R version 2.9.0 (2009-04-17)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
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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(6.5
+ ,8.9
+ ,-0.6
+ ,9
+ ,6.3
+ ,8.4
+ ,1.1
+ ,11
+ ,5.9
+ ,8.1
+ ,1.4
+ ,13
+ ,5.5
+ ,8.3
+ ,1.4
+ ,12
+ ,5.2
+ ,8.1
+ ,1.3
+ ,13
+ ,4.9
+ ,8
+ ,1.4
+ ,15
+ ,5.4
+ ,8.7
+ ,-0.1
+ ,13
+ ,5.8
+ ,9.2
+ ,1.8
+ ,16
+ ,5.7
+ ,9
+ ,1.5
+ ,10
+ ,5.6
+ ,8.9
+ ,1.5
+ ,14
+ ,5.5
+ ,8.5
+ ,1.4
+ ,14
+ ,5.4
+ ,8.1
+ ,1.6
+ ,15
+ ,5.4
+ ,7.5
+ ,1.6
+ ,13
+ ,5.4
+ ,7.1
+ ,1.6
+ ,8
+ ,5.5
+ ,6.9
+ ,1.4
+ ,7
+ ,5.8
+ ,7.1
+ ,1.7
+ ,3
+ ,5.7
+ ,7
+ ,1.8
+ ,3
+ ,5.4
+ ,6.7
+ ,1.9
+ ,4
+ ,5.6
+ ,7
+ ,2.2
+ ,4
+ ,5.8
+ ,7.3
+ ,2.1
+ ,0
+ ,6.2
+ ,7.7
+ ,2.4
+ ,-4
+ ,6.8
+ ,8.4
+ ,2.6
+ ,-14
+ ,6.7
+ ,8.4
+ ,2.8
+ ,-18
+ ,6.7
+ ,8.8
+ ,2.7
+ ,-8
+ ,6.4
+ ,9.1
+ ,2.6
+ ,-1
+ ,6.3
+ ,9
+ ,2.9
+ ,1
+ ,6.3
+ ,8.6
+ ,2.8
+ ,2
+ ,6.4
+ ,7.9
+ ,2.2
+ ,0
+ ,6.3
+ ,7.7
+ ,2.2
+ ,1
+ ,6
+ ,7.8
+ ,2.2
+ ,0
+ ,6.3
+ ,9.2
+ ,2
+ ,-1
+ ,6.3
+ ,9.4
+ ,2
+ ,-3
+ ,6.6
+ ,9.2
+ ,1.7
+ ,-3
+ ,7.5
+ ,8.7
+ ,1.4
+ ,-3
+ ,7.8
+ ,8.4
+ ,1.3
+ ,-4
+ ,7.9
+ ,8.6
+ ,1.4
+ ,-8
+ ,7.8
+ ,9
+ ,1.3
+ ,-9
+ ,7.6
+ ,9.1
+ ,1.3
+ ,-13
+ ,7.5
+ ,8.7
+ ,1.4
+ ,-18
+ ,7.6
+ ,8.2
+ ,2
+ ,-11
+ ,7.5
+ ,7.9
+ ,1.7
+ ,-9
+ ,7.3
+ ,7.9
+ ,1.8
+ ,-10
+ ,7.6
+ ,9.1
+ ,1.7
+ ,-13
+ ,7.5
+ ,9.4
+ ,1.6
+ ,-11
+ ,7.6
+ ,9.4
+ ,1.7
+ ,-5
+ ,7.9
+ ,9.1
+ ,1.9
+ ,-15
+ ,7.9
+ ,9
+ ,1.8
+ ,-6
+ ,8.1
+ ,9.3
+ ,1.7
+ ,-6
+ ,8.2
+ ,9.9
+ ,1.6
+ ,-3
+ ,8
+ ,9.8
+ ,1.8
+ ,-1
+ ,7.5
+ ,9.3
+ ,1.6
+ ,-3
+ ,6.8
+ ,8.3
+ ,1.5
+ ,-4
+ ,6.5
+ ,8
+ ,1.5
+ ,-6
+ ,6.6
+ ,8.5
+ ,1.3
+ ,0
+ ,7.6
+ ,10.4
+ ,1.4
+ ,-4
+ ,8
+ ,11.1
+ ,1.4
+ ,-2
+ ,8.1
+ ,10.9
+ ,1.3
+ ,-2
+ ,7.7
+ ,10
+ ,1.3
+ ,-6
+ ,7.5
+ ,9.2
+ ,1.2
+ ,-7
+ ,7.6
+ ,9.2
+ ,1.1
+ ,-6
+ ,7.8
+ ,9.5
+ ,1.4
+ ,-6
+ ,7.8
+ ,9.6
+ ,1.2
+ ,-3
+ ,7.8
+ ,9.5
+ ,1.5
+ ,-2
+ ,7.5
+ ,9.1
+ ,1.1
+ ,-5
+ ,7.5
+ ,8.9
+ ,1.3
+ ,-11
+ ,7.1
+ ,9
+ ,1.5
+ ,-11
+ ,7.5
+ ,10.1
+ ,1.1
+ ,-11
+ ,7.5
+ ,10.3
+ ,1.4
+ ,-10
+ ,7.6
+ ,10.2
+ ,1.3
+ ,-14
+ ,7.7
+ ,9.6
+ ,1.5
+ ,-8
+ ,7.7
+ ,9.2
+ ,1.6
+ ,-9
+ ,7.9
+ ,9.3
+ ,1.7
+ ,-5
+ ,8.1
+ ,9.4
+ ,1.1
+ ,-1
+ ,8.2
+ ,9.4
+ ,1.6
+ ,-2
+ ,8.2
+ ,9.2
+ ,1.3
+ ,-5
+ ,8.2
+ ,9
+ ,1.7
+ ,-4
+ ,7.9
+ ,9
+ ,1.6
+ ,-6
+ ,7.3
+ ,9
+ ,1.7
+ ,-2
+ ,6.9
+ ,9.8
+ ,1.9
+ ,-2
+ ,6.6
+ ,10
+ ,1.8
+ ,-2
+ ,6.7
+ ,9.8
+ ,1.9
+ ,-2
+ ,6.9
+ ,9.3
+ ,1.6
+ ,2
+ ,7
+ ,9
+ ,1.5
+ ,1
+ ,7.1
+ ,9
+ ,1.6
+ ,-8
+ ,7.2
+ ,9.1
+ ,1.6
+ ,-1
+ ,7.1
+ ,9.1
+ ,1.7
+ ,1
+ ,6.9
+ ,9.1
+ ,2
+ ,-1
+ ,7
+ ,9.2
+ ,2
+ ,2
+ ,6.8
+ ,8.8
+ ,1.9
+ ,2
+ ,6.4
+ ,8.3
+ ,1.7
+ ,1
+ ,6.7
+ ,8.4
+ ,1.8
+ ,-1
+ ,6.6
+ ,8.1
+ ,1.9
+ ,-2
+ ,6.4
+ ,7.7
+ ,1.7
+ ,-2
+ ,6.3
+ ,7.9
+ ,2
+ ,-1
+ ,6.2
+ ,7.9
+ ,2.1
+ ,-8
+ ,6.5
+ ,8
+ ,2.4
+ ,-4
+ ,6.8
+ ,7.9
+ ,2.5
+ ,-6
+ ,6.8
+ ,7.6
+ ,2.5
+ ,-3
+ ,6.4
+ ,7.1
+ ,2.6
+ ,-3
+ ,6.1
+ ,6.8
+ ,2.2
+ ,-7
+ ,5.8
+ ,6.5
+ ,2.5
+ ,-9
+ ,6.1
+ ,6.9
+ ,2.8
+ ,-11
+ ,7.2
+ ,8.2
+ ,2.8
+ ,-13
+ ,7.3
+ ,8.7
+ ,2.9
+ ,-11
+ ,6.9
+ ,8.3
+ ,3
+ ,-9
+ ,6.1
+ ,7.9
+ ,3.1
+ ,-17
+ ,5.8
+ ,7.5
+ ,2.9
+ ,-22
+ ,6.2
+ ,7.8
+ ,2.7
+ ,-25
+ ,7.1
+ ,8.3
+ ,2.2
+ ,-20
+ ,7.7
+ ,8.4
+ ,2.5
+ ,-24
+ ,8
+ ,8.2
+ ,2.3
+ ,-24
+ ,7.8
+ ,7.6
+ ,2.6
+ ,-22
+ ,7.4
+ ,7.2
+ ,2.3
+ ,-19
+ ,7.4
+ ,7.5
+ ,2.2
+ ,-18
+ ,7.7
+ ,8.7
+ ,1.8
+ ,-17
+ ,7.8
+ ,9
+ ,1.8
+ ,-11
+ ,7.8
+ ,8.6
+ ,2
+ ,-11
+ ,8
+ ,7.9
+ ,1.6
+ ,-12
+ ,8.1
+ ,7.8
+ ,1.5
+ ,-10
+ ,8.4
+ ,8.2
+ ,1.4
+ ,-15)
+ ,dim=c(4
+ ,120)
