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(69
+ ,26
+ ,9
+ ,15
+ ,25
+ ,25
+ ,53
+ ,20
+ ,9
+ ,15
+ ,25
+ ,24
+ ,43
+ ,21
+ ,9
+ ,14
+ ,19
+ ,21
+ ,60
+ ,31
+ ,14
+ ,10
+ ,18
+ ,23
+ ,49
+ ,21
+ ,8
+ ,10
+ ,18
+ ,17
+ ,62
+ ,18
+ ,8
+ ,12
+ ,22
+ ,19
+ ,45
+ ,26
+ ,11
+ ,18
+ ,29
+ ,18
+ ,50
+ ,22
+ ,10
+ ,12
+ ,26
+ ,27
+ ,75
+ ,22
+ ,9
+ ,14
+ ,25
+ ,23
+ ,82
+ ,29
+ ,15
+ ,18
+ ,23
+ ,23
+ ,60
+ ,15
+ ,14
+ ,9
+ ,23
+ ,29
+ ,59
+ ,16
+ ,11
+ ,11
+ ,23
+ ,21
+ ,21
+ ,24
+ ,14
+ ,11
+ ,24
+ ,26
+ ,62
+ ,17
+ ,6
+ ,17
+ ,30
+ ,25
+ ,54
+ ,19
+ ,20
+ ,8
+ ,19
+ ,25
+ ,47
+ ,22
+ ,9
+ ,16
+ ,24
+ ,23
+ ,59
+ ,31
+ ,10
+ ,21
+ ,32
+ ,26
+ ,37
+ ,28
+ ,8
+ ,24
+ ,30
+ ,20
+ ,43
+ ,38
+ ,11
+ ,21
+ ,29
+ ,29
+ ,48
+ ,26
+ ,14
+ ,14
+ ,17
+ ,24
+ ,79
+ ,25
+ ,11
+ ,7
+ ,25
+ ,23
+ ,62
+ ,25
+ ,16
+ ,18
+ ,26
+ ,24
+ ,16
+ ,29
+ ,14
+ ,18
+ ,26
+ ,30
+ ,38
+ ,28
+ ,11
+ ,13
+ ,25
+ ,22
+ ,58
+ ,15
+ ,11
+ ,11
+ ,23
+ ,22
+ ,60
+ ,18
+ ,12
+ ,13
+ ,21
+ ,13
+ ,67
+ ,21
+ ,9
+ ,13
+ ,19
+ ,24
+ ,55
+ ,25
+ ,7
+ ,18
+ ,35
+ ,17
+ ,47
+ ,23
+ ,13
+ ,14
+ ,19
+ ,24
+ ,59
+ ,23
+ ,10
+ ,12
+ ,20
+ ,21
+ ,49
+ ,19
+ ,9
+ ,9
+ ,21
+ ,23
+ ,47
+ ,18
+ ,9
+ ,12
+ ,21
+ ,24
+ ,57
+ ,18
+ ,13
+ ,8
+ ,24
+ ,24
+ ,39
+ ,26
+ ,16
+ ,5
+ ,23
+ ,24
+ ,49
+ ,18
+ ,12
+ ,10
+ ,19
+ ,23
+ ,26
+ ,18
+ ,6
+ ,11
+ ,17
+ ,26
+ ,53
+ ,28
+ ,14
+ ,11
+ ,24
+ ,24
+ ,75
+ ,17
+ ,14
+ ,12
+ ,15
+ ,21
+ ,65
+ ,29
+ ,10
+ ,12
+ ,25
+ ,23
+ ,49
+ ,12
+ ,4
+ ,15
+ ,27
+ ,28
+ ,48
+ ,25
+ ,12
+ ,12
+ ,29
+ ,23
+ ,45
+ ,28
+ ,12
+ ,16
+ ,27
+ ,22
+ ,31
+ ,20
+ ,14
+ ,14
+ ,18
+ ,24
+ ,61
+ ,17
+ ,9
+ ,17
+ ,25
+ ,21
+ ,49
+ ,17
+ ,9
+ ,13
+ ,22
+ ,23
+ ,69
+ ,20
+ ,10
+ ,10
+ ,26
+ ,23
+ ,54
+ ,31
+ ,14
+ ,17
+ ,23
+ ,20
+ ,80
+ ,21
+ ,10
+ ,12
+ ,16
+ ,23
+ ,57
+ ,19
+ ,9
+ ,13
+ ,27
+ ,21
+ ,34
+ ,23
+ ,14
+ ,13
+ ,25
+ ,27
+ ,69
+ ,15
+ ,8
+ ,11
+ ,14
+ ,12
+ ,44
+ ,24
+ ,9
+ ,13
+ ,19
+ ,15
+ ,70
+ ,28
+ ,8
+ ,12
+ ,20
+ ,22
+ ,51
+ ,16
+ ,9
+ ,12
+ ,16
+ ,21
+ ,66
+ ,19
+ ,9
+ ,12
+ ,18
+ ,21
+ ,18
+ ,21
+ ,9
+ ,9
+ ,22
+ ,20
+ ,74
+ ,21
+ ,15
+ ,7
+ ,21
+ ,24
+ ,59
+ ,20
+ ,8
+ ,17
+ ,22
+ ,24
+ ,48
+ ,16
+ ,10
+ ,12
+ ,22
+ ,29
+ ,55
+ ,25
+ ,8
+ ,12
+ ,32
+ ,25
+ ,44
+ ,30
+ ,14
+ ,9
+ ,23
+ ,14
+ ,56
+ ,29
+ ,11
+ ,9
+ ,31
+ ,30
+ ,65
+ ,22
+ ,10
+ ,13
+ ,18
+ ,19
+ ,77
+ ,19
+ ,12
+ ,10
+ ,23
+ ,29
+ ,46
+ ,33
+ ,14
+ ,11
+ ,26
+ ,25
+ ,70
+ ,17
+ ,9
+ ,12
+ ,24
+ ,25
+ ,39
+ ,9
+ ,13
+ ,10
+ ,19
+ ,25
+ ,55
+ ,14
+ ,15
+ ,13
+ ,14
+ ,16
+ ,44
+ ,15
+ ,8
+ ,6
+ ,20
+ ,25
+ ,45
+ ,12
+ ,7
+ ,7
+ ,22
+ ,28
+ ,45
+ ,21
+ ,10
+ ,13
+ ,24
+ ,24
+ ,49
+ ,20
+ ,10
+ ,11
+ ,25
+ ,25
+ ,65
+ ,29
+ ,13
+ ,18
+ ,21
+ ,21
+ ,45
+ ,33
+ ,11
+ ,9
+ ,28
+ ,22
+ ,71
+ ,21
+ ,8
+ ,9
+ ,24
+ ,20
+ ,48
+ ,15
+ ,12
+ ,11
+ ,20
+ ,25
+ ,41
+ ,19
+ ,9
+ ,11
+ ,21
+ ,27
+ ,40
+ ,23
+ ,10
+ ,15
+ ,23
+ ,21
+ ,64
+ ,20
+ ,11
+ ,8
+ ,13
+ ,13
+ ,56
+ ,20
+ ,11
+ ,11
+ ,24
+ ,26
+ ,52
+ ,18
+ ,10
+ ,14
+ ,21
+ ,26
+ ,41
+ ,31
+ ,16
+ ,14
+ ,21
+ ,25
+ ,42
+ ,18
+ ,16
+ ,12
+ ,17
+ ,22
+ ,54
+ ,13
+ ,8
+ ,12
+ ,14
+ ,19
+ ,40
+ ,9
+ ,6
+ ,8
+ ,29
+ ,23
+ ,40
+ ,20
+ ,11
+ ,11
+ ,25
+ ,25
+ ,51
+ ,18
+ ,12
+ ,10
+ ,16
+ ,15
+ ,48
+ ,23
+ ,14
+ ,17
+ ,25
+ ,21
+ ,80
+ ,17
+ ,9
+ ,16
+ ,25
+ ,23
+ ,38
+ ,17
+ ,11
+ ,13
+ ,21
+ ,25
+ ,57
+ ,16
+ ,8
+ ,15
+ ,23
+ ,24
+ ,28
+ ,31
+ ,8
+ ,11
+ ,22
+ ,24
+ ,51
+ ,15
+ ,7
+ ,12
+ ,19
+ ,21
+ ,46
+ ,28
+ ,16
+ ,16
+ ,24
+ ,24
+ ,58
+ ,26
+ ,13
+ ,20
+ ,26
+ ,22
+ ,67
+ ,20
+ ,8
+ ,16
+ ,25
+ ,24
+ ,72
+ ,19
+ ,11
+ ,11
+ ,20
+ ,28
+ ,26
+ ,25
+ ,14
+ ,15
+ ,22
+ ,21
+ ,54
+ ,18
+ ,10
+ ,15
+ ,14
+ ,17
+ ,53
+ ,20
+ ,10
+ ,12
+ ,20
+ ,28
+ ,64
+ ,33
+ ,14
+ ,9
+ ,32
+ ,24
+ ,47
+ ,24
+ ,14
+ ,24
+ ,21
+ ,10
+ ,43
+ ,22
+ ,10
+ ,15
+ ,22
+ ,20
+ ,66
+ ,32
+ ,12
+ ,18
+ ,28
+ ,22
+ ,54
+ ,31
+ ,9
+ ,17
+ ,25
+ ,19
+ ,62
+ ,13
+ ,16
+ ,12
+ ,17
+ ,22
+ ,52
+ ,18
+ ,8
+ ,15
+ ,21
+ ,22
+ ,64
+ ,17
+ ,9
+ ,11
+ ,23
+ ,26
+ ,55
+ ,29
+ ,16
+ ,11
+ ,27
+ ,24
+ ,57
+ ,22
+ ,13
+ ,15
+ ,22
+ ,22
+ ,74
+ ,18
+ ,13
+ ,12
+ ,19
+ ,20
+ ,32
+ ,22
+ ,8
+ ,14
+ ,20
+ ,20
+ ,38
+ ,25
+ ,14
+ ,11
+ ,17
+ ,15
+ ,66
+ ,20
