R version 2.9.0 (2009-04-17)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> x <- array(list(206010
+ ,0
+ ,198112
+ ,0
+ ,194519
+ ,0
+ ,185705
+ ,0
+ ,180173
+ ,0
+ ,176142
+ ,0
+ ,203401
+ ,0
+ ,221902
+ ,0
+ ,197378
+ ,0
+ ,185001
+ ,0
+ ,176356
+ ,0
+ ,180449
+ ,0
+ ,180144
+ ,0
+ ,173666
+ ,0
+ ,165688
+ ,0
+ ,161570
+ ,0
+ ,156145
+ ,0
+ ,153730
+ ,0
+ ,182698
+ ,0
+ ,200765
+ ,0
+ ,176512
+ ,0
+ ,166618
+ ,0
+ ,158644
+ ,0
+ ,159585
+ ,0
+ ,163095
+ ,0
+ ,159044
+ ,0
+ ,155511
+ ,0
+ ,153745
+ ,0
+ ,150569
+ ,0
+ ,150605
+ ,0
+ ,179612
+ ,0
+ ,194690
+ ,0
+ ,189917
+ ,0
+ ,184128
+ ,0
+ ,175335
+ ,0
+ ,179566
+ ,0
+ ,181140
+ ,0
+ ,177876
+ ,0
+ ,175041
+ ,0
+ ,169292
+ ,0
+ ,166070
+ ,0
+ ,166972
+ ,0
+ ,206348
+ ,0
+ ,215706
+ ,0
+ ,202108
+ ,0
+ ,195411
+ ,0
+ ,193111
+ ,0
+ ,195198
+ ,0
+ ,198770
+ ,0
+ ,194163
+ ,0
+ ,190420
+ ,0
+ ,189733
+ ,0
+ ,186029
+ ,0
+ ,191531
+ ,0
+ ,232571
+ ,0
+ ,243477
+ ,0
+ ,227247
+ ,0
+ ,217859
+ ,0
+ ,208679
+ ,0
+ ,213188
+ ,0
+ ,216234
+ ,0
+ ,213586
+ ,0
+ ,209465
+ ,0
+ ,204045
+ ,0
+ ,200237
+ ,0
+ ,203666
+ ,0
+ ,241476
+ ,0
+ ,260307
+ ,0
+ ,243324
+ ,0
+ ,244460
+ ,0
+ ,233575
+ ,0
+ ,237217
+ ,0
+ ,235243
+ ,0
+ ,230354
+ ,0
+ ,227184
+ ,0
+ ,221678
+ ,0
+ ,217142
+ ,0
+ ,219452
+ ,0
+ ,256446
+ ,0
+ ,265845
+ ,0
+ ,248624
+ ,0
+ ,241114
+ ,0
+ ,229245
+ ,0
+ ,231805
+ ,0
+ ,219277
+ ,0
+ ,219313
+ ,0
+ ,212610
+ ,0
+ ,214771
+ ,0
+ ,211142
+ ,0
+ ,211457
+ ,0
+ ,240048
+ ,0
+ ,240636
+ ,0
+ ,230580
+ ,0
+ ,208795
+ ,0
+ ,197922
+ ,0
+ ,194596
+ ,0
+ ,194581
+ ,0
+ ,185686
+ ,0
+ ,178106
+ ,0
+ ,172608
+ ,0
+ ,167302
+ ,0
+ ,168053
+ ,0
+ ,202300
+ ,0
+ ,202388
+ ,0
+ ,182516
+ ,0
+ ,173476
+ ,0
+ ,166444
+ ,0
+ ,171297
+ ,0
+ ,169701
+ ,0
+ ,164182
+ ,0
+ ,161914
+ ,0
+ ,159612
+ ,0
+ ,151001
+ ,0
+ ,158114
+ ,0
+ ,186530
+ ,1
+ ,187069
+ ,1
+ ,174330
+ ,1
+ ,169362
+ ,1
+ ,166827
+ ,1
+ ,178037
+ ,1
+ ,186413
+ ,1
+ ,189226
+ ,1
+ ,191563
+ ,1
+ ,188906
+ ,1
+ ,186005
+ ,1
+ ,195309
+ ,1
+ ,223532
+ ,1
+ ,226899
+ ,1
+ ,214126
+ ,1
+ ,206903
+ ,1
+ ,204442
+ ,1
+ ,220375
+ ,1
+ ,214320
+ ,1
+ ,212588
+ ,1
+ ,205816
+ ,1
+ ,202196
+ ,1
+ ,195722
+ ,1
+ ,198563
+ ,1
+ ,229139
+ ,1
+ ,229527
+ ,1
+ ,211868
+ ,1
+ ,203555
+ ,1
+ ,195770
+ ,1)
+ ,dim=c(2
+ ,143)
+ ,dimnames=list(c('Werkloosheid'
+ ,'Dummy_crisis')
+ ,1:143))
> y <- array(NA,dim=c(2,143),dimnames=list(c('Werkloosheid','Dummy_crisis'),1:143))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par3 = 'Linear Trend'
> par2 = 'Include Monthly Dummies'
> par1 = '1'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: Write here your technical program description (don't use hard returns!)