+ ,dimnames=list(c('Mannen'
+ ,'Vrouwen'
+ ,'Inflatie'
+ ,'Consumvertr')
+ ,1:120))
> y <- array(NA,dim=c(4,120),dimnames=list(c('Mannen','Vrouwen','Inflatie','Consumvertr'),1:120))
> 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 = 'Do not include Seasonal 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
Mannen Vrouwen Inflatie Consumvertr t
1 6.5 8.9 -0.6 9 1
2 6.3 8.4 1.1 11 2
3 5.9 8.1 1.4 13 3
4 5.5 8.3 1.4 12 4
5 5.2 8.1 1.3 13 5
6 4.9 8.0 1.4 15 6
7 5.4 8.7 -0.1 13 7
8 5.8 9.2 1.8 16 8
9 5.7 9.0 1.5 10 9
10 5.6 8.9 1.5 14 10
11 5.5 8.5 1.4 14 11
12 5.4 8.1 1.6 15 12
13 5.4 7.5 1.6 13 13
14 5.4 7.1 1.6 8 14
15 5.5 6.9 1.4 7 15
16 5.8 7.1 1.7 3 16
17 5.7 7.0 1.8 3 17
18 5.4 6.7 1.9 4 18
19 5.6 7.0 2.2 4 19
20 5.8 7.3 2.1 0 20
21 6.2 7.7 2.4 -4 21
22 6.8 8.4 2.6 -14 22
23 6.7 8.4 2.8 -18 23
24 6.7 8.8 2.7 -8 24
25 6.4 9.1 2.6 -1 25
26 6.3 9.0 2.9 1 26
27 6.3 8.6 2.8 2 27
28 6.4 7.9 2.2 0 28
29 6.3 7.7 2.2 1 29
30 6.0 7.8 2.2 0 30
31 6.3 9.2 2.0 -1 31
32 6.3 9.4 2.0 -3 32
33 6.6 9.2 1.7 -3 33
34 7.5 8.7 1.4 -3 34
35 7.8 8.4 1.3 -4 35
36 7.9 8.6 1.4 -8 36
37 7.8 9.0 1.3 -9 37
38 7.6 9.1 1.3 -13 38
39 7.5 8.7 1.4 -18 39
40 7.6 8.2 2.0 -11 40
41 7.5 7.9 1.7 -9 41
42 7.3 7.9 1.8 -10 42
43 7.6 9.1 1.7 -13 43
44 7.5 9.4 1.6 -11 44
45 7.6 9.4 1.7 -5 45
46 7.9 9.1 1.9 -15 46
47 7.9 9.0 1.8 -6 47
48 8.1 9.3 1.7 -6 48
49 8.2 9.9 1.6 -3 49
50 8.0 9.8 1.8 -1 50
51 7.5 9.3 1.6 -3 51
52 6.8 8.3 1.5 -4 52
53 6.5 8.0 1.5 -6 53
54 6.6 8.5 1.3 0 54
55 7.6 10.4 1.4 -4 55
56 8.0 11.1 1.4 -2 56
57 8.1 10.9 1.3 -2 57
58 7.7 10.0 1.3 -6 58
59 7.5 9.2 1.2 -7 59
60 7.6 9.2 1.1 -6 60
61 7.8 9.5 1.4 -6 61
62 7.8 9.6 1.2 -3 62
63 7.8 9.5 1.5 -2 63
64 7.5 9.1 1.1 -5 64
65 7.5 8.9 1.3 -11 65
66 7.1 9.0 1.5 -11 66
67 7.5 10.1 1.1 -11 67
68 7.5 10.3 1.4 -10 68
69 7.6 10.2 1.3 -14 69
70 7.7 9.6 1.5 -8 70
71 7.7 9.2 1.6 -9 71
72 7.9 9.3 1.7 -5 72
73 8.1 9.4 1.1 -1 73
74 8.2 9.4 1.6 -2 74
75 8.2 9.2 1.3 -5 75
76 8.2 9.0 1.7 -4 76
77 7.9 9.0 1.6 -6 77
78 7.3 9.0 1.7 -2 78
79 6.9 9.8 1.9 -2 79
80 6.6 10.0 1.8 -2 80
81 6.7 9.8 1.9 -2 81
82 6.9 9.3 1.6 2 82
83 7.0 9.0 1.5 1 83
84 7.1 9.0 1.6 -8 84
85 7.2 9.1 1.6 -1 85
86 7.1 9.1 1.7 1 86
87 6.9 9.1 2.0 -1 87
88 7.0 9.2 2.0 2 88
89 6.8 8.8 1.9 2 89
90 6.4 8.3 1.7 1 90
91 6.7 8.4 1.8 -1 91
92 6.6 8.1 1.9 -2 92
93 6.4 7.7 1.7 -2 93
94 6.3 7.9 2.0 -1 94
95 6.2 7.9 2.1 -8 95
96 6.5 8.0 2.4 -4 96
97 6.8 7.9 2.5 -6 97
98 6.8 7.6 2.5 -3 98
99 6.4 7.1 2.6 -3 99
100 6.1 6.8 2.2 -7 100
101 5.8 6.5 2.5 -9 101
102 6.1 6.9 2.8 -11 102
103 7.2 8.2 2.8 -13 103
104 7.3 8.7 2.9 -11 104
105 6.9 8.3 3.0 -9 105
106 6.1 7.9 3.1 -17 106
107 5.8 7.5 2.9 -22 107
108 6.2 7.8 2.7 -25 108
109 7.1 8.3 2.2 -20 109
110 7.7 8.4 2.5 -24 110
111 8.0 8.2 2.3 -24 111
112 7.8 7.6 2.6 -22 112
113 7.4 7.2 2.3 -19 113
114 7.4 7.5 2.2 -18 114
115 7.7 8.7 1.8 -17 115
116 7.8 9.0 1.8 -11 116
117 7.8 8.6 2.0 -11 117
118 8.0 7.9 1.6 -12 118
119 8.1 7.8 1.5 -10 119
120 8.4 8.2 1.4 -15 120
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Vrouwen Inflatie Consumvertr t
3.511845 0.424760 -0.431370 -0.054045 0.005112
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-1.382561 -0.243238 -0.004503 0.298765 0.993947
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 3.511845 0.546731 6.423 3.12e-09 ***
Vrouwen 0.424760 0.052987 8.016 1.00e-12 ***
Inflatie -0.431370 0.093452 -4.616 1.03e-05 ***
Consumvertr -0.054045 0.006619 -8.165 4.61e-13 ***
