R version 2.12.0 (2010-10-15)
Copyright (C) 2010 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.
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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(-45.6
+ ,16.1
+ ,23.9
+ ,39.3
+ ,-39.4
+ ,-0.3
+ ,17.3
+ ,17.7
+ ,31.4
+ ,-28.6
+ ,-17.2
+ ,-79
+ ,-47.9
+ ,9.1
+ ,10.6
+ ,-23.9
+ ,-45
+ ,-42.2
+ ,43.2
+ ,32.1
+ ,-15.3
+ ,21.8
+ ,-12
+ ,-95.8
+ ,-14.3
+ ,47.8
+ ,64.8
+ ,40.2
+ ,-28.8
+ ,23.5
+ ,70.3
+ ,12.3
+ ,43.5
+ ,-30.1
+ ,-5.3
+ ,-24
+ ,11.1
+ ,21.5
+ ,38.5
+ ,16.8
+ ,-36.2
+ ,6
+ ,26.6
+ ,-8
+ ,13.2
+ ,-23.6
+ ,19.4
+ ,-46.2
+ ,-8.2
+ ,33.8
+ ,16.6
+ ,5.4
+ ,-25
+ ,-5.3
+ ,16.7
+ ,19
+ ,24.8
+ ,-11.4
+ ,4.9
+ ,-58.7
+ ,16.8
+ ,13.6
+ ,6.4
+ ,22.8
+ ,-19.6
+ ,2.2
+ ,19.8
+ ,-10.7
+ ,4.7
+ ,-44.5
+ ,-34.7
+ ,-119.7
+ ,-42.2
+ ,-5.4
+ ,19.1
+ ,18.8
+ ,-2.3
+ ,0.2
+ ,20.9
+ ,3.7
+ ,50.4
+ ,-18.6
+ ,10.6
+ ,-66
+ ,10
+ ,27.2
+ ,13.5
+ ,47.2
+ ,-20.3
+ ,23.1
+ ,12.6
+ ,19.8
+ ,5.4
+ ,-25.2
+ ,-6.5
+ ,-46.5
+ ,-2.6
+ ,-0.3
+ ,38.5
+ ,-8.9
+ ,-38
+ ,19.5
+ ,51.7
+ ,19.4
+ ,18.2
+ ,-50.8
+ ,-6.1
+ ,-54.6
+ ,12.1
+ ,26.3
+ ,19.5
+ ,-0.8
+ ,-49.6
+ ,28.8
+ ,31.7
+ ,2.3
+ ,3.8
+ ,-66.2
+ ,-20.5
+ ,-113.2
+ ,-65.2
+ ,-3.9
+ ,9.1
+ ,23.2
+ ,-39.1
+ ,12.5
+ ,49.1
+ ,54.9
+ ,30.8
+ ,-3.5
+ ,-28.3
+ ,-61
+ ,-2
+ ,40
+ ,74
+ ,23.1
+ ,-45.3
+ ,17.5
+ ,25.8
+ ,15.2
+ ,-3.6
+ ,-40.5
+ ,11.5
+ ,-59.8
+ ,23.3
+ ,-27.8
+ ,55.7
+ ,22.7
+ ,-79.2
+ ,28.8
+ ,17.3
+ ,39.6
+ ,-22.2
+ ,-43
+ ,-50.3
+ ,-86.5
+ ,-31.9
+ ,23.1
+ ,53.6
+ ,21.6
+ ,-64.2
+ ,35.2
+ ,52.1
+ ,40.6
+ ,17.1
+ ,-7.8
+ ,-10
+ ,-58
+ ,14
+ ,15.8
+ ,46
+ ,-8.9
+ ,-26.7
+ ,39
+ ,-1.3
+ ,38.7
+ ,22.1
+ ,-49.2
+ ,-3.4
+ ,-86.7
+ ,-24.3
+ ,42.8
+ ,44.9
+ ,4.4
+ ,-60.5
+ ,41.4
+ ,38.5
+ ,28.5
+ ,7.6
+ ,-46.4
+ ,7
+ ,-73
+ ,5.7
+ ,23.6
+ ,39.4
+ ,30.3
+ ,-92.5
+ ,77.8
+ ,12.4
+ ,28.9
+ ,6.4
+ ,-12
+ ,-9.1
+ ,-53.2
+ ,-23.1
+ ,47.3
+ ,20.7
+ ,27.8
+ ,-84.3
+ ,62.8
+ ,26.4
+ ,32.3
+ ,13.3
+ ,-17.9
+ ,10
+ ,-45.6
+ ,13.5
+ ,11.9
+ ,26
+ ,-6.3
+ ,-79.9
+ ,54.2
+ ,22.9
+ ,31.8
+ ,3.8
+ ,-11.4
+ ,-8.6
+ ,-49.4
+ ,-2.5
+ ,23
+ ,29
+ ,20.6
+ ,-117
+ ,37.9
+ ,30.7
+ ,4.7
+ ,-5.7
+ ,4.9
+ ,18.3
+ ,-35.4
+ ,-21.3
+ ,35.8
+ ,43.8
+ ,18.7
+ ,-131.1
+ ,39.8
+ ,44.5
+ ,16.5
+ ,9.7
+ ,-6.6
+ ,15.8
+ ,-45.7
+ ,-4.8
+ ,17.6
+ ,20.5
+ ,24.2
+ ,-109
+ ,20.8
+ ,31.2
+ ,-8.8
+ ,11.8
+ ,13
+ ,8.3
+ ,-77.9
+ ,-38.8
+ ,6.1
+ ,18.1
+ ,16.8
+ ,-128.5
+ ,15.9
+ ,29
+ ,-7.2
+ ,3.3
+ ,-34.8
+ ,-2.9
+ ,-77.8
+ ,-2.8
+ ,26.7
+ ,48.1
+ ,30
+ ,-109.6
+ ,16
+ ,26.9
+ ,22.1
+ ,27
+ ,-24.5
+ ,12
+ ,-75.2
+ ,3.5
+ ,19.7
+ ,51.8
+ ,35.3
+ ,-108.2
+ ,25.3
+ ,31.6
+ ,19.9
+ ,18.8
+ ,20.4
+ ,15
+ ,-55.9
+ ,-17
+ ,33.3
+ ,33.8
+ ,37.5
+ ,-104.8
+ ,29.7
+ ,34.2
+ ,4.3
+ ,40.2
+ ,-29.3
+ ,-0.2
+ ,-95
+ ,-13.2
+ ,38.5
+ ,45.4
+ ,15.7
+ ,-123.6
+ ,12
+ ,37.5
+ ,-31.7
+ ,15.8
+ ,-64.1
+ ,-42.1
+ ,-207.4
+ ,-12.9
+ ,-5
+ ,53.9
+ ,19.7
+ ,-94.6
+ ,36
+ ,51.3
+ ,17.4
+ ,27.8
+ ,1.3
+ ,3.6
+ ,-97.9
+ ,14.1
+ ,50.8
+ ,63.5
+ ,58.6
+ ,-135.1
+ ,7.8
+ ,25.5
+ ,29.6
+ ,19.3
+ ,-26.2
+ ,7.3
+ ,-82.6
+ ,-26.1
+ ,55.3
+ ,98.8
+ ,41.7
+ ,-130.2
+ ,51.2
+ ,18.4
+ ,32
+ ,21.6
+ ,-12.5
+ ,46.6
+ ,-101.7
+ ,15.8
+ ,26
+ ,79.1
+ ,23.1
+ ,-86.9
+ ,-11.2
+ ,50.7
+ ,13.4
+ ,33.7
+ ,-16.9
+ ,-9.6)
+ ,dim=c(1
+ ,371)
+ ,dimnames=list(c('y')
+ ,1:371))
> y <- array(NA,dim=c(1,371),dimnames=list(c('y'),1:371))
> 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
y M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11
1 -45.6 1 0 0 0 0 0 0 0 0 0 0
2 16.1 0 1 0 0 0 0 0 0 0 0 0
3 23.9 0 0 1 0 0 0 0 0 0 0 0
4 39.3 0 0 0 1 0 0 0 0 0 0 0
5 -39.4 0 0 0 0 1 0 0 0 0 0 0
6 -0.3 0 0 0 0 0 1 0 0 0 0 0
7 17.3 0 0 0 0 0 0 1 0 0 0 0
8 17.7 0 0 0 0 0 0 0 1 0 0 0
9 31.4 0 0 0 0 0 0 0 0 1 0 0
10 -28.6 0 0 0 0 0 0 0 0 0 1 0
11 -17.2 0 0 0 0 0 0 0 0 0 0 1
12 -79.0 0 0 0 0 0 0 0 0 0 0 0
13 -47.9 1 0 0 0 0 0 0 0 0 0 0
14 9.1 0 1 0 0 0 0 0 0 0 0 0
15 10.6 0 0 1 0 0 0 0 0 0 0 0
16 -23.9 0 0 0 1 0 0 0 0 0 0 0
17 -45.0 0 0 0 0 1 0 0 0 0 0 0
18 -42.2 0 0 0 0 0 1 0 0 0 0 0
19 43.2 0 0 0 0 0 0 1 0 0 0 0
20 32.1 0 0 0 0 0 0 0 1 0 0 0
21 -15.3 0 0 0 0 0 0 0 0 1 0 0
22 21.8 0 0 0 0 0 0 0 0 0 1 0
23 -12.0 0 0 0 0 0 0 0 0 0 0 1
24 -95.8 0 0 0 0 0 0 0 0 0 0 0
25 -14.3 1 0 0 0 0 0 0 0 0 0 0
26 47.8 0 1 0 0 0 0 0 0 0 0 0
27 64.8 0 0 1 0 0 0 0 0 0 0 0
28 40.2 0 0 0 1 0 0 0 0 0 0 0
29 -28.8 0 0 0 0 1 0 0 0 0 0 0
30 23.5 0 0 0 0 0 1 0 0 0 0 0
31 70.3 0 0 0 0 0 0 1 0 0 0 0
32 12.3 0 0 0 0 0 0 0 1 0 0 0
33 43.5 0 0 0 0 0 0 0 0 1 0 0
34 -30.1 0 0 0 0 0 0 0 0 0 1 0
35 -5.3 0 0 0 0 0 0 0 0 0 0 1
36 -24.0 0 0 0 0 0 0 0 0 0 0 0
37 11.1 1 0 0 0 0 0 0 0 0 0 0
38 21.5 0 1 0 0 0 0 0 0 0 0 0
39 38.5 0 0 1 0 0 0 0 0 0 0 0
40 16.8 0 0 0 1 0 0 0 0 0 0 0
41 -36.2 0 0 0 0 1 0 0 0 0 0 0
42 6.0 0 0 0 0 0 1 0 0 0 0 0
43 26.6 0 0 0 0 0 0 1 0 0 0 0
44 -8.0 0 0 0 0 0 0 0 1 0 0 0
45 13.2 0 0 0 0 0 0 0 0 1 0 0
46 -23.6 0 0 0 0 0 0 0 0 0 1 0
47 19.4 0 0 0 0 0 0 0 0 0 0 1
48 -46.2 0 0 0 0 0 0 0 0 0 0 0
49 -8.2 1 0 0 0 0 0 0 0 0 0 0
50 33.8 0 1 0 0 0 0 0 0 0 0 0
51 16.6 0 0 1 0 0 0 0 0 0 0 0
52 5.4 0 0 0 1 0 0 0 0 0 0 0
53 -25.0 0 0 0 0 1 0 0 0 0 0 0
54 -5.3 0 0 0 0 0 1 0 0 0 0 0
55 16.7 0 0 0 0 0 0 1 0 0 0 0
56 19.0 0 0 0 0 0 0 0 1 0 0 0
57 24.8 0 0 0 0 0 0 0 0 1 0 0
58 -11.4 0 0 0 0 0 0 0 0 0 1 0
59 4.9 0 0 0 0 0 0 0 0 0 0 1
60 -58.7 0 0 0 0 0 0 0 0 0 0 0
61 16.8 1 0 0 0 0 0 0 0 0 0 0
62 13.6 0 1 0 0 0 0 0 0 0 0 0
63 6.4 0 0 1 0 0 0 0 0 0 0 0
64 22.8 0 0 0 1 0 0 0 0 0 0 0
65 -19.6 0 0 0 0 1 0 0 0 0 0 0
66 2.2 0 0 0 0 0 1 0 0 0 0 0
67 19.8 0 0 0 0 0 0 1 0 0 0 0
68 -10.7 0 0 0 0 0 0 0 1 0 0 0
69 4.7 0 0 0 0 0 0 0 0 1 0 0
70 -44.5 0 0 0 0 0 0 0 0 0 1 0
71 -34.7 0 0 0 0 0 0 0 0 0 0 1
72 -119.7 0 0 0 0 0 0 0 0 0 0 0
73 -42.2 1 0 0 0 0 0 0 0 0 0 0
74 -5.4 0 1 0 0 0 0 0 0 0 0 0
75 19.1 0 0 1 0 0 0 0 0 0 0 0
76 18.8 0 0 0 1 0 0 0 0 0 0 0
77 -2.3 0 0 0 0 1 0 0 0 0 0 0
78 0.2 0 0 0 0 0 1 0 0 0 0 0
79 20.9 0 0 0 0 0 0 1 0 0 0 0
80 3.7 0 0 0 0 0 0 0 1 0 0 0
81 50.4 0 0 0 0 0 0 0 0 1 0 0
82 -18.6 0 0 0 0 0 0 0 0 0 1 0
83 10.6 0 0 0 0 0 0 0 0 0 0 1
84 -66.0 0 0 0 0 0 0 0 0 0 0 0
85 10.0 1 0 0 0 0 0 0 0 0 0 0
86 27.2 0 1 0 0 0 0 0 0 0 0 0
87 13.5 0 0 1 0 0 0 0 0 0 0 0
88 47.2 0 0 0 1 0 0 0 0 0 0 0
89 -20.3 0 0 0 0 1 0 0 0 0 0 0
90 23.1 0 0 0 0 0 1 0 0 0 0 0
91 12.6 0 0 0 0 0 0 1 0 0 0 0
92 19.8 0 0 0 0 0 0 0 1 0 0 0
93 5.4 0 0 0 0 0 0 0 0 1 0 0
94 -25.2 0 0 0 0 0 0 0 0 0 1 0
95 -6.5 0 0 0 0 0 0 0 0 0 0 1
96 -46.5 0 0 0 0 0 0 0 0 0 0 0
97 -2.6 1 0 0 0 0 0 0 0 0 0 0
98 -0.3 0 1 0 0 0 0 0 0 0 0 0
99 38.5 0 0 1 0 0 0 0 0 0 0 0
100 -8.9 0 0 0 1 0 0 0 0 0 0 0
101 -38.0 0 0 0 0 1 0 0 0 0 0 0
102 19.5 0 0 0 0 0 1 0 0 0 0 0
103 51.7 0 0 0 0 0 0 1 0 0 0 0
104 19.4 0 0 0 0 0 0 0 1 0 0 0
105 18.2 0 0 0 0 0 0 0 0 1 0 0
106 -50.8 0 0 0 0 0 0 0 0 0 1 0
107 -6.1 0 0 0 0 0 0 0 0 0 0 1
108 -54.6 0 0 0 0 0 0 0 0 0 0 0
109 12.1 1 0 0 0 0 0 0 0 0 0 0
110 26.3 0 1 0 0 0 0 0 0 0 0 0
111 19.5 0 0 1 0 0 0 0 0 0 0 0
112 -0.8 0 0 0 1 0 0 0 0 0 0 0
113 -49.6 0 0 0 0 1 0 0 0 0 0 0
114 28.8 0 0 0 0 0 1 0 0 0 0 0
115 31.7 0 0 0 0 0 0 1 0 0 0 0
116 2.3 0 0 0 0 0 0 0 1 0 0 0
117 3.8 0 0 0 0 0 0 0 0 1 0 0
118 -66.2 0 0 0 0 0 0 0 0 0 1 0
119 -20.5 0 0 0 0 0 0 0 0 0 0 1
120 -113.2 0 0 0 0 0 0 0 0 0 0 0
121 -65.2 1 0 0 0 0 0 0 0 0 0 0
122 -3.9 0 1 0 0 0 0 0 0 0 0 0
123 9.1 0 0 1 0 0 0 0 0 0 0 0
124 23.2 0 0 0 1 0 0 0 0 0 0 0
125 -39.1 0 0 0 0 1 0 0 0 0 0 0
126 12.5 0 0 0 0 0 1 0 0 0 0 0
127 49.1 0 0 0 0 0 0 1 0 0 0 0
128 54.9 0 0 0 0 0 0 0 1 0 0 0
129 30.8 0 0 0 0 0 0 0 0 1 0 0
130 -3.5 0 0 0 0 0 0 0 0 0 1 0
131 -28.3 0 0 0 0 0 0 0 0 0 0 1
132 -61.0 0 0 0 0 0 0 0 0 0 0 0
133 -2.0 1 0 0 0 0 0 0 0 0 0 0
134 40.0 0 1 0 0 0 0 0 0 0 0 0
135 74.0 0 0 1 0 0 0 0 0 0 0 0
136 23.1 0 0 0 1 0 0 0 0 0 0 0
137 -45.3 0 0 0 0 1 0 0 0 0 0 0
138 17.5 0 0 0 0 0 1 0 0 0 0 0
139 25.8 0 0 0 0 0 0 1 0 0 0 0
140 15.2 0 0 0 0 0 0 0 1 0 0 0
141 -3.6 0 0 0 0 0 0 0 0 1 0 0
142 -40.5 0 0 0 0 0 0 0 0 0 1 0
143 11.5 0 0 0 0 0 0 0 0 0 0 1
144 -59.8 0 0 0 0 0 0 0 0 0 0 0
145 23.3 1 0 0 0 0 0 0 0 0 0 0
146 -27.8 0 1 0 0 0 0 0 0 0 0 0
147 55.7 0 0 1 0 0 0 0 0 0 0 0
148 22.7 0 0 0 1 0 0 0 0 0 0 0
149 -79.2 0 0 0 0 1 0 0 0 0 0 0
150 28.8 0 0 0 0 0 1 0 0 0 0 0
151 17.3 0 0 0 0 0 0 1 0 0 0 0
152 39.6 0 0 0 0 0 0 0 1 0 0 0
153 -22.2 0 0 0 0 0 0 0 0 1 0 0
154 -43.0 0 0 0 0 0 0 0 0 0 1 0
155 -50.3 0 0 0 0 0 0 0 0 0 0 1
156 -86.5 0 0 0 0 0 0 0 0 0 0 0
157 -31.9 1 0 0 0 0 0 0 0 0 0 0
158 23.1 0 1 0 0 0 0 0 0 0 0 0
159 53.6 0 0 1 0 0 0 0 0 0 0 0
160 21.6 0 0 0 1 0 0 0 0 0 0 0
161 -64.2 0 0 0 0 1 0 0 0 0 0 0
162 35.2 0 0 0 0 0 1 0 0 0 0 0
163 52.1 0 0 0 0 0 0 1 0 0 0 0
164 40.6 0 0 0 0 0 0 0 1 0 0 0
165 17.1 0 0 0 0 0 0 0 0 1 0 0
166 -7.8 0 0 0 0 0 0 0 0 0 1 0
167 -10.0 0 0 0 0 0 0 0 0 0 0 1
168 -58.0 0 0 0 0 0 0 0 0 0 0 0
169 14.0 1 0 0 0 0 0 0 0 0 0 0
170 15.8 0 1 0 0 0 0 0 0 0 0 0
171 46.0 0 0 1 0 0 0 0 0 0 0 0
172 -8.9 0 0 0 1 0 0 0 0 0 0 0
173 -26.7 0 0 0 0 1 0 0 0 0 0 0
174 39.0 0 0 0 0 0 1 0 0 0 0 0
175 -1.3 0 0 0 0 0 0 1 0 0 0 0
176 38.7 0 0 0 0 0 0 0 1 0 0 0
177 22.1 0 0 0 0 0 0 0 0 1 0 0
178 -49.2 0 0 0 0 0 0 0 0 0 1 0
179 -3.4 0 0 0 0 0 0 0 0 0 0 1
180 -86.7 0 0 0 0 0 0 0 0 0 0 0
181 -24.3 1 0 0 0 0 0 0 0 0 0 0
182 42.8 0 1 0 0 0 0 0 0 0 0 0
183 44.9 0 0 1 0 0 0 0 0 0 0 0
184 4.4 0 0 0 1 0 0 0 0 0 0 0
185 -60.5 0 0 0 0 1 0 0 0 0 0 0
186 41.4 0 0 0 0 0 1 0 0 0 0 0
187 38.5 0 0 0 0 0 0 1 0 0 0 0
188 28.5 0 0 0 0 0 0 0 1 0 0 0
189 7.6 0 0 0 0 0 0 0 0 1 0 0
190 -46.4 0 0 0 0 0 0 0 0 0 1 0
191 7.0 0 0 0 0 0 0 0 0 0 0 1
