-11 6.685811e-11 1.0000000000
[137,] 2.513609e-11 5.027217e-11 1.0000000000
[138,] 2.011754e-11 4.023509e-11 1.0000000000
[139,] 1.457022e-11 2.914043e-11 1.0000000000
[140,] 1.255845e-11 2.511690e-11 1.0000000000
[141,] 1.192890e-11 2.385779e-11 1.0000000000
[142,] 1.645668e-11 3.291335e-11 1.0000000000
[143,] 2.987662e-11 5.975324e-11 1.0000000000
[144,] 6.710386e-11 1.342077e-10 0.9999999999
[145,] 1.320320e-10 2.640640e-10 0.9999999999
[146,] 1.960633e-10 3.921267e-10 0.9999999998
[147,] 2.751226e-10 5.502451e-10 0.9999999997
[148,] 4.867734e-10 9.735468e-10 0.9999999995
[149,] 6.553108e-10 1.310622e-09 0.9999999993
[150,] 7.345403e-10 1.469081e-09 0.9999999993
[151,] 6.987716e-10 1.397543e-09 0.9999999993
[152,] 6.511132e-10 1.302226e-09 0.9999999993
[153,] 5.425765e-10 1.085153e-09 0.9999999995
[154,] 4.472094e-10 8.944187e-10 0.9999999996
[155,] 3.646239e-10 7.292478e-10 0.9999999996
[156,] 2.671626e-10 5.343252e-10 0.9999999997
[157,] 1.932886e-10 3.865773e-10 0.9999999998
[158,] 1.327211e-10 2.654422e-10 0.9999999999
[159,] 9.890515e-11 1.978103e-10 0.9999999999
[160,] 7.509174e-11 1.501835e-10 0.9999999999
[161,] 5.236252e-11 1.047250e-10 0.9999999999
[162,] 3.917272e-11 7.834544e-11 1.0000000000
[163,] 2.793101e-11 5.586202e-11 1.0000000000
[164,] 1.958533e-11 3.917067e-11 1.0000000000
[165,] 1.420842e-11 2.841683e-11 1.0000000000
[166,] 9.929689e-12 1.985938e-11 1.0000000000
[167,] 7.667039e-12 1.533408e-11 1.0000000000
[168,] 6.266411e-12 1.253282e-11 1.0000000000
[169,] 4.501141e-12 9.002282e-12 1.0000000000
[170,] 3.068030e-12 6.136059e-12 1.0000000000
[171,] 2.161604e-12 4.323208e-12 1.0000000000
[172,] 1.764979e-12 3.529959e-12 1.0000000000
[173,] 1.267414e-12 2.534829e-12 1.0000000000
[174,] 8.877615e-13 1.775523e-12 1.0000000000
[175,] 6.158539e-13 1.231708e-12 1.0000000000
[176,] 4.311670e-13 8.623341e-13 1.0000000000
[177,] 3.118506e-13 6.237012e-13 1.0000000000
[178,] 2.102461e-13 4.204922e-13 1.0000000000
[179,] 1.475061e-13 2.950123e-13 1.0000000000
[180,] 9.770472e-14 1.954094e-13 1.0000000000
[181,] 6.290476e-14 1.258095e-13 1.0000000000
[182,] 3.936999e-14 7.873999e-14 1.0000000000
[183,] 2.374506e-14 4.749012e-14 1.0000000000
[184,] 1.770769e-14 3.541537e-14 1.0000000000
[185,] 1.179183e-14 2.358367e-14 1.0000000000
[186,] 7.780226e-15 1.556045e-14 1.0000000000
[187,] 5.206447e-15 1.041289e-14 1.0000000000
[188,] 3.458277e-15 6.916555e-15 1.0000000000
[189,] 2.220151e-15 4.440302e-15 1.0000000000
[190,] 1.378069e-15 2.756139e-15 1.0000000000
[191,] 8.751416e-16 1.750283e-15 1.0000000000
[192,] 5.449134e-16 1.089827e-15 1.0000000000
[193,] 3.437078e-16 6.874156e-16 1.0000000000
[194,] 2.052162e-16 4.104325e-16 1.0000000000
[195,] 1.215157e-16 2.430315e-16 1.0000000000
[196,] 8.233866e-17 1.646773e-16 1.0000000000
[197,] 5.834660e-17 1.166932e-16 1.0000000000
[198,] 4.041173e-17 8.082347e-17 1.0000000000
[199,] 3.021727e-17 6.043455e-17 1.0000000000
[200,] 2.226408e-17 4.452816e-17 1.0000000000
[201,] 1.627111e-17 3.254221e-17 1.0000000000
[202,] 1.244058e-17 2.488115e-17 1.0000000000
[203,] 1.116806e-17 2.233612e-17 1.0000000000
[204,] 1.230366e-17 2.460732e-17 1.0000000000
[205,] 1.224575e-17 2.449150e-17 1.0000000000
[206,] 1.073330e-17 2.146661e-17 1.0000000000
[207,] 7.690026e-18 1.538005e-17 1.0000000000
[208,] 6.152827e-18 1.230565e-17 1.0000000000
[209,] 5.943138e-18 1.188628e-17 1.0000000000
[210,] 5.382592e-18 1.076518e-17 1.0000000000
[211,] 5.654138e-18 1.130828e-17 1.0000000000
[212,] 5.409697e-18 1.081939e-17 1.0000000000
[213,] 5.485141e-18 1.097028e-17 1.0000000000
[214,] 5.161495e-18 1.032299e-17 1.0000000000
[215,] 5.912511e-18 1.182502e-17 1.0000000000
[216,] 7.338132e-18 1.467626e-17 1.0000000000
[217,] 9.067886e-18 1.813577e-17 1.0000000000
[218,] 9.795526e-18 1.959105e-17 1.0000000000
[219,] 1.034223e-17 2.068446e-17 1.0000000000
[220,] 9.542031e-18 1.908406e-17 1.0000000000
[221,] 9.753993e-18 1.950799e-17 1.0000000000
[222,] 9.829401e-18 1.965880e-17 1.0000000000
[223,] 9.645456e-18 1.929091e-17 1.0000000000
[224,] 8.326930e-18 1.665386e-17 1.0000000000
[225,] 8.031632e-18 1.606326e-17 1.0000000000
[226,] 8.767245e-18 1.753449e-17 1.0000000000
[227,] 1.460749e-17 2.921498e-17 1.0000000000
[228,] 2.160108e-17 4.320217e-17 1.0000000000
[229,] 3.673998e-17 7.347997e-17 1.0000000000
[230,] 6.264283e-17 1.252857e-16 1.0000000000
[231,] 1.003502e-16 2.007004e-16 1.0000000000
[232,] 1.197176e-16 2.394352e-16 1.0000000000
[233,] 1.683839e-16 3.367678e-16 1.0000000000
[234,] 2.679443e-16 5.358887e-16 1.0000000000
[235,] 4.598685e-16 9.197369e-16 1.0000000000
[236,] 7.227010e-16 1.445402e-15 1.0000000000
[237,] 1.311616e-15 2.623232e-15 1.0000000000
[238,] 2.889276e-15 5.778552e-15 1.0000000000
[239,] 1.074951e-14 2.149903e-14 1.0000000000
[240,] 4.419401e-14 8.838802e-14 1.0000000000
[241,] 1.654851e-13 3.309702e-13 1.0000000000
[242,] 4.246517e-13 8.493034e-13 1.0000000000
[243,] 1.072943e-12 2.145886e-12 1.0000000000
[244,] 2.559328e-12 5.118655e-12 1.0000000000
[245,] 6.288165e-12 1.257633e-11 1.0000000000
[246,] 1.545405e-11 3.090811e-11 1.0000000000
[247,] 3.178256e-11 6.356513e-11 1.0000000000
[248,] 5.997824e-11 1.199565e-10 0.9999999999
[249,] 1.643699e-10 3.287397e-10 0.9999999998
[250,] 4.979758e-10 9.959517e-10 0.9999999995
[251,] 1.832891e-09 3.665782e-09 0.9999999982
[252,] 4.719136e-09 9.438273e-09 0.9999999953
[253,] 9.765499e-09 1.953100e-08 0.9999999902
[254,] 1.445344e-08 2.890687e-08 0.9999999855
[255,] 1.906341e-08 3.812683e-08 0.9999999809
[256,] 2.723889e-08 5.447777e-08 0.9999999728
[257,] 3.890463e-08 7.780926e-08 0.9999999611
[258,] 5.379204e-08 1.075841e-07 0.9999999462
[259,] 7.396528e-08 1.479306e-07 0.9999999260
[260,] 9.414500e-08 1.882900e-07 0.9999999059
[261,] 1.181670e-07 2.363341e-07 0.9999998818
[262,] 1.414275e-07 2.828551e-07 0.9999998586
[263,] 2.034505e-07 4.069009e-07 0.9999997965
[264,] 2.780710e-07 5.561420e-07 0.9999997219