+ ,11
+ ,20
+ ,24
+ ,20
+ ,37
+ ,20
+ ,9
+ ,11
+ ,21
+ ,20
+ ,26
+ ,17
+ ,8
+ ,12
+ ,21
+ ,24
+ ,64
+ ,21
+ ,13
+ ,17
+ ,23
+ ,22
+ ,28
+ ,26
+ ,13
+ ,12
+ ,24
+ ,29
+ ,66
+ ,10
+ ,10
+ ,11
+ ,19
+ ,23
+ ,65
+ ,15
+ ,8
+ ,10
+ ,22
+ ,24
+ ,48
+ ,20
+ ,7
+ ,11
+ ,26
+ ,22
+ ,44
+ ,14
+ ,11
+ ,12
+ ,17
+ ,16
+ ,64
+ ,16
+ ,11
+ ,9
+ ,17
+ ,23
+ ,39
+ ,23
+ ,14
+ ,8
+ ,19
+ ,27
+ ,50
+ ,11
+ ,6
+ ,6
+ ,15
+ ,16
+ ,66
+ ,19
+ ,10
+ ,12
+ ,17
+ ,21
+ ,48
+ ,30
+ ,9
+ ,15
+ ,27
+ ,26
+ ,70
+ ,21
+ ,12
+ ,13
+ ,19
+ ,22
+ ,66
+ ,20
+ ,11
+ ,17
+ ,21
+ ,23
+ ,61
+ ,22
+ ,14
+ ,14
+ ,25
+ ,19
+ ,31
+ ,30
+ ,12
+ ,16
+ ,19
+ ,18
+ ,61
+ ,25
+ ,14
+ ,15
+ ,22
+ ,24
+ ,54
+ ,28
+ ,8
+ ,16
+ ,18
+ ,24
+ ,34
+ ,23
+ ,14
+ ,11
+ ,20
+ ,29
+ ,62
+ ,23
+ ,8
+ ,11
+ ,15
+ ,22
+ ,47
+ ,21
+ ,11
+ ,16
+ ,20
+ ,24
+ ,52
+ ,30
+ ,12
+ ,15
+ ,29
+ ,22
+ ,37
+ ,22
+ ,9
+ ,14
+ ,19
+ ,12
+ ,46
+ ,32
+ ,16
+ ,9
+ ,29
+ ,26
+ ,38
+ ,22
+ ,11
+ ,13
+ ,24
+ ,18
+ ,63
+ ,15
+ ,11
+ ,11
+ ,23
+ ,22
+ ,34
+ ,21
+ ,12
+ ,14
+ ,22
+ ,24
+ ,46
+ ,27
+ ,15
+ ,11
+ ,23
+ ,21
+ ,40
+ ,22
+ ,13
+ ,12
+ ,22
+ ,15
+ ,30
+ ,9
+ ,6
+ ,8
+ ,29
+ ,23
+ ,35
+ ,29
+ ,11
+ ,7
+ ,26
+ ,22
+ ,51
+ ,20
+ ,7
+ ,11
+ ,26
+ ,22
+ ,56
+ ,16
+ ,8
+ ,13
+ ,21
+ ,24
+ ,68
+ ,16
+ ,8
+ ,9
+ ,18
+ ,23
+ ,39
+ ,16
+ ,9
+ ,12
+ ,10
+ ,13
+ ,44
+ ,18
+ ,12
+ ,10
+ ,19
+ ,23
+ ,58
+ ,16
+ ,9
+ ,12
+ ,10
+ ,13)
+ ,dim=c(6
+ ,152)
+ ,dimnames=list(c('Anxiety'
+ ,'Concern'
+ ,'Doubts'
+ ,'Pexpectations'
+ ,'Standards'
+ ,'Organization')
+ ,1:152))
> y <- array(NA,dim=c(6,152),dimnames=list(c('Anxiety','Concern','Doubts','Pexpectations','Standards','Organization'),1:152))
> 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 = '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
Anxiety Concern Doubts Pexpectations Standards Organization
1 69 26 9 15 25 25
2 53 20 9 15 25 24
3 43 21 9 14 19 21
4 60 31 14 10 18 23
5 49 21 8 10 18 17
6 62 18 8 12 22 19
7 45 26 11 18 29 18
8 50 22 10 12 26 27
9 75 22 9 14 25 23
10 82 29 15 18 23 23
11 60 15 14 9 23 29
12 59 16 11 11 23 21
13 21 24 14 11 24 26
14 62 17 6 17 30 25
15 54 19 20 8 19 25
16 47 22 9 16 24 23
17 59 31 10 21 32 26
18 37 28 8 24 30 20
19 43 38 11 21 29 29
20 48 26 14 14 17 24
21 79 25 11 7 25 23
22 62 25 16 18 26 24
23 16 29 14 18 26 30
24 38 28 11 13 25 22
25 58 15 11 11 23 22
26 60 18 12 13 21 13
27 67 21 9 13 19 24
28 55 25 7 18 35 17
29 47 23 13 14 19 24
30 59 23 10 12 20 21
31 49 19 9 9 21 23
32 47 18 9 12 21 24
33 57 18 13 8 24 24
34 39 26 16 5 23 24
35 49 18 12 10 19 23
36 26 18 6 11 17 26
37 53 28 14 11 24 24
38 75 17 14 12 15 21
39 65 29 10 12 25 23
40 49 12 4 15 27 28
41 48 25 12 12 29 23
42 45 28 12 16 27 22
43 31 20 14 14 18 24
44 61 17 9 17 25 21
45 49 17 9 13 22 23
46 69 20 10 10 26 23
47 54 31 14 17 23 20
48 80 21 10 12 16 23
49 57 19 9 13 27 21
50 34 23 14 13 25 27
51 69 15 8 11 14 12
52 44 24 9 13 19 15
53 70 28 8 12 20 22
54 51 16 9 12 16 21
55 66 19 9 12 18 21
56 18 21 9 9 22 20
57 74 21 15 7 21 24
58 59 20 8 17 22 24
59 48 16 10 12 22 29
60 55 25 8 12 32 25
61 44 30 14 9 23 14
62 56 29 11 9 31 30
63 65 22 10 13 18 19
64 77 19 12 10 23 29
65 46 33 14 11 26 25
66 70 17 9 12 24 25
67 39 9 13 10 19 25
68 55 14 15 13 14 16
69 44 15 8 6 20 25
70 45 12 7 7 22 28
71 45 21 10 13 24 24
72 49 20 10 11 25 25
73 65 29 13 18 21 21
74 45 33 11 9 28 22
75 71 21 8 9 24 20
76 48 15 12 11 20 25
77 41 19 9 11 21 27
78 40 23 10 15 23 21
79 64 20 11 8 13 13
80 56 20 11 11 24 26
81 52 18 10 14 21 26
82 41 31 16 14 21 25
83 42 18 16 12 17 22
84 54 13 8 12 14 19
85 40 9 6 8 29 23
86 40 20 11 11 25 25
87 51 18 12 10 16 15
88 48 23 14 17 25 21
89 80 17 9 16 25 23
90 38 17 11 13 21 25
91 57 16 8 15 23 24
92 28 31 8 11 22 24
93 51 15 7 12 19 21
94 46 28 16 16 24 24
95 58 26 13 20 26 22
96 67 20 8 16 25 24
97 72 19 11 11 20 28
98 26 25 14 15 22 21
99 54 18 10 15 14 17
100 53 20 10 12 20 28
101 64 33 14 9 32 24
102 47 24 14 24 21 10
103 43 22 10 15 22 20
104 66 32 12 18 28 22
105 54 31 9 17 25 19
106 62 13 16 12 17 22
107 52 18 8 15 21 22
108 64 17 9 11 23 26
109 55 29 16 11 27 24
110 57 22 13 15 22 22