> library(lattice)
> library(lmtest)
Loading required package: zoo
Attaching package: 'zoo'
The following object(s) are masked from package:base :
as.Date.numeric
> n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
> par1 <- as.numeric(par1)
> x <- t(y)
> k <- length(x[1,])
> n <- length(x[,1])
> x1 <- cbind(x[,par1], x[,1:k!=par1])
> mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
> colnames(x1) <- mycolnames #colnames(x)[par1]
> x <- x1
> if (par3 == 'First Differences'){
+ x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
+ for (i in 1:n-1) {
+ for (j in 1:k) {
+ x2[i,j] <- x[i+1,j] - x[i,j]
+ }
+ }
+ x <- x2
+ }
> if (par2 == 'Include Monthly Dummies'){
+ x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
+ for (i in 1:11){
+ x2[seq(i,n,12),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> if (par2 == 'Include Quarterly Dummies'){
+ x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
+ for (i in 1:3){
+ x2[seq(i,n,4),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> k <- length(x[1,])
> if (par3 == 'Linear Trend'){
+ x <- cbind(x, c(1:n))
+ colnames(x)[k+1] <- 't'
+ }
> x
Werkloosheid Dummy_crisis M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 206010 0 1 0 0 0 0 0 0 0 0 0 0 1
2 198112 0 0 1 0 0 0 0 0 0 0 0 0 2
3 194519 0 0 0 1 0 0 0 0 0 0 0 0 3
4 185705 0 0 0 0 1 0 0 0 0 0 0 0 4
5 180173 0 0 0 0 0 1 0 0 0 0 0 0 5
6 176142 0 0 0 0 0 0 1 0 0 0 0 0 6
7 203401 0 0 0 0 0 0 0 1 0 0 0 0 7
8 221902 0 0 0 0 0 0 0 0 1 0 0 0 8
9 197378 0 0 0 0 0 0 0 0 0 1 0 0 9
10 185001 0 0 0 0 0 0 0 0 0 0 1 0 10
11 176356 0 0 0 0 0 0 0 0 0 0 0 1 11
12 180449 0 0 0 0 0 0 0 0 0 0 0 0 12
13 180144 0 1 0 0 0 0 0 0 0 0 0 0 13
14 173666 0 0 1 0 0 0 0 0 0 0 0 0 14
15 165688 0 0 0 1 0 0 0 0 0 0 0 0 15
16 161570 0 0 0 0 1 0 0 0 0 0 0 0 16
17 156145 0 0 0 0 0 1 0 0 0 0 0 0 17
18 153730 0 0 0 0 0 0 1 0 0 0 0 0 18
19 182698 0 0 0 0 0 0 0 1 0 0 0 0 19
20 200765 0 0 0 0 0 0 0 0 1 0 0 0 20
21 176512 0 0 0 0 0 0 0 0 0 1 0 0 21
22 166618 0 0 0 0 0 0 0 0 0 0 1 0 22
23 158644 0 0 0 0 0 0 0 0 0 0 0 1 23
24 159585 0 0 0 0 0 0 0 0 0 0 0 0 24
25 163095 0 1 0 0 0 0 0 0 0 0 0 0 25
26 159044 0 0 1 0 0 0 0 0 0 0 0 0 26
27 155511 0 0 0 1 0 0 0 0 0 0 0 0 27
28 153745 0 0 0 0 1 0 0 0 0 0 0 0 28
29 150569 0 0 0 0 0 1 0 0 0 0 0 0 29
30 150605 0 0 0 0 0 0 1 0 0 0 0 0 30
31 179612 0 0 0 0 0 0 0 1 0 0 0 0 31
32 194690 0 0 0 0 0 0 0 0 1 0 0 0 32
33 189917 0 0 0 0 0 0 0 0 0 1 0 0 33
34 184128 0 0 0 0 0 0 0 0 0 0 1 0 34
35 175335 0 0 0 0 0 0 0 0 0 0 0 1 35
36 179566 0 0 0 0 0 0 0 0 0 0 0 0 36
37 181140 0 1 0 0 0 0 0 0 0 0 0 0 37
38 177876 0 0 1 0 0 0 0 0 0 0 0 0 38
39 175041 0 0 0 1 0 0 0 0 0 0 0 0 39
40 169292 0 0 0 0 1 0 0 0 0 0 0 0 40
41 166070 0 0 0 0 0 1 0 0 0 0 0 0 41
42 166972 0 0 0 0 0 0 1 0 0 0 0 0 42
43 206348 0 0 0 0 0 0 0 1 0 0 0 0 43
44 215706 0 0 0 0 0 0 0 0 1 0 0 0 44
45 202108 0 0 0 0 0 0 0 0 0 1 0 0 45
46 195411 0 0 0 0 0 0 0 0 0 0 1 0 46
47 193111 0 0 0 0 0 0 0 0 0 0 0 1 47
48 195198 0 0 0 0 0 0 0 0 0 0 0 0 48
49 198770 0 1 0 0 0 0 0 0 0 0 0 0 49
50 194163 0 0 1 0 0 0 0 0 0 0 0 0 50
51 190420 0 0 0 1 0 0 0 0 0 0 0 0 51
52 189733 0 0 0 0 1 0 0 0 0 0 0 0 52
53 186029 0 0 0 0 0 1 0 0 0 0 0 0 53
54 191531 0 0 0 0 0 0 1 0 0 0 0 0 54
55 232571 0 0 0 0 0 0 0 1 0 0 0 0 55
56 243477 0 0 0 0 0 0 0 0 1 0 0 0 56
57 227247 0 0 0 0 0 0 0 0 0 1 0 0 57
58 217859 0 0 0 0 0 0 0 0 0 0 1 0 58
59 208679 0 0 0 0 0 0 0 0 0 0 0 1 59
60 213188 0 0 0 0 0 0 0 0 0 0 0 0 60
61 216234 0 1 0 0 0 0 0 0 0 0 0 0 61
62 213586 0 0 1 0 0 0 0 0 0 0 0 0 62
63 209465 0 0 0 1 0 0 0 0 0 0 0 0 63
64 204045 0 0 0 0 1 0 0 0 0 0 0 0 64
65 200237 0 0 0 0 0 1 0 0 0 0 0 0 65