[265,] 3.547555e-07 7.095110e-07 0.9999996452
[266,] 3.942429e-07 7.884858e-07 0.9999996058
[267,] 4.069722e-07 8.139443e-07 0.9999995930
[268,] 5.313701e-07 1.062740e-06 0.9999994686
[269,] 6.968093e-07 1.393619e-06 0.9999993032
[270,] 8.874287e-07 1.774857e-06 0.9999991126
[271,] 1.133624e-06 2.267248e-06 0.9999988664
[272,] 1.341697e-06 2.683394e-06 0.9999986583
[273,] 1.547003e-06 3.094006e-06 0.9999984530
[274,] 1.707167e-06 3.414334e-06 0.9999982928
[275,] 2.276733e-06 4.553465e-06 0.9999977233
[276,] 2.990484e-06 5.980967e-06 0.9999970095
[277,] 3.646982e-06 7.293965e-06 0.9999963530
[278,] 3.947367e-06 7.894734e-06 0.9999960526
[279,] 4.083374e-06 8.166749e-06 0.9999959166
[280,] 4.991092e-06 9.982184e-06 0.9999950089
[281,] 6.138820e-06 1.227764e-05 0.9999938612
[282,] 7.293406e-06 1.458681e-05 0.9999927066
[283,] 8.958880e-06 1.791776e-05 0.9999910411
[284,] 1.034082e-05 2.068165e-05 0.9999896592
[285,] 1.360427e-05 2.720854e-05 0.9999863957
[286,] 1.895115e-05 3.790229e-05 0.9999810489
[287,] 4.363141e-05 8.726283e-05 0.9999563686
[288,] 9.102382e-05 1.820476e-04 0.9999089762
[289,] 1.864718e-04 3.729437e-04 0.9998135282
[290,] 2.921284e-04 5.842569e-04 0.9997078716
[291,] 4.687144e-04 9.374288e-04 0.9995312856
[292,] 8.499893e-04 1.699979e-03 0.9991500107
[293,] 1.652030e-03 3.304060e-03 0.9983479702
[294,] 3.113448e-03 6.226897e-03 0.9968865515
[295,] 5.583523e-03 1.116705e-02 0.9944164767
[296,] 1.089218e-02 2.178436e-02 0.9891078202
[297,] 2.019856e-02 4.039711e-02 0.9798014425
[298,] 3.632046e-02 7.264093e-02 0.9636795367
[299,] 8.438178e-02 1.687636e-01 0.9156182248
[300,] 1.680827e-01 3.361654e-01 0.8319172875
[301,] 3.131737e-01 6.263473e-01 0.6868263470
[302,] 4.638633e-01 9.277266e-01 0.5361367107
[303,] 6.020581e-01 7.958838e-01 0.3979418824
[304,] 7.292896e-01 5.414209e-01 0.2707104374
[305,] 8.308891e-01 3.382217e-01 0.1691108723
[306,] 9.092479e-01 1.815041e-01 0.0907520716
[307,] 9.373373e-01 1.253254e-01 0.0626626994
[308,] 9.554406e-01 8.911882e-02 0.0445594107
[309,] 9.594505e-01 8.109910e-02 0.0405495478
[310,] 9.574531e-01 8.509372e-02 0.0425468615
[311,] 9.658881e-01 6.822385e-02 0.0341119275
[312,] 9.731261e-01 5.374790e-02 0.0268739486
[313,] 9.839988e-01 3.200241e-02 0.0160012065
[314,] 9.920877e-01 1.582455e-02 0.0079122773
[315,] 9.971082e-01 5.783634e-03 0.0028918169
[316,] 9.987836e-01 2.432859e-03 0.0012164294
[317,] 9.993493e-01 1.301443e-03 0.0006507217
[318,] 9.995450e-01 9.100597e-04 0.0004550299
[319,] 9.997034e-01 5.932609e-04 0.0002966304
[320,] 9.997935e-01 4.129140e-04 0.0002064570
[321,] 9.998095e-01 3.809460e-04 0.0001904730
[322,] 9.998411e-01 3.178646e-04 0.0001589323
[323,] 9.998322e-01 3.355912e-04 0.0001677956
[324,] 9.997805e-01 4.389347e-04 0.0002194674
[325,] 9.996775e-01 6.449797e-04 0.0003224899
[326,] 9.995867e-01 8.266565e-04 0.0004133283
[327,] 9.993375e-01 1.324963e-03 0.0006624814
[328,] 9.991473e-01 1.705301e-03 0.0008526506
[329,] 9.990083e-01 1.983308e-03 0.0009916540
[330,] 9.989344e-01 2.131238e-03 0.0010656189
[331,] 9.987389e-01 2.522131e-03 0.0012610654
[332,] 9.986156e-01 2.768716e-03 0.0013843580
[333,] 9.986908e-01 2.618388e-03 0.0013091942
[334,] 9.989947e-01 2.010662e-03 0.0010053312
[335,] 9.986403e-01 2.719455e-03 0.0013597273
[336,] 9.990197e-01 1.960552e-03 0.0009802759
[337,] 9.989110e-01 2.178063e-03 0.0010890317
[338,] 9.983442e-01 3.311646e-03 0.0016558229
[339,] 9.967205e-01 6.559080e-03 0.0032795399
[340,] 9.969723e-01 6.055332e-03 0.0030276659
[341,] 9.920914e-01 1.581721e-02 0.0079086057
[342,] 9.869092e-01 2.618152e-02 0.0130907609
[343,] 9.694511e-01 6.109781e-02 0.0305489036
> postscript(file="/var/wessaorg/rcomp/tmp/1c7ja1322470618.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/2kmdi1322470618.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3pmmh1322470618.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/4vqe31322470618.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/5bg5n1322470618.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
-197.929032 -162.225806 -156.058065 -141.035484 -159.796774 -193.122581
7 8 9 10 11 12
-170.051613 -156.206452 -156.800000 -172.758065 -166.229032 -151.496774
13 14 15 16 17 18
-133.529032 -95.525806 -82.358065 -54.035484 -9.596774 -37.322581
19 20 21 22 23 24
27.648387 15.593548 0.600000 31.341935 -12.529032 -2.996774
25 26 27 28 29 30
31.770968 36.174194 10.641935 -15.235484 -34.896774 -78.822581
31 32 33 34 35 36
-79.551613 -118.706452 -113.900000 -141.958065 -133.929032 -131.096774
37 38 39 40 41 42
-168.129032 -189.125806 -188.358065 -187.935484 -184.196774 -220.722581
43 44 45 46 47 48
-203.951613 -199.406452 -174.300000 -172.058065 -170.529032 -192.396774
49 50 51 52 53 54
-207.229032 -208.925806 -220.458065 -198.135484 -182.996774 -230.722581
55 56 57 58 59 60
-202.651613 -188.206452 -190.100000 -199.458065 -210.129032 -217.496774
61 62 63 64 65 66
-219.829032 -246.525806 -237.858065 -205.335484 -207.596774 -260.722581
67 68 69 70 71 72
-240.151613 -228.806452 -201.000000 -190.258065 -167.829032 -135.596774
73 74 75 76 77 78
-76.929032 -44.625806 -16.958065 2.864516 4.603226 -65.822581
79 80 81 82 83 84
-43.251613 -33.006452 -19.600000 -54.558065 -58.029032 -71.096774
85 86 87 88 89 90
-66.129032 -86.025806 -90.958065 -65.535484 -92.196774 -144.622581
91 92 93 94 95 96
-144.951613 -126.406452 -129.100000 -119.058065 -115.929032 -111.896774
97 98 99 100 101 102
-126.429032 -133.725806 -111.158065 -110.735484 -81.296774 -116.022581
103 104 105 106 107 108
-112.751613 -133.306452 -135.600000 -138.358065 -109.629032 -105.996774
109 110 111 112 113 114
-112.429032 -134.425806 -138.458065 -119.035484 -97.696774 -120.822581
115 116 117 118 119 120
-126.851613 -127.406452 -112.600000 -100.958065 -56.829032 -38.796774
121 122 123 124 125 126
13.370968 68.674194 94.841935 124.664516 122.003226 88.377419
127 128 129 130 131 132