192 -73.0 0 0 0 0 0 0 0 0 0 0 0
193 5.7 1 0 0 0 0 0 0 0 0 0 0
194 23.6 0 1 0 0 0 0 0 0 0 0 0
195 39.4 0 0 1 0 0 0 0 0 0 0 0
196 30.3 0 0 0 1 0 0 0 0 0 0 0
197 -92.5 0 0 0 0 1 0 0 0 0 0 0
198 77.8 0 0 0 0 0 1 0 0 0 0 0
199 12.4 0 0 0 0 0 0 1 0 0 0 0
200 28.9 0 0 0 0 0 0 0 1 0 0 0
201 6.4 0 0 0 0 0 0 0 0 1 0 0
202 -12.0 0 0 0 0 0 0 0 0 0 1 0
203 -9.1 0 0 0 0 0 0 0 0 0 0 1
204 -53.2 0 0 0 0 0 0 0 0 0 0 0
205 -23.1 1 0 0 0 0 0 0 0 0 0 0
206 47.3 0 1 0 0 0 0 0 0 0 0 0
207 20.7 0 0 1 0 0 0 0 0 0 0 0
208 27.8 0 0 0 1 0 0 0 0 0 0 0
209 -84.3 0 0 0 0 1 0 0 0 0 0 0
210 62.8 0 0 0 0 0 1 0 0 0 0 0
211 26.4 0 0 0 0 0 0 1 0 0 0 0
212 32.3 0 0 0 0 0 0 0 1 0 0 0
213 13.3 0 0 0 0 0 0 0 0 1 0 0
214 -17.9 0 0 0 0 0 0 0 0 0 1 0
215 10.0 0 0 0 0 0 0 0 0 0 0 1
216 -45.6 0 0 0 0 0 0 0 0 0 0 0
217 13.5 1 0 0 0 0 0 0 0 0 0 0
218 11.9 0 1 0 0 0 0 0 0 0 0 0
219 26.0 0 0 1 0 0 0 0 0 0 0 0
220 -6.3 0 0 0 1 0 0 0 0 0 0 0
221 -79.9 0 0 0 0 1 0 0 0 0 0 0
222 54.2 0 0 0 0 0 1 0 0 0 0 0
223 22.9 0 0 0 0 0 0 1 0 0 0 0
224 31.8 0 0 0 0 0 0 0 1 0 0 0
225 3.8 0 0 0 0 0 0 0 0 1 0 0
226 -11.4 0 0 0 0 0 0 0 0 0 1 0
227 -8.6 0 0 0 0 0 0 0 0 0 0 1
228 -49.4 0 0 0 0 0 0 0 0 0 0 0
229 -2.5 1 0 0 0 0 0 0 0 0 0 0
230 23.0 0 1 0 0 0 0 0 0 0 0 0
231 29.0 0 0 1 0 0 0 0 0 0 0 0
232 20.6 0 0 0 1 0 0 0 0 0 0 0
233 -117.0 0 0 0 0 1 0 0 0 0 0 0
234 37.9 0 0 0 0 0 1 0 0 0 0 0
235 30.7 0 0 0 0 0 0 1 0 0 0 0
236 4.7 0 0 0 0 0 0 0 1 0 0 0
237 -5.7 0 0 0 0 0 0 0 0 1 0 0
238 4.9 0 0 0 0 0 0 0 0 0 1 0
239 18.3 0 0 0 0 0 0 0 0 0 0 1
240 -35.4 0 0 0 0 0 0 0 0 0 0 0
241 -21.3 1 0 0 0 0 0 0 0 0 0 0
242 35.8 0 1 0 0 0 0 0 0 0 0 0
243 43.8 0 0 1 0 0 0 0 0 0 0 0
244 18.7 0 0 0 1 0 0 0 0 0 0 0
245 -131.1 0 0 0 0 1 0 0 0 0 0 0
246 39.8 0 0 0 0 0 1 0 0 0 0 0
247 44.5 0 0 0 0 0 0 1 0 0 0 0
248 16.5 0 0 0 0 0 0 0 1 0 0 0
249 9.7 0 0 0 0 0 0 0 0 1 0 0
250 -6.6 0 0 0 0 0 0 0 0 0 1 0
251 15.8 0 0 0 0 0 0 0 0 0 0 1
252 -45.7 0 0 0 0 0 0 0 0 0 0 0
253 -4.8 1 0 0 0 0 0 0 0 0 0 0
254 17.6 0 1 0 0 0 0 0 0 0 0 0
255 20.5 0 0 1 0 0 0 0 0 0 0 0
256 24.2 0 0 0 1 0 0 0 0 0 0 0
257 -109.0 0 0 0 0 1 0 0 0 0 0 0
258 20.8 0 0 0 0 0 1 0 0 0 0 0
259 31.2 0 0 0 0 0 0 1 0 0 0 0
260 -8.8 0 0 0 0 0 0 0 1 0 0 0
261 11.8 0 0 0 0 0 0 0 0 1 0 0
262 13.0 0 0 0 0 0 0 0 0 0 1 0
263 8.3 0 0 0 0 0 0 0 0 0 0 1
264 -77.9 0 0 0 0 0 0 0 0 0 0 0
265 -38.8 1 0 0 0 0 0 0 0 0 0 0
266 6.1 0 1 0 0 0 0 0 0 0 0 0
267 18.1 0 0 1 0 0 0 0 0 0 0 0
268 16.8 0 0 0 1 0 0 0 0 0 0 0
269 -128.5 0 0 0 0 1 0 0 0 0 0 0
270 15.9 0 0 0 0 0 1 0 0 0 0 0
271 29.0 0 0 0 0 0 0 1 0 0 0 0
272 -7.2 0 0 0 0 0 0 0 1 0 0 0
273 3.3 0 0 0 0 0 0 0 0 1 0 0
274 -34.8 0 0 0 0 0 0 0 0 0 1 0
275 -2.9 0 0 0 0 0 0 0 0 0 0 1
276 -77.8 0 0 0 0 0 0 0 0 0 0 0
277 -2.8 1 0 0 0 0 0 0 0 0 0 0
278 26.7 0 1 0 0 0 0 0 0 0 0 0
279 48.1 0 0 1 0 0 0 0 0 0 0 0
280 30.0 0 0 0 1 0 0 0 0 0 0 0
281 -109.6 0 0 0 0 1 0 0 0 0 0 0
282 16.0 0 0 0 0 0 1 0 0 0 0 0
283 26.9 0 0 0 0 0 0 1 0 0 0 0
284 22.1 0 0 0 0 0 0 0 1 0 0 0
285 27.0 0 0 0 0 0 0 0 0 1 0 0
286 -24.5 0 0 0 0 0 0 0 0 0 1 0
287 12.0 0 0 0 0 0 0 0 0 0 0 1
288 -75.2 0 0 0 0 0 0 0 0 0 0 0
289 3.5 1 0 0 0 0 0 0 0 0 0 0
290 19.7 0 1 0 0 0 0 0 0 0 0 0
291 51.8 0 0 1 0 0 0 0 0 0 0 0
292 35.3 0 0 0 1 0 0 0 0 0 0 0
293 -108.2 0 0 0 0 1 0 0 0 0 0 0
294 25.3 0 0 0 0 0 1 0 0 0 0 0
295 31.6 0 0 0 0 0 0 1 0 0 0 0
296 19.9 0 0 0 0 0 0 0 1 0 0 0
297 18.8 0 0 0 0 0 0 0 0 1 0 0
298 20.4 0 0 0 0 0 0 0 0 0 1 0
299 15.0 0 0 0 0 0 0 0 0 0 0 1
300 -55.9 0 0 0 0 0 0 0 0 0 0 0
301 -17.0 1 0 0 0 0 0 0 0 0 0 0
302 33.3 0 1 0 0 0 0 0 0 0 0 0
303 33.8 0 0 1 0 0 0 0 0 0 0 0
304 37.5 0 0 0 1 0 0 0 0 0 0 0
305 -104.8 0 0 0 0 1 0 0 0 0 0 0
306 29.7 0 0 0 0 0 1 0 0 0 0 0
307 34.2 0 0 0 0 0 0 1 0 0 0 0
308 4.3 0 0 0 0 0 0 0 1 0 0 0
309 40.2 0 0 0 0 0 0 0 0 1 0 0
310 -29.3 0 0 0 0 0 0 0 0 0 1 0
311 -0.2 0 0 0 0 0 0 0 0 0 0 1
312 -95.0 0 0 0 0 0 0 0 0 0 0 0
313 -13.2 1 0 0 0 0 0 0 0 0 0 0
314 38.5 0 1 0 0 0 0 0 0 0 0 0
315 45.4 0 0 1 0 0 0 0 0 0 0 0
316 15.7 0 0 0 1 0 0 0 0 0 0 0
317 -123.6 0 0 0 0 1 0 0 0 0 0 0
318 12.0 0 0 0 0 0 1 0 0 0 0 0
319 37.5 0 0 0 0 0 0 1 0 0 0 0
320 -31.7 0 0 0 0 0 0 0 1 0 0 0
321 15.8 0 0 0 0 0 0 0 0 1 0 0
322 -64.1 0 0 0 0 0 0 0 0 0 1 0
323 -42.1 0 0 0 0 0 0 0 0 0 0 1
324 -207.4 0 0 0 0 0 0 0 0 0 0 0
325 -12.9 1 0 0 0 0 0 0 0 0 0 0
326 -5.0 0 1 0 0 0 0 0 0 0 0 0
327 53.9 0 0 1 0 0 0 0 0 0 0 0
328 19.7 0 0 0 1 0 0 0 0 0 0 0
329 -94.6 0 0 0 0 1 0 0 0 0 0 0
330 36.0 0 0 0 0 0 1 0 0 0 0 0
331 51.3 0 0 0 0 0 0 1 0 0 0 0
332 17.4 0 0 0 0 0 0 0 1 0 0 0
333 27.8 0 0 0 0 0 0 0 0 1 0 0
334 1.3 0 0 0 0 0 0 0 0 0 1 0
335 3.6 0 0 0 0 0 0 0 0 0 0 1
336 -97.9 0 0 0 0 0 0 0 0 0 0 0
337 14.1 1 0 0 0 0 0 0 0 0 0 0
338 50.8 0 1 0 0 0 0 0 0 0 0 0
339 63.5 0 0 1 0 0 0 0 0 0 0 0
340 58.6 0 0 0 1 0 0 0 0 0 0 0
341 -135.1 0 0 0 0 1 0 0 0 0 0 0
342 7.8 0 0 0 0 0 1 0 0 0 0 0
343 25.5 0 0 0 0 0 0 1 0 0 0 0
344 29.6 0 0 0 0 0 0 0 1 0 0 0
345 19.3 0 0 0 0 0 0 0 0 1 0 0
346 -26.2 0 0 0 0 0 0 0 0 0 1 0
347 7.3 0 0 0 0 0 0 0 0 0 0 1
348 -82.6 0 0 0 0 0 0 0 0 0 0 0
349 -26.1 1 0 0 0 0 0 0 0 0 0 0
350 55.3 0 1 0 0 0 0 0 0 0 0 0
351 98.8 0 0 1 0 0 0 0 0 0 0 0
352 41.7 0 0 0 1 0 0 0 0 0 0 0
353 -130.2 0 0 0 0 1 0 0 0 0 0 0
354 51.2 0 0 0 0 0 1 0 0 0 0 0
355 18.4 0 0 0 0 0 0 1 0 0 0 0
356 32.0 0 0 0 0 0 0 0 1 0 0 0
357 21.6 0 0 0 0 0 0 0 0 1 0 0
358 -12.5 0 0 0 0 0 0 0 0 0 1 0
359 46.6 0 0 0 0 0 0 0 0 0 0 1
360 -101.7 0 0 0 0 0 0 0 0 0 0 0
361 15.8 1 0 0 0 0 0 0 0 0 0 0
362 26.0 0 1 0 0 0 0 0 0 0 0 0
363 79.1 0 0 1 0 0 0 0 0 0 0 0
364 23.1 0 0 0 1 0 0 0 0 0 0 0
365 -86.9 0 0 0 0 1 0 0 0 0 0 0
366 -11.2 0 0 0 0 0 1 0 0 0 0 0
367 50.7 0 0 0 0 0 0 1 0 0 0 0
368 13.4 0 0 0 0 0 0 0 1 0 0 0
369 33.7 0 0 0 0 0 0 0 0 1 0 0
370 -16.9 0 0 0 0 0 0 0 0 0 1 0
371 -9.6 0 0 0 0 0 0 0 0 0 0 1
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) M1 M2 M3 M4 M5
-74.313 64.417 96.581 113.236 94.852 1.588
M6 M7 M8 M9 M10 M11
97.084 105.458 91.420 89.755 52.242 71.846
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-133.087 -13.045 0.477 14.935 70.426
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -74.313 4.318 -17.211 <2e-16 ***
M1 64.417 6.057 10.636 <2e-16 ***
M2 96.581 6.057 15.946 <2e-16 ***
M3 113.236 6.057 18.696 <2e-16 ***
M4 94.852 6.057 15.661 <2e-16 ***
M5 1.588 6.057 0.262 0.793
M6 97.084 6.057 16.029 <2e-16 ***
M7 105.458 6.057 17.412 <2e-16 ***
M8 91.420 6.057 15.094 <2e-16 ***
M9 89.755 6.057 14.819 <2e-16 ***
M10 52.242 6.057 8.626 <2e-16 ***
M11 71.846 6.057 11.862 <2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 23.65 on 359 degrees of freedom
Multiple R-squared: 0.7075, Adjusted R-squared: 0.6986
F-statistic: 78.95 on 11 and 359 DF, p-value: < 2.2e-16
> if (n > n25) {
+ kp3 <- k + 3
+ nmkm3 <- n - k - 3
+ gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
+ numgqtests <- 0
+ numsignificant1 <- 0
+ numsignificant5 <- 0
+ numsignificant10 <- 0
+ for (mypoint in kp3:nmkm3) {
+ j <- 0
+ numgqtests <- numgqtests + 1
+ for (myalt in c('greater', 'two.sided', 'less')) {
+ j <- j + 1
+ gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
+ }
+ if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
+ }
+ gqarr
+ }
[,1] [,2] [,3]
[1,] 0.02329919 0.04659839 0.97670081
[2,] 0.56187941 0.87624118 0.43812059
[3,] 0.42271437 0.84542875 0.57728563
[4,] 0.51695023 0.96609954 0.48304977
[5,] 0.47062285 0.94124571 0.52937715
[6,] 0.38353628 0.76707255 0.61646372
[7,] 0.49247492 0.98494983 0.50752508
[8,] 0.61390877 0.77218246 0.38609123
[9,] 0.52752378 0.94495244 0.47247622
[10,] 0.46448200 0.92896401 0.53551800
[11,] 0.48640276 0.97280552 0.51359724
[12,] 0.52601491 0.94797018 0.47398509
[13,] 0.64370308 0.71259384 0.35629692
[14,] 0.65543265 0.68913469 0.34456735
[15,] 0.61445379 0.77109242 0.38554621
[16,] 0.68942684 0.62114631 0.31057316
[17,] 0.73778050 0.52443900 0.26221950
[18,] 0.69169033 0.61661933 0.30830967
[19,] 0.71463160 0.57073679 0.28536840
[20,] 0.70142628 0.59714744 0.29857372
[21,] 0.65147426 0.69705148 0.34852574
[22,] 0.81806229 0.36387542 0.18193771
[23,] 0.86887352 0.26225296 0.13112648
[24,] 0.83666944 0.32666113 0.16333056
[25,] 0.80111576 0.39776848 0.19888424
[26,] 0.76060432 0.47879136 0.23939568
[27,] 0.72866558 0.54266884 0.27133442
[28,] 0.69385091 0.61229818 0.30614909
[29,] 0.66237957 0.67524087 0.33762043
[30,] 0.66619787 0.66760426 0.33380213
[31,] 0.62031124 0.75937751 0.37968876
[32,] 0.57816368 0.84367263 0.42183632
[33,] 0.58948066 0.82103868 0.41051934
[34,] 0.57214457 0.85571085 0.42785543
[35,] 0.53913472 0.92173056 0.46086528
[36,] 0.49799395 0.99598791 0.50200605
[37,] 0.47487221 0.94974442 0.52512779
[38,] 0.43948731 0.87897463 0.56051269
[39,] 0.43046910 0.86093820 0.56953090
[40,] 0.39497710 0.78995420 0.60502290
[41,] 0.38301486 0.76602971 0.61698514
[42,] 0.34107405 0.68214811 0.65892595
[43,] 0.30293083 0.60586166 0.69706917
[44,] 0.26590367 0.53180733 0.73409633
[45,] 0.23385197 0.46770394 0.76614803
[46,] 0.20317457 0.40634914 0.79682543
[47,] 0.24463903 0.48927806 0.75536097
[48,] 0.21838629 0.43677258 0.78161371
[49,] 0.22388942 0.44777885 0.77611058
[50,] 0.19476019 0.38952037 0.80523981
[51,] 0.20462259 0.40924518 0.79537741
[52,] 0.18189933 0.36379866 0.81810067
[53,] 0.16451734 0.32903468 0.83548266
[54,] 0.16940882 0.33881765 0.83059118
[55,] 0.15273686 0.30547372 0.84726314
[56,] 0.16479770 0.32959540 0.83520230
[57,] 0.18839095 0.37678190 0.81160905
[58,] 0.33619837 0.67239675 0.66380163