66 203666 0 0 0 0 0 0 1 0 0 0 0 0 66
67 241476 0 0 0 0 0 0 0 1 0 0 0 0 67
68 260307 0 0 0 0 0 0 0 0 1 0 0 0 68
69 243324 0 0 0 0 0 0 0 0 0 1 0 0 69
70 244460 0 0 0 0 0 0 0 0 0 0 1 0 70
71 233575 0 0 0 0 0 0 0 0 0 0 0 1 71
72 237217 0 0 0 0 0 0 0 0 0 0 0 0 72
73 235243 0 1 0 0 0 0 0 0 0 0 0 0 73
74 230354 0 0 1 0 0 0 0 0 0 0 0 0 74
75 227184 0 0 0 1 0 0 0 0 0 0 0 0 75
76 221678 0 0 0 0 1 0 0 0 0 0 0 0 76
77 217142 0 0 0 0 0 1 0 0 0 0 0 0 77
78 219452 0 0 0 0 0 0 1 0 0 0 0 0 78
79 256446 0 0 0 0 0 0 0 1 0 0 0 0 79
80 265845 0 0 0 0 0 0 0 0 1 0 0 0 80
81 248624 0 0 0 0 0 0 0 0 0 1 0 0 81
82 241114 0 0 0 0 0 0 0 0 0 0 1 0 82
83 229245 0 0 0 0 0 0 0 0 0 0 0 1 83
84 231805 0 0 0 0 0 0 0 0 0 0 0 0 84
85 219277 0 1 0 0 0 0 0 0 0 0 0 0 85
86 219313 0 0 1 0 0 0 0 0 0 0 0 0 86
87 212610 0 0 0 1 0 0 0 0 0 0 0 0 87
88 214771 0 0 0 0 1 0 0 0 0 0 0 0 88
89 211142 0 0 0 0 0 1 0 0 0 0 0 0 89
90 211457 0 0 0 0 0 0 1 0 0 0 0 0 90
91 240048 0 0 0 0 0 0 0 1 0 0 0 0 91
92 240636 0 0 0 0 0 0 0 0 1 0 0 0 92
93 230580 0 0 0 0 0 0 0 0 0 1 0 0 93
94 208795 0 0 0 0 0 0 0 0 0 0 1 0 94
95 197922 0 0 0 0 0 0 0 0 0 0 0 1 95
96 194596 0 0 0 0 0 0 0 0 0 0 0 0 96
97 194581 0 1 0 0 0 0 0 0 0 0 0 0 97
98 185686 0 0 1 0 0 0 0 0 0 0 0 0 98
99 178106 0 0 0 1 0 0 0 0 0 0 0 0 99
100 172608 0 0 0 0 1 0 0 0 0 0 0 0 100
101 167302 0 0 0 0 0 1 0 0 0 0 0 0 101
102 168053 0 0 0 0 0 0 1 0 0 0 0 0 102
103 202300 0 0 0 0 0 0 0 1 0 0 0 0 103
104 202388 0 0 0 0 0 0 0 0 1 0 0 0 104
105 182516 0 0 0 0 0 0 0 0 0 1 0 0 105
106 173476 0 0 0 0 0 0 0 0 0 0 1 0 106
107 166444 0 0 0 0 0 0 0 0 0 0 0 1 107
108 171297 0 0 0 0 0 0 0 0 0 0 0 0 108
109 169701 0 1 0 0 0 0 0 0 0 0 0 0 109
110 164182 0 0 1 0 0 0 0 0 0 0 0 0 110
111 161914 0 0 0 1 0 0 0 0 0 0 0 0 111
112 159612 0 0 0 0 1 0 0 0 0 0 0 0 112
113 151001 0 0 0 0 0 1 0 0 0 0 0 0 113
114 158114 0 0 0 0 0 0 1 0 0 0 0 0 114
115 186530 1 0 0 0 0 0 0 1 0 0 0 0 115
116 187069 1 0 0 0 0 0 0 0 1 0 0 0 116
117 174330 1 0 0 0 0 0 0 0 0 1 0 0 117
118 169362 1 0 0 0 0 0 0 0 0 0 1 0 118
119 166827 1 0 0 0 0 0 0 0 0 0 0 1 119
120 178037 1 0 0 0 0 0 0 0 0 0 0 0 120
121 186413 1 1 0 0 0 0 0 0 0 0 0 0 121
122 189226 1 0 1 0 0 0 0 0 0 0 0 0 122
123 191563 1 0 0 1 0 0 0 0 0 0 0 0 123
124 188906 1 0 0 0 1 0 0 0 0 0 0 0 124
125 186005 1 0 0 0 0 1 0 0 0 0 0 0 125
126 195309 1 0 0 0 0 0 1 0 0 0 0 0 126
127 223532 1 0 0 0 0 0 0 1 0 0 0 0 127
128 226899 1 0 0 0 0 0 0 0 1 0 0 0 128
129 214126 1 0 0 0 0 0 0 0 0 1 0 0 129
130 206903 1 0 0 0 0 0 0 0 0 0 1 0 130
131 204442 1 0 0 0 0 0 0 0 0 0 0 1 131
132 220375 1 0 0 0 0 0 0 0 0 0 0 0 132
133 214320 1 1 0 0 0 0 0 0 0 0 0 0 133
134 212588 1 0 1 0 0 0 0 0 0 0 0 0 134
135 205816 1 0 0 1 0 0 0 0 0 0 0 0 135
136 202196 1 0 0 0 1 0 0 0 0 0 0 0 136
137 195722 1 0 0 0 0 1 0 0 0 0 0 0 137
138 198563 1 0 0 0 0 0 1 0 0 0 0 0 138
139 229139 1 0 0 0 0 0 0 1 0 0 0 0 139
140 229527 1 0 0 0 0 0 0 0 1 0 0 0 140
141 211868 1 0 0 0 0 0 0 0 0 1 0 0 141
142 203555 1 0 0 0 0 0 0 0 0 0 1 0 142
143 195770 1 0 0 0 0 0 0 0 0 0 0 1 143
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Dummy_crisis M1 M2 M3
181196.2 -17091.5 1612.8 -2570.4 -6989.1
M4 M5 M6 M7 M8
-10909.3 -15858.4 -13942.5 19768.6 28272.3
M9 M10 M11 t
12126.7 3383.9 -4399.2 255.5
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-43206 -17351 1739 17114 41996
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 181196.23 7910.81 22.905 < 2e-16 ***
Dummy_crisis -17091.52 6639.10 -2.574 0.011171 *
M1 1612.75 9529.67 0.169 0.865877
M2 -2570.39 9528.17 -0.270 0.787770
M3 -6989.12 9527.12 -0.734 0.464522
M4 -10909.26 9526.50 -1.145 0.254268
M5 -15858.40 9526.32 -1.665 0.098401 .