98.648387 80.693548 42.900000 27.541935 8.970968 34.803226
133 134 135 136 137 138
34.770968 26.874194 9.141935 -25.935484 -28.496774 -55.922581
139 140 141 142 143 144
-50.651613 -45.306452 -43.400000 -24.358065 -5.929032 -19.896774
145 146 147 148 149 150
-21.129032 -54.325806 -4.258065 -21.035484 -23.196774 -16.722581
151 152 153 154 155 156
-22.751613 -8.906452 -31.400000 6.241935 27.170968 75.003226
157 158 159 160 161 162
100.470968 122.474194 121.641935 106.964516 105.903226 97.377419
163 164 165 166 167 168
84.948387 63.993548 40.500000 38.841935 24.570968 32.103226
169 170 171 172 173 174
29.070968 5.174194 11.641935 4.564516 34.003226 -12.022581
175 176 177 178 179 180
-28.251613 4.193548 -17.400000 -24.058065 3.070968 4.003226
181 182 183 184 185 186
29.670968 44.074194 23.541935 17.564516 33.703226 21.477419
187 188 189 190 191 192
2.848387 -4.506452 -15.900000 -8.058065 16.270968 6.803226
193 194 195 196 197 198
18.770968 3.174194 1.841935 1.364516 -8.396774 11.377419
199 200 201 202 203 204
-43.651613 -24.906452 -36.700000 -27.658065 -37.729032 -31.096774
205 206 207 208 209 210
-38.929032 -25.725806 -50.758065 -32.535484 -39.796774 -28.222581
211 212 213 214 215 216
-68.251613 -63.506452 -78.700000 -76.558065 -80.729032 -93.196774
217 218 219 220 221 222
-108.629032 -132.025806 -121.658065 -108.735484 -81.896774 -74.722581
223 224 225 226 227 228
-106.151613 -97.906452 -112.600000 -100.958065 -111.629032 -105.496774
229 230 231 232 233 234
-117.129032 -124.525806 -125.258065 -115.335484 -115.396774 -71.122581
235 236 237 238 239 240
-86.251613 -85.806452 -73.400000 -52.258065 -79.229032 -99.996774
241 242 243 244 245 246
-125.629032 -114.225806 -127.758065 -132.635484 -130.796774 -72.422581
247 248 249 250 251 252
-89.451613 -102.806452 -102.200000 -96.458065 -111.929032 -130.196774
253 254 255 256 257 258
-145.529032 -150.625806 -145.958065 -127.535484 -131.196774 -94.922581
259 260 261 262 263 264
-92.951613 -93.006452 -67.100000 -63.458065 -98.529032 -109.296774
265 266 267 268 269 270
-92.429032 -63.525806 -47.358065 -26.535484 -22.796774 32.977419
271 272 273 274 275 276
39.848387 41.993548 66.300000 78.441935 91.170968 91.603226
277 278 279 280 281 282
108.370968 101.274194 96.841935 87.664516 78.203226 115.077419
283 284 285 286 287 288
121.848387 126.093548 121.100000 109.541935 111.970968 97.503226
289 290 291 292 293 294
111.670968 98.274194 100.841935 87.964516 73.203226 108.677419
295 296 297 298 299 300
106.148387 105.693548 102.900000 99.541935 57.070968 39.603226
301 302 303 304 305 306
34.470968 41.574194 30.541935 35.664516 18.703226 50.777419
307 308 309 310 311 312
43.848387 40.793548 53.600000 28.841935 36.070968 33.803226
313 314 315 316 317 318
67.770968 71.074194 54.841935 48.364516 53.203226 104.077419
319 320 321 322 323 324
114.848387 108.493548 157.300000 156.941935 198.970968 238.603226
325 326 327 328 329 330
384.970968 387.974194 415.241935 400.264516 401.103226 422.977419
331 332 333 334 335 336
409.748387 389.593548 389.300000 376.941935 353.570968 347.503226
337 338 339 340 341 342
384.370968 360.374194 331.841935 307.264516 269.203226 331.577419
343 344 345 346 347 348
346.548387 352.193548 339.700000 335.841935 339.970968 330.203226
349 350 351 352 353 354
351.770968 367.974194 334.941935 275.064516 253.903226 311.377419
355 356 357 358 359 360
282.948387 295.693548 280.800000 274.641935 265.070968 216.003226
361 362 363 364 365 366
256.670968 230.974194 227.241935 187.064516 184.503226 198.677419
367 368 369 370 371 372
232.648387 213.093548 216.800000 198.541935 193.370968 200.503226
> postscript(file="/var/wessaorg/rcomp/tmp/6h7ue1322470618.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 -197.929032 NA
1 -162.225806 -197.929032
2 -156.058065 -162.225806
3 -141.035484 -156.058065
4 -159.796774 -141.035484
5 -193.122581 -159.796774
6 -170.051613 -193.122581
7 -156.206452 -170.051613
8 -156.800000 -156.206452
9 -172.758065 -156.800000
10 -166.229032 -172.758065
11 -151.496774 -166.229032
12 -133.529032 -151.496774
13 -95.525806 -133.529032
14 -82.358065 -95.525806
15 -54.035484 -82.358065
16 -9.596774 -54.035484
17 -37.322581 -9.596774
18 27.648387 -37.322581
19 15.593548 27.648387
20 0.600000 15.593548
21 31.341935 0.600000
22 -12.529032 31.341935
23 -2.996774 -12.529032
24 31.770968 -2.996774
25 36.174194 31.770968
26 10.641935 36.174194
27 -15.235484 10.641935
28 -34.896774 -15.235484
29 -78.822581 -34.896774
30 -79.551613 -78.822581
31 -118.706452 -79.551613
32 -113.900000 -118.706452
33 -141.958065 -113.900000
34 -133.929032 -141.958065
35 -131.096774 -133.929032
36 -168.129032 -131.096774
37 -189.125806 -168.129032
38 -188.358065 -189.125806
39 -187.935484 -188.358065
40 -184.196774 -187.935484
41 -220.722581 -184.196774
42 -203.951613 -220.722581
43 -199.406452 -203.951613
44 -174.300000 -199.406452
45 -172.058065 -174.300000
46 -170.529032 -172.058065
47 -192.396774 -170.529032
48 -207.229032 -192.396774
49 -208.925806 -207.229032
50 -220.458065 -208.925806
51 -198.135484 -220.458065
52 -182.996774 -198.135484
53 -230.722581 -182.996774
54 -202.651613 -230.722581
55 -188.206452 -202.651613
56 -190.100000 -188.206452
57 -199.458065 -190.100000
58 -210.129032 -199.458065
59 -217.496774 -210.129032
60 -219.829032 -217.496774
61 -246.525806 -219.829032
62 -237.858065 -246.525806
63 -205.335484 -237.858065
64 -207.596774 -205.335484
65 -260.722581 -207.596774
66 -240.151613 -260.722581
67 -228.806452 -240.151613
68 -201.000000 -228.806452
69 -190.258065 -201.000000
70 -167.829032 -190.258065
71 -135.596774 -167.829032
72 -76.929032 -135.596774
73 -44.625806 -76.929032
74 -16.958065 -44.625806
75 2.864516 -16.958065
76 4.603226 2.864516
77 -65.822581 4.603226
78 -43.251613 -65.822581
79 -33.006452 -43.251613
80 -19.600000 -33.006452
81 -54.558065 -19.600000
82 -58.029032 -54.558065
83 -71.096774 -58.029032
84 -66.129032 -71.096774
85 -86.025806 -66.129032