[59,] 0.35242509 0.70485019 0.64757491
[60,] 0.36868773 0.73737546 0.63131227
[61,] 0.34111819 0.68223638 0.65888181
[62,] 0.30563425 0.61126849 0.69436575
[63,] 0.40038749 0.80077498 0.59961251
[64,] 0.37491177 0.74982354 0.62508823
[65,] 0.34655318 0.69310637 0.65344682
[66,] 0.31661451 0.63322902 0.68338549
[67,] 0.35461468 0.70922937 0.64538532
[68,] 0.31980208 0.63960415 0.68019792
[69,] 0.30368869 0.60737738 0.69631131
[70,] 0.27326295 0.54652590 0.72673705
[71,] 0.28340079 0.56680157 0.71659921
[72,] 0.25515685 0.51031370 0.74484315
[73,] 0.24249898 0.48499797 0.75750102
[74,] 0.26049608 0.52099217 0.73950392
[75,] 0.29042742 0.58085485 0.70957258
[76,] 0.28932686 0.57865373 0.71067314
[77,] 0.27800026 0.55600052 0.72199974
[78,] 0.25268029 0.50536057 0.74731971
[79,] 0.23620144 0.47240287 0.76379856
[80,] 0.21048962 0.42097925 0.78951038
[81,] 0.18560660 0.37121321 0.81439340
[82,] 0.19072021 0.38144042 0.80927979
[83,] 0.17279453 0.34558906 0.82720547
[84,] 0.17059914 0.34119829 0.82940086
[85,] 0.15565430 0.31130861 0.84434570
[86,] 0.17187604 0.34375208 0.82812396
[87,] 0.18270933 0.36541867 0.81729067
[88,] 0.17296348 0.34592695 0.82703652
[89,] 0.17304404 0.34608807 0.82695596
[90,] 0.15383295 0.30766591 0.84616705
[91,] 0.13426824 0.26853648 0.86573176
[92,] 0.15033745 0.30067490 0.84966255
[93,] 0.13119973 0.26239947 0.86880027
[94,] 0.12217042 0.24434084 0.87782958
[95,] 0.12606956 0.25213912 0.87393044
[96,] 0.11076694 0.22153389 0.88923306
[97,] 0.10133950 0.20267899 0.89866050
[98,] 0.09816682 0.19633365 0.90183318
[99,] 0.10814603 0.21629206 0.89185397
[100,] 0.10808720 0.21617440 0.89191280
[101,] 0.09317137 0.18634273 0.90682863
[102,] 0.08369715 0.16739429 0.91630285
[103,] 0.07653638 0.15307275 0.92346362
[104,] 0.11780193 0.23560385 0.88219807
[105,] 0.11075815 0.22151630 0.88924185
[106,] 0.16572080 0.33144160 0.83427920
[107,] 0.29196976 0.58393952 0.70803024
[108,] 0.29849855 0.59699711 0.70150145
[109,] 0.30559667 0.61119333 0.69440333
[110,] 0.27960756 0.55921513 0.72039244
[111,] 0.31112387 0.62224774 0.68887613
[112,] 0.29150136 0.58300272 0.70849864
[113,] 0.28259576 0.56519152 0.71740424
[114,] 0.35593539 0.71187079 0.64406461
[115,] 0.33869364 0.67738728 0.66130636
[116,] 0.33796573 0.67593147 0.66203427
[117,] 0.34396088 0.68792175 0.65603912
[118,] 0.32331768 0.64663537 0.67668232
[119,] 0.30283578 0.60567156 0.69716422
[120,] 0.29960022 0.59920043 0.70039978
[121,] 0.38406664 0.76813328 0.61593336
[122,] 0.35574886 0.71149773 0.64425114
[123,] 0.39369802 0.78739604 0.60630198
[124,] 0.37350660 0.74701319 0.62649340
[125,] 0.34618457 0.69236915 0.65381543
[126,] 0.31768906 0.63537812 0.68231094
[127,] 0.31516986 0.63033972 0.68483014
[128,] 0.30486206 0.60972412 0.69513794
[129,] 0.29445394 0.58890787 0.70554606
[130,] 0.27759076 0.55518152 0.72240924
[131,] 0.32227501 0.64455002 0.67772499
[132,] 0.44429836 0.88859672 0.55570164
[133,] 0.44576223 0.89152447 0.55423777
[134,] 0.41634641 0.83269283 0.58365359
[135,] 0.47793896 0.95587791 0.52206104
[136,] 0.46488318 0.92976636 0.53511682
[137,] 0.44701291 0.89402582 0.55298709
[138,] 0.45108231 0.90216463 0.54891769
[139,] 0.51445825 0.97108351 0.48554175
[140,] 0.50938257 0.98123485 0.49061743
[141,] 0.61842284 0.76315432 0.38157716
[142,] 0.60157008 0.79685985 0.39842992
[143,] 0.60132521 0.79734958 0.39867479
[144,] 0.57399085 0.85201831 0.42600915
[145,] 0.56495254 0.87009492 0.43504746
[146,] 0.53516906 0.92966187 0.46483094
[147,] 0.56906133 0.86187734 0.43093867
[148,] 0.56271604 0.87456793 0.43728396
[149,] 0.56066464 0.87867071 0.43933536
[150,] 0.56600629 0.86798743 0.43399371
[151,] 0.53598328 0.92803344 0.46401672
[152,] 0.52237164 0.95525673 0.47762836
[153,] 0.49726251 0.99452501 0.50273749
[154,] 0.48359538 0.96719076 0.51640462
[155,] 0.49221853 0.98443706 0.50778147
[156,] 0.46615166 0.93230331 0.53384834
[157,] 0.44272923 0.88545847 0.55727077
[158,] 0.46778665 0.93557329 0.53221335
[159,] 0.62403091 0.75193819 0.37596909
[160,] 0.62162612 0.75674777 0.37837388
[161,] 0.65996876 0.68006248 0.34003124
[162,] 0.66080936 0.67838128 0.33919064
[163,] 0.63542119 0.72915761 0.36457881
[164,] 0.65383030 0.69233940 0.34616970
[165,] 0.62865082 0.74269836 0.37134918
[166,] 0.61115436 0.77769129 0.38884564
[167,] 0.59565746 0.80868509 0.40434254
[168,] 0.59607581 0.80784839 0.40392419
[169,] 0.57104231 0.85791537 0.42895769
[170,] 0.56017944 0.87964112 0.43982056
[171,] 0.62123415 0.75753171 0.37876585
[172,] 0.62001430 0.75997139 0.37998570
[173,] 0.59432832 0.81134337 0.40567168
[174,] 0.57401853 0.85196294 0.42598147
[175,] 0.54822463 0.90355074 0.45177537
[176,] 0.56199136 0.87601727 0.43800864
[177,] 0.54081741 0.91836517 0.45918259
[178,] 0.51176835 0.97646331 0.48823165
[179,] 0.49787725 0.99575449 0.50212275
[180,] 0.46921443 0.93842885 0.53078557
[181,] 0.44121516 0.88243032 0.55878484
[182,] 0.41881521 0.83763041 0.58118479
[183,] 0.48563782 0.97127564 0.51436218
[184,] 0.65067594 0.69864811 0.34932406
[185,] 0.64470913 0.71058174 0.35529087
[186,] 0.62664033 0.74671935 0.37335967
[187,] 0.60305046 0.79389907 0.39694954
[188,] 0.58170657 0.83658685 0.41829343
[189,] 0.55871792 0.88256416 0.44128208
[190,] 0.56264616 0.87470768 0.43735384
[191,] 0.54513616 0.90972768 0.45486384
[192,] 0.55439577 0.89120846 0.44560423
[193,] 0.55314883 0.89370234 0.44685117
[194,] 0.52659926 0.94680148 0.47340074
[195,] 0.57249231 0.85501537 0.42750769
[196,] 0.64196086 0.71607829 0.35803914
[197,] 0.61482420 0.77035160 0.38517580
[198,] 0.60445394 0.79109212 0.39554606
[199,] 0.57511256 0.84977487 0.42488744
[200,] 0.54791438 0.90417125 0.45208562
[201,] 0.52744905 0.94510190 0.47255095
[202,] 0.56413688 0.87172623 0.43586312
[203,] 0.56852923 0.86294155 0.43147077
[204,] 0.54821739 0.90356523 0.45178261
[205,] 0.53819651 0.92360697 0.46180349
[206,] 0.56663265 0.86673469 0.43336735
[207,] 0.61394685 0.77210629 0.38605315
[208,] 0.64639177 0.70721646 0.35360823
[209,] 0.62289395 0.75421210 0.37710605
[210,] 0.61472324 0.77055351 0.38527676
[211,] 0.59550128 0.80899743 0.40449872
[212,] 0.57171548 0.85656904 0.42828452
[213,] 0.54922738 0.90154523 0.45077262
[214,] 0.58151596 0.83696808 0.41848404
[215,] 0.55407061 0.89185879 0.44592939
[216,] 0.52407958 0.95184084 0.47592042
[217,] 0.51192202 0.97615597 0.48807798
[218,] 0.48408008 0.96816017 0.51591992
[219,] 0.57206274 0.85587451 0.42793726
[220,] 0.55633120 0.88733761 0.44366880
[221,] 0.52549541 0.94900919 0.47450459
[222,] 0.50173925 0.99652151 0.49826075
[223,] 0.50705011 0.98589979 0.49294989
[224,] 0.51666365 0.96667270 0.48333635
[225,] 0.50755870 0.98488261 0.49244130
[226,] 0.62847287 0.74305426 0.37152713
[227,] 0.60741254 0.78517492 0.39258746
[228,] 0.58534392 0.82931216 0.41465608
[229,] 0.55880492 0.88239017 0.44119508
[230,] 0.53264443 0.93471114 0.46735557
[231,] 0.65141436 0.69717128 0.34858564
[232,] 0.64159543 0.71680914 0.35840457
[233,] 0.62012844 0.75974312 0.37987156
[234,] 0.59137485 0.81725030 0.40862515
[235,] 0.56582530 0.86834940 0.43417470
[236,] 0.54532282 0.90935436 0.45467718
[237,] 0.52888163 0.94223674 0.47111837
[238,] 0.61632317 0.76735367 0.38367683
[239,] 0.58565981 0.82868038 0.41434019
[240,] 0.55790561 0.88418878 0.44209439
[241,] 0.58012792 0.83974416 0.41987208
[242,] 0.55068249 0.89863502 0.44931751
[243,] 0.57788053 0.84423895 0.42211947
[244,] 0.54502371 0.90995258 0.45497629
[245,] 0.51194849 0.97610302 0.48805151
[246,] 0.51304337 0.97391326 0.48695663
[247,] 0.48508871 0.97017743 0.51491129
[248,] 0.52937196 0.94125607 0.47062804
[249,] 0.50013492 0.99973017 0.49986508
[250,] 0.49001146 0.98002292 0.50998854
[251,] 0.52390758 0.95218483 0.47609242
[252,] 0.52131978 0.95736045 0.47868022
[253,] 0.57103452 0.85793097 0.42896548
[254,] 0.54894797 0.90210407 0.45105203
[255,] 0.61872134 0.76255732 0.38127866
[256,] 0.58719740 0.82560520 0.41280260
[257,] 0.55425316 0.89149368 0.44574684
[258,] 0.55186952 0.89626097 0.44813048
[259,] 0.54213729 0.91572542 0.45786271
[260,] 0.52162782 0.95674436 0.47837218
[261,] 0.48865221 0.97730441 0.51134779
[262,] 0.48465076 0.96930153 0.51534924
[263,] 0.45067406 0.90134812 0.54932594
[264,] 0.41727027 0.83454053 0.58272973
[265,] 0.39439853 0.78879706 0.60560147
[266,] 0.36347871 0.72695741 0.63652129
[267,] 0.36886781 0.73773563 0.63113219
[268,] 0.33729158 0.67458317 0.66270842
[269,] 0.30797353 0.61594706 0.69202647
[270,] 0.28075305 0.56150610 0.71924695
[271,] 0.25366377 0.50732753 0.74633623
[272,] 0.22653322 0.45306643 0.77346678
[273,] 0.20561701 0.41123402 0.79438299
[274,] 0.21395330 0.42790661 0.78604670
[275,] 0.19341743 0.38683486 0.80658257
[276,] 0.17427269 0.34854537 0.82572731
[277,] 0.15784555 0.31569111 0.84215445
[278,] 0.13923729 0.27847459 0.86076271
[279,] 0.13756749 0.27513499 0.86243251
[280,] 0.11816261 0.23632521 0.88183739
[281,] 0.10075446 0.20150893 0.89924554
[282,] 0.08635262 0.17270524 0.91364738
[283,] 0.07328382 0.14656764 0.92671618
[284,] 0.10874738 0.21749476 0.89125262
[285,] 0.09790844 0.19581688 0.90209156
[286,] 0.17650221 0.35300442 0.82349779
[287,] 0.15694252 0.31388504 0.84305748
[288,] 0.13549759 0.27099518 0.86450241
[289,] 0.14694227 0.29388453 0.85305773
[290,] 0.12860331 0.25720662 0.87139669
[291,] 0.12230960 0.24461921 0.87769040