111 74 18 13 12 19 20
112 32 22 8 14 20 20
113 38 25 14 11 17 15
114 66 20 11 20 24 20
115 37 20 9 11 21 20
116 26 17 8 12 21 24
117 64 21 13 17 23 22
118 28 26 13 12 24 29
119 66 10 10 11 19 23
120 65 15 8 10 22 24
121 48 20 7 11 26 22
122 44 14 11 12 17 16
123 64 16 11 9 17 23
124 39 23 14 8 19 27
125 50 11 6 6 15 16
126 66 19 10 12 17 21
127 48 30 9 15 27 26
128 70 21 12 13 19 22
129 66 20 11 17 21 23
130 61 22 14 14 25 19
131 31 30 12 16 19 18
132 61 25 14 15 22 24
133 54 28 8 16 18 24
134 34 23 14 11 20 29
135 62 23 8 11 15 22
136 47 21 11 16 20 24
137 52 30 12 15 29 22
138 37 22 9 14 19 12
139 46 32 16 9 29 26
140 38 22 11 13 24 18
141 63 15 11 11 23 22
142 34 21 12 14 22 24
143 46 27 15 11 23 21
144 40 22 13 12 22 15
145 30 9 6 8 29 23
146 35 29 11 7 26 22
147 51 20 7 11 26 22
148 56 16 8 13 21 24
149 68 16 8 9 18 23
150 39 16 9 12 10 13
151 44 18 12 10 19 23
152 58 16 9 12 10 13
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Concern Doubts Pexpectations Standards
56.071094 -0.342981 0.077428 0.306566 0.004335
Organization
-0.065349
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-34.879 -8.438 -1.064 9.225 30.599
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 56.071094 9.180962 6.107 8.73e-09 ***
Concern -0.342981 0.247037 -1.388 0.167
Doubts 0.077428 0.448984 0.172 0.863
Pexpectations 0.306566 0.355773 0.862 0.390
Standards 0.004335 0.314703 0.014 0.989
Organization -0.065349 0.317583 -0.206 0.837
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 13.52 on 146 degrees of freedom
Multiple R-squared: 0.01918, Adjusted R-squared: -0.01441
F-statistic: 0.5709 on 5 and 146 DF, p-value: 0.7222
> 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,] 0.6788305 0.64233893 0.32116947
[2,] 0.8228854 0.35422912 0.17711456
[3,] 0.7220371 0.55592579 0.27796289
[4,] 0.6301743 0.73965149 0.36982575
[5,] 0.9321368 0.13572630 0.06786315
[6,] 0.8937679 0.21246419 0.10623210
[7,] 0.8450014 0.30999717 0.15499859
[8,] 0.8472663 0.30546738 0.15273369
[9,] 0.7934435 0.41311304 0.20655652
[10,] 0.8622127 0.27557451 0.13778725
[11,] 0.8444334 0.31113326 0.15556663
[12,] 0.8118904 0.37621911 0.18810956
[13,] 0.8665344 0.26693124 0.13346562
[14,] 0.8437746 0.31245077 0.15622538
[15,] 0.9526787 0.09464267 0.04732134
[16,] 0.9607773 0.07844538 0.03922269
[17,] 0.9447486 0.11050275 0.05525137
[18,] 0.9253758 0.14924837 0.07462419
[19,] 0.9256547 0.14869059 0.07434530
[20,] 0.9017948 0.19641035 0.09820518
[21,] 0.8752328 0.24953450 0.12476725
[22,] 0.8438457 0.31230868 0.15615434
[23,] 0.8194628 0.36107438 0.18053719
[24,] 0.7886992 0.42260160 0.21130080
[25,] 0.7452939 0.50941230 0.25470615
[26,] 0.7513105 0.49737896 0.24868948
[27,] 0.7101616 0.57967675 0.28983838
[28,] 0.8063018 0.38739631 0.19369816
[29,] 0.7655265 0.46894698 0.23447349
[30,] 0.8093821 0.38123578 0.19061789
[31,] 0.8119147 0.37617052 0.18808526
[32,] 0.7765824 0.44683513 0.22341756
[33,] 0.7408701 0.51825972 0.25912986
[34,] 0.7088773 0.58224531 0.29112266
[35,] 0.7686136 0.46277283 0.23138642
[36,] 0.7338292 0.53234167 0.26617084
[37,] 0.6931217 0.61375657 0.30687829
[38,] 0.7041191 0.59176184 0.29588092
[39,] 0.6582302 0.68353954 0.34176977
[40,] 0.7902325 0.41953508 0.20976754
[41,] 0.7533089 0.49338214 0.24669107
[42,] 0.7681547 0.46369066 0.23184533
[43,] 0.7570998 0.48580035 0.24290017
[44,] 0.7593925 0.48121503 0.24060751
[45,] 0.7903190 0.41936209 0.20968104
[46,] 0.7562595 0.48748107 0.24374054
[47,] 0.7475343 0.50493146 0.25246573
[48,] 0.9179444 0.16411119 0.08205560
[49,] 0.9456871 0.10862587 0.05431293
[50,] 0.9336296 0.13274072 0.06637036
[51,] 0.9187256 0.16254876 0.08127438
[52,] 0.9008772 0.19824558 0.09912279
[53,] 0.8923960 0.21520791 0.10760396
[54,] 0.8776247 0.24475064 0.12237532
[55,] 0.8726412 0.25471764 0.12735882
[56,] 0.9235943 0.15281150 0.07640575
[57,] 0.9057521 0.18849587 0.09424793
[58,] 0.9143541 0.17129175 0.08564587
[59,] 0.9243538 0.15129236 0.07564618
[60,] 0.9058317 0.18833654 0.09416827
[61,] 0.8947620 0.21047603 0.10523802
[62,] 0.8799562 0.24008767 0.12004384
[63,] 0.8619735 0.27605302 0.13802651