M6 -13942.46 9526.57 -1.464 0.145754
M7 19768.60 9534.88 2.073 0.040135 *
M8 28272.29 9533.40 2.966 0.003600 **
M9 12126.73 9532.36 1.272 0.205603
M10 3383.92 9531.76 0.355 0.723158
M11 -4399.22 9531.60 -0.462 0.645188
t 255.48 64.52 3.960 0.000123 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 22820 on 129 degrees of freedom
Multiple R-squared: 0.3168, Adjusted R-squared: 0.2479
F-statistic: 4.601 on 13 and 129 DF, p-value: 1.892e-06
> 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,] 4.515884e-04 9.031768e-04 9.995484e-01
[2,] 5.485343e-05 1.097069e-04 9.999451e-01
[3,] 1.173666e-05 2.347331e-05 9.999883e-01
[4,] 1.567478e-06 3.134957e-06 9.999984e-01
[5,] 2.080358e-07 4.160715e-07 9.999998e-01
[6,] 6.755330e-08 1.351066e-07 9.999999e-01
[7,] 2.101879e-08 4.203758e-08 1.000000e+00
[8,] 2.409749e-09 4.819498e-09 1.000000e+00
[9,] 4.618110e-10 9.236219e-10 1.000000e+00
[10,] 2.554913e-10 5.109826e-10 1.000000e+00
[11,] 2.207987e-10 4.415973e-10 1.000000e+00
[12,] 7.929248e-10 1.585850e-09 1.000000e+00
[13,] 2.019930e-09 4.039859e-09 1.000000e+00
[14,] 6.405195e-09 1.281039e-08 1.000000e+00
[15,] 1.248895e-08 2.497789e-08 1.000000e+00
[16,] 7.576110e-09 1.515222e-08 1.000000e+00
[17,] 4.884794e-07 9.769588e-07 9.999995e-01
[18,] 9.197599e-06 1.839520e-05 9.999908e-01
[19,] 4.040368e-05 8.080736e-05 9.999596e-01
[20,] 1.209918e-04 2.419835e-04 9.998790e-01
[21,] 1.546803e-04 3.093606e-04 9.998453e-01
[22,] 2.060680e-04 4.121359e-04 9.997939e-01
[23,] 2.712469e-04 5.424938e-04 9.997288e-01
[24,] 3.091064e-04 6.182127e-04 9.996909e-01
[25,] 3.543661e-04 7.087321e-04 9.996456e-01
[26,] 4.853700e-04 9.707400e-04 9.995146e-01
[27,] 1.170521e-03 2.341041e-03 9.988295e-01
[28,] 1.374410e-03 2.748819e-03 9.986256e-01
[29,] 1.871771e-03 3.743542e-03 9.981282e-01
[30,] 2.684342e-03 5.368684e-03 9.973157e-01
[31,] 4.590185e-03 9.180370e-03 9.954098e-01
[32,] 6.850538e-03 1.370108e-02 9.931495e-01
[33,] 7.536349e-03 1.507270e-02 9.924637e-01
[34,] 8.451989e-03 1.690398e-02 9.915480e-01
[35,] 9.530377e-03 1.906075e-02 9.904696e-01
[36,] 1.182150e-02 2.364300e-02 9.881785e-01
[37,] 1.440139e-02 2.880278e-02 9.855986e-01
[38,] 2.114706e-02 4.229412e-02 9.788529e-01
[39,] 3.607344e-02 7.214688e-02 9.639266e-01
[40,] 4.432173e-02 8.864346e-02 9.556783e-01
[41,] 5.257421e-02 1.051484e-01 9.474258e-01
[42,] 5.934483e-02 1.186897e-01 9.406552e-01
[43,] 6.329993e-02 1.265999e-01 9.367001e-01
[44,] 6.822598e-02 1.364520e-01 9.317740e-01
[45,] 6.267504e-02 1.253501e-01 9.373250e-01
[46,] 5.932164e-02 1.186433e-01 9.406784e-01
[47,] 5.618079e-02 1.123616e-01 9.438192e-01
[48,] 5.396518e-02 1.079304e-01 9.460348e-01
[49,] 5.189244e-02 1.037849e-01 9.481076e-01
[50,] 5.343059e-02 1.068612e-01 9.465694e-01
[51,] 5.200725e-02 1.040145e-01 9.479927e-01
[52,] 5.082136e-02 1.016427e-01 9.491786e-01
[53,] 4.810322e-02 9.620645e-02 9.518968e-01
[54,] 5.645163e-02 1.129033e-01 9.435484e-01
[55,] 5.777463e-02 1.155493e-01 9.422254e-01
[56,] 5.842888e-02 1.168578e-01 9.415711e-01
[57,] 4.914959e-02 9.829919e-02 9.508504e-01
[58,] 4.043061e-02 8.086122e-02 9.595694e-01
[59,] 3.343704e-02 6.687408e-02 9.665630e-01
[60,] 2.664453e-02 5.328907e-02 9.733555e-01
[61,] 2.098045e-02 4.196089e-02 9.790196e-01
[62,] 1.649712e-02 3.299424e-02 9.835029e-01
[63,] 1.519924e-02 3.039849e-02 9.848008e-01
[64,] 1.566228e-02 3.132456e-02 9.843377e-01
[65,] 1.605471e-02 3.210942e-02 9.839453e-01
[66,] 1.875494e-02 3.750988e-02 9.812451e-01
[67,] 2.028934e-02 4.057867e-02 9.797107e-01
[68,] 2.269393e-02 4.538785e-02 9.773061e-01
[69,] 2.314009e-02 4.628018e-02 9.768599e-01
[70,] 2.441076e-02 4.882152e-02 9.755892e-01
[71,] 2.584214e-02 5.168427e-02 9.741579e-01
[72,] 3.160477e-02 6.320954e-02 9.683952e-01
[73,] 4.582831e-02 9.165662e-02 9.541717e-01
[74,] 6.511622e-02 1.302324e-01 9.348838e-01
[75,] 1.075092e-01 2.150183e-01 8.924908e-01
[76,] 2.129677e-01 4.259354e-01 7.870323e-01
[77,] 4.702435e-01 9.404871e-01 5.297565e-01
[78,] 7.097990e-01 5.804020e-01 2.902010e-01
[79,] 8.849497e-01 2.301007e-01 1.150503e-01
[80,] 9.395794e-01 1.208412e-01 6.042058e-02
[81,] 9.756884e-01 4.862317e-02 2.431158e-02
[82,] 9.886567e-01 2.268666e-02 1.134333e-02
[83,] 9.938214e-01 1.235718e-02 6.178588e-03
[84,] 9.963483e-01 7.303361e-03 3.651680e-03
[85,] 9.980409e-01 3.918236e-03 1.959118e-03
[86,] 9.985767e-01 2.846591e-03 1.423295e-03
[87,] 9.992886e-01 1.422849e-03 7.114245e-04
[88,] 9.997548e-01 4.903769e-04 2.451885e-04
[89,] 9.998963e-01 2.074756e-04 1.037378e-04
[90,] 9.999572e-01 8.559874e-05 4.279937e-05
[91,] 9.999828e-01 3.447889e-05 1.723945e-05
[92,] 9.999761e-01 4.789138e-05 2.394569e-05
[93,] 9.999648e-01 7.048080e-05 3.524040e-05
[94,] 9.999393e-01 1.213061e-04 6.065307e-05
[95,] 9.998882e-01 2.235658e-04 1.117829e-04
[96,] 9.997888e-01 4.224990e-04 2.112495e-04
[97,] 9.996035e-01 7.929457e-04 3.964729e-04
[98,] 9.992071e-01 1.585721e-03 7.928606e-04
[99,] 9.986912e-01 2.617645e-03 1.308823e-03
[100,] 9.982067e-01 3.586542e-03 1.793271e-03
[101,] 9.975000e-01 5.000039e-03 2.500020e-03