[292,] 0.10555673 0.21111346 0.89444327
[293,] 0.08811218 0.17622437 0.91188782
[294,] 0.07473117 0.14946234 0.92526883
[295,] 0.06877544 0.13755089 0.93122456
[296,] 0.05659193 0.11318386 0.94340807
[297,] 0.04557991 0.09115982 0.95442009
[298,] 0.04707184 0.09414368 0.95292816
[299,] 0.03867931 0.07735862 0.96132069
[300,] 0.03161808 0.06323616 0.96838192
[301,] 0.03143121 0.06286242 0.96856879
[302,] 0.02751420 0.05502840 0.97248580
[303,] 0.02867383 0.05734767 0.97132617
[304,] 0.02285268 0.04570535 0.97714732
[305,] 0.01748388 0.03496776 0.98251612
[306,] 0.03932229 0.07864459 0.96067771
[307,] 0.03135087 0.06270174 0.96864913
[308,] 0.05728524 0.11457047 0.94271476
[309,] 0.10893506 0.21787013 0.89106494
[310,] 0.89332829 0.21334342 0.10667171
[311,] 0.87517125 0.24965750 0.12482875
[312,] 0.93795846 0.12408309 0.06204154
[313,] 0.94130059 0.11739882 0.05869941
[314,] 0.93704646 0.12590709 0.06295354
[315,] 0.93615947 0.12768105 0.06384053
[316,] 0.93014284 0.13971433 0.06985716
[317,] 0.92384967 0.15230066 0.07615033
[318,] 0.90233076 0.19533847 0.09766924
[319,] 0.87447278 0.25105444 0.12552722
[320,] 0.86428097 0.27143805 0.13571903
[321,] 0.83501956 0.32996088 0.16498044
[322,] 0.79749490 0.40501020 0.20250510
[323,] 0.77691778 0.44616443 0.22308222
[324,] 0.73707008 0.52585983 0.26292992
[325,] 0.73324741 0.53350517 0.26675259
[326,] 0.73596827 0.52806346 0.26403173
[327,] 0.75303641 0.49392719 0.24696359
[328,] 0.70532769 0.58934461 0.29467231
[329,] 0.64522699 0.70954602 0.35477301
[330,] 0.57720093 0.84559813 0.42279907
[331,] 0.50614231 0.98771538 0.49385769
[332,] 0.43850562 0.87701124 0.56149438
[333,] 0.37039974 0.74079948 0.62960026
[334,] 0.31567297 0.63134595 0.68432703
[335,] 0.35082022 0.70164045 0.64917978
[336,] 0.32966620 0.65933240 0.67033380
[337,] 0.28487112 0.56974224 0.71512888
[338,] 0.22459976 0.44919953 0.77540024
[339,] 0.26749502 0.53499005 0.73250498
[340,] 0.52355074 0.95289852 0.47644926
[341,] 0.51485284 0.97029432 0.48514716
[342,] 0.39824219 0.79648438 0.60175781
> postscript(file="/var/www/rcomp/tmp/15ttc1322152751.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
> points(x[,1]-mysum$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/2klht1322152751.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/3eaqp1322152751.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/4c67c1322152751.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/52j4f1322152751.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 = 371
Frequency = 1
1 2 3 4 5
-35.70322581 -6.16774194 -15.02258065 18.76129032 33.32580645
6 7 8 9 10
-23.07096774 -13.84516129 0.59354839 15.95806452 -6.52903226
11 12 13 14 15
-14.73225806 -4.68666667 -38.00322581 -13.16774194 -28.32258065
16 17 18 19 20
-44.43870968 27.72580645 -64.97096774 12.05483871 14.99354839
21 22 23 24 25
-30.74193548 43.87096774 -9.53225806 -21.48666667 -4.40322581
26 27 28 29 30
25.53225806 25.87741935 19.66129032 43.92580645 0.72903226
31 32 33 34 35
39.15483871 -4.80645161 28.05806452 -8.02903226 -2.83225806
36 37 38 39 40
50.31333333 20.99677419 -0.76774194 -0.42258065 -3.73870968
41 42 43 44 45
36.52580645 -16.77096774 -4.54516129 -25.10645161 -2.24193548
46 47 48 49 50
-1.52903226 21.86774194 28.11333333 1.69677419 11.53225806
51 52 53 54 55
-22.32258065 -15.13870968 47.72580645 -28.07096774 -14.44516129
56 57 58 59 60
1.89354839 9.35806452 10.67096774 7.36774194 15.61333333
61 62 63 64 65
26.69677419 -8.66774194 -32.52258065 2.26129032 53.12580645
66 67 68 69 70
-20.57096774 -11.34516129 -27.80645161 -10.74193548 -22.42903226
71 72 73 74 75
-32.23225806 -45.38666667 -32.30322581 -27.66774194 -19.82258065
76 77 78 79 80
-1.73870968 70.42580645 -22.57096774 -10.24516129 -13.40645161
81 82 83 84 85
34.95806452 3.47096774 13.06774194 8.31333333 19.89677419
86 87 88 89 90
4.93225806 -25.42258065 26.66129032 52.42580645 0.32903226
91 92 93 94 95
-18.54516129 2.69354839 -10.04193548 -3.12903226 -4.03225806
96 97 98 99 100
27.81333333 7.29677419 -22.56774194 -0.42258065 -29.43870968
101 102 103 104 105
34.72580645 -3.27096774 20.55483871 2.29354839 2.75806452
106 107 108 109 110
-28.72903226 -3.63225806 19.71333333 21.99677419 4.03225806
111 112 113 114 115
-19.42258065 -21.33870968 23.12580645 6.02903226 0.55483871
116 117 118 119 120
-14.80645161 -11.64193548 -44.12903226 -18.03225806 -38.88666667
121 122 123 124 125
-55.30322581 -26.16774194 -29.82258065 2.66129032 33.62580645
126 127 128 129 130
-10.27096774 17.95483871 37.79354839 15.35806452 18.57096774
131 132 133 134 135
-25.83225806 13.31333333 7.89677419 17.73225806 35.07741935
136 137 138 139 140
2.56129032 27.42580645 -5.27096774 -5.34516129 -1.90645161
141 142 143 144 145
-19.04193548 -18.42903226 13.96774194 14.51333333 33.19677419
146 147 148 149 150
-50.06774194 16.77741935 2.16129032 -6.47419355 6.02903226
151 152 153 154 155
-13.84516129 22.49354839 -37.64193548 -20.92903226 -47.83225806
156 157 158 159 160
-12.18666667 -22.00322581 0.83225806 14.67741935 1.06129032
161 162 163 164 165
8.52580645 12.42903226 20.95483871 23.49354839 1.65806452
166 167 168 169 170
14.27096774 -7.53225806 16.31333333 23.89677419 -6.46774194
171 172 173 174 175
7.07741935 -29.43870968 46.02580645 16.22903226 -32.44516129
176 177 178 179 180
21.59354839 6.65806452 -27.12903226 -0.93225806 -12.38666667
181 182 183 184 185
-14.40322581 20.53225806 5.97741935 -16.13870968 12.22580645
186 187 188 189 190
18.62903226 7.35483871 11.39354839 -7.84193548 -24.32903226
191 192 193 194 195
9.46774194 1.31333333 15.59677419 1.33225806 0.47741935
196 197 198 199 200
9.76129032 -19.77419355 55.02903226 -18.74516129 11.79354839
201 202 203 204 205
-9.04193548 10.07096774 -6.63225806 21.11333333 -13.20322581
206 207 208 209 210
25.03225806 -18.22258065 7.26129032 -11.57419355 40.02903226
211 212 213 214 215
-4.74516129 15.19354839 -2.14193548 4.17096774 12.46774194
216 217 218 219 220
28.71333333 23.39677419 -10.36774194 -12.92258065 -26.83870968
221 222 223 224 225
-7.17419355 31.42903226 -8.24516129 14.69354839 -11.64193548
226 227 228 229 230
10.67096774 -6.13225806 24.91333333 7.39677419 0.73225806
231 232 233 234 235
-9.92258065 0.06129032 -44.27419355 15.12903226 -0.44516129
236 237 238 239 240
-12.40645161 -21.14193548 26.97096774 20.76774194 38.91333333
241 242 243 244 245
-11.40322581 13.53225806 4.87741935 -1.83870968 -58.37419355
246 247 248 249 250
17.02903226 13.35483871 -0.60645161 -5.74193548 15.47096774
251 252 253 254 255
18.26774194 28.61333333 5.09677419 -4.66774194 -18.42258065
256 257 258 259 260
3.66129032 -36.27419355 -1.97096774 0.05483871 -25.90645161
261 262 263 264 265
-3.64193548 35.07096774 10.76774194 -3.58666667 -28.90322581
266 267 268 269 270
-16.16774194 -20.82258065 -3.73870968 -55.77419355 -6.87096774
271 272 273 274 275
-2.14516129 -24.30645161 -12.14193548 -12.72903226 -0.43225806
276 277 278 279 280
-3.48666667 7.09677419 4.43225806 9.17741935 9.46129032
281 282 283 284 285
-36.87419355 -6.77096774 -4.24516129 4.99354839 11.55806452
286 287 288 289 290
-2.42903226 14.46774194 -0.88666667 13.39677419 -2.56774194
291 292 293 294 295
12.87741935 14.76129032 -35.47419355 2.52903226 0.45483871
296 297 298 299 300
2.79354839 3.35806452 42.47096774 17.46774194 18.41333333
301 302 303 304 305
-7.10322581 11.03225806 -5.12258065 16.96129032 -32.07419355
306 307 308 309 310
6.92903226 3.05483871 -12.80645161 24.75806452 -7.22903226
311 312 313 314 315
2.26774194 -20.68666667 -3.30322581 16.23225806 6.47741935
316 317 318 319 320
-4.83870968 -50.87419355 -10.77096774 6.35483871 -48.80645161
321 322 323 324 325
0.35806452 -42.02903226 -39.63225806 -133.08666667 -3.00322581
326 327 328 329 330
-27.26774194 14.97741935 -0.83870968 -21.87419355 13.22903226
331 332 333 334 335
20.15483871 0.29354839 12.35806452 23.37096774 6.06774194
336 337 338 339 340
-23.58666667 23.99677419 28.53225806 24.57741935 38.06129032
341 342 343 344 345
-62.37419355 -14.97096774 -5.64516129 12.49354839 3.85806452
346 347 348 349 350
-4.12903226 9.76774194 -8.28666667 -16.20322581 33.03225806
351 352 353 354 355
59.87741935 21.16129032 -57.47419355 28.42903226 -12.74516129
356 357 358 359 360
14.89354839 6.15806452 9.57096774 49.06774194 -27.38666667
361 362 363 364 365
25.69677419 3.73225806 40.17741935 2.56129032 -14.17419355
366 367 368 369 370
-33.97096774 19.55483871 -3.70645161 18.25806452 5.17096774
371
-7.13225806
> postscript(file="/var/www/rcomp/tmp/6ty6u1322152751.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 = 371
Frequency = 1
lag(myerror, k = 1) myerror
0 -35.70322581 NA
1 -6.16774194 -35.70322581
2 -15.02258065 -6.16774194
3 18.76129032 -15.02258065
4 33.32580645 18.76129032
5 -23.07096774 33.32580645
6 -13.84516129 -23.07096774
7 0.59354839 -13.84516129
8 15.95806452 0.59354839
9 -6.52903226 15.95806452
10 -14.73225806 -6.52903226
11 -4.68666667 -14.73225806
12 -38.00322581 -4.68666667
13 -13.16774194 -38.00322581
14 -28.32258065 -13.16774194
15 -44.43870968 -28.32258065
16 27.72580645 -44.43870968
17 -64.97096774 27.72580645
18 12.05483871 -64.97096774
19 14.99354839 12.05483871
20 -30.74193548 14.99354839
21 43.87096774 -30.74193548
22 -9.53225806 43.87096774
23 -21.48666667 -9.53225806
24 -4.40322581 -21.48666667
25 25.53225806 -4.40322581
26 25.87741935 25.53225806