[64,] 0.8351536 0.32969276 0.16484638
[65,] 0.8339994 0.33200119 0.16600060
[66,] 0.8082474 0.38350522 0.19175261
[67,] 0.8522085 0.29558294 0.14779147
[68,] 0.8288961 0.34220776 0.17110388
[69,] 0.8183628 0.36327430 0.18163715
[70,] 0.8133689 0.37326218 0.18663109
[71,] 0.8306733 0.33865335 0.16932668
[72,] 0.8018947 0.39621061 0.19810530
[73,] 0.7688932 0.46221360 0.23110680
[74,] 0.7451356 0.50972874 0.25486437
[75,] 0.7372990 0.52540197 0.26270099
[76,] 0.6974047 0.60519060 0.30259530
[77,] 0.7026383 0.59472333 0.29736167
[78,] 0.6950736 0.60985274 0.30492637
[79,] 0.6598496 0.68030082 0.34015041
[80,] 0.6246296 0.75074086 0.37537043
[81,] 0.7228828 0.55423436 0.27711718
[82,] 0.7496069 0.50078614 0.25039307
[83,] 0.7100162 0.57996750 0.28998375
[84,] 0.7431819 0.51363613 0.25681807
[85,] 0.7035523 0.59289542 0.29644771
[86,] 0.6699694 0.66006111 0.33003056
[87,] 0.6265295 0.74694109 0.37347054
[88,] 0.6203441 0.75931182 0.37965591
[89,] 0.6628446 0.67431071 0.33715535
[90,] 0.7822170 0.43556598 0.21778299
[91,] 0.7435697 0.51286068 0.25643034
[92,] 0.7010044 0.59799130 0.29899565
[93,] 0.7657024 0.46859528 0.23429764
[94,] 0.7536015 0.49279700 0.24639850
[95,] 0.7334914 0.53301712 0.26650856
[96,] 0.7577523 0.48449542 0.24224771
[97,] 0.7383810 0.52323792 0.26161896
[98,] 0.6997227 0.60055453 0.30027727
[99,] 0.6525822 0.69483570 0.34741785
[100,] 0.6385858 0.72282848 0.36141424
[101,] 0.6152963 0.76940731 0.38470366
[102,] 0.5649286 0.87014279 0.43507140
[103,] 0.6397163 0.72056741 0.36028371
[104,] 0.6872637 0.62547253 0.31273626
[105,] 0.6581231 0.68375390 0.34187695
[106,] 0.6270162 0.74596770 0.37298385
[107,] 0.6157542 0.76849153 0.38424577
[108,] 0.7873596 0.42528080 0.21264040
[109,] 0.7661922 0.46761559 0.23380780
[110,] 0.8514040 0.29719209 0.14859605
[111,] 0.8281394 0.34372115 0.17186057
[112,] 0.8213530 0.35729397 0.17864698
[113,] 0.7777354 0.44452925 0.22226462
[114,] 0.7465324 0.50693524 0.25346762
[115,] 0.7339595 0.53208101 0.26604051
[116,] 0.7185345 0.56293091 0.28146546
[117,] 0.6617991 0.67640185 0.33820093
[118,] 0.6645662 0.67086759 0.33543379
[119,] 0.5977121 0.80457585 0.40228792
[120,] 0.6621474 0.67570511 0.33785255
[121,] 0.6558112 0.68837765 0.34418882
[122,] 0.7196119 0.56077617 0.28038809
[123,] 0.7619479 0.47610411 0.23805205
[124,] 0.7767635 0.44647298 0.22323649
[125,] 0.7146183 0.57076337 0.28538168
[126,] 0.8025212 0.39495765 0.19747883
[127,] 0.7388278 0.52234435 0.26117217
[128,] 0.6889264 0.62214722 0.31107361
[129,] 0.6584113 0.68317734 0.34158867
[130,] 0.5659630 0.86807407 0.43403703
[131,] 0.4673066 0.93461320 0.53269340
[132,] 0.3597190 0.71943794 0.64028103
[133,] 0.4911522 0.98230446 0.50884777
[134,] 0.5960794 0.80784121 0.40392061
[135,] 0.4348553 0.86971054 0.56514473
> postscript(file="/var/www/html/rcomp/tmp/1v1y71292686405.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2v1y71292686405.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/36bga1292686405.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/46bga1292686405.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/56bga1292686405.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 = 152
Frequency = 1
1 2 3 4 5 6
18.07638721 -0.04684491 -9.56733261 11.83663065 -2.52069781 8.95058404
7 8 9 10 11 12
-7.47294856 -1.32690213 22.88033417 30.59903429 7.02592295 5.46526682
13 14 15 16 17 18
-29.70076523 7.58703762 1.99578952 -5.72846351 7.90946611 -16.26773959
19 20 21 22 23 24
-5.55804679 -3.03485432 29.90038464 9.20202688 -34.87910331 -11.97542059
25 26 27 28 29 30
4.18763476 5.94654912 14.93527940 2.40242390 -4.99503829 7.64999815
31 32 33 34 35 36
-2.59843496 -5.79576628 5.10778148 -9.45662369 -3.47159604 -26.10887787
37 38 39 40 41 42
3.54046010 21.30407782 15.81690308 -6.15082528 -2.72721613 -5.98121824
43 44 45 46 47 48
-22.09707306 6.11503487 -4.51499697 17.33887537 3.47294443 28.11207460
49 50 51 52 53 54
4.01859144 -17.59586527 14.80545011 -7.62391559 20.58510591 -2.65609734
55 56 57 58 59 60
13.36417417 -33.11285451 23.30143889 5.43045582 -5.23674808 4.70018796