t 0.005112 0.001651 3.096 0.00246 **
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.4739 on 115 degrees of freedom
Multiple R-squared: 0.7094, Adjusted R-squared: 0.6993
F-statistic: 70.18 on 4 and 115 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,] 0.1078794554 0.2157589109 0.892120545
[2,] 0.0635432549 0.1270865099 0.936456745
[3,] 0.0641880504 0.1283761009 0.935811950
[4,] 0.1571601002 0.3143202004 0.842839900
[5,] 0.2377194576 0.4754389152 0.762280542
[6,] 0.2272135179 0.4544270358 0.772786482
[7,] 0.1563823123 0.3127646245 0.843617688
[8,] 0.1050809340 0.2101618681 0.894919066
[9,] 0.0665690862 0.1331381724 0.933430914
[10,] 0.0411245833 0.0822491666 0.958875417
[11,] 0.0265328424 0.0530656848 0.973467158
[12,] 0.0151697819 0.0303395638 0.984830218
[13,] 0.0095562436 0.0191124873 0.990443756
[14,] 0.0052940102 0.0105880204 0.994705990
[15,] 0.0035760792 0.0071521585 0.996423921
[16,] 0.0033700659 0.0067401319 0.996629934
[17,] 0.0024567665 0.0049135330 0.997543234
[18,] 0.0016106297 0.0032212594 0.998389370
[19,] 0.0010330188 0.0020660377 0.998966981
[20,] 0.0008662631 0.0017325262 0.999133737
[21,] 0.0009235820 0.0018471640 0.999076418
[22,] 0.0007362595 0.0014725190 0.999263740
[23,] 0.0004257307 0.0008514613 0.999574269
[24,] 0.0003629585 0.0007259171 0.999637041
[25,] 0.0004238447 0.0008476895 0.999576155
[26,] 0.0002827006 0.0005654012 0.999717299
[27,] 0.0042901746 0.0085803493 0.995709825
[28,] 0.0278337598 0.0556675196 0.972166240
[29,] 0.0427285469 0.0854570938 0.957271453
[30,] 0.0334267494 0.0668534988 0.966573251
[31,] 0.0260730971 0.0521461943 0.973926903
[32,] 0.0251390003 0.0502780007 0.974861000
[33,] 0.0247203744 0.0494407487 0.975279626
[34,] 0.0214005319 0.0428010637 0.978599468
[35,] 0.0157256327 0.0314512654 0.984274367
[36,] 0.0113896486 0.0227792973 0.988610351
[37,] 0.0089988036 0.0179976072 0.991001196
[38,] 0.0064068763 0.0128137527 0.993593124
[39,] 0.0048269067 0.0096538135 0.995173093
[40,] 0.0065880262 0.0131760525 0.993411974
[41,] 0.0102192376 0.0204384753 0.989780762
[42,] 0.0143075501 0.0286151001 0.985692450
[43,] 0.0208268690 0.0416537379 0.979173131
[44,] 0.0209445055 0.0418890110 0.979055495
[45,] 0.0375663797 0.0751327594 0.962433620
[46,] 0.0840210559 0.1680421118 0.915978944
[47,] 0.1074218084 0.2148436167 0.892578192
[48,] 0.1016011945 0.2032023889 0.898398806
[49,] 0.0824165061 0.1648330122 0.917583494
[50,] 0.0664239157 0.1328478315 0.933576084
[51,] 0.0567982969 0.1135965938 0.943201703
[52,] 0.0485761122 0.0971522244 0.951423888
[53,] 0.0381233318 0.0762466636 0.961876668
[54,] 0.0310067292 0.0620134583 0.968993271
[55,] 0.0239252457 0.0478504913 0.976074754
[56,] 0.0232674064 0.0465348129 0.976732594
[57,] 0.0183911255 0.0367822510 0.981608874
[58,] 0.0170552706 0.0341105412 0.982944729
[59,] 0.0261519929 0.0523039857 0.973848007
[60,] 0.0484660642 0.0969321284 0.951533936
[61,] 0.0668951266 0.1337902532 0.933104873
[62,] 0.1110631812 0.2221263623 0.888936819
[63,] 0.0888213214 0.1776426429 0.911178679
[64,] 0.0695412918 0.1390825835 0.930458708
[65,] 0.0714198669 0.1428397338 0.928580133
[66,] 0.0733384609 0.1466769218 0.926661539
[67,] 0.1329942319 0.2659884638 0.867005768
[68,] 0.1772213935 0.3544427869 0.822778607
[69,] 0.4686567157 0.9373134315 0.531343284
[70,] 0.7239259896 0.5521480207 0.276074010
[71,] 0.8177169841 0.3645660317 0.182283016
[72,] 0.8378636487 0.3242727026 0.162136351