27 19.66129032 25.87741935
28 43.92580645 19.66129032
29 0.72903226 43.92580645
30 39.15483871 0.72903226
31 -4.80645161 39.15483871
32 28.05806452 -4.80645161
33 -8.02903226 28.05806452
34 -2.83225806 -8.02903226
35 50.31333333 -2.83225806
36 20.99677419 50.31333333
37 -0.76774194 20.99677419
38 -0.42258065 -0.76774194
39 -3.73870968 -0.42258065
40 36.52580645 -3.73870968
41 -16.77096774 36.52580645
42 -4.54516129 -16.77096774
43 -25.10645161 -4.54516129
44 -2.24193548 -25.10645161
45 -1.52903226 -2.24193548
46 21.86774194 -1.52903226
47 28.11333333 21.86774194
48 1.69677419 28.11333333
49 11.53225806 1.69677419
50 -22.32258065 11.53225806
51 -15.13870968 -22.32258065
52 47.72580645 -15.13870968
53 -28.07096774 47.72580645
54 -14.44516129 -28.07096774
55 1.89354839 -14.44516129
56 9.35806452 1.89354839
57 10.67096774 9.35806452
58 7.36774194 10.67096774
59 15.61333333 7.36774194
60 26.69677419 15.61333333
61 -8.66774194 26.69677419
62 -32.52258065 -8.66774194
63 2.26129032 -32.52258065
64 53.12580645 2.26129032
65 -20.57096774 53.12580645
66 -11.34516129 -20.57096774
67 -27.80645161 -11.34516129
68 -10.74193548 -27.80645161
69 -22.42903226 -10.74193548
70 -32.23225806 -22.42903226
71 -45.38666667 -32.23225806
72 -32.30322581 -45.38666667
73 -27.66774194 -32.30322581
74 -19.82258065 -27.66774194
75 -1.73870968 -19.82258065
76 70.42580645 -1.73870968
77 -22.57096774 70.42580645
78 -10.24516129 -22.57096774
79 -13.40645161 -10.24516129
80 34.95806452 -13.40645161
81 3.47096774 34.95806452
82 13.06774194 3.47096774
83 8.31333333 13.06774194
84 19.89677419 8.31333333
85 4.93225806 19.89677419
86 -25.42258065 4.93225806
87 26.66129032 -25.42258065
88 52.42580645 26.66129032
89 0.32903226 52.42580645
90 -18.54516129 0.32903226
91 2.69354839 -18.54516129
92 -10.04193548 2.69354839
93 -3.12903226 -10.04193548
94 -4.03225806 -3.12903226
95 27.81333333 -4.03225806
96 7.29677419 27.81333333
97 -22.56774194 7.29677419
98 -0.42258065 -22.56774194
99 -29.43870968 -0.42258065
100 34.72580645 -29.43870968
101 -3.27096774 34.72580645
102 20.55483871 -3.27096774
103 2.29354839 20.55483871
104 2.75806452 2.29354839
105 -28.72903226 2.75806452
106 -3.63225806 -28.72903226
107 19.71333333 -3.63225806
108 21.99677419 19.71333333
109 4.03225806 21.99677419
110 -19.42258065 4.03225806
111 -21.33870968 -19.42258065
112 23.12580645 -21.33870968
113 6.02903226 23.12580645
114 0.55483871 6.02903226
115 -14.80645161 0.55483871
116 -11.64193548 -14.80645161
117 -44.12903226 -11.64193548
118 -18.03225806 -44.12903226
119 -38.88666667 -18.03225806
120 -55.30322581 -38.88666667
121 -26.16774194 -55.30322581
122 -29.82258065 -26.16774194
123 2.66129032 -29.82258065
124 33.62580645 2.66129032
125 -10.27096774 33.62580645
126 17.95483871 -10.27096774
127 37.79354839 17.95483871
128 15.35806452 37.79354839
129 18.57096774 15.35806452
130 -25.83225806 18.57096774
131 13.31333333 -25.83225806
132 7.89677419 13.31333333
133 17.73225806 7.89677419
134 35.07741935 17.73225806
135 2.56129032 35.07741935
136 27.42580645 2.56129032
137 -5.27096774 27.42580645
138 -5.34516129 -5.27096774
139 -1.90645161 -5.34516129
140 -19.04193548 -1.90645161
141 -18.42903226 -19.04193548
142 13.96774194 -18.42903226
143 14.51333333 13.96774194
144 33.19677419 14.51333333
145 -50.06774194 33.19677419
146 16.77741935 -50.06774194
147 2.16129032 16.77741935
148 -6.47419355 2.16129032
149 6.02903226 -6.47419355
150 -13.84516129 6.02903226
151 22.49354839 -13.84516129
152 -37.64193548 22.49354839
153 -20.92903226 -37.64193548
154 -47.83225806 -20.92903226
155 -12.18666667 -47.83225806
156 -22.00322581 -12.18666667
157 0.83225806 -22.00322581
158 14.67741935 0.83225806
159 1.06129032 14.67741935
160 8.52580645 1.06129032
161 12.42903226 8.52580645
162 20.95483871 12.42903226
163 23.49354839 20.95483871
164 1.65806452 23.49354839
165 14.27096774 1.65806452
166 -7.53225806 14.27096774
167 16.31333333 -7.53225806
168 23.89677419 16.31333333
169 -6.46774194 23.89677419
170 7.07741935 -6.46774194
171 -29.43870968 7.07741935
172 46.02580645 -29.43870968
173 16.22903226 46.02580645
174 -32.44516129 16.22903226
175 21.59354839 -32.44516129
176 6.65806452 21.59354839
177 -27.12903226 6.65806452
178 -0.93225806 -27.12903226
179 -12.38666667 -0.93225806
180 -14.40322581 -12.38666667
181 20.53225806 -14.40322581
182 5.97741935 20.53225806
183 -16.13870968 5.97741935
184 12.22580645 -16.13870968
185 18.62903226 12.22580645
186 7.35483871 18.62903226
187 11.39354839 7.35483871
188 -7.84193548 11.39354839
189 -24.32903226 -7.84193548
190 9.46774194 -24.32903226
191 1.31333333 9.46774194
192 15.59677419 1.31333333
193 1.33225806 15.59677419
194 0.47741935 1.33225806
195 9.76129032 0.47741935
196 -19.77419355 9.76129032
197 55.02903226 -19.77419355
198 -18.74516129 55.02903226
199 11.79354839 -18.74516129
200 -9.04193548 11.79354839
201 10.07096774 -9.04193548
202 -6.63225806 10.07096774
203 21.11333333 -6.63225806
204 -13.20322581 21.11333333
205 25.03225806 -13.20322581
206 -18.22258065 25.03225806
207 7.26129032 -18.22258065
208 -11.57419355 7.26129032
209 40.02903226 -11.57419355
210 -4.74516129 40.02903226
211 15.19354839 -4.74516129
212 -2.14193548 15.19354839
213 4.17096774 -2.14193548
214 12.46774194 4.17096774
215 28.71333333 12.46774194
216 23.39677419 28.71333333
217 -10.36774194 23.39677419
218 -12.92258065 -10.36774194
219 -26.83870968 -12.92258065
220 -7.17419355 -26.83870968
221 31.42903226 -7.17419355
222 -8.24516129 31.42903226
223 14.69354839 -8.24516129
224 -11.64193548 14.69354839
225 10.67096774 -11.64193548
226 -6.13225806 10.67096774
227 24.91333333 -6.13225806
228 7.39677419 24.91333333
229 0.73225806 7.39677419
230 -9.92258065 0.73225806
231 0.06129032 -9.92258065
232 -44.27419355 0.06129032
233 15.12903226 -44.27419355
234 -0.44516129 15.12903226
235 -12.40645161 -0.44516129
236 -21.14193548 -12.40645161
237 26.97096774 -21.14193548
238 20.76774194 26.97096774
239 38.91333333 20.76774194
240 -11.40322581 38.91333333
241 13.53225806 -11.40322581
242 4.87741935 13.53225806
243 -1.83870968 4.87741935
244 -58.37419355 -1.83870968
245 17.02903226 -58.37419355
246 13.35483871 17.02903226
247 -0.60645161 13.35483871
248 -5.74193548 -0.60645161
249 15.47096774 -5.74193548
250 18.26774194 15.47096774
251 28.61333333 18.26774194
252 5.09677419 28.61333333
253 -4.66774194 5.09677419
254 -18.42258065 -4.66774194
255 3.66129032 -18.42258065
256 -36.27419355 3.66129032
257 -1.97096774 -36.27419355
258 0.05483871 -1.97096774
259 -25.90645161 0.05483871
260 -3.64193548 -25.90645161
261 35.07096774 -3.64193548
262 10.76774194 35.07096774
263 -3.58666667 10.76774194
264 -28.90322581 -3.58666667
265 -16.16774194 -28.90322581
266 -20.82258065 -16.16774194
267 -3.73870968 -20.82258065
268 -55.77419355 -3.73870968
269 -6.87096774 -55.77419355
270 -2.14516129 -6.87096774
271 -24.30645161 -2.14516129
272 -12.14193548 -24.30645161
273 -12.72903226 -12.14193548
274 -0.43225806 -12.72903226
275 -3.48666667 -0.43225806
276 7.09677419 -3.48666667
277 4.43225806 7.09677419
278 9.17741935 4.43225806
279 9.46129032 9.17741935
280 -36.87419355 9.46129032
281 -6.77096774 -36.87419355
282 -4.24516129 -6.77096774
283 4.99354839 -4.24516129
284 11.55806452 4.99354839
285 -2.42903226 11.55806452
286 14.46774194 -2.42903226
287 -0.88666667 14.46774194
288 13.39677419 -0.88666667
289 -2.56774194 13.39677419
290 12.87741935 -2.56774194
291 14.76129032 12.87741935
292 -35.47419355 14.76129032
293 2.52903226 -35.47419355
294 0.45483871 2.52903226
295 2.79354839 0.45483871
296 3.35806452 2.79354839
297 42.47096774 3.35806452
298 17.46774194 42.47096774
299 18.41333333 17.46774194
300 -7.10322581 18.41333333
301 11.03225806 -7.10322581
302 -5.12258065 11.03225806
303 16.96129032 -5.12258065
304 -32.07419355 16.96129032
305 6.92903226 -32.07419355
306 3.05483871 6.92903226
307 -12.80645161 3.05483871
308 24.75806452 -12.80645161
309 -7.22903226 24.75806452
310 2.26774194 -7.22903226
311 -20.68666667 2.26774194
312 -3.30322581 -20.68666667
313 16.23225806 -3.30322581
314 6.47741935 16.23225806
315 -4.83870968 6.47741935
316 -50.87419355 -4.83870968
317 -10.77096774 -50.87419355
318 6.35483871 -10.77096774
319 -48.80645161 6.35483871
320 0.35806452 -48.80645161
321 -42.02903226 0.35806452
322 -39.63225806 -42.02903226
323 -133.08666667 -39.63225806
324 -3.00322581 -133.08666667
325 -27.26774194 -3.00322581
326 14.97741935 -27.26774194
327 -0.83870968 14.97741935
328 -21.87419355 -0.83870968
329 13.22903226 -21.87419355
330 20.15483871 13.22903226
331 0.29354839 20.15483871
332 12.35806452 0.29354839
333 23.37096774 12.35806452
334 6.06774194 23.37096774
335 -23.58666667 6.06774194
336 23.99677419 -23.58666667
337 28.53225806 23.99677419
338 24.57741935 28.53225806
339 38.06129032 24.57741935
340 -62.37419355 38.06129032
341 -14.97096774 -62.37419355
342 -5.64516129 -14.97096774
343 12.49354839 -5.64516129
344 3.85806452 12.49354839
345 -4.12903226 3.85806452
346 9.76774194 -4.12903226
347 -8.28666667 9.76774194
348 -16.20322581 -8.28666667
349 33.03225806 -16.20322581
350 59.87741935 33.03225806
351 21.16129032 59.87741935
352 -57.47419355 21.16129032
353 28.42903226 -57.47419355
354 -12.74516129 28.42903226
355 14.89354839 -12.74516129
356 6.15806452 14.89354839
357 9.57096774 6.15806452