86 -90.958065 -86.025806
87 -65.535484 -90.958065
88 -92.196774 -65.535484
89 -144.622581 -92.196774
90 -144.951613 -144.622581
91 -126.406452 -144.951613
92 -129.100000 -126.406452
93 -119.058065 -129.100000
94 -115.929032 -119.058065
95 -111.896774 -115.929032
96 -126.429032 -111.896774
97 -133.725806 -126.429032
98 -111.158065 -133.725806
99 -110.735484 -111.158065
100 -81.296774 -110.735484
101 -116.022581 -81.296774
102 -112.751613 -116.022581
103 -133.306452 -112.751613
104 -135.600000 -133.306452
105 -138.358065 -135.600000
106 -109.629032 -138.358065
107 -105.996774 -109.629032
108 -112.429032 -105.996774
109 -134.425806 -112.429032
110 -138.458065 -134.425806
111 -119.035484 -138.458065
112 -97.696774 -119.035484
113 -120.822581 -97.696774
114 -126.851613 -120.822581
115 -127.406452 -126.851613
116 -112.600000 -127.406452
117 -100.958065 -112.600000
118 -56.829032 -100.958065
119 -38.796774 -56.829032
120 13.370968 -38.796774
121 68.674194 13.370968
122 94.841935 68.674194
123 124.664516 94.841935
124 122.003226 124.664516
125 88.377419 122.003226
126 98.648387 88.377419
127 80.693548 98.648387
128 42.900000 80.693548
129 27.541935 42.900000
130 8.970968 27.541935
131 34.803226 8.970968
132 34.770968 34.803226
133 26.874194 34.770968
134 9.141935 26.874194
135 -25.935484 9.141935
136 -28.496774 -25.935484
137 -55.922581 -28.496774
138 -50.651613 -55.922581
139 -45.306452 -50.651613
140 -43.400000 -45.306452
141 -24.358065 -43.400000
142 -5.929032 -24.358065
143 -19.896774 -5.929032
144 -21.129032 -19.896774
145 -54.325806 -21.129032
146 -4.258065 -54.325806
147 -21.035484 -4.258065
148 -23.196774 -21.035484
149 -16.722581 -23.196774
150 -22.751613 -16.722581
151 -8.906452 -22.751613
152 -31.400000 -8.906452
153 6.241935 -31.400000
154 27.170968 6.241935
155 75.003226 27.170968
156 100.470968 75.003226
157 122.474194 100.470968
158 121.641935 122.474194
159 106.964516 121.641935
160 105.903226 106.964516
161 97.377419 105.903226
162 84.948387 97.377419
163 63.993548 84.948387
164 40.500000 63.993548
165 38.841935 40.500000
166 24.570968 38.841935
167 32.103226 24.570968
168 29.070968 32.103226
169 5.174194 29.070968
170 11.641935 5.174194
171 4.564516 11.641935
172 34.003226 4.564516
173 -12.022581 34.003226
174 -28.251613 -12.022581
175 4.193548 -28.251613
176 -17.400000 4.193548
177 -24.058065 -17.400000
178 3.070968 -24.058065
179 4.003226 3.070968
180 29.670968 4.003226
181 44.074194 29.670968
182 23.541935 44.074194
183 17.564516 23.541935
184 33.703226 17.564516
185 21.477419 33.703226
186 2.848387 21.477419
187 -4.506452 2.848387
188 -15.900000 -4.506452
189 -8.058065 -15.900000
190 16.270968 -8.058065
191 6.803226 16.270968
192 18.770968 6.803226
193 3.174194 18.770968
194 1.841935 3.174194
195 1.364516 1.841935
196 -8.396774 1.364516
197 11.377419 -8.396774
198 -43.651613 11.377419
199 -24.906452 -43.651613
200 -36.700000 -24.906452
201 -27.658065 -36.700000
202 -37.729032 -27.658065
203 -31.096774 -37.729032
204 -38.929032 -31.096774
205 -25.725806 -38.929032
206 -50.758065 -25.725806
207 -32.535484 -50.758065
208 -39.796774 -32.535484
209 -28.222581 -39.796774
210 -68.251613 -28.222581
211 -63.506452 -68.251613
212 -78.700000 -63.506452
213 -76.558065 -78.700000
214 -80.729032 -76.558065
215 -93.196774 -80.729032
216 -108.629032 -93.196774
217 -132.025806 -108.629032
218 -121.658065 -132.025806
219 -108.735484 -121.658065
220 -81.896774 -108.735484
221 -74.722581 -81.896774
222 -106.151613 -74.722581
223 -97.906452 -106.151613
224 -112.600000 -97.906452
225 -100.958065 -112.600000
226 -111.629032 -100.958065
227 -105.496774 -111.629032
228 -117.129032 -105.496774
229 -124.525806 -117.129032
230 -125.258065 -124.525806
231 -115.335484 -125.258065
232 -115.396774 -115.335484
233 -71.122581 -115.396774
234 -86.251613 -71.122581
235 -85.806452 -86.251613
236 -73.400000 -85.806452
237 -52.258065 -73.400000
238 -79.229032 -52.258065
239 -99.996774 -79.229032
240 -125.629032 -99.996774
241 -114.225806 -125.629032
242 -127.758065 -114.225806
243 -132.635484 -127.758065
244 -130.796774 -132.635484
245 -72.422581 -130.796774
246 -89.451613 -72.422581
247 -102.806452 -89.451613
248 -102.200000 -102.806452
249 -96.458065 -102.200000
250 -111.929032 -96.458065
251 -130.196774 -111.929032
252 -145.529032 -130.196774
253 -150.625806 -145.529032
254 -145.958065 -150.625806
255 -127.535484 -145.958065
256 -131.196774 -127.535484
257 -94.922581 -131.196774
258 -92.951613 -94.922581
259 -93.006452 -92.951613
260 -67.100000 -93.006452
261 -63.458065 -67.100000
262 -98.529032 -63.458065
263 -109.296774 -98.529032
264 -92.429032 -109.296774
265 -63.525806 -92.429032
266 -47.358065 -63.525806
267 -26.535484 -47.358065
268 -22.796774 -26.535484
269 32.977419 -22.796774
270 39.848387 32.977419
271 41.993548 39.848387
272 66.300000 41.993548
273 78.441935 66.300000
274 91.170968 78.441935
275 91.603226 91.170968
276 108.370968 91.603226
277 101.274194 108.370968
278 96.841935 101.274194
279 87.664516 96.841935
280 78.203226 87.664516
281 115.077419 78.203226
282 121.848387 115.077419
283 126.093548 121.848387
284 121.100000 126.093548
285 109.541935 121.100000
286 111.970968 109.541935
287 97.503226 111.970968
288 111.670968 97.503226
289 98.274194 111.670968
290 100.841935 98.274194
291 87.964516 100.841935
292 73.203226 87.964516
293 108.677419 73.203226
294 106.148387 108.677419
295 105.693548 106.148387
296 102.900000 105.693548
297 99.541935 102.900000
298 57.070968 99.541935
299 39.603226 57.070968
300 34.470968 39.603226
301 41.574194 34.470968
302 30.541935 41.574194
303 35.664516 30.541935
304 18.703226 35.664516
305 50.777419 18.703226
306 43.848387 50.777419
307 40.793548 43.848387
308 53.600000 40.793548
309 28.841935 53.600000
310 36.070968 28.841935
311 33.803226 36.070968
312 67.770968 33.803226
313 71.074194 67.770968
314 54.841935 71.074194
315 48.364516 54.841935
316 53.203226 48.364516