[102,] 9.964685e-01 7.063010e-03 3.531505e-03
[103,] 9.952073e-01 9.585437e-03 4.792718e-03
[104,] 9.989924e-01 2.015109e-03 1.007555e-03
[105,] 9.993843e-01 1.231393e-03 6.156966e-04
[106,] 9.996424e-01 7.152454e-04 3.576227e-04
[107,] 9.993629e-01 1.274160e-03 6.370802e-04
[108,] 9.990563e-01 1.887341e-03 9.436705e-04
[109,] 9.981315e-01 3.737015e-03 1.868508e-03
[110,] 9.907271e-01 1.854581e-02 9.272906e-03
> postscript(file="/var/www/html/rcomp/tmp/10tch1293091094.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
> points(x[,1]-mysum$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/20tch1293091094.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/3t2uk1293091094.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4t2uk1293091094.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5t2uk1293091094.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 = 143
Frequency = 1
1 2 3 4 5 6
22945.5420 18975.2087 19545.4587 14396.1254 13557.7920 7355.3754
7 8 9 10 11 12
647.8316 10389.6650 1755.7483 -2133.9184 -3251.2517 -3812.9474
13 14 15 16 17 18
-5986.1785 -8536.5118 -12351.2618 -12804.5951 -13535.9285 -18122.3451
19 20 21 22 23 24
-23120.8889 -13813.0555 -22175.9722 -23582.6389 -24028.9722 -27742.6679
25 26 27 28 29 30
-26100.8990 -26224.2323 -25593.9823 -23695.3157 -22177.6490 -24313.0657
31 32 33 34 35 36
-29272.6094 -22953.7760 -11836.6927 -9138.3594 -10403.6927 -10827.3884
37 38 39 40 41 42
-11121.6195 -10457.9528 -9129.7028 -11214.0362 -9742.3695 -11011.7862
43 44 45 46 47 48
-5602.3299 -5003.4966 -2711.4132 -921.0799 4306.5868 1738.8911
49 50 51 52 53 54
3442.6600 2763.3266 3183.5766 6161.2433 7150.9100 10481.4933
55 56 57 58 59 60
17554.9496 19701.7829 19361.8663 18461.1996 16808.8663 16663.1706
61 62 63 64 65 66
17840.9395 19120.6061 19162.8561 17407.5228 18293.1895 19550.7728
67 68 69 70 71 72
23394.2291 33466.0624 32373.1457 41996.4791 38639.1457 37626.4500
73 74 75 76 77 78
33784.2190 32822.8856 33816.1356 31974.8023 32132.4690 32271.0523
79 80 81 82 83 84
35298.5086 35938.3419 34607.4252 35584.7586 31243.4252 29148.7295
85 86 87 88 89 90
14752.4984 18716.1651 16176.4151 22002.0818 23066.7484 21210.3318
91 92 93 94 95 96
15834.7880 7663.6214 13497.7047 200.0380 -3145.2953 -11125.9910
97 98 99 100 101 102
-13009.2221 -17976.5554 -21393.3054 -23226.6387 -23838.9721 -25259.3887
103 104 105 106 107 108
-24978.9325 -33650.0991 -37632.0158 -38184.6825 -37689.0158 -37490.7115
109 110 111 112 113 114
-40954.9426 -42546.2759 -40651.0259 -39288.3593 -43205.6926 -38264.1093
115 116 117 118 119 120
-26723.1282 -34943.2949 -31792.2116 -28272.8782 -23280.2116 -16724.9073
121 122 123 124 125 126
-10217.1384 -3476.4717 3023.7783 4031.4450 5824.1116 12956.6950
127 128 129 130 131 132
7213.1512 1820.9846 4938.0679 6202.4012 11269.0679 22547.3722
133 134 135 136 137 138
14624.1411 16819.8078 14211.0578 14255.7245 12475.3911 13144.9745
139 140 141 142 143
9754.4307 1383.2641 -385.6526 -211.3193 -468.6526
> postscript(file="/var/www/html/rcomp/tmp/64ct51293091094.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 = 143
Frequency = 1
lag(myerror, k = 1) myerror
0 22945.5420 NA
1 18975.2087 22945.5420
2 19545.4587 18975.2087
3 14396.1254 19545.4587
4 13557.7920 14396.1254
5 7355.3754 13557.7920
6 647.8316 7355.3754
7 10389.6650 647.8316
8 1755.7483 10389.6650
9 -2133.9184 1755.7483
10 -3251.2517 -2133.9184
11 -3812.9474 -3251.2517
12 -5986.1785 -3812.9474
13 -8536.5118 -5986.1785
14 -12351.2618 -8536.5118
15 -12804.5951 -12351.2618
16 -13535.9285 -12804.5951
17 -18122.3451 -13535.9285
18 -23120.8889 -18122.3451
19 -13813.0555 -23120.8889
20 -22175.9722 -13813.0555
21 -23582.6389 -22175.9722
22 -24028.9722 -23582.6389
23 -27742.6679 -24028.9722
24 -26100.8990 -27742.6679
25 -26224.2323 -26100.8990
26 -25593.9823 -26224.2323
27 -23695.3157 -25593.9823
28 -22177.6490 -23695.3157
29 -24313.0657 -22177.6490
30 -29272.6094 -24313.0657
31 -22953.7760 -29272.6094
32 -11836.6927 -22953.7760
33 -9138.3594 -11836.6927
34 -10403.6927 -9138.3594
35 -10827.3884 -10403.6927
36 -11121.6195 -10827.3884
37 -10457.9528 -11121.6195
38 -9129.7028 -10457.9528
39 -11214.0362 -9129.7028
40 -9742.3695 -11214.0362
41 -11011.7862 -9742.3695
42 -5602.3299 -11011.7862
43 -5003.4966 -5602.3299
44 -2711.4132 -5003.4966
45 -921.0799 -2711.4132
46 4306.5868 -921.0799
47 1738.8911 4306.5868
48 3442.6600 1738.8911
49 2763.3266 3442.6600
50 3183.5766 2763.3266
51 6161.2433 3183.5766
52 7150.9100 6161.2433
53 10481.4933 7150.9100
54 17554.9496 10481.4933
55 19701.7829 17554.9496
56 19361.8663 19701.7829
57 18461.1996 19361.8663
58 16808.8663 18461.1996
59 16663.1706 16808.8663
60 17840.9395 16663.1706
61 19120.6061 17840.9395
62 19162.8561 19120.6061
63 17407.5228 19162.8561
64 18293.1895 17407.5228
65 19550.7728 18293.1895
66 23394.2291 19550.7728
67 33466.0624 23394.2291
68 32373.1457 33466.0624
69 41996.4791 32373.1457
70 38639.1457 41996.4791
71 37626.4500 38639.1457
72 33784.2190 37626.4500
73 32822.8856 33784.2190
74 33816.1356 32822.8856