61 62 63 64 65 66
-4.80959604 8.09060305 12.87842437 25.24613517 -1.68795867 16.91359622
67 68 69 70 71 72
-16.50515248 -0.43126602 -7.83819779 -7.90890258 -7.16382445 -2.83265883
73 74 75 76 77 78
13.63186375 -2.04725737 19.95590332 -5.68074233 -10.95017367 -12.28270653
79 80 81 82 83 84
12.27745167 4.15959673 -1.35563016 -8.42679962 -11.45111957 -0.72963779
85 86 87 88 89 90
-14.52407135 -11.91008695 -1.98137885 -5.21422212 25.55229835 -15.53482099
91 92 93 94 95 96
2.66733111 -19.95735911 -2.85722714 -5.14722821 5.03346193 13.72401680
97 98 99 100 101 102
19.96465377 -25.90212266 -0.21998734 1.07849607 16.83381476 -8.71869969
103 104 105 106 107 108
-9.68670051 15.77323618 3.78606619 6.83397743 -1.76873447 11.28984631
109 110 111 112 113 114
5.71557903 4.21171220 20.64179742 -20.21660757 -13.04627245 11.00840781
115 116 117 118 119 120
-15.06463279 -27.06131876 10.25126362 -22.04789674 10.63284900 11.86151773
121 122 123 124 125 126
-3.80075522 -10.82799257 11.23510759 -11.03702232 -3.62172500 13.29108119
127 128 129 130 131 132
-1.49501215 17.57229798 12.13715808 8.23179946 -19.52197000 9.29392294
133 134 135 136 137 138
3.49820760 -16.83035965 11.19844506 -6.14361123 2.00263908 -15.81248879
139 140 141 142 143 144
-1.52031958 -14.29036315 9.18763476 -18.61657681 -4.07165906 -12.32602828
145 146 147 148 149 150
-24.52407135 -12.79737664 -0.80075522 2.28913423 15.46305680 -15.15287471
151 152
-8.47159604 3.84712529
> postscript(file="/var/www/html/rcomp/tmp/6h2fv1292686405.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 = 152
Frequency = 1
lag(myerror, k = 1) myerror
0 18.07638721 NA
1 -0.04684491 18.07638721
2 -9.56733261 -0.04684491
3 11.83663065 -9.56733261
4 -2.52069781 11.83663065
5 8.95058404 -2.52069781
6 -7.47294856 8.95058404
7 -1.32690213 -7.47294856
8 22.88033417 -1.32690213
9 30.59903429 22.88033417
10 7.02592295 30.59903429
11 5.46526682 7.02592295
12 -29.70076523 5.46526682
13 7.58703762 -29.70076523
14 1.99578952 7.58703762
15 -5.72846351 1.99578952
16 7.90946611 -5.72846351
17 -16.26773959 7.90946611
18 -5.55804679 -16.26773959
19 -3.03485432 -5.55804679
20 29.90038464 -3.03485432
21 9.20202688 29.90038464
22 -34.87910331 9.20202688
23 -11.97542059 -34.87910331
24 4.18763476 -11.97542059
25 5.94654912 4.18763476
26 14.93527940 5.94654912
27 2.40242390 14.93527940
28 -4.99503829 2.40242390
29 7.64999815 -4.99503829
30 -2.59843496 7.64999815
31 -5.79576628 -2.59843496
32 5.10778148 -5.79576628
33 -9.45662369 5.10778148
34 -3.47159604 -9.45662369
35 -26.10887787 -3.47159604
36 3.54046010 -26.10887787
37 21.30407782 3.54046010
38 15.81690308 21.30407782
39 -6.15082528 15.81690308
40 -2.72721613 -6.15082528
41 -5.98121824 -2.72721613
42 -22.09707306 -5.98121824
43 6.11503487 -22.09707306
44 -4.51499697 6.11503487
45 17.33887537 -4.51499697
46 3.47294443 17.33887537
47 28.11207460 3.47294443
48 4.01859144 28.11207460
49 -17.59586527 4.01859144
50 14.80545011 -17.59586527
51 -7.62391559 14.80545011
52 20.58510591 -7.62391559
53 -2.65609734 20.58510591
54 13.36417417 -2.65609734
55 -33.11285451 13.36417417
56 23.30143889 -33.11285451
57 5.43045582 23.30143889
58 -5.23674808 5.43045582
59 4.70018796 -5.23674808
60 -4.80959604 4.70018796
61 8.09060305 -4.80959604
62 12.87842437 8.09060305
63 25.24613517 12.87842437
64 -1.68795867 25.24613517
65 16.91359622 -1.68795867
66 -16.50515248 16.91359622
67 -0.43126602 -16.50515248
68 -7.83819779 -0.43126602
69 -7.90890258 -7.83819779
70 -7.16382445 -7.90890258
71 -2.83265883 -7.16382445
72 13.63186375 -2.83265883
73 -2.04725737 13.63186375
74 19.95590332 -2.04725737
75 -5.68074233 19.95590332
76 -10.95017367 -5.68074233
77 -12.28270653 -10.95017367
78 12.27745167 -12.28270653
79 4.15959673 12.27745167
80 -1.35563016 4.15959673
81 -8.42679962 -1.35563016
82 -11.45111957 -8.42679962
83 -0.72963779 -11.45111957
84 -14.52407135 -0.72963779
85 -11.91008695 -14.52407135
86 -1.98137885 -11.91008695
87 -5.21422212 -1.98137885
88 25.55229835 -5.21422212
89 -15.53482099 25.55229835
90 2.66733111 -15.53482099
91 -19.95735911 2.66733111