358 49.06774194 9.57096774
359 -27.38666667 49.06774194
360 25.69677419 -27.38666667
361 3.73225806 25.69677419
362 40.17741935 3.73225806
363 2.56129032 40.17741935
364 -14.17419355 2.56129032
365 -33.97096774 -14.17419355
366 19.55483871 -33.97096774
367 -3.70645161 19.55483871
368 18.25806452 -3.70645161
369 5.17096774 18.25806452
370 -7.13225806 5.17096774
371 NA -7.13225806
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -6.16774194 -35.70322581
[2,] -15.02258065 -6.16774194
[3,] 18.76129032 -15.02258065
[4,] 33.32580645 18.76129032
[5,] -23.07096774 33.32580645
[6,] -13.84516129 -23.07096774
[7,] 0.59354839 -13.84516129
[8,] 15.95806452 0.59354839
[9,] -6.52903226 15.95806452
[10,] -14.73225806 -6.52903226
[11,] -4.68666667 -14.73225806
[12,] -38.00322581 -4.68666667
[13,] -13.16774194 -38.00322581
[14,] -28.32258065 -13.16774194
[15,] -44.43870968 -28.32258065
[16,] 27.72580645 -44.43870968
[17,] -64.97096774 27.72580645
[18,] 12.05483871 -64.97096774
[19,] 14.99354839 12.05483871
[20,] -30.74193548 14.99354839
[21,] 43.87096774 -30.74193548
[22,] -9.53225806 43.87096774
[23,] -21.48666667 -9.53225806
[24,] -4.40322581 -21.48666667
[25,] 25.53225806 -4.40322581
[26,] 25.87741935 25.53225806
[27,] 19.66129032 25.87741935
[28,] 43.92580645 19.66129032
[29,] 0.72903226 43.92580645
[30,] 39.15483871 0.72903226
[31,] -4.80645161 39.15483871
[32,] 28.05806452 -4.80645161
[33,] -8.02903226 28.05806452
[34,] -2.83225806 -8.02903226
[35,] 50.31333333 -2.83225806
[36,] 20.99677419 50.31333333
[37,] -0.76774194 20.99677419
[38,] -0.42258065 -0.76774194
[39,] -3.73870968 -0.42258065
[40,] 36.52580645 -3.73870968
[41,] -16.77096774 36.52580645
[42,] -4.54516129 -16.77096774
[43,] -25.10645161 -4.54516129
[44,] -2.24193548 -25.10645161
[45,] -1.52903226 -2.24193548
[46,] 21.86774194 -1.52903226
[47,] 28.11333333 21.86774194
[48,] 1.69677419 28.11333333
[49,] 11.53225806 1.69677419
[50,] -22.32258065 11.53225806
[51,] -15.13870968 -22.32258065
[52,] 47.72580645 -15.13870968
[53,] -28.07096774 47.72580645
[54,] -14.44516129 -28.07096774
[55,] 1.89354839 -14.44516129
[56,] 9.35806452 1.89354839
[57,] 10.67096774 9.35806452
[58,] 7.36774194 10.67096774
[59,] 15.61333333 7.36774194
[60,] 26.69677419 15.61333333
[61,] -8.66774194 26.69677419
[62,] -32.52258065 -8.66774194
[63,] 2.26129032 -32.52258065
[64,] 53.12580645 2.26129032
[65,] -20.57096774 53.12580645
[66,] -11.34516129 -20.57096774
[67,] -27.80645161 -11.34516129
[68,] -10.74193548 -27.80645161
[69,] -22.42903226 -10.74193548
[70,] -32.23225806 -22.42903226
[71,] -45.38666667 -32.23225806
[72,] -32.30322581 -45.38666667
[73,] -27.66774194 -32.30322581
[74,] -19.82258065 -27.66774194
[75,] -1.73870968 -19.82258065
[76,] 70.42580645 -1.73870968
[77,] -22.57096774 70.42580645
[78,] -10.24516129 -22.57096774
[79,] -13.40645161 -10.24516129
[80,] 34.95806452 -13.40645161
[81,] 3.47096774 34.95806452
[82,] 13.06774194 3.47096774
[83,] 8.31333333 13.06774194
[84,] 19.89677419 8.31333333
[85,] 4.93225806 19.89677419
[86,] -25.42258065 4.93225806
[87,] 26.66129032 -25.42258065
[88,] 52.42580645 26.66129032
[89,] 0.32903226 52.42580645
[90,] -18.54516129 0.32903226
[91,] 2.69354839 -18.54516129
[92,] -10.04193548 2.69354839
[93,] -3.12903226 -10.04193548
[94,] -4.03225806 -3.12903226
[95,] 27.81333333 -4.03225806
[96,] 7.29677419 27.81333333
[97,] -22.56774194 7.29677419
[98,] -0.42258065 -22.56774194
[99,] -29.43870968 -0.42258065
[100,] 34.72580645 -29.43870968
[101,] -3.27096774 34.72580645
[102,] 20.55483871 -3.27096774
[103,] 2.29354839 20.55483871
[104,] 2.75806452 2.29354839
[105,] -28.72903226 2.75806452
[106,] -3.63225806 -28.72903226
[107,] 19.71333333 -3.63225806
[108,] 21.99677419 19.71333333
[109,] 4.03225806 21.99677419
[110,] -19.42258065 4.03225806
[111,] -21.33870968 -19.42258065
[112,] 23.12580645 -21.33870968
[113,] 6.02903226 23.12580645
[114,] 0.55483871 6.02903226
[115,] -14.80645161 0.55483871
[116,] -11.64193548 -14.80645161
[117,] -44.12903226 -11.64193548
[118,] -18.03225806 -44.12903226
[119,] -38.88666667 -18.03225806
[120,] -55.30322581 -38.88666667
[121,] -26.16774194 -55.30322581
[122,] -29.82258065 -26.16774194
[123,] 2.66129032 -29.82258065
[124,] 33.62580645 2.66129032
[125,] -10.27096774 33.62580645
[126,] 17.95483871 -10.27096774
[127,] 37.79354839 17.95483871
[128,] 15.35806452 37.79354839
[129,] 18.57096774 15.35806452
[130,] -25.83225806 18.57096774
[131,] 13.31333333 -25.83225806
[132,] 7.89677419 13.31333333
[133,] 17.73225806 7.89677419
[134,] 35.07741935 17.73225806
[135,] 2.56129032 35.07741935
[136,] 27.42580645 2.56129032
[137,] -5.27096774 27.42580645
[138,] -5.34516129 -5.27096774
[139,] -1.90645161 -5.34516129
[140,] -19.04193548 -1.90645161
[141,] -18.42903226 -19.04193548
[142,] 13.96774194 -18.42903226
[143,] 14.51333333 13.96774194
[144,] 33.19677419 14.51333333
[145,] -50.06774194 33.19677419
[146,] 16.77741935 -50.06774194
[147,] 2.16129032 16.77741935
[148,] -6.47419355 2.16129032
[149,] 6.02903226 -6.47419355
[150,] -13.84516129 6.02903226
[151,] 22.49354839 -13.84516129
[152,] -37.64193548 22.49354839
[153,] -20.92903226 -37.64193548
[154,] -47.83225806 -20.92903226
[155,] -12.18666667 -47.83225806
[156,] -22.00322581 -12.18666667
[157,] 0.83225806 -22.00322581
[158,] 14.67741935 0.83225806
[159,] 1.06129032 14.67741935
[160,] 8.52580645 1.06129032
[161,] 12.42903226 8.52580645
[162,] 20.95483871 12.42903226
[163,] 23.49354839 20.95483871
[164,] 1.65806452 23.49354839
[165,] 14.27096774 1.65806452
[166,] -7.53225806 14.27096774
[167,] 16.31333333 -7.53225806
[168,] 23.89677419 16.31333333
[169,] -6.46774194 23.89677419
[170,] 7.07741935 -6.46774194
[171,] -29.43870968 7.07741935
[172,] 46.02580645 -29.43870968
[173,] 16.22903226 46.02580645
[174,] -32.44516129 16.22903226
[175,] 21.59354839 -32.44516129
[176,] 6.65806452 21.59354839
[177,] -27.12903226 6.65806452
[178,] -0.93225806 -27.12903226
[179,] -12.38666667 -0.93225806
[180,] -14.40322581 -12.38666667
[181,] 20.53225806 -14.40322581
[182,] 5.97741935 20.53225806
[183,] -16.13870968 5.97741935
[184,] 12.22580645 -16.13870968
[185,] 18.62903226 12.22580645
[186,] 7.35483871 18.62903226
[187,] 11.39354839 7.35483871
[188,] -7.84193548 11.39354839
[189,] -24.32903226 -7.84193548
[190,] 9.46774194 -24.32903226
[191,] 1.31333333 9.46774194
[192,] 15.59677419 1.31333333
[193,] 1.33225806 15.59677419
[194,] 0.47741935 1.33225806
[195,] 9.76129032 0.47741935
[196,] -19.77419355 9.76129032
[197,] 55.02903226 -19.77419355
[198,] -18.74516129 55.02903226
[199,] 11.79354839 -18.74516129
[200,] -9.04193548 11.79354839
[201,] 10.07096774 -9.04193548
[202,] -6.63225806 10.07096774
[203,] 21.11333333 -6.63225806
[204,] -13.20322581 21.11333333
[205,] 25.03225806 -13.20322581
[206,] -18.22258065 25.03225806
[207,] 7.26129032 -18.22258065
[208,] -11.57419355 7.26129032
[209,] 40.02903226 -11.57419355
[210,] -4.74516129 40.02903226
[211,] 15.19354839 -4.74516129
[212,] -2.14193548 15.19354839
[213,] 4.17096774 -2.14193548
[214,] 12.46774194 4.17096774
[215,] 28.71333333 12.46774194
[216,] 23.39677419 28.71333333
[217,] -10.36774194 23.39677419
[218,] -12.92258065 -10.36774194
[219,] -26.83870968 -12.92258065
[220,] -7.17419355 -26.83870968
[221,] 31.42903226 -7.17419355
[222,] -8.24516129 31.42903226
[223,] 14.69354839 -8.24516129
[224,] -11.64193548 14.69354839
[225,] 10.67096774 -11.64193548
[226,] -6.13225806 10.67096774
[227,] 24.91333333 -6.13225806
[228,] 7.39677419 24.91333333
[229,] 0.73225806 7.39677419
[230,] -9.92258065 0.73225806
[231,] 0.06129032 -9.92258065
[232,] -44.27419355 0.06129032
[233,] 15.12903226 -44.27419355
[234,] -0.44516129 15.12903226
[235,] -12.40645161 -0.44516129
[236,] -21.14193548 -12.40645161
[237,] 26.97096774 -21.14193548
[238,] 20.76774194 26.97096774
[239,] 38.91333333 20.76774194
[240,] -11.40322581 38.91333333
[241,] 13.53225806 -11.40322581
[242,] 4.87741935 13.53225806
[243,] -1.83870968 4.87741935
[244,] -58.37419355 -1.83870968
[245,] 17.02903226 -58.37419355
[246,] 13.35483871 17.02903226
[247,] -0.60645161 13.35483871
[248,] -5.74193548 -0.60645161
[249,] 15.47096774 -5.74193548
[250,] 18.26774194 15.47096774
[251,] 28.61333333 18.26774194
[252,] 5.09677419 28.61333333
[253,] -4.66774194 5.09677419
[254,] -18.42258065 -4.66774194
[255,] 3.66129032 -18.42258065
[256,] -36.27419355 3.66129032
[257,] -1.97096774 -36.27419355
[258,] 0.05483871 -1.97096774
[259,] -25.90645161 0.05483871
[260,] -3.64193548 -25.90645161
[261,] 35.07096774 -3.64193548
[262,] 10.76774194 35.07096774
[263,] -3.58666667 10.76774194
[264,] -28.90322581 -3.58666667
[265,] -16.16774194 -28.90322581
[266,] -20.82258065 -16.16774194
[267,] -3.73870968 -20.82258065
[268,] -55.77419355 -3.73870968
[269,] -6.87096774 -55.77419355
[270,] -2.14516129 -6.87096774
[271,] -24.30645161 -2.14516129
[272,] -12.14193548 -24.30645161
[273,] -12.72903226 -12.14193548
[274,] -0.43225806 -12.72903226
[275,] -3.48666667 -0.43225806
[276,] 7.09677419 -3.48666667
[277,] 4.43225806 7.09677419
[278,] 9.17741935 4.43225806
[279,] 9.46129032 9.17741935
[280,] -36.87419355 9.46129032
[281,] -6.77096774 -36.87419355
[282,] -4.24516129 -6.77096774
[283,] 4.99354839 -4.24516129
[284,] 11.55806452 4.99354839
[285,] -2.42903226 11.55806452
[286,] 14.46774194 -2.42903226