317 104.077419 53.203226
318 114.848387 104.077419
319 108.493548 114.848387
320 157.300000 108.493548
321 156.941935 157.300000
322 198.970968 156.941935
323 238.603226 198.970968
324 384.970968 238.603226
325 387.974194 384.970968
326 415.241935 387.974194
327 400.264516 415.241935
328 401.103226 400.264516
329 422.977419 401.103226
330 409.748387 422.977419
331 389.593548 409.748387
332 389.300000 389.593548
333 376.941935 389.300000
334 353.570968 376.941935
335 347.503226 353.570968
336 384.370968 347.503226
337 360.374194 384.370968
338 331.841935 360.374194
339 307.264516 331.841935
340 269.203226 307.264516
341 331.577419 269.203226
342 346.548387 331.577419
343 352.193548 346.548387
344 339.700000 352.193548
345 335.841935 339.700000
346 339.970968 335.841935
347 330.203226 339.970968
348 351.770968 330.203226
349 367.974194 351.770968
350 334.941935 367.974194
351 275.064516 334.941935
352 253.903226 275.064516
353 311.377419 253.903226
354 282.948387 311.377419
355 295.693548 282.948387
356 280.800000 295.693548
357 274.641935 280.800000
358 265.070968 274.641935
359 216.003226 265.070968
360 256.670968 216.003226
361 230.974194 256.670968
362 227.241935 230.974194
363 187.064516 227.241935
364 184.503226 187.064516
365 198.677419 184.503226
366 232.648387 198.677419
367 213.093548 232.648387
368 216.800000 213.093548
369 198.541935 216.800000
370 193.370968 198.541935
371 200.503226 193.370968
372 NA 200.503226
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -162.225806 -197.929032
[2,] -156.058065 -162.225806
[3,] -141.035484 -156.058065
[4,] -159.796774 -141.035484
[5,] -193.122581 -159.796774
[6,] -170.051613 -193.122581
[7,] -156.206452 -170.051613
[8,] -156.800000 -156.206452
[9,] -172.758065 -156.800000
[10,] -166.229032 -172.758065
[11,] -151.496774 -166.229032
[12,] -133.529032 -151.496774
[13,] -95.525806 -133.529032
[14,] -82.358065 -95.525806
[15,] -54.035484 -82.358065
[16,] -9.596774 -54.035484
[17,] -37.322581 -9.596774
[18,] 27.648387 -37.322581
[19,] 15.593548 27.648387
[20,] 0.600000 15.593548
[21,] 31.341935 0.600000
[22,] -12.529032 31.341935
[23,] -2.996774 -12.529032
[24,] 31.770968 -2.996774
[25,] 36.174194 31.770968
[26,] 10.641935 36.174194
[27,] -15.235484 10.641935
[28,] -34.896774 -15.235484
[29,] -78.822581 -34.896774
[30,] -79.551613 -78.822581
[31,] -118.706452 -79.551613
[32,] -113.900000 -118.706452
[33,] -141.958065 -113.900000
[34,] -133.929032 -141.958065
[35,] -131.096774 -133.929032
[36,] -168.129032 -131.096774
[37,] -189.125806 -168.129032
[38,] -188.358065 -189.125806
[39,] -187.935484 -188.358065
[40,] -184.196774 -187.935484
[41,] -220.722581 -184.196774
[42,] -203.951613 -220.722581
[43,] -199.406452 -203.951613
[44,] -174.300000 -199.406452
[45,] -172.058065 -174.300000
[46,] -170.529032 -172.058065
[47,] -192.396774 -170.529032
[48,] -207.229032 -192.396774
[49,] -208.925806 -207.229032
[50,] -220.458065 -208.925806
[51,] -198.135484 -220.458065
[52,] -182.996774 -198.135484
[53,] -230.722581 -182.996774
[54,] -202.651613 -230.722581
[55,] -188.206452 -202.651613
[56,] -190.100000 -188.206452
[57,] -199.458065 -190.100000
[58,] -210.129032 -199.458065
[59,] -217.496774 -210.129032
[60,] -219.829032 -217.496774
[61,] -246.525806 -219.829032
[62,] -237.858065 -246.525806
[63,] -205.335484 -237.858065
[64,] -207.596774 -205.335484
[65,] -260.722581 -207.596774
[66,] -240.151613 -260.722581
[67,] -228.806452 -240.151613
[68,] -201.000000 -228.806452
[69,] -190.258065 -201.000000
[70,] -167.829032 -190.258065
[71,] -135.596774 -167.829032
[72,] -76.929032 -135.596774
[73,] -44.625806 -76.929032
[74,] -16.958065 -44.625806
[75,] 2.864516 -16.958065
[76,] 4.603226 2.864516
[77,] -65.822581 4.603226
[78,] -43.251613 -65.822581
[79,] -33.006452 -43.251613
[80,] -19.600000 -33.006452
[81,] -54.558065 -19.600000
[82,] -58.029032 -54.558065
[83,] -71.096774 -58.029032
[84,] -66.129032 -71.096774
[85,] -86.025806 -66.129032
[86,] -90.958065 -86.025806
[87,] -65.535484 -90.958065
[88,] -92.196774 -65.535484
[89,] -144.622581 -92.196774
[90,] -144.951613 -144.622581
[91,] -126.406452 -144.951613
[92,] -129.100000 -126.406452
[93,] -119.058065 -129.100000
[94,] -115.929032 -119.058065
[95,] -111.896774 -115.929032
[96,] -126.429032 -111.896774
[97,] -133.725806 -126.429032
[98,] -111.158065 -133.725806
[99,] -110.735484 -111.158065
[100,] -81.296774 -110.735484
[101,] -116.022581 -81.296774
[102,] -112.751613 -116.022581
[103,] -133.306452 -112.751613
[104,] -135.600000 -133.306452
[105,] -138.358065 -135.600000
[106,] -109.629032 -138.358065
[107,] -105.996774 -109.629032
[108,] -112.429032 -105.996774
[109,] -134.425806 -112.429032
[110,] -138.458065 -134.425806
[111,] -119.035484 -138.458065
[112,] -97.696774 -119.035484
[113,] -120.822581 -97.696774
[114,] -126.851613 -120.822581
[115,] -127.406452 -126.851613
[116,] -112.600000 -127.406452
[117,] -100.958065 -112.600000
[118,] -56.829032 -100.958065
[119,] -38.796774 -56.829032
[120,] 13.370968 -38.796774
[121,] 68.674194 13.370968
[122,] 94.841935 68.674194
[123,] 124.664516 94.841935
[124,] 122.003226 124.664516
[125,] 88.377419 122.003226
[126,] 98.648387 88.377419
[127,] 80.693548 98.648387
[128,] 42.900000 80.693548
[129,] 27.541935 42.900000
[130,] 8.970968 27.541935
[131,] 34.803226 8.970968
[132,] 34.770968 34.803226
[133,] 26.874194 34.770968
[134,] 9.141935 26.874194
[135,] -25.935484 9.141935
[136,] -28.496774 -25.935484
[137,] -55.922581 -28.496774
[138,] -50.651613 -55.922581
[139,] -45.306452 -50.651613
[140,] -43.400000 -45.306452
[141,] -24.358065 -43.400000
[142,] -5.929032 -24.358065
[143,] -19.896774 -5.929032
[144,] -21.129032 -19.896774
[145,] -54.325806 -21.129032
[146,] -4.258065 -54.325806
[147,] -21.035484 -4.258065
[148,] -23.196774 -21.035484
[149,] -16.722581 -23.196774
[150,] -22.751613 -16.722581
[151,] -8.906452 -22.751613
[152,] -31.400000 -8.906452