92 -2.85722714 -19.95735911
93 -5.14722821 -2.85722714
94 5.03346193 -5.14722821
95 13.72401680 5.03346193
96 19.96465377 13.72401680
97 -25.90212266 19.96465377
98 -0.21998734 -25.90212266
99 1.07849607 -0.21998734
100 16.83381476 1.07849607
101 -8.71869969 16.83381476
102 -9.68670051 -8.71869969
103 15.77323618 -9.68670051
104 3.78606619 15.77323618
105 6.83397743 3.78606619
106 -1.76873447 6.83397743
107 11.28984631 -1.76873447
108 5.71557903 11.28984631
109 4.21171220 5.71557903
110 20.64179742 4.21171220
111 -20.21660757 20.64179742
112 -13.04627245 -20.21660757
113 11.00840781 -13.04627245
114 -15.06463279 11.00840781
115 -27.06131876 -15.06463279
116 10.25126362 -27.06131876
117 -22.04789674 10.25126362
118 10.63284900 -22.04789674
119 11.86151773 10.63284900
120 -3.80075522 11.86151773
121 -10.82799257 -3.80075522
122 11.23510759 -10.82799257
123 -11.03702232 11.23510759
124 -3.62172500 -11.03702232
125 13.29108119 -3.62172500
126 -1.49501215 13.29108119
127 17.57229798 -1.49501215
128 12.13715808 17.57229798
129 8.23179946 12.13715808
130 -19.52197000 8.23179946
131 9.29392294 -19.52197000
132 3.49820760 9.29392294
133 -16.83035965 3.49820760
134 11.19844506 -16.83035965
135 -6.14361123 11.19844506
136 2.00263908 -6.14361123
137 -15.81248879 2.00263908
138 -1.52031958 -15.81248879
139 -14.29036315 -1.52031958
140 9.18763476 -14.29036315
141 -18.61657681 9.18763476
142 -4.07165906 -18.61657681
143 -12.32602828 -4.07165906
144 -24.52407135 -12.32602828
145 -12.79737664 -24.52407135
146 -0.80075522 -12.79737664
147 2.28913423 -0.80075522
148 15.46305680 2.28913423
149 -15.15287471 15.46305680
150 -8.47159604 -15.15287471
151 3.84712529 -8.47159604
152 NA 3.84712529
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -0.04684491 18.07638721
[2,] -9.56733261 -0.04684491
[3,] 11.83663065 -9.56733261
[4,] -2.52069781 11.83663065
[5,] 8.95058404 -2.52069781
[6,] -7.47294856 8.95058404
[7,] -1.32690213 -7.47294856
[8,] 22.88033417 -1.32690213
[9,] 30.59903429 22.88033417
[10,] 7.02592295 30.59903429
[11,] 5.46526682 7.02592295
[12,] -29.70076523 5.46526682
[13,] 7.58703762 -29.70076523
[14,] 1.99578952 7.58703762
[15,] -5.72846351 1.99578952
[16,] 7.90946611 -5.72846351
[17,] -16.26773959 7.90946611
[18,] -5.55804679 -16.26773959
[19,] -3.03485432 -5.55804679
[20,] 29.90038464 -3.03485432
[21,] 9.20202688 29.90038464
[22,] -34.87910331 9.20202688
[23,] -11.97542059 -34.87910331
[24,] 4.18763476 -11.97542059
[25,] 5.94654912 4.18763476
[26,] 14.93527940 5.94654912
[27,] 2.40242390 14.93527940
[28,] -4.99503829 2.40242390
[29,] 7.64999815 -4.99503829
[30,] -2.59843496 7.64999815
[31,] -5.79576628 -2.59843496
[32,] 5.10778148 -5.79576628
[33,] -9.45662369 5.10778148
[34,] -3.47159604 -9.45662369
[35,] -26.10887787 -3.47159604
[36,] 3.54046010 -26.10887787
[37,] 21.30407782 3.54046010
[38,] 15.81690308 21.30407782
[39,] -6.15082528 15.81690308
[40,] -2.72721613 -6.15082528
[41,] -5.98121824 -2.72721613
[42,] -22.09707306 -5.98121824
[43,] 6.11503487 -22.09707306
[44,] -4.51499697 6.11503487
[45,] 17.33887537 -4.51499697
[46,] 3.47294443 17.33887537
[47,] 28.11207460 3.47294443
[48,] 4.01859144 28.11207460
[49,] -17.59586527 4.01859144
[50,] 14.80545011 -17.59586527
[51,] -7.62391559 14.80545011
[52,] 20.58510591 -7.62391559
[53,] -2.65609734 20.58510591
[54,] 13.36417417 -2.65609734
[55,] -33.11285451 13.36417417
[56,] 23.30143889 -33.11285451
[57,] 5.43045582 23.30143889
[58,] -5.23674808 5.43045582
[59,] 4.70018796 -5.23674808
[60,] -4.80959604 4.70018796
[61,] 8.09060305 -4.80959604
[62,] 12.87842437 8.09060305
[63,] 25.24613517 12.87842437
[64,] -1.68795867 25.24613517
[65,] 16.91359622 -1.68795867
[66,] -16.50515248 16.91359622
[67,] -0.43126602 -16.50515248
[68,] -7.83819779 -0.43126602
[69,] -7.90890258 -7.83819779
[70,] -7.16382445 -7.90890258
[71,] -2.83265883 -7.16382445
[72,] 13.63186375 -2.83265883
[73,] -2.04725737 13.63186375
[74,] 19.95590332 -2.04725737
[75,] -5.68074233 19.95590332
[76,] -10.95017367 -5.68074233
[77,] -12.28270653 -10.95017367
[78,] 12.27745167 -12.28270653
[79,] 4.15959673 12.27745167