[73,] 0.9031826518 0.1936346964 0.096817348
[74,] 0.9180739021 0.1638521957 0.081926098
[75,] 0.8986477824 0.2027044352 0.101352218
[76,] 0.8748370271 0.2503259458 0.125162973
[77,] 0.8735290395 0.2529419211 0.126470961
[78,] 0.8601228810 0.2797542380 0.139877119
[79,] 0.8377870290 0.3244259420 0.162212971
[80,] 0.8097771729 0.3804456542 0.190222827
[81,] 0.7739727590 0.4520544820 0.226027241
[82,] 0.7293741969 0.5412516061 0.270625803
[83,] 0.6959555913 0.6080888174 0.304044409
[84,] 0.6439576778 0.7120846444 0.356042322
[85,] 0.5915635730 0.8168728541 0.408436427
[86,] 0.5360548933 0.9278902134 0.463945107
[87,] 0.4896824975 0.9793649949 0.510317503
[88,] 0.5095266283 0.9809467433 0.490473372
[89,] 0.4481024308 0.8962048615 0.551897569
[90,] 0.3914424673 0.7828849346 0.608557533
[91,] 0.3728944045 0.7457888089 0.627105596
[92,] 0.3315363628 0.6630727256 0.668463637
[93,] 0.2738574689 0.5477149379 0.726142531
[94,] 0.2420690262 0.4841380524 0.757930974
[95,] 0.1987639268 0.3975278537 0.801236073
[96,] 0.1953564755 0.3907129511 0.804643524
[97,] 0.2598395797 0.5196791594 0.740160420
[98,] 0.5917301266 0.8165397468 0.408269873
[99,] 0.5983044489 0.8033911023 0.401695551
[100,] 0.7085824171 0.5828351657 0.291417583
[101,] 0.9882408537 0.0235182926 0.011759146
[102,] 0.9733319146 0.0533361707 0.026668085
[103,] 0.9379543805 0.1240912389 0.062045619
[104,] 0.9555299672 0.0889400657 0.044470033
[105,] 0.9958414077 0.0083171846 0.004158592
> postscript(file="/var/www/html/rcomp/tmp/1jw4t1292700717.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2jw4t1292700717.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3c64x1292700717.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4c64x1292700717.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5c64x1292700717.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 = 120
Frequency = 1
1 2 3 4 5
-5.697312e-01 2.789565e-01 2.387741e-01 -3.053353e-01 -5.145871e-01
6 7 8 9 10
-6.259955e-01 -1.183585e+00 -1.933774e-02 -4.931812e-01 -3.396359e-01
11 12 13 14 15
-3.179811e-01 -1.128700e-01 2.878288e-02 -7.665223e-02 -3.713182e-02
16 17 18 19 20
8.603377e-02 6.653464e-02 -1.396720e-02 1.829039e-01 -8.954551e-03
21 22 23 24 25
1.292591e-01 -2.736428e-02 -2.623838e-01 5.991692e-02 -3.744249e-02
26 27 28 29 30
1.374232e-01 3.131232e-01 3.384300e-01 3.723152e-01 -2.931826e-02
31 32 33 34 35
-4.694131e-01 -6.675679e-01 -4.171391e-01 5.607175e-01 8.858509e-01
36 37 38 39 40
7.227425e-01 3.505442e-01 -1.132253e-01 -2.755234e-01 6.688839e-01
41 42 43 44 45
6.698794e-01 4.538589e-01 3.376225e-02 -1.338240e-01 3.284731e-01
46 47 48 49 50
2.966093e-01 7.772444e-01 8.015674e-01 7.605987e-01 7.923273e-01
51 52 53 54 55
3.052302e-01 -7.230471e-02 -3.580797e-01 -2.375734e-01 -2.227731e-01
56 57 58 59 60
-1.712611e-02 1.195767e-01 -1.194333e-01 -8.192012e-02 2.387614e-02
61 62 63 64 65
2.207472e-01 2.490212e-01 4.698415e-01 -5.092375e-05 -1.582093e-01
66 67 68 69 70
-5.195233e-01 -7.644190e-01 -6.710265e-01 -7.929812e-01 -3.269130e-02
71 72 73 74 75
1.211921e-01 5.329225e-01 6.426938e-01 8.992214e-01 6.875141e-01
76 77 78 79 80
9.939474e-01 5.376075e-01 1.918139e-01 -4.668318e-01 -9.000328e-01
81 82 83 84 85
-6.770560e-01 -1.830179e-01 -5.788451e-02 -4.062679e-01 2.446163e-02
86 87 88 89 90
7.057729e-02 -1.132145e-01 1.013336e-01 2.298827e-02 -3.100635e-01
91 92 93 94 95