[153,] 6.241935 -31.400000
[154,] 27.170968 6.241935
[155,] 75.003226 27.170968
[156,] 100.470968 75.003226
[157,] 122.474194 100.470968
[158,] 121.641935 122.474194
[159,] 106.964516 121.641935
[160,] 105.903226 106.964516
[161,] 97.377419 105.903226
[162,] 84.948387 97.377419
[163,] 63.993548 84.948387
[164,] 40.500000 63.993548
[165,] 38.841935 40.500000
[166,] 24.570968 38.841935
[167,] 32.103226 24.570968
[168,] 29.070968 32.103226
[169,] 5.174194 29.070968
[170,] 11.641935 5.174194
[171,] 4.564516 11.641935
[172,] 34.003226 4.564516
[173,] -12.022581 34.003226
[174,] -28.251613 -12.022581
[175,] 4.193548 -28.251613
[176,] -17.400000 4.193548
[177,] -24.058065 -17.400000
[178,] 3.070968 -24.058065
[179,] 4.003226 3.070968
[180,] 29.670968 4.003226
[181,] 44.074194 29.670968
[182,] 23.541935 44.074194
[183,] 17.564516 23.541935
[184,] 33.703226 17.564516
[185,] 21.477419 33.703226
[186,] 2.848387 21.477419
[187,] -4.506452 2.848387
[188,] -15.900000 -4.506452
[189,] -8.058065 -15.900000
[190,] 16.270968 -8.058065
[191,] 6.803226 16.270968
[192,] 18.770968 6.803226
[193,] 3.174194 18.770968
[194,] 1.841935 3.174194
[195,] 1.364516 1.841935
[196,] -8.396774 1.364516
[197,] 11.377419 -8.396774
[198,] -43.651613 11.377419
[199,] -24.906452 -43.651613
[200,] -36.700000 -24.906452
[201,] -27.658065 -36.700000
[202,] -37.729032 -27.658065
[203,] -31.096774 -37.729032
[204,] -38.929032 -31.096774
[205,] -25.725806 -38.929032
[206,] -50.758065 -25.725806
[207,] -32.535484 -50.758065
[208,] -39.796774 -32.535484
[209,] -28.222581 -39.796774
[210,] -68.251613 -28.222581
[211,] -63.506452 -68.251613
[212,] -78.700000 -63.506452
[213,] -76.558065 -78.700000
[214,] -80.729032 -76.558065
[215,] -93.196774 -80.729032
[216,] -108.629032 -93.196774
[217,] -132.025806 -108.629032
[218,] -121.658065 -132.025806
[219,] -108.735484 -121.658065
[220,] -81.896774 -108.735484
[221,] -74.722581 -81.896774
[222,] -106.151613 -74.722581
[223,] -97.906452 -106.151613
[224,] -112.600000 -97.906452
[225,] -100.958065 -112.600000
[226,] -111.629032 -100.958065
[227,] -105.496774 -111.629032
[228,] -117.129032 -105.496774
[229,] -124.525806 -117.129032
[230,] -125.258065 -124.525806
[231,] -115.335484 -125.258065
[232,] -115.396774 -115.335484
[233,] -71.122581 -115.396774
[234,] -86.251613 -71.122581
[235,] -85.806452 -86.251613
[236,] -73.400000 -85.806452
[237,] -52.258065 -73.400000
[238,] -79.229032 -52.258065
[239,] -99.996774 -79.229032
[240,] -125.629032 -99.996774
[241,] -114.225806 -125.629032
[242,] -127.758065 -114.225806
[243,] -132.635484 -127.758065
[244,] -130.796774 -132.635484
[245,] -72.422581 -130.796774
[246,] -89.451613 -72.422581
[247,] -102.806452 -89.451613
[248,] -102.200000 -102.806452
[249,] -96.458065 -102.200000
[250,] -111.929032 -96.458065
[251,] -130.196774 -111.929032
[252,] -145.529032 -130.196774
[253,] -150.625806 -145.529032
[254,] -145.958065 -150.625806
[255,] -127.535484 -145.958065
[256,] -131.196774 -127.535484
[257,] -94.922581 -131.196774
[258,] -92.951613 -94.922581
[259,] -93.006452 -92.951613
[260,] -67.100000 -93.006452
[261,] -63.458065 -67.100000
[262,] -98.529032 -63.458065
[263,] -109.296774 -98.529032
[264,] -92.429032 -109.296774
[265,] -63.525806 -92.429032
[266,] -47.358065 -63.525806
[267,] -26.535484 -47.358065
[268,] -22.796774 -26.535484
[269,] 32.977419 -22.796774
[270,] 39.848387 32.977419
[271,] 41.993548 39.848387
[272,] 66.300000 41.993548
[273,] 78.441935 66.300000
[274,] 91.170968 78.441935
[275,] 91.603226 91.170968
[276,] 108.370968 91.603226
[277,] 101.274194 108.370968
[278,] 96.841935 101.274194
[279,] 87.664516 96.841935
[280,] 78.203226 87.664516
[281,] 115.077419 78.203226
[282,] 121.848387 115.077419
[283,] 126.093548 121.848387
[284,] 121.100000 126.093548
[285,] 109.541935 121.100000
[286,] 111.970968 109.541935
[287,] 97.503226 111.970968
[288,] 111.670968 97.503226
[289,] 98.274194 111.670968
[290,] 100.841935 98.274194
[291,] 87.964516 100.841935
[292,] 73.203226 87.964516
[293,] 108.677419 73.203226
[294,] 106.148387 108.677419
[295,] 105.693548 106.148387
[296,] 102.900000 105.693548
[297,] 99.541935 102.900000
[298,] 57.070968 99.541935
[299,] 39.603226 57.070968
[300,] 34.470968 39.603226
[301,] 41.574194 34.470968
[302,] 30.541935 41.574194
[303,] 35.664516 30.541935
[304,] 18.703226 35.664516
[305,] 50.777419 18.703226
[306,] 43.848387 50.777419
[307,] 40.793548 43.848387
[308,] 53.600000 40.793548
[309,] 28.841935 53.600000
[310,] 36.070968 28.841935
[311,] 33.803226 36.070968
[312,] 67.770968 33.803226
[313,] 71.074194 67.770968
[314,] 54.841935 71.074194
[315,] 48.364516 54.841935
[316,] 53.203226 48.364516
[317,] 104.077419 53.203226
[318,] 114.848387 104.077419
[319,] 108.493548 114.848387
[320,] 157.300000 108.493548
[321,] 156.941935 157.300000
[322,] 198.970968 156.941935
[323,] 238.603226 198.970968
[324,] 384.970968 238.603226
[325,] 387.974194 384.970968
[326,] 415.241935 387.974194
[327,] 400.264516 415.241935
[328,] 401.103226 400.264516
[329,] 422.977419 401.103226
[330,] 409.748387 422.977419
[331,] 389.593548 409.748387
[332,] 389.300000 389.593548
[333,] 376.941935 389.300000
[334,] 353.570968 376.941935
[335,] 347.503226 353.570968
[336,] 384.370968 347.503226
[337,] 360.374194 384.370968
[338,] 331.841935 360.374194
[339,] 307.264516 331.841935
[340,] 269.203226 307.264516
[341,] 331.577419 269.203226
[342,] 346.548387 331.577419
[343,] 352.193548 346.548387
[344,] 339.700000 352.193548
[345,] 335.841935 339.700000
[346,] 339.970968 335.841935
[347,] 330.203226 339.970968
[348,] 351.770968 330.203226
[349,] 367.974194 351.770968
[350,] 334.941935 367.974194
[351,] 275.064516 334.941935
[352,] 253.903226 275.064516
[353,] 311.377419 253.903226
[354,] 282.948387 311.377419
[355,] 295.693548 282.948387
[356,] 280.800000 295.693548
[357,] 274.641935 280.800000
[358,] 265.070968 274.641935
[359,] 216.003226 265.070968
[360,] 256.670968 216.003226