[80,] -1.35563016 4.15959673
[81,] -8.42679962 -1.35563016
[82,] -11.45111957 -8.42679962
[83,] -0.72963779 -11.45111957
[84,] -14.52407135 -0.72963779
[85,] -11.91008695 -14.52407135
[86,] -1.98137885 -11.91008695
[87,] -5.21422212 -1.98137885
[88,] 25.55229835 -5.21422212
[89,] -15.53482099 25.55229835
[90,] 2.66733111 -15.53482099
[91,] -19.95735911 2.66733111
[92,] -2.85722714 -19.95735911
[93,] -5.14722821 -2.85722714
[94,] 5.03346193 -5.14722821
[95,] 13.72401680 5.03346193
[96,] 19.96465377 13.72401680
[97,] -25.90212266 19.96465377
[98,] -0.21998734 -25.90212266
[99,] 1.07849607 -0.21998734
[100,] 16.83381476 1.07849607
[101,] -8.71869969 16.83381476
[102,] -9.68670051 -8.71869969
[103,] 15.77323618 -9.68670051
[104,] 3.78606619 15.77323618
[105,] 6.83397743 3.78606619
[106,] -1.76873447 6.83397743
[107,] 11.28984631 -1.76873447
[108,] 5.71557903 11.28984631
[109,] 4.21171220 5.71557903
[110,] 20.64179742 4.21171220
[111,] -20.21660757 20.64179742
[112,] -13.04627245 -20.21660757
[113,] 11.00840781 -13.04627245
[114,] -15.06463279 11.00840781
[115,] -27.06131876 -15.06463279
[116,] 10.25126362 -27.06131876
[117,] -22.04789674 10.25126362
[118,] 10.63284900 -22.04789674
[119,] 11.86151773 10.63284900
[120,] -3.80075522 11.86151773
[121,] -10.82799257 -3.80075522
[122,] 11.23510759 -10.82799257
[123,] -11.03702232 11.23510759
[124,] -3.62172500 -11.03702232
[125,] 13.29108119 -3.62172500
[126,] -1.49501215 13.29108119
[127,] 17.57229798 -1.49501215
[128,] 12.13715808 17.57229798
[129,] 8.23179946 12.13715808
[130,] -19.52197000 8.23179946
[131,] 9.29392294 -19.52197000
[132,] 3.49820760 9.29392294
[133,] -16.83035965 3.49820760
[134,] 11.19844506 -16.83035965
[135,] -6.14361123 11.19844506
[136,] 2.00263908 -6.14361123
[137,] -15.81248879 2.00263908
[138,] -1.52031958 -15.81248879
[139,] -14.29036315 -1.52031958
[140,] 9.18763476 -14.29036315
[141,] -18.61657681 9.18763476
[142,] -4.07165906 -18.61657681
[143,] -12.32602828 -4.07165906
[144,] -24.52407135 -12.32602828
[145,] -12.79737664 -24.52407135
[146,] -0.80075522 -12.79737664
[147,] 2.28913423 -0.80075522
[148,] 15.46305680 2.28913423
[149,] -15.15287471 15.46305680
[150,] -8.47159604 -15.15287471
[151,] 3.84712529 -8.47159604
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -0.04684491 18.07638721
2 -9.56733261 -0.04684491
3 11.83663065 -9.56733261
4 -2.52069781 11.83663065
5 8.95058404 -2.52069781
6 -7.47294856 8.95058404
7 -1.32690213 -7.47294856
8 22.88033417 -1.32690213
9 30.59903429 22.88033417
10 7.02592295 30.59903429
11 5.46526682 7.02592295
12 -29.70076523 5.46526682
13 7.58703762 -29.70076523
14 1.99578952 7.58703762
15 -5.72846351 1.99578952
16 7.90946611 -5.72846351
17 -16.26773959 7.90946611
18 -5.55804679 -16.26773959
19 -3.03485432 -5.55804679
20 29.90038464 -3.03485432
21 9.20202688 29.90038464
22 -34.87910331 9.20202688
23 -11.97542059 -34.87910331
24 4.18763476 -11.97542059
25 5.94654912 4.18763476
26 14.93527940 5.94654912
27 2.40242390 14.93527940
28 -4.99503829 2.40242390
29 7.64999815 -4.99503829
30 -2.59843496 7.64999815
31 -5.79576628 -2.59843496
32 5.10778148 -5.79576628
33 -9.45662369 5.10778148
34 -3.47159604 -9.45662369
35 -26.10887787 -3.47159604
36 3.54046010 -26.10887787
37 21.30407782 3.54046010
38 15.81690308 21.30407782
39 -6.15082528 15.81690308
40 -2.72721613 -6.15082528
41 -5.98121824 -2.72721613
42 -22.09707306 -5.98121824
43 6.11503487 -22.09707306
44 -4.51499697 6.11503487
45 17.33887537 -4.51499697
46 3.47294443 17.33887537
47 28.11207460 3.47294443
48 4.01859144 28.11207460
49 -17.59586527 4.01859144
50 14.80545011 -17.59586527
51 -7.62391559 14.80545011
52 20.58510591 -7.62391559
53 -2.65609734 20.58510591
54 13.36417417 -2.65609734
55 -33.11285451 13.36417417
56 23.30143889 -33.11285451
57 5.43045582 23.30143889
58 -5.23674808 5.43045582
59 4.70018796 -5.23674808
60 -4.80959604 4.70018796
61 8.09060305 -4.80959604
62 12.87842437 8.09060305
63 25.24613517 12.87842437
64 -1.68795867 25.24613517
65 16.91359622 -1.68795867
66 -16.50515248 16.91359622
67 -0.43126602 -16.50515248