-1.226052e-01 -1.111978e-01 -2.326801e-01 -2.392877e-01 -6.795803e-01
96 97 98 99 100
-8.157587e-02 1.908343e-01 4.752861e-01 3.256908e-01 -2.407229e-01
101 102 103 104 105
-3.970868e-01 -2.507824e-01 1.838273e-01 2.175632e-01 1.335827e-01
106 107 108 109 110
-8.908515e-01 -1.382561e+00 -1.363511e+00 -6.264609e-01 -1.608193e-01
111 112 113 114 115
1.327465e-01 4.199919e-01 2.175086e-01 9.587703e-02 -2.374492e-01
116 117 118 119 120
5.428301e-02 3.053488e-01 5.709749e-01 7.732925e-01 5.849127e-01
> postscript(file="/var/www/html/rcomp/tmp/6mf3z1292700717.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 = 120
Frequency = 1
lag(myerror, k = 1) myerror
0 -5.697312e-01 NA
1 2.789565e-01 -5.697312e-01
2 2.387741e-01 2.789565e-01
3 -3.053353e-01 2.387741e-01
4 -5.145871e-01 -3.053353e-01
5 -6.259955e-01 -5.145871e-01
6 -1.183585e+00 -6.259955e-01
7 -1.933774e-02 -1.183585e+00
8 -4.931812e-01 -1.933774e-02
9 -3.396359e-01 -4.931812e-01
10 -3.179811e-01 -3.396359e-01
11 -1.128700e-01 -3.179811e-01
12 2.878288e-02 -1.128700e-01
13 -7.665223e-02 2.878288e-02
14 -3.713182e-02 -7.665223e-02
15 8.603377e-02 -3.713182e-02
16 6.653464e-02 8.603377e-02
17 -1.396720e-02 6.653464e-02
18 1.829039e-01 -1.396720e-02
19 -8.954551e-03 1.829039e-01
20 1.292591e-01 -8.954551e-03
21 -2.736428e-02 1.292591e-01
22 -2.623838e-01 -2.736428e-02
23 5.991692e-02 -2.623838e-01
24 -3.744249e-02 5.991692e-02
25 1.374232e-01 -3.744249e-02
26 3.131232e-01 1.374232e-01
27 3.384300e-01 3.131232e-01
28 3.723152e-01 3.384300e-01
29 -2.931826e-02 3.723152e-01
30 -4.694131e-01 -2.931826e-02
31 -6.675679e-01 -4.694131e-01
32 -4.171391e-01 -6.675679e-01
33 5.607175e-01 -4.171391e-01
34 8.858509e-01 5.607175e-01
35 7.227425e-01 8.858509e-01
36 3.505442e-01 7.227425e-01
37 -1.132253e-01 3.505442e-01
38 -2.755234e-01 -1.132253e-01
39 6.688839e-01 -2.755234e-01
40 6.698794e-01 6.688839e-01
41 4.538589e-01 6.698794e-01
42 3.376225e-02 4.538589e-01
43 -1.338240e-01 3.376225e-02
44 3.284731e-01 -1.338240e-01
45 2.966093e-01 3.284731e-01
46 7.772444e-01 2.966093e-01
47 8.015674e-01 7.772444e-01
48 7.605987e-01 8.015674e-01
49 7.923273e-01 7.605987e-01
50 3.052302e-01 7.923273e-01
51 -7.230471e-02 3.052302e-01
52 -3.580797e-01 -7.230471e-02
53 -2.375734e-01 -3.580797e-01
54 -2.227731e-01 -2.375734e-01
55 -1.712611e-02 -2.227731e-01
56 1.195767e-01 -1.712611e-02
57 -1.194333e-01 1.195767e-01
58 -8.192012e-02 -1.194333e-01
59 2.387614e-02 -8.192012e-02
60 2.207472e-01 2.387614e-02
61 2.490212e-01 2.207472e-01
62 4.698415e-01 2.490212e-01
63 -5.092375e-05 4.698415e-01
64 -1.582093e-01 -5.092375e-05
65 -5.195233e-01 -1.582093e-01
66 -7.644190e-01 -5.195233e-01
67 -6.710265e-01 -7.644190e-01
68 -7.929812e-01 -6.710265e-01
69 -3.269130e-02 -7.929812e-01
70 1.211921e-01 -3.269130e-02
71 5.329225e-01 1.211921e-01
72 6.426938e-01 5.329225e-01
73 8.992214e-01 6.426938e-01
74 6.875141e-01 8.992214e-01
75 9.939474e-01 6.875141e-01
76 5.376075e-01 9.939474e-01
77 1.918139e-01 5.376075e-01
78 -4.668318e-01 1.918139e-01
79 -9.000328e-01 -4.668318e-01
80 -6.770560e-01 -9.000328e-01
81 -1.830179e-01 -6.770560e-01
82 -5.788451e-02 -1.830179e-01
83 -4.062679e-01 -5.788451e-02
84 2.446163e-02 -4.062679e-01
85 7.057729e-02 2.446163e-02
86 -1.132145e-01 7.057729e-02
87 1.013336e-01 -1.132145e-01
88 2.298827e-02 1.013336e-01
89 -3.100635e-01 2.298827e-02
90 -1.226052e-01 -3.100635e-01
91 -1.111978e-01 -1.226052e-01
92 -2.326801e-01 -1.111978e-01