75 31974.8023 33816.1356
76 32132.4690 31974.8023
77 32271.0523 32132.4690
78 35298.5086 32271.0523
79 35938.3419 35298.5086
80 34607.4252 35938.3419
81 35584.7586 34607.4252
82 31243.4252 35584.7586
83 29148.7295 31243.4252
84 14752.4984 29148.7295
85 18716.1651 14752.4984
86 16176.4151 18716.1651
87 22002.0818 16176.4151
88 23066.7484 22002.0818
89 21210.3318 23066.7484
90 15834.7880 21210.3318
91 7663.6214 15834.7880
92 13497.7047 7663.6214
93 200.0380 13497.7047
94 -3145.2953 200.0380
95 -11125.9910 -3145.2953
96 -13009.2221 -11125.9910
97 -17976.5554 -13009.2221
98 -21393.3054 -17976.5554
99 -23226.6387 -21393.3054
100 -23838.9721 -23226.6387
101 -25259.3887 -23838.9721
102 -24978.9325 -25259.3887
103 -33650.0991 -24978.9325
104 -37632.0158 -33650.0991
105 -38184.6825 -37632.0158
106 -37689.0158 -38184.6825
107 -37490.7115 -37689.0158
108 -40954.9426 -37490.7115
109 -42546.2759 -40954.9426
110 -40651.0259 -42546.2759
111 -39288.3593 -40651.0259
112 -43205.6926 -39288.3593
113 -38264.1093 -43205.6926
114 -26723.1282 -38264.1093
115 -34943.2949 -26723.1282
116 -31792.2116 -34943.2949
117 -28272.8782 -31792.2116
118 -23280.2116 -28272.8782
119 -16724.9073 -23280.2116
120 -10217.1384 -16724.9073
121 -3476.4717 -10217.1384
122 3023.7783 -3476.4717
123 4031.4450 3023.7783
124 5824.1116 4031.4450
125 12956.6950 5824.1116
126 7213.1512 12956.6950
127 1820.9846 7213.1512
128 4938.0679 1820.9846
129 6202.4012 4938.0679
130 11269.0679 6202.4012
131 22547.3722 11269.0679
132 14624.1411 22547.3722
133 16819.8078 14624.1411
134 14211.0578 16819.8078
135 14255.7245 14211.0578
136 12475.3911 14255.7245
137 13144.9745 12475.3911
138 9754.4307 13144.9745
139 1383.2641 9754.4307
140 -385.6526 1383.2641
141 -211.3193 -385.6526
142 -468.6526 -211.3193
143 NA -468.6526
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 18975.2087 22945.5420
[2,] 19545.4587 18975.2087
[3,] 14396.1254 19545.4587
[4,] 13557.7920 14396.1254
[5,] 7355.3754 13557.7920
[6,] 647.8316 7355.3754
[7,] 10389.6650 647.8316
[8,] 1755.7483 10389.6650
[9,] -2133.9184 1755.7483
[10,] -3251.2517 -2133.9184
[11,] -3812.9474 -3251.2517
[12,] -5986.1785 -3812.9474
[13,] -8536.5118 -5986.1785
[14,] -12351.2618 -8536.5118
[15,] -12804.5951 -12351.2618
[16,] -13535.9285 -12804.5951
[17,] -18122.3451 -13535.9285
[18,] -23120.8889 -18122.3451
[19,] -13813.0555 -23120.8889
[20,] -22175.9722 -13813.0555
[21,] -23582.6389 -22175.9722
[22,] -24028.9722 -23582.6389
[23,] -27742.6679 -24028.9722
[24,] -26100.8990 -27742.6679
[25,] -26224.2323 -26100.8990
[26,] -25593.9823 -26224.2323
[27,] -23695.3157 -25593.9823
[28,] -22177.6490 -23695.3157
[29,] -24313.0657 -22177.6490
[30,] -29272.6094 -24313.0657
[31,] -22953.7760 -29272.6094
[32,] -11836.6927 -22953.7760
[33,] -9138.3594 -11836.6927
[34,] -10403.6927 -9138.3594
[35,] -10827.3884 -10403.6927
[36,] -11121.6195 -10827.3884
[37,] -10457.9528 -11121.6195
[38,] -9129.7028 -10457.9528
[39,] -11214.0362 -9129.7028
[40,] -9742.3695 -11214.0362
[41,] -11011.7862 -9742.3695
[42,] -5602.3299 -11011.7862
[43,] -5003.4966 -5602.3299
[44,] -2711.4132 -5003.4966
[45,] -921.0799 -2711.4132
[46,] 4306.5868 -921.0799
[47,] 1738.8911 4306.5868
[48,] 3442.6600 1738.8911
[49,] 2763.3266 3442.6600
[50,] 3183.5766 2763.3266
[51,] 6161.2433 3183.5766
[52,] 7150.9100 6161.2433
[53,] 10481.4933 7150.9100
[54,] 17554.9496 10481.4933
[55,] 19701.7829 17554.9496
[56,] 19361.8663 19701.7829
[57,] 18461.1996 19361.8663
[58,] 16808.8663 18461.1996
[59,] 16663.1706 16808.8663
[60,] 17840.9395 16663.1706
[61,] 19120.6061 17840.9395
[62,] 19162.8561 19120.6061
[63,] 17407.5228 19162.8561
[64,] 18293.1895 17407.5228
[65,] 19550.7728 18293.1895
[66,] 23394.2291 19550.7728
[67,] 33466.0624 23394.2291
[68,] 32373.1457 33466.0624
[69,] 41996.4791 32373.1457
[70,] 38639.1457 41996.4791
[71,] 37626.4500 38639.1457
[72,] 33784.2190 37626.4500
[73,] 32822.8856 33784.2190
[74,] 33816.1356 32822.8856
[75,] 31974.8023 33816.1356
[76,] 32132.4690 31974.8023
[77,] 32271.0523 32132.4690
[78,] 35298.5086 32271.0523
[79,] 35938.3419 35298.5086
[80,] 34607.4252 35938.3419
[81,] 35584.7586 34607.4252
[82,] 31243.4252 35584.7586
[83,] 29148.7295 31243.4252
[84,] 14752.4984 29148.7295
[85,] 18716.1651 14752.4984
[86,] 16176.4151 18716.1651
[87,] 22002.0818 16176.4151
[88,] 23066.7484 22002.0818
[89,] 21210.3318 23066.7484
[90,] 15834.7880 21210.3318
[91,] 7663.6214 15834.7880
[92,] 13497.7047 7663.6214
[93,] 200.0380 13497.7047
[94,] -3145.2953 200.0380
[95,] -11125.9910 -3145.2953
[96,] -13009.2221 -11125.9910
[97,] -17976.5554 -13009.2221
[98,] -21393.3054 -17976.5554
[99,] -23226.6387 -21393.3054
[100,] -23838.9721 -23226.6387
[101,] -25259.3887 -23838.9721
[102,] -24978.9325 -25259.3887
[103,] -33650.0991 -24978.9325
[104,] -37632.0158 -33650.0991
[105,] -38184.6825 -37632.0158
[106,] -37689.0158 -38184.6825
[107,] -37490.7115 -37689.0158
[108,] -40954.9426 -37490.7115
[109,] -42546.2759 -40954.9426
[110,] -40651.0259 -42546.2759
[111,] -39288.3593 -40651.0259
[112,] -43205.6926 -39288.3593