[287,] -0.88666667 14.46774194
[288,] 13.39677419 -0.88666667
[289,] -2.56774194 13.39677419
[290,] 12.87741935 -2.56774194
[291,] 14.76129032 12.87741935
[292,] -35.47419355 14.76129032
[293,] 2.52903226 -35.47419355
[294,] 0.45483871 2.52903226
[295,] 2.79354839 0.45483871
[296,] 3.35806452 2.79354839
[297,] 42.47096774 3.35806452
[298,] 17.46774194 42.47096774
[299,] 18.41333333 17.46774194
[300,] -7.10322581 18.41333333
[301,] 11.03225806 -7.10322581
[302,] -5.12258065 11.03225806
[303,] 16.96129032 -5.12258065
[304,] -32.07419355 16.96129032
[305,] 6.92903226 -32.07419355
[306,] 3.05483871 6.92903226
[307,] -12.80645161 3.05483871
[308,] 24.75806452 -12.80645161
[309,] -7.22903226 24.75806452
[310,] 2.26774194 -7.22903226
[311,] -20.68666667 2.26774194
[312,] -3.30322581 -20.68666667
[313,] 16.23225806 -3.30322581
[314,] 6.47741935 16.23225806
[315,] -4.83870968 6.47741935
[316,] -50.87419355 -4.83870968
[317,] -10.77096774 -50.87419355
[318,] 6.35483871 -10.77096774
[319,] -48.80645161 6.35483871
[320,] 0.35806452 -48.80645161
[321,] -42.02903226 0.35806452
[322,] -39.63225806 -42.02903226
[323,] -133.08666667 -39.63225806
[324,] -3.00322581 -133.08666667
[325,] -27.26774194 -3.00322581
[326,] 14.97741935 -27.26774194
[327,] -0.83870968 14.97741935
[328,] -21.87419355 -0.83870968
[329,] 13.22903226 -21.87419355
[330,] 20.15483871 13.22903226
[331,] 0.29354839 20.15483871
[332,] 12.35806452 0.29354839
[333,] 23.37096774 12.35806452
[334,] 6.06774194 23.37096774
[335,] -23.58666667 6.06774194
[336,] 23.99677419 -23.58666667
[337,] 28.53225806 23.99677419
[338,] 24.57741935 28.53225806
[339,] 38.06129032 24.57741935
[340,] -62.37419355 38.06129032
[341,] -14.97096774 -62.37419355
[342,] -5.64516129 -14.97096774
[343,] 12.49354839 -5.64516129
[344,] 3.85806452 12.49354839
[345,] -4.12903226 3.85806452
[346,] 9.76774194 -4.12903226
[347,] -8.28666667 9.76774194
[348,] -16.20322581 -8.28666667
[349,] 33.03225806 -16.20322581
[350,] 59.87741935 33.03225806
[351,] 21.16129032 59.87741935
[352,] -57.47419355 21.16129032
[353,] 28.42903226 -57.47419355
[354,] -12.74516129 28.42903226
[355,] 14.89354839 -12.74516129
[356,] 6.15806452 14.89354839
[357,] 9.57096774 6.15806452
[358,] 49.06774194 9.57096774
[359,] -27.38666667 49.06774194
[360,] 25.69677419 -27.38666667
[361,] 3.73225806 25.69677419
[362,] 40.17741935 3.73225806
[363,] 2.56129032 40.17741935
[364,] -14.17419355 2.56129032
[365,] -33.97096774 -14.17419355
[366,] 19.55483871 -33.97096774
[367,] -3.70645161 19.55483871
[368,] 18.25806452 -3.70645161
[369,] 5.17096774 18.25806452
[370,] -7.13225806 5.17096774
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -6.16774194 -35.70322581
2 -15.02258065 -6.16774194
3 18.76129032 -15.02258065
4 33.32580645 18.76129032
5 -23.07096774 33.32580645
6 -13.84516129 -23.07096774
7 0.59354839 -13.84516129
8 15.95806452 0.59354839
9 -6.52903226 15.95806452
10 -14.73225806 -6.52903226
11 -4.68666667 -14.73225806
12 -38.00322581 -4.68666667
13 -13.16774194 -38.00322581
14 -28.32258065 -13.16774194
15 -44.43870968 -28.32258065
16 27.72580645 -44.43870968
17 -64.97096774 27.72580645
18 12.05483871 -64.97096774
19 14.99354839 12.05483871
20 -30.74193548 14.99354839
21 43.87096774 -30.74193548
22 -9.53225806 43.87096774
23 -21.48666667 -9.53225806
24 -4.40322581 -21.48666667
25 25.53225806 -4.40322581
26 25.87741935 25.53225806
27 19.66129032 25.87741935
28 43.92580645 19.66129032
29 0.72903226 43.92580645
30 39.15483871 0.72903226
31 -4.80645161 39.15483871
32 28.05806452 -4.80645161
33 -8.02903226 28.05806452
34 -2.83225806 -8.02903226
35 50.31333333 -2.83225806
36 20.99677419 50.31333333
37 -0.76774194 20.99677419
38 -0.42258065 -0.76774194
39 -3.73870968 -0.42258065
40 36.52580645 -3.73870968
41 -16.77096774 36.52580645
42 -4.54516129 -16.77096774
43 -25.10645161 -4.54516129
44 -2.24193548 -25.10645161
45 -1.52903226 -2.24193548
46 21.86774194 -1.52903226
47 28.11333333 21.86774194
48 1.69677419 28.11333333
49 11.53225806 1.69677419
50 -22.32258065 11.53225806
51 -15.13870968 -22.32258065
52 47.72580645 -15.13870968
53 -28.07096774 47.72580645
54 -14.44516129 -28.07096774
55 1.89354839 -14.44516129
56 9.35806452 1.89354839
57 10.67096774 9.35806452
58 7.36774194 10.67096774
59 15.61333333 7.36774194
60 26.69677419 15.61333333
61 -8.66774194 26.69677419
62 -32.52258065 -8.66774194
63 2.26129032 -32.52258065
64 53.12580645 2.26129032
65 -20.57096774 53.12580645
66 -11.34516129 -20.57096774
67 -27.80645161 -11.34516129
68 -10.74193548 -27.80645161
69 -22.42903226 -10.74193548
70 -32.23225806 -22.42903226
71 -45.38666667 -32.23225806
72 -32.30322581 -45.38666667
73 -27.66774194 -32.30322581
74 -19.82258065 -27.66774194
75 -1.73870968 -19.82258065
76 70.42580645 -1.73870968
77 -22.57096774 70.42580645
78 -10.24516129 -22.57096774
79 -13.40645161 -10.24516129
80 34.95806452 -13.40645161
81 3.47096774 34.95806452
82 13.06774194 3.47096774
83 8.31333333 13.06774194
84 19.89677419 8.31333333
85 4.93225806 19.89677419
86 -25.42258065 4.93225806
87 26.66129032 -25.42258065
88 52.42580645 26.66129032
89 0.32903226 52.42580645
90 -18.54516129 0.32903226
91 2.69354839 -18.54516129
92 -10.04193548 2.69354839
93 -3.12903226 -10.04193548
94 -4.03225806 -3.12903226
95 27.81333333 -4.03225806
96 7.29677419 27.81333333
97 -22.56774194 7.29677419
98 -0.42258065 -22.56774194
99 -29.43870968 -0.42258065
100 34.72580645 -29.43870968
101 -3.27096774 34.72580645
102 20.55483871 -3.27096774
103 2.29354839 20.55483871
104 2.75806452 2.29354839
105 -28.72903226 2.75806452
106 -3.63225806 -28.72903226
107 19.71333333 -3.63225806
108 21.99677419 19.71333333
109 4.03225806 21.99677419
110 -19.42258065 4.03225806
111 -21.33870968 -19.42258065
112 23.12580645 -21.33870968
113 6.02903226 23.12580645
114 0.55483871 6.02903226
115 -14.80645161 0.55483871
116 -11.64193548 -14.80645161
117 -44.12903226 -11.64193548
118 -18.03225806 -44.12903226
119 -38.88666667 -18.03225806
120 -55.30322581 -38.88666667
121 -26.16774194 -55.30322581
122 -29.82258065 -26.16774194
123 2.66129032 -29.82258065
124 33.62580645 2.66129032
125 -10.27096774 33.62580645
126 17.95483871 -10.27096774
127 37.79354839 17.95483871
128 15.35806452 37.79354839
129 18.57096774 15.35806452
130 -25.83225806 18.57096774
131 13.31333333 -25.83225806
132 7.89677419 13.31333333
133 17.73225806 7.89677419
134 35.07741935 17.73225806
135 2.56129032 35.07741935
136 27.42580645 2.56129032
137 -5.27096774 27.42580645
138 -5.34516129 -5.27096774
139 -1.90645161 -5.34516129
140 -19.04193548 -1.90645161
141 -18.42903226 -19.04193548
142 13.96774194 -18.42903226
143 14.51333333 13.96774194
144 33.19677419 14.51333333
145 -50.06774194 33.19677419
146 16.77741935 -50.06774194
147 2.16129032 16.77741935
148 -6.47419355 2.16129032
149 6.02903226 -6.47419355
150 -13.84516129 6.02903226
151 22.49354839 -13.84516129
152 -37.64193548 22.49354839
153 -20.92903226 -37.64193548
154 -47.83225806 -20.92903226
155 -12.18666667 -47.83225806
156 -22.00322581 -12.18666667
157 0.83225806 -22.00322581
158 14.67741935 0.83225806
159 1.06129032 14.67741935
160 8.52580645 1.06129032
161 12.42903226 8.52580645
162 20.95483871 12.42903226
163 23.49354839 20.95483871
164 1.65806452 23.49354839
165 14.27096774 1.65806452
166 -7.53225806 14.27096774
167 16.31333333 -7.53225806
168 23.89677419 16.31333333
169 -6.46774194 23.89677419
170 7.07741935 -6.46774194
171 -29.43870968 7.07741935
172 46.02580645 -29.43870968
173 16.22903226 46.02580645
174 -32.44516129 16.22903226
175 21.59354839 -32.44516129
176 6.65806452 21.59354839
177 -27.12903226 6.65806452
178 -0.93225806 -27.12903226
179 -12.38666667 -0.93225806
180 -14.40322581 -12.38666667
181 20.53225806 -14.40322581
182 5.97741935 20.53225806
183 -16.13870968 5.97741935
184 12.22580645 -16.13870968
185 18.62903226 12.22580645
186 7.35483871 18.62903226
187 11.39354839 7.35483871
188 -7.84193548 11.39354839
189 -24.32903226 -7.84193548
190 9.46774194 -24.32903226
191 1.31333333 9.46774194
192 15.59677419 1.31333333
193 1.33225806 15.59677419
194 0.47741935 1.33225806
195 9.76129032 0.47741935
196 -19.77419355 9.76129032
197 55.02903226 -19.77419355
198 -18.74516129 55.02903226
199 11.79354839 -18.74516129
200 -9.04193548 11.79354839
201 10.07096774 -9.04193548
202 -6.63225806 10.07096774
203 21.11333333 -6.63225806
204 -13.20322581 21.11333333
205 25.03225806 -13.20322581
206 -18.22258065 25.03225806
207 7.26129032 -18.22258065
208 -11.57419355 7.26129032
209 40.02903226 -11.57419355
210 -4.74516129 40.02903226
211 15.19354839 -4.74516129
212 -2.14193548 15.19354839
213 4.17096774 -2.14193548
214 12.46774194 4.17096774
215 28.71333333 12.46774194
216 23.39677419 28.71333333
217 -10.36774194 23.39677419
218 -12.92258065 -10.36774194
219 -26.83870968 -12.92258065
220 -7.17419355 -26.83870968
221 31.42903226 -7.17419355
222 -8.24516129 31.42903226
223 14.69354839 -8.24516129
224 -11.64193548 14.69354839
225 10.67096774 -11.64193548
226 -6.13225806 10.67096774
227 24.91333333 -6.13225806
228 7.39677419 24.91333333
229 0.73225806 7.39677419
230 -9.92258065 0.73225806
231 0.06129032 -9.92258065
232 -44.27419355 0.06129032
233 15.12903226 -44.27419355
234 -0.44516129 15.12903226
235 -12.40645161 -0.44516129
236 -21.14193548 -12.40645161
237 26.97096774 -21.14193548
238 20.76774194 26.97096774