93 -2.392877e-01 -2.326801e-01
94 -6.795803e-01 -2.392877e-01
95 -8.157587e-02 -6.795803e-01
96 1.908343e-01 -8.157587e-02
97 4.752861e-01 1.908343e-01
98 3.256908e-01 4.752861e-01
99 -2.407229e-01 3.256908e-01
100 -3.970868e-01 -2.407229e-01
101 -2.507824e-01 -3.970868e-01
102 1.838273e-01 -2.507824e-01
103 2.175632e-01 1.838273e-01
104 1.335827e-01 2.175632e-01
105 -8.908515e-01 1.335827e-01
106 -1.382561e+00 -8.908515e-01
107 -1.363511e+00 -1.382561e+00
108 -6.264609e-01 -1.363511e+00
109 -1.608193e-01 -6.264609e-01
110 1.327465e-01 -1.608193e-01
111 4.199919e-01 1.327465e-01
112 2.175086e-01 4.199919e-01
113 9.587703e-02 2.175086e-01
114 -2.374492e-01 9.587703e-02
115 5.428301e-02 -2.374492e-01
116 3.053488e-01 5.428301e-02
117 5.709749e-01 3.053488e-01
118 7.732925e-01 5.709749e-01
119 5.849127e-01 7.732925e-01
120 NA 5.849127e-01
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 2.789565e-01 -5.697312e-01
[2,] 2.387741e-01 2.789565e-01
[3,] -3.053353e-01 2.387741e-01
[4,] -5.145871e-01 -3.053353e-01
[5,] -6.259955e-01 -5.145871e-01
[6,] -1.183585e+00 -6.259955e-01
[7,] -1.933774e-02 -1.183585e+00
[8,] -4.931812e-01 -1.933774e-02
[9,] -3.396359e-01 -4.931812e-01
[10,] -3.179811e-01 -3.396359e-01
[11,] -1.128700e-01 -3.179811e-01
[12,] 2.878288e-02 -1.128700e-01
[13,] -7.665223e-02 2.878288e-02
[14,] -3.713182e-02 -7.665223e-02
[15,] 8.603377e-02 -3.713182e-02
[16,] 6.653464e-02 8.603377e-02
[17,] -1.396720e-02 6.653464e-02
[18,] 1.829039e-01 -1.396720e-02
[19,] -8.954551e-03 1.829039e-01
[20,] 1.292591e-01 -8.954551e-03
[21,] -2.736428e-02 1.292591e-01
[22,] -2.623838e-01 -2.736428e-02
[23,] 5.991692e-02 -2.623838e-01
[24,] -3.744249e-02 5.991692e-02
[25,] 1.374232e-01 -3.744249e-02
[26,] 3.131232e-01 1.374232e-01
[27,] 3.384300e-01 3.131232e-01
[28,] 3.723152e-01 3.384300e-01
[29,] -2.931826e-02 3.723152e-01
[30,] -4.694131e-01 -2.931826e-02
[31,] -6.675679e-01 -4.694131e-01
[32,] -4.171391e-01 -6.675679e-01
[33,] 5.607175e-01 -4.171391e-01
[34,] 8.858509e-01 5.607175e-01
[35,] 7.227425e-01 8.858509e-01
[36,] 3.505442e-01 7.227425e-01
[37,] -1.132253e-01 3.505442e-01
[38,] -2.755234e-01 -1.132253e-01
[39,] 6.688839e-01 -2.755234e-01
[40,] 6.698794e-01 6.688839e-01
[41,] 4.538589e-01 6.698794e-01
[42,] 3.376225e-02 4.538589e-01
[43,] -1.338240e-01 3.376225e-02
[44,] 3.284731e-01 -1.338240e-01
[45,] 2.966093e-01 3.284731e-01
[46,] 7.772444e-01 2.966093e-01
[47,] 8.015674e-01 7.772444e-01
[48,] 7.605987e-01 8.015674e-01
[49,] 7.923273e-01 7.605987e-01
[50,] 3.052302e-01 7.923273e-01
[51,] -7.230471e-02 3.052302e-01
[52,] -3.580797e-01 -7.230471e-02
[53,] -2.375734e-01 -3.580797e-01
[54,] -2.227731e-01 -2.375734e-01
[55,] -1.712611e-02 -2.227731e-01
[56,] 1.195767e-01 -1.712611e-02
[57,] -1.194333e-01 1.195767e-01
[58,] -8.192012e-02 -1.194333e-01
[59,] 2.387614e-02 -8.192012e-02
[60,] 2.207472e-01 2.387614e-02
[61,] 2.490212e-01 2.207472e-01
[62,] 4.698415e-01 2.490212e-01
[63,] -5.092375e-05 4.698415e-01
[64,] -1.582093e-01 -5.092375e-05
[65,] -5.195233e-01 -1.582093e-01
[66,] -7.644190e-01 -5.195233e-01
[67,] -6.710265e-01 -7.644190e-01
[68,] -7.929812e-01 -6.710265e-01
[69,] -3.269130e-02 -7.929812e-01
[70,] 1.211921e-01 -3.269130e-02
[71,] 5.329225e-01 1.211921e-01
[72,] 6.426938e-01 5.329225e-01
[73,] 8.992214e-01 6.426938e-01
[74,] 6.875141e-01 8.992214e-01
[75,] 9.939474e-01 6.875141e-01
[76,] 5.376075e-01 9.939474e-01