68 -7.83819779 -0.43126602
69 -7.90890258 -7.83819779
70 -7.16382445 -7.90890258
71 -2.83265883 -7.16382445
72 13.63186375 -2.83265883
73 -2.04725737 13.63186375
74 19.95590332 -2.04725737
75 -5.68074233 19.95590332
76 -10.95017367 -5.68074233
77 -12.28270653 -10.95017367
78 12.27745167 -12.28270653
79 4.15959673 12.27745167
80 -1.35563016 4.15959673
81 -8.42679962 -1.35563016
82 -11.45111957 -8.42679962
83 -0.72963779 -11.45111957
84 -14.52407135 -0.72963779
85 -11.91008695 -14.52407135
86 -1.98137885 -11.91008695
87 -5.21422212 -1.98137885
88 25.55229835 -5.21422212
89 -15.53482099 25.55229835
90 2.66733111 -15.53482099
91 -19.95735911 2.66733111
92 -2.85722714 -19.95735911
93 -5.14722821 -2.85722714
94 5.03346193 -5.14722821
95 13.72401680 5.03346193
96 19.96465377 13.72401680
97 -25.90212266 19.96465377
98 -0.21998734 -25.90212266
99 1.07849607 -0.21998734
100 16.83381476 1.07849607
101 -8.71869969 16.83381476
102 -9.68670051 -8.71869969
103 15.77323618 -9.68670051
104 3.78606619 15.77323618
105 6.83397743 3.78606619
106 -1.76873447 6.83397743
107 11.28984631 -1.76873447
108 5.71557903 11.28984631
109 4.21171220 5.71557903
110 20.64179742 4.21171220
111 -20.21660757 20.64179742
112 -13.04627245 -20.21660757
113 11.00840781 -13.04627245
114 -15.06463279 11.00840781
115 -27.06131876 -15.06463279
116 10.25126362 -27.06131876
117 -22.04789674 10.25126362
118 10.63284900 -22.04789674
119 11.86151773 10.63284900
120 -3.80075522 11.86151773
121 -10.82799257 -3.80075522
122 11.23510759 -10.82799257
123 -11.03702232 11.23510759
124 -3.62172500 -11.03702232
125 13.29108119 -3.62172500
126 -1.49501215 13.29108119
127 17.57229798 -1.49501215
128 12.13715808 17.57229798
129 8.23179946 12.13715808
130 -19.52197000 8.23179946
131 9.29392294 -19.52197000
132 3.49820760 9.29392294
133 -16.83035965 3.49820760
134 11.19844506 -16.83035965
135 -6.14361123 11.19844506
136 2.00263908 -6.14361123
137 -15.81248879 2.00263908
138 -1.52031958 -15.81248879
139 -14.29036315 -1.52031958
140 9.18763476 -14.29036315
141 -18.61657681 9.18763476
142 -4.07165906 -18.61657681
143 -12.32602828 -4.07165906
144 -24.52407135 -12.32602828
145 -12.79737664 -24.52407135
146 -0.80075522 -12.79737664
147 2.28913423 -0.80075522
148 15.46305680 2.28913423
149 -15.15287471 15.46305680
150 -8.47159604 -15.15287471
151 3.84712529 -8.47159604
> 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/7h2fv1292686405.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/89bwf1292686405.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/99bwf1292686405.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/109bwf1292686405.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11n3u61292686405.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/12gutr1292686405.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/135vql1292686405.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/14x4po1292686405.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/1515oc1292686405.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/16ff321292686405.tab")
+ }
>
> try(system("convert tmp/1v1y71292686405.ps tmp/1v1y71292686405.png",intern=TRUE))
character(0)
> try(system("convert tmp/2v1y71292686405.ps tmp/2v1y71292686405.png",intern=TRUE))
character(0)
> try(system("convert tmp/36bga1292686405.ps tmp/36bga1292686405.png",intern=TRUE))
character(0)
> try(system("convert tmp/46bga1292686405.ps tmp/46bga1292686405.png",intern=TRUE))
character(0)
> try(system("convert tmp/56bga1292686405.ps tmp/56bga1292686405.png",intern=TRUE))
character(0)
> try(system("convert tmp/6h2fv1292686405.ps tmp/6h2fv1292686405.png",intern=TRUE))
character(0)
> try(system("convert tmp/7h2fv1292686405.ps tmp/7h2fv1292686405.png",intern=TRUE))
character(0)
> try(system("convert tmp/89bwf1292686405.ps tmp/89bwf1292686405.png",intern=TRUE))
character(0)
> try(system("convert tmp/99bwf1292686405.ps tmp/99bwf1292686405.png",intern=TRUE))
character(0)
> try(system("convert tmp/109bwf1292686405.ps tmp/109bwf1292686405.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
4.061 2.018 11.691