239 38.91333333 20.76774194
240 -11.40322581 38.91333333
241 13.53225806 -11.40322581
242 4.87741935 13.53225806
243 -1.83870968 4.87741935
244 -58.37419355 -1.83870968
245 17.02903226 -58.37419355
246 13.35483871 17.02903226
247 -0.60645161 13.35483871
248 -5.74193548 -0.60645161
249 15.47096774 -5.74193548
250 18.26774194 15.47096774
251 28.61333333 18.26774194
252 5.09677419 28.61333333
253 -4.66774194 5.09677419
254 -18.42258065 -4.66774194
255 3.66129032 -18.42258065
256 -36.27419355 3.66129032
257 -1.97096774 -36.27419355
258 0.05483871 -1.97096774
259 -25.90645161 0.05483871
260 -3.64193548 -25.90645161
261 35.07096774 -3.64193548
262 10.76774194 35.07096774
263 -3.58666667 10.76774194
264 -28.90322581 -3.58666667
265 -16.16774194 -28.90322581
266 -20.82258065 -16.16774194
267 -3.73870968 -20.82258065
268 -55.77419355 -3.73870968
269 -6.87096774 -55.77419355
270 -2.14516129 -6.87096774
271 -24.30645161 -2.14516129
272 -12.14193548 -24.30645161
273 -12.72903226 -12.14193548
274 -0.43225806 -12.72903226
275 -3.48666667 -0.43225806
276 7.09677419 -3.48666667
277 4.43225806 7.09677419
278 9.17741935 4.43225806
279 9.46129032 9.17741935
280 -36.87419355 9.46129032
281 -6.77096774 -36.87419355
282 -4.24516129 -6.77096774
283 4.99354839 -4.24516129
284 11.55806452 4.99354839
285 -2.42903226 11.55806452
286 14.46774194 -2.42903226
287 -0.88666667 14.46774194
288 13.39677419 -0.88666667
289 -2.56774194 13.39677419
290 12.87741935 -2.56774194
291 14.76129032 12.87741935
292 -35.47419355 14.76129032
293 2.52903226 -35.47419355
294 0.45483871 2.52903226
295 2.79354839 0.45483871
296 3.35806452 2.79354839
297 42.47096774 3.35806452
298 17.46774194 42.47096774
299 18.41333333 17.46774194
300 -7.10322581 18.41333333
301 11.03225806 -7.10322581
302 -5.12258065 11.03225806
303 16.96129032 -5.12258065
304 -32.07419355 16.96129032
305 6.92903226 -32.07419355
306 3.05483871 6.92903226
307 -12.80645161 3.05483871
308 24.75806452 -12.80645161
309 -7.22903226 24.75806452
310 2.26774194 -7.22903226
311 -20.68666667 2.26774194
312 -3.30322581 -20.68666667
313 16.23225806 -3.30322581
314 6.47741935 16.23225806
315 -4.83870968 6.47741935
316 -50.87419355 -4.83870968
317 -10.77096774 -50.87419355
318 6.35483871 -10.77096774
319 -48.80645161 6.35483871
320 0.35806452 -48.80645161
321 -42.02903226 0.35806452
322 -39.63225806 -42.02903226
323 -133.08666667 -39.63225806
324 -3.00322581 -133.08666667
325 -27.26774194 -3.00322581
326 14.97741935 -27.26774194
327 -0.83870968 14.97741935
328 -21.87419355 -0.83870968
329 13.22903226 -21.87419355
330 20.15483871 13.22903226
331 0.29354839 20.15483871
332 12.35806452 0.29354839
333 23.37096774 12.35806452
334 6.06774194 23.37096774
335 -23.58666667 6.06774194
336 23.99677419 -23.58666667
337 28.53225806 23.99677419
338 24.57741935 28.53225806
339 38.06129032 24.57741935
340 -62.37419355 38.06129032
341 -14.97096774 -62.37419355
342 -5.64516129 -14.97096774
343 12.49354839 -5.64516129
344 3.85806452 12.49354839
345 -4.12903226 3.85806452
346 9.76774194 -4.12903226
347 -8.28666667 9.76774194
348 -16.20322581 -8.28666667
349 33.03225806 -16.20322581
350 59.87741935 33.03225806
351 21.16129032 59.87741935
352 -57.47419355 21.16129032
353 28.42903226 -57.47419355
354 -12.74516129 28.42903226
355 14.89354839 -12.74516129
356 6.15806452 14.89354839
357 9.57096774 6.15806452
358 49.06774194 9.57096774
359 -27.38666667 49.06774194
360 25.69677419 -27.38666667
361 3.73225806 25.69677419
362 40.17741935 3.73225806
363 2.56129032 40.17741935
364 -14.17419355 2.56129032
365 -33.97096774 -14.17419355
366 19.55483871 -33.97096774
367 -3.70645161 19.55483871
368 18.25806452 -3.70645161
369 5.17096774 18.25806452
370 -7.13225806 5.17096774
> plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
> lines(lowess(z))
> abline(lm(z))
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/7hgtd1322152751.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/8zr951322152751.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/9l3i61322152751.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/rcomp/tmp/10o0z31322152751.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
+ myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ')
+ if (rownames(mysum$coefficients)[i] != '(Intercept)') {
+ myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
+ if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
+ }
+ }
> myeq <- paste(myeq, ' + e[t]')
> a<-table.row.start(a)
> a<-table.element(a, myeq)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/rcomp/tmp/11apsn1322152751.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Variable',header=TRUE)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
> a<-table.element(a,'2-tail p-value',header=TRUE)
> a<-table.element(a,'1-tail p-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:k){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
+ a<-table.element(a,mysum$coefficients[i,1])
+ a<-table.element(a, round(mysum$coefficients[i,2],6))
+ a<-table.element(a, round(mysum$coefficients[i,3],4))
+ a<-table.element(a, round(mysum$coefficients[i,4],6))
+ a<-table.element(a, round(mysum$coefficients[i,4]/2,6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/rcomp/tmp/12wzzy1322152751.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple R',1,TRUE)
> a<-table.element(a, sqrt(mysum$r.squared))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'R-squared',1,TRUE)
> a<-table.element(a, mysum$r.squared)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Adjusted R-squared',1,TRUE)
> a<-table.element(a, mysum$adj.r.squared)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (value)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[1])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[2])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[3])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'p-value',1,TRUE)
> a<-table.element(a, 1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
> a<-table.element(a, mysum$sigma)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a, sum(myerror*myerror))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/rcomp/tmp/13j4dd1322152751.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Time or Index', 1, TRUE)
> a<-table.element(a, 'Actuals', 1, TRUE)
> a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
> a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
> a<-table.row.end(a)
> for (i in 1:n) {
+ a<-table.row.start(a)
+ a<-table.element(a,i, 1, TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]-mysum$resid[i])
+ a<-table.element(a,mysum$resid[i])
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/rcomp/tmp/143k7k1322152751.tab")
> if (n > n25) {
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'p-values',header=TRUE)
+ a<-table.element(a,'Alternative Hypothesis',3,header=TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'breakpoint index',header=TRUE)
+ a<-table.element(a,'greater',header=TRUE)
+ a<-table.element(a,'2-sided',header=TRUE)
+ a<-table.element(a,'less',header=TRUE)
+ a<-table.row.end(a)
+ for (mypoint in kp3:nmkm3) {
+ a<-table.row.start(a)
+ a<-table.element(a,mypoint,header=TRUE)
+ a<-table.element(a,gqarr[mypoint-kp3+1,1])
+ a<-table.element(a,gqarr[mypoint-kp3+1,2])
+ a<-table.element(a,gqarr[mypoint-kp3+1,3])
+ a<-table.row.end(a)
+ }
+ a<-table.end(a)
+ table.save(a,file="/var/www/rcomp/tmp/1501y01322152751.tab")
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'Description',header=TRUE)
+ a<-table.element(a,'# significant tests',header=TRUE)
+ a<-table.element(a,'% significant tests',header=TRUE)
+ a<-table.element(a,'OK/NOK',header=TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'1% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant1)
+ a<-table.element(a,numsignificant1/numgqtests)
+ if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'5% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant5)
+ a<-table.element(a,numsignificant5/numgqtests)
+ if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'10% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant10)
+ a<-table.element(a,numsignificant10/numgqtests)
+ if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.end(a)
+ table.save(a,file="/var/www/rcomp/tmp/16t86e1322152752.tab")
+ }
>
> try(system("convert tmp/15ttc1322152751.ps tmp/15ttc1322152751.png",intern=TRUE))
character(0)
> try(system("convert tmp/2klht1322152751.ps tmp/2klht1322152751.png",intern=TRUE))
character(0)
> try(system("convert tmp/3eaqp1322152751.ps tmp/3eaqp1322152751.png",intern=TRUE))
character(0)
> try(system("convert tmp/4c67c1322152751.ps tmp/4c67c1322152751.png",intern=TRUE))
character(0)
> try(system("convert tmp/52j4f1322152751.ps tmp/52j4f1322152751.png",intern=TRUE))
character(0)
> try(system("convert tmp/6ty6u1322152751.ps tmp/6ty6u1322152751.png",intern=TRUE))
character(0)
> try(system("convert tmp/7hgtd1322152751.ps tmp/7hgtd1322152751.png",intern=TRUE))
character(0)
> try(system("convert tmp/8zr951322152751.ps tmp/8zr951322152751.png",intern=TRUE))
character(0)
> try(system("convert tmp/9l3i61322152751.ps tmp/9l3i61322152751.png",intern=TRUE))
character(0)
> try(system("convert tmp/10o0z31322152751.ps tmp/10o0z31322152751.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
10.170 0.500 10.661