[77,] 1.918139e-01 5.376075e-01
[78,] -4.668318e-01 1.918139e-01
[79,] -9.000328e-01 -4.668318e-01
[80,] -6.770560e-01 -9.000328e-01
[81,] -1.830179e-01 -6.770560e-01
[82,] -5.788451e-02 -1.830179e-01
[83,] -4.062679e-01 -5.788451e-02
[84,] 2.446163e-02 -4.062679e-01
[85,] 7.057729e-02 2.446163e-02
[86,] -1.132145e-01 7.057729e-02
[87,] 1.013336e-01 -1.132145e-01
[88,] 2.298827e-02 1.013336e-01
[89,] -3.100635e-01 2.298827e-02
[90,] -1.226052e-01 -3.100635e-01
[91,] -1.111978e-01 -1.226052e-01
[92,] -2.326801e-01 -1.111978e-01
[93,] -2.392877e-01 -2.326801e-01
[94,] -6.795803e-01 -2.392877e-01
[95,] -8.157587e-02 -6.795803e-01
[96,] 1.908343e-01 -8.157587e-02
[97,] 4.752861e-01 1.908343e-01
[98,] 3.256908e-01 4.752861e-01
[99,] -2.407229e-01 3.256908e-01
[100,] -3.970868e-01 -2.407229e-01
[101,] -2.507824e-01 -3.970868e-01
[102,] 1.838273e-01 -2.507824e-01
[103,] 2.175632e-01 1.838273e-01
[104,] 1.335827e-01 2.175632e-01
[105,] -8.908515e-01 1.335827e-01
[106,] -1.382561e+00 -8.908515e-01
[107,] -1.363511e+00 -1.382561e+00
[108,] -6.264609e-01 -1.363511e+00
[109,] -1.608193e-01 -6.264609e-01
[110,] 1.327465e-01 -1.608193e-01
[111,] 4.199919e-01 1.327465e-01
[112,] 2.175086e-01 4.199919e-01
[113,] 9.587703e-02 2.175086e-01
[114,] -2.374492e-01 9.587703e-02
[115,] 5.428301e-02 -2.374492e-01
[116,] 3.053488e-01 5.428301e-02
[117,] 5.709749e-01 3.053488e-01
[118,] 7.732925e-01 5.709749e-01
[119,] 5.849127e-01 7.732925e-01
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 2.789565e-01 -5.697312e-01
2 2.387741e-01 2.789565e-01
3 -3.053353e-01 2.387741e-01
4 -5.145871e-01 -3.053353e-01
5 -6.259955e-01 -5.145871e-01
6 -1.183585e+00 -6.259955e-01
7 -1.933774e-02 -1.183585e+00
8 -4.931812e-01 -1.933774e-02
9 -3.396359e-01 -4.931812e-01
10 -3.179811e-01 -3.396359e-01
11 -1.128700e-01 -3.179811e-01
12 2.878288e-02 -1.128700e-01
13 -7.665223e-02 2.878288e-02
14 -3.713182e-02 -7.665223e-02
15 8.603377e-02 -3.713182e-02
16 6.653464e-02 8.603377e-02
17 -1.396720e-02 6.653464e-02
18 1.829039e-01 -1.396720e-02
19 -8.954551e-03 1.829039e-01
20 1.292591e-01 -8.954551e-03
21 -2.736428e-02 1.292591e-01
22 -2.623838e-01 -2.736428e-02
23 5.991692e-02 -2.623838e-01
24 -3.744249e-02 5.991692e-02
25 1.374232e-01 -3.744249e-02
26 3.131232e-01 1.374232e-01
27 3.384300e-01 3.131232e-01
28 3.723152e-01 3.384300e-01
29 -2.931826e-02 3.723152e-01
30 -4.694131e-01 -2.931826e-02
31 -6.675679e-01 -4.694131e-01
32 -4.171391e-01 -6.675679e-01
33 5.607175e-01 -4.171391e-01
34 8.858509e-01 5.607175e-01
35 7.227425e-01 8.858509e-01
36 3.505442e-01 7.227425e-01
37 -1.132253e-01 3.505442e-01
38 -2.755234e-01 -1.132253e-01
39 6.688839e-01 -2.755234e-01
40 6.698794e-01 6.688839e-01
41 4.538589e-01 6.698794e-01
42 3.376225e-02 4.538589e-01
43 -1.338240e-01 3.376225e-02
44 3.284731e-01 -1.338240e-01
45 2.966093e-01 3.284731e-01
46 7.772444e-01 2.966093e-01
47 8.015674e-01 7.772444e-01
48 7.605987e-01 8.015674e-01
49 7.923273e-01 7.605987e-01
50 3.052302e-01 7.923273e-01
51 -7.230471e-02 3.052302e-01
52 -3.580797e-01 -7.230471e-02
53 -2.375734e-01 -3.580797e-01
54 -2.227731e-01 -2.375734e-01
55 -1.712611e-02 -2.227731e-01
56 1.195767e-01 -1.712611e-02
57 -1.194333e-01 1.195767e-01
58 -8.192012e-02 -1.194333e-01
59 2.387614e-02 -8.192012e-02
60 2.207472e-01 2.387614e-02
61 2.490212e-01 2.207472e-01
62 4.698415e-01 2.490212e-01
63 -5.092375e-05 4.698415e-01
64 -1.582093e-01 -5.092375e-05