[113,] -38264.1093 -43205.6926
[114,] -26723.1282 -38264.1093
[115,] -34943.2949 -26723.1282
[116,] -31792.2116 -34943.2949
[117,] -28272.8782 -31792.2116
[118,] -23280.2116 -28272.8782
[119,] -16724.9073 -23280.2116
[120,] -10217.1384 -16724.9073
[121,] -3476.4717 -10217.1384
[122,] 3023.7783 -3476.4717
[123,] 4031.4450 3023.7783
[124,] 5824.1116 4031.4450
[125,] 12956.6950 5824.1116
[126,] 7213.1512 12956.6950
[127,] 1820.9846 7213.1512
[128,] 4938.0679 1820.9846
[129,] 6202.4012 4938.0679
[130,] 11269.0679 6202.4012
[131,] 22547.3722 11269.0679
[132,] 14624.1411 22547.3722
[133,] 16819.8078 14624.1411
[134,] 14211.0578 16819.8078
[135,] 14255.7245 14211.0578
[136,] 12475.3911 14255.7245
[137,] 13144.9745 12475.3911
[138,] 9754.4307 13144.9745
[139,] 1383.2641 9754.4307
[140,] -385.6526 1383.2641
[141,] -211.3193 -385.6526
[142,] -468.6526 -211.3193
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 18975.2087 22945.5420
2 19545.4587 18975.2087
3 14396.1254 19545.4587
4 13557.7920 14396.1254
5 7355.3754 13557.7920
6 647.8316 7355.3754
7 10389.6650 647.8316
8 1755.7483 10389.6650
9 -2133.9184 1755.7483
10 -3251.2517 -2133.9184
11 -3812.9474 -3251.2517
12 -5986.1785 -3812.9474
13 -8536.5118 -5986.1785
14 -12351.2618 -8536.5118
15 -12804.5951 -12351.2618
16 -13535.9285 -12804.5951
17 -18122.3451 -13535.9285
18 -23120.8889 -18122.3451
19 -13813.0555 -23120.8889
20 -22175.9722 -13813.0555
21 -23582.6389 -22175.9722
22 -24028.9722 -23582.6389
23 -27742.6679 -24028.9722
24 -26100.8990 -27742.6679
25 -26224.2323 -26100.8990
26 -25593.9823 -26224.2323
27 -23695.3157 -25593.9823
28 -22177.6490 -23695.3157
29 -24313.0657 -22177.6490
30 -29272.6094 -24313.0657
31 -22953.7760 -29272.6094
32 -11836.6927 -22953.7760
33 -9138.3594 -11836.6927
34 -10403.6927 -9138.3594
35 -10827.3884 -10403.6927
36 -11121.6195 -10827.3884
37 -10457.9528 -11121.6195
38 -9129.7028 -10457.9528
39 -11214.0362 -9129.7028
40 -9742.3695 -11214.0362
41 -11011.7862 -9742.3695
42 -5602.3299 -11011.7862
43 -5003.4966 -5602.3299
44 -2711.4132 -5003.4966
45 -921.0799 -2711.4132
46 4306.5868 -921.0799
47 1738.8911 4306.5868
48 3442.6600 1738.8911
49 2763.3266 3442.6600
50 3183.5766 2763.3266
51 6161.2433 3183.5766
52 7150.9100 6161.2433
53 10481.4933 7150.9100
54 17554.9496 10481.4933
55 19701.7829 17554.9496
56 19361.8663 19701.7829
57 18461.1996 19361.8663
58 16808.8663 18461.1996
59 16663.1706 16808.8663
60 17840.9395 16663.1706
61 19120.6061 17840.9395
62 19162.8561 19120.6061
63 17407.5228 19162.8561
64 18293.1895 17407.5228
65 19550.7728 18293.1895
66 23394.2291 19550.7728
67 33466.0624 23394.2291
68 32373.1457 33466.0624
69 41996.4791 32373.1457
70 38639.1457 41996.4791
71 37626.4500 38639.1457
72 33784.2190 37626.4500
73 32822.8856 33784.2190
74 33816.1356 32822.8856
75 31974.8023 33816.1356
76 32132.4690 31974.8023
77 32271.0523 32132.4690
78 35298.5086 32271.0523
79 35938.3419 35298.5086
80 34607.4252 35938.3419
81 35584.7586 34607.4252
82 31243.4252 35584.7586
83 29148.7295 31243.4252
84 14752.4984 29148.7295
85 18716.1651 14752.4984
86 16176.4151 18716.1651
87 22002.0818 16176.4151
88 23066.7484 22002.0818
89 21210.3318 23066.7484
90 15834.7880 21210.3318
91 7663.6214 15834.7880
92 13497.7047 7663.6214
93 200.0380 13497.7047
94 -3145.2953 200.0380
95 -11125.9910 -3145.2953
96 -13009.2221 -11125.9910
97 -17976.5554 -13009.2221
98 -21393.3054 -17976.5554
99 -23226.6387 -21393.3054
100 -23838.9721 -23226.6387
101 -25259.3887 -23838.9721
102 -24978.9325 -25259.3887
103 -33650.0991 -24978.9325
104 -37632.0158 -33650.0991
105 -38184.6825 -37632.0158
106 -37689.0158 -38184.6825
107 -37490.7115 -37689.0158
108 -40954.9426 -37490.7115
109 -42546.2759 -40954.9426
110 -40651.0259 -42546.2759
111 -39288.3593 -40651.0259
112 -43205.6926 -39288.3593
113 -38264.1093 -43205.6926
114 -26723.1282 -38264.1093
115 -34943.2949 -26723.1282
116 -31792.2116 -34943.2949
117 -28272.8782 -31792.2116
118 -23280.2116 -28272.8782
119 -16724.9073 -23280.2116
120 -10217.1384 -16724.9073
121 -3476.4717 -10217.1384
122 3023.7783 -3476.4717
123 4031.4450 3023.7783
124 5824.1116 4031.4450
125 12956.6950 5824.1116
126 7213.1512 12956.6950
127 1820.9846 7213.1512
128 4938.0679 1820.9846
129 6202.4012 4938.0679
130 11269.0679 6202.4012
131 22547.3722 11269.0679
132 14624.1411 22547.3722
133 16819.8078 14624.1411
134 14211.0578 16819.8078
135 14255.7245 14211.0578
136 12475.3911 14255.7245
137 13144.9745 12475.3911
138 9754.4307 13144.9745
139 1383.2641 9754.4307
140 -385.6526 1383.2641
141 -211.3193 -385.6526
142 -468.6526 -211.3193
> plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
> lines(lowess(z))
> abline(lm(z))
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/7e3aq1293091094.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8e3aq1293091094.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9e3aq1293091094.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/107crb1293091094.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
+ myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ')