[361,] 230.974194 256.670968
[362,] 227.241935 230.974194
[363,] 187.064516 227.241935
[364,] 184.503226 187.064516
[365,] 198.677419 184.503226
[366,] 232.648387 198.677419
[367,] 213.093548 232.648387
[368,] 216.800000 213.093548
[369,] 198.541935 216.800000
[370,] 193.370968 198.541935
[371,] 200.503226 193.370968
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -162.225806 -197.929032
2 -156.058065 -162.225806
3 -141.035484 -156.058065
4 -159.796774 -141.035484
5 -193.122581 -159.796774
6 -170.051613 -193.122581
7 -156.206452 -170.051613
8 -156.800000 -156.206452
9 -172.758065 -156.800000
10 -166.229032 -172.758065
11 -151.496774 -166.229032
12 -133.529032 -151.496774
13 -95.525806 -133.529032
14 -82.358065 -95.525806
15 -54.035484 -82.358065
16 -9.596774 -54.035484
17 -37.322581 -9.596774
18 27.648387 -37.322581
19 15.593548 27.648387
20 0.600000 15.593548
21 31.341935 0.600000
22 -12.529032 31.341935
23 -2.996774 -12.529032
24 31.770968 -2.996774
25 36.174194 31.770968
26 10.641935 36.174194
27 -15.235484 10.641935
28 -34.896774 -15.235484
29 -78.822581 -34.896774
30 -79.551613 -78.822581
31 -118.706452 -79.551613
32 -113.900000 -118.706452
33 -141.958065 -113.900000
34 -133.929032 -141.958065
35 -131.096774 -133.929032
36 -168.129032 -131.096774
37 -189.125806 -168.129032
38 -188.358065 -189.125806
39 -187.935484 -188.358065
40 -184.196774 -187.935484
41 -220.722581 -184.196774
42 -203.951613 -220.722581
43 -199.406452 -203.951613
44 -174.300000 -199.406452
45 -172.058065 -174.300000
46 -170.529032 -172.058065
47 -192.396774 -170.529032
48 -207.229032 -192.396774
49 -208.925806 -207.229032
50 -220.458065 -208.925806
51 -198.135484 -220.458065
52 -182.996774 -198.135484
53 -230.722581 -182.996774
54 -202.651613 -230.722581
55 -188.206452 -202.651613
56 -190.100000 -188.206452
57 -199.458065 -190.100000
58 -210.129032 -199.458065
59 -217.496774 -210.129032
60 -219.829032 -217.496774
61 -246.525806 -219.829032
62 -237.858065 -246.525806
63 -205.335484 -237.858065
64 -207.596774 -205.335484
65 -260.722581 -207.596774
66 -240.151613 -260.722581
67 -228.806452 -240.151613
68 -201.000000 -228.806452
69 -190.258065 -201.000000
70 -167.829032 -190.258065
71 -135.596774 -167.829032
72 -76.929032 -135.596774
73 -44.625806 -76.929032
74 -16.958065 -44.625806
75 2.864516 -16.958065
76 4.603226 2.864516
77 -65.822581 4.603226
78 -43.251613 -65.822581
79 -33.006452 -43.251613
80 -19.600000 -33.006452
81 -54.558065 -19.600000
82 -58.029032 -54.558065
83 -71.096774 -58.029032
84 -66.129032 -71.096774
85 -86.025806 -66.129032
86 -90.958065 -86.025806
87 -65.535484 -90.958065
88 -92.196774 -65.535484
89 -144.622581 -92.196774
90 -144.951613 -144.622581
91 -126.406452 -144.951613
92 -129.100000 -126.406452
93 -119.058065 -129.100000
94 -115.929032 -119.058065
95 -111.896774 -115.929032
96 -126.429032 -111.896774
97 -133.725806 -126.429032
98 -111.158065 -133.725806
99 -110.735484 -111.158065
100 -81.296774 -110.735484
101 -116.022581 -81.296774
102 -112.751613 -116.022581
103 -133.306452 -112.751613
104 -135.600000 -133.306452
105 -138.358065 -135.600000
106 -109.629032 -138.358065
107 -105.996774 -109.629032
108 -112.429032 -105.996774
109 -134.425806 -112.429032
110 -138.458065 -134.425806
111 -119.035484 -138.458065
112 -97.696774 -119.035484
113 -120.822581 -97.696774
114 -126.851613 -120.822581
115 -127.406452 -126.851613
116 -112.600000 -127.406452
117 -100.958065 -112.600000
118 -56.829032 -100.958065
119 -38.796774 -56.829032
120 13.370968 -38.796774
121 68.674194 13.370968
122 94.841935 68.674194
123 124.664516 94.841935
124 122.003226 124.664516
125 88.377419 122.003226
126 98.648387 88.377419
127 80.693548 98.648387
128 42.900000 80.693548
129 27.541935 42.900000
130 8.970968 27.541935
131 34.803226 8.970968
132 34.770968 34.803226
133 26.874194 34.770968
134 9.141935 26.874194
135 -25.935484 9.141935
136 -28.496774 -25.935484
137 -55.922581 -28.496774
138 -50.651613 -55.922581
139 -45.306452 -50.651613
140 -43.400000 -45.306452
141 -24.358065 -43.400000
142 -5.929032 -24.358065
143 -19.896774 -5.929032
144 -21.129032 -19.896774
145 -54.325806 -21.129032
146 -4.258065 -54.325806
147 -21.035484 -4.258065
148 -23.196774 -21.035484
149 -16.722581 -23.196774
150 -22.751613 -16.722581
151 -8.906452 -22.751613
152 -31.400000 -8.906452
153 6.241935 -31.400000
154 27.170968 6.241935
155 75.003226 27.170968
156 100.470968 75.003226
157 122.474194 100.470968
158 121.641935 122.474194
159 106.964516 121.641935
160 105.903226 106.964516
161 97.377419 105.903226
162 84.948387 97.377419
163 63.993548 84.948387
164 40.500000 63.993548
165 38.841935 40.500000
166 24.570968 38.841935
167 32.103226 24.570968
168 29.070968 32.103226
169 5.174194 29.070968
170 11.641935 5.174194
171 4.564516 11.641935
172 34.003226 4.564516
173 -12.022581 34.003226
174 -28.251613 -12.022581
175 4.193548 -28.251613
176 -17.400000 4.193548
177 -24.058065 -17.400000
178 3.070968 -24.058065
179 4.003226 3.070968
180 29.670968 4.003226
181 44.074194 29.670968
182 23.541935 44.074194
183 17.564516 23.541935
184 33.703226 17.564516
185 21.477419 33.703226
186 2.848387 21.477419
187 -4.506452 2.848387
188 -15.900000 -4.506452
189 -8.058065 -15.900000
190 16.270968 -8.058065
191 6.803226 16.270968
192 18.770968 6.803226
193 3.174194 18.770968
194 1.841935 3.174194
195 1.364516 1.841935
196 -8.396774 1.364516
197 11.377419 -8.396774
198 -43.651613 11.377419
199 -24.906452 -43.651613
200 -36.700000 -24.906452
201 -27.658065 -36.700000
202 -37.729032 -27.658065
203 -31.096774 -37.729032
204 -38.929032 -31.096774
205 -25.725806 -38.929032
206 -50.758065 -25.725806
207 -32.535484 -50.758065
208 -39.796774 -32.535484
209 -28.222581 -39.796774
210 -68.251613 -28.222581
211 -63.506452 -68.251613
212 -78.700000 -63.506452
213 -76.558065 -78.700000
214 -80.729032 -76.558065
215 -93.196774 -80.729032
216 -108.629032 -93.196774