65 -5.195233e-01 -1.582093e-01
66 -7.644190e-01 -5.195233e-01
67 -6.710265e-01 -7.644190e-01
68 -7.929812e-01 -6.710265e-01
69 -3.269130e-02 -7.929812e-01
70 1.211921e-01 -3.269130e-02
71 5.329225e-01 1.211921e-01
72 6.426938e-01 5.329225e-01
73 8.992214e-01 6.426938e-01
74 6.875141e-01 8.992214e-01
75 9.939474e-01 6.875141e-01
76 5.376075e-01 9.939474e-01
77 1.918139e-01 5.376075e-01
78 -4.668318e-01 1.918139e-01
79 -9.000328e-01 -4.668318e-01
80 -6.770560e-01 -9.000328e-01
81 -1.830179e-01 -6.770560e-01
82 -5.788451e-02 -1.830179e-01
83 -4.062679e-01 -5.788451e-02
84 2.446163e-02 -4.062679e-01
85 7.057729e-02 2.446163e-02
86 -1.132145e-01 7.057729e-02
87 1.013336e-01 -1.132145e-01
88 2.298827e-02 1.013336e-01
89 -3.100635e-01 2.298827e-02
90 -1.226052e-01 -3.100635e-01
91 -1.111978e-01 -1.226052e-01
92 -2.326801e-01 -1.111978e-01
93 -2.392877e-01 -2.326801e-01
94 -6.795803e-01 -2.392877e-01
95 -8.157587e-02 -6.795803e-01
96 1.908343e-01 -8.157587e-02
97 4.752861e-01 1.908343e-01
98 3.256908e-01 4.752861e-01
99 -2.407229e-01 3.256908e-01
100 -3.970868e-01 -2.407229e-01
101 -2.507824e-01 -3.970868e-01
102 1.838273e-01 -2.507824e-01
103 2.175632e-01 1.838273e-01
104 1.335827e-01 2.175632e-01
105 -8.908515e-01 1.335827e-01
106 -1.382561e+00 -8.908515e-01
107 -1.363511e+00 -1.382561e+00
108 -6.264609e-01 -1.363511e+00
109 -1.608193e-01 -6.264609e-01
110 1.327465e-01 -1.608193e-01
111 4.199919e-01 1.327465e-01
112 2.175086e-01 4.199919e-01
113 9.587703e-02 2.175086e-01
114 -2.374492e-01 9.587703e-02
115 5.428301e-02 -2.374492e-01
116 3.053488e-01 5.428301e-02
117 5.709749e-01 3.053488e-01
118 7.732925e-01 5.709749e-01
119 5.849127e-01 7.732925e-01
> 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/7mf3z1292700717.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8x6221292700717.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9x6221292700717.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10qgk51292700717.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11tyit1292700717.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/12egyh1292700717.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/13sqwq1292700717.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/14wrvw1292700717.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/15zru21292700717.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/163aa71292700717.tab")
+ }
>
> try(system("convert tmp/1jw4t1292700717.ps tmp/1jw4t1292700717.png",intern=TRUE))
character(0)
> try(system("convert tmp/2jw4t1292700717.ps tmp/2jw4t1292700717.png",intern=TRUE))
character(0)
> try(system("convert tmp/3c64x1292700717.ps tmp/3c64x1292700717.png",intern=TRUE))
character(0)
> try(system("convert tmp/4c64x1292700717.ps tmp/4c64x1292700717.png",intern=TRUE))
character(0)
> try(system("convert tmp/5c64x1292700717.ps tmp/5c64x1292700717.png",intern=TRUE))
character(0)
> try(system("convert tmp/6mf3z1292700717.ps tmp/6mf3z1292700717.png",intern=TRUE))
character(0)
> try(system("convert tmp/7mf3z1292700717.ps tmp/7mf3z1292700717.png",intern=TRUE))
character(0)
> try(system("convert tmp/8x6221292700717.ps tmp/8x6221292700717.png",intern=TRUE))
character(0)
> try(system("convert tmp/9x6221292700717.ps tmp/9x6221292700717.png",intern=TRUE))
character(0)
> try(system("convert tmp/10qgk51292700717.ps tmp/10qgk51292700717.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
3.349 1.718 8.638