+ if (rownames(mysum$coefficients)[i] != '(Intercept)') {
+ myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
+ if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
+ }
+ }
> myeq <- paste(myeq, ' + e[t]')
> a<-table.row.start(a)
> a<-table.element(a, myeq)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/11ad8z1293091094.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Variable',header=TRUE)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
> a<-table.element(a,'2-tail p-value',header=TRUE)
> a<-table.element(a,'1-tail p-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:k){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
+ a<-table.element(a,mysum$coefficients[i,1])
+ a<-table.element(a, round(mysum$coefficients[i,2],6))
+ a<-table.element(a, round(mysum$coefficients[i,3],4))
+ a<-table.element(a, round(mysum$coefficients[i,4],6))
+ a<-table.element(a, round(mysum$coefficients[i,4]/2,6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/12wvo51293091094.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple R',1,TRUE)
> a<-table.element(a, sqrt(mysum$r.squared))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'R-squared',1,TRUE)
> a<-table.element(a, mysum$r.squared)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Adjusted R-squared',1,TRUE)
> a<-table.element(a, mysum$adj.r.squared)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (value)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[1])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[2])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[3])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'p-value',1,TRUE)
> a<-table.element(a, 1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
> a<-table.element(a, mysum$sigma)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a, sum(myerror*myerror))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/13a5me1293091094.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Time or Index', 1, TRUE)
> a<-table.element(a, 'Actuals', 1, TRUE)
> a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
> a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
> a<-table.row.end(a)
> for (i in 1:n) {
+ a<-table.row.start(a)
+ a<-table.element(a,i, 1, TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]-mysum$resid[i])
+ a<-table.element(a,mysum$resid[i])
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/142wlz1293091094.tab")
> if (n > n25) {
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'p-values',header=TRUE)
+ a<-table.element(a,'Alternative Hypothesis',3,header=TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'breakpoint index',header=TRUE)
+ a<-table.element(a,'greater',header=TRUE)
+ a<-table.element(a,'2-sided',header=TRUE)
+ a<-table.element(a,'less',header=TRUE)
+ a<-table.row.end(a)
+ for (mypoint in kp3:nmkm3) {
+ a<-table.row.start(a)
+ a<-table.element(a,mypoint,header=TRUE)
+ a<-table.element(a,gqarr[mypoint-kp3+1,1])
+ a<-table.element(a,gqarr[mypoint-kp3+1,2])
+ a<-table.element(a,gqarr[mypoint-kp3+1,3])
+ a<-table.row.end(a)
+ }
+ a<-table.end(a)
+ table.save(a,file="/var/www/html/rcomp/tmp/15oxk51293091094.tab")
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'Description',header=TRUE)
+ a<-table.element(a,'# significant tests',header=TRUE)
+ a<-table.element(a,'% significant tests',header=TRUE)
+ a<-table.element(a,'OK/NOK',header=TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'1% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant1)
+ a<-table.element(a,numsignificant1/numgqtests)
+ if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'5% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant5)
+ a<-table.element(a,numsignificant5/numgqtests)
+ if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'10% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant10)
+ a<-table.element(a,numsignificant10/numgqtests)
+ if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.end(a)
+ table.save(a,file="/var/www/html/rcomp/tmp/1626iv1293091094.tab")
+ }
>
> try(system("convert tmp/10tch1293091094.ps tmp/10tch1293091094.png",intern=TRUE))
character(0)
> try(system("convert tmp/20tch1293091094.ps tmp/20tch1293091094.png",intern=TRUE))
character(0)
> try(system("convert tmp/3t2uk1293091094.ps tmp/3t2uk1293091094.png",intern=TRUE))
character(0)
> try(system("convert tmp/4t2uk1293091094.ps tmp/4t2uk1293091094.png",intern=TRUE))
character(0)
> try(system("convert tmp/5t2uk1293091094.ps tmp/5t2uk1293091094.png",intern=TRUE))
character(0)
> try(system("convert tmp/64ct51293091094.ps tmp/64ct51293091094.png",intern=TRUE))
character(0)
> try(system("convert tmp/7e3aq1293091094.ps tmp/7e3aq1293091094.png",intern=TRUE))
character(0)
> try(system("convert tmp/8e3aq1293091094.ps tmp/8e3aq1293091094.png",intern=TRUE))
character(0)
> try(system("convert tmp/9e3aq1293091094.ps tmp/9e3aq1293091094.png",intern=TRUE))
character(0)
> try(system("convert tmp/107crb1293091094.ps tmp/107crb1293091094.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
3.723 1.752 8.250