217 -132.025806 -108.629032
218 -121.658065 -132.025806
219 -108.735484 -121.658065
220 -81.896774 -108.735484
221 -74.722581 -81.896774
222 -106.151613 -74.722581
223 -97.906452 -106.151613
224 -112.600000 -97.906452
225 -100.958065 -112.600000
226 -111.629032 -100.958065
227 -105.496774 -111.629032
228 -117.129032 -105.496774
229 -124.525806 -117.129032
230 -125.258065 -124.525806
231 -115.335484 -125.258065
232 -115.396774 -115.335484
233 -71.122581 -115.396774
234 -86.251613 -71.122581
235 -85.806452 -86.251613
236 -73.400000 -85.806452
237 -52.258065 -73.400000
238 -79.229032 -52.258065
239 -99.996774 -79.229032
240 -125.629032 -99.996774
241 -114.225806 -125.629032
242 -127.758065 -114.225806
243 -132.635484 -127.758065
244 -130.796774 -132.635484
245 -72.422581 -130.796774
246 -89.451613 -72.422581
247 -102.806452 -89.451613
248 -102.200000 -102.806452
249 -96.458065 -102.200000
250 -111.929032 -96.458065
251 -130.196774 -111.929032
252 -145.529032 -130.196774
253 -150.625806 -145.529032
254 -145.958065 -150.625806
255 -127.535484 -145.958065
256 -131.196774 -127.535484
257 -94.922581 -131.196774
258 -92.951613 -94.922581
259 -93.006452 -92.951613
260 -67.100000 -93.006452
261 -63.458065 -67.100000
262 -98.529032 -63.458065
263 -109.296774 -98.529032
264 -92.429032 -109.296774
265 -63.525806 -92.429032
266 -47.358065 -63.525806
267 -26.535484 -47.358065
268 -22.796774 -26.535484
269 32.977419 -22.796774
270 39.848387 32.977419
271 41.993548 39.848387
272 66.300000 41.993548
273 78.441935 66.300000
274 91.170968 78.441935
275 91.603226 91.170968
276 108.370968 91.603226
277 101.274194 108.370968
278 96.841935 101.274194
279 87.664516 96.841935
280 78.203226 87.664516
281 115.077419 78.203226
282 121.848387 115.077419
283 126.093548 121.848387
284 121.100000 126.093548
285 109.541935 121.100000
286 111.970968 109.541935
287 97.503226 111.970968
288 111.670968 97.503226
289 98.274194 111.670968
290 100.841935 98.274194
291 87.964516 100.841935
292 73.203226 87.964516
293 108.677419 73.203226
294 106.148387 108.677419
295 105.693548 106.148387
296 102.900000 105.693548
297 99.541935 102.900000
298 57.070968 99.541935
299 39.603226 57.070968
300 34.470968 39.603226
301 41.574194 34.470968
302 30.541935 41.574194
303 35.664516 30.541935
304 18.703226 35.664516
305 50.777419 18.703226
306 43.848387 50.777419
307 40.793548 43.848387
308 53.600000 40.793548
309 28.841935 53.600000
310 36.070968 28.841935
311 33.803226 36.070968
312 67.770968 33.803226
313 71.074194 67.770968
314 54.841935 71.074194
315 48.364516 54.841935
316 53.203226 48.364516
317 104.077419 53.203226
318 114.848387 104.077419
319 108.493548 114.848387
320 157.300000 108.493548
321 156.941935 157.300000
322 198.970968 156.941935
323 238.603226 198.970968
324 384.970968 238.603226
325 387.974194 384.970968
326 415.241935 387.974194
327 400.264516 415.241935
328 401.103226 400.264516
329 422.977419 401.103226
330 409.748387 422.977419
331 389.593548 409.748387
332 389.300000 389.593548
333 376.941935 389.300000
334 353.570968 376.941935
335 347.503226 353.570968
336 384.370968 347.503226
337 360.374194 384.370968
338 331.841935 360.374194
339 307.264516 331.841935
340 269.203226 307.264516
341 331.577419 269.203226
342 346.548387 331.577419
343 352.193548 346.548387
344 339.700000 352.193548
345 335.841935 339.700000
346 339.970968 335.841935
347 330.203226 339.970968
348 351.770968 330.203226
349 367.974194 351.770968
350 334.941935 367.974194
351 275.064516 334.941935
352 253.903226 275.064516
353 311.377419 253.903226
354 282.948387 311.377419
355 295.693548 282.948387
356 280.800000 295.693548
357 274.641935 280.800000
358 265.070968 274.641935
359 216.003226 265.070968
360 256.670968 216.003226
361 230.974194 256.670968
362 227.241935 230.974194
363 187.064516 227.241935
364 184.503226 187.064516
365 198.677419 184.503226
366 232.648387 198.677419
367 213.093548 232.648387
368 216.800000 213.093548
369 198.541935 216.800000
370 193.370968 198.541935
371 200.503226 193.370968
> 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/733331322470618.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/89i0m1322470618.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/9qkwb1322470618.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
hat values (leverages) are all = 0.03225806
and there are no factor predictors; no plot no. 5
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/wessaorg/rcomp/tmp/106atw1322470618.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11wgds1322470618.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/126rwh1322470618.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/13815q1322470618.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/149z5c1322470618.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/1528gb1322470618.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/16qgxh1322470618.tab")
+ }
>
> try(system("convert tmp/1c7ja1322470618.ps tmp/1c7ja1322470618.png",intern=TRUE))
character(0)
> try(system("convert tmp/2kmdi1322470618.ps tmp/2kmdi1322470618.png",intern=TRUE))
character(0)
> try(system("convert tmp/3pmmh1322470618.ps tmp/3pmmh1322470618.png",intern=TRUE))
character(0)
> try(system("convert tmp/4vqe31322470618.ps tmp/4vqe31322470618.png",intern=TRUE))
character(0)
> try(system("convert tmp/5bg5n1322470618.ps tmp/5bg5n1322470618.png",intern=TRUE))
character(0)
> try(system("convert tmp/6h7ue1322470618.ps tmp/6h7ue1322470618.png",intern=TRUE))
character(0)
> try(system("convert tmp/733331322470618.ps tmp/733331322470618.png",intern=TRUE))
character(0)
> try(system("convert tmp/89i0m1322470618.ps tmp/89i0m1322470618.png",intern=TRUE))
character(0)
> try(system("convert tmp/9qkwb1322470618.ps tmp/9qkwb1322470618.png",intern=TRUE))
character(0)
> try(system("convert tmp/106atw1322470618.ps tmp/106atw1322470618.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
9.877 0.568 10.558