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(3.7
+ ,0
+ ,3.7
+ ,3.93
+ ,4.15
+ ,4.24
+ ,3.65
+ ,0
+ ,3.7
+ ,3.7
+ ,3.93
+ ,4.15
+ ,3.55
+ ,0
+ ,3.65
+ ,3.7
+ ,3.7
+ ,3.93
+ ,3.43
+ ,0
+ ,3.55
+ ,3.65
+ ,3.7
+ ,3.7
+ ,3.47
+ ,0
+ ,3.43
+ ,3.55
+ ,3.65
+ ,3.7
+ ,3.58
+ ,0
+ ,3.47
+ ,3.43
+ ,3.55
+ ,3.65
+ ,3.67
+ ,0
+ ,3.58
+ ,3.47
+ ,3.43
+ ,3.55
+ ,3.72
+ ,0
+ ,3.67
+ ,3.58
+ ,3.47
+ ,3.43
+ ,3.8
+ ,0
+ ,3.72
+ ,3.67
+ ,3.58
+ ,3.47
+ ,3.76
+ ,0
+ ,3.8
+ ,3.72
+ ,3.67
+ ,3.58
+ ,3.63
+ ,0
+ ,3.76
+ ,3.8
+ ,3.72
+ ,3.67
+ ,3.48
+ ,0
+ ,3.63
+ ,3.76
+ ,3.8
+ ,3.72
+ ,3.41
+ ,0
+ ,3.48
+ ,3.63
+ ,3.76
+ ,3.8
+ ,3.43
+ ,0
+ ,3.41
+ ,3.48
+ ,3.63
+ ,3.76
+ ,3.5
+ ,0
+ ,3.43
+ ,3.41
+ ,3.48
+ ,3.63
+ ,3.62
+ ,0
+ ,3.5
+ ,3.43
+ ,3.41
+ ,3.48
+ ,3.58
+ ,0
+ ,3.62
+ ,3.5
+ ,3.43
+ ,3.41
+ ,3.52
+ ,0
+ ,3.58
+ ,3.62
+ ,3.5
+ ,3.43
+ ,3.45
+ ,0
+ ,3.52
+ ,3.58
+ ,3.62
+ ,3.5
+ ,3.36
+ ,0
+ ,3.45
+ ,3.52
+ ,3.58
+ ,3.62
+ ,3.27
+ ,0
+ ,3.36
+ ,3.45
+ ,3.52
+ ,3.58
+ ,3.21
+ ,0
+ ,3.27
+ ,3.36
+ ,3.45
+ ,3.52
+ ,3.19
+ ,0
+ ,3.21
+ ,3.27
+ ,3.36
+ ,3.45
+ ,3.16
+ ,0
+ ,3.19
+ ,3.21
+ ,3.27
+ ,3.36
+ ,3.12
+ ,0
+ ,3.16
+ ,3.19
+ ,3.21
+ ,3.27
+ ,3.06
+ ,0
+ ,3.12
+ ,3.16
+ ,3.19
+ ,3.21
+ ,3.01
+ ,0
+ ,3.06
+ ,3.12
+ ,3.16
+ ,3.19
+ ,2.98
+ ,0
+ ,3.01
+ ,3.06
+ ,3.12
+ ,3.16
+ ,2.97
+ ,0
+ ,2.98
+ ,3.01
+ ,3.06
+ ,3.12
+ ,3.02
+ ,0
+ ,2.97
+ ,2.98
+ ,3.01
+ ,3.06
+ ,3.07
+ ,0
+ ,3.02
+ ,2.97
+ ,2.98
+ ,3.01
+ ,3.18
+ ,0
+ ,3.07
+ ,3.02
+ ,2.97
+ ,2.98
+ ,3.29
+ ,1
+ ,3.18
+ ,3.07
+ ,3.02
+ ,2.97
+ ,3.43
+ ,1
+ ,3.29
+ ,3.18
+ ,3.07
+ ,3.02
+ ,3.61
+ ,1
+ ,3.43
+ ,3.29
+ ,3.18
+ ,3.07
+ ,3.74
+ ,1
+ ,3.61
+ ,3.43
+ ,3.29
+ ,3.18
+ ,3.87
+ ,1
+ ,3.74
+ ,3.61
+ ,3.43
+ ,3.29
+ ,3.88
+ ,1
+ ,3.87
+ ,3.74
+ ,3.61
+ ,3.43
+ ,4.09
+ ,1
+ ,3.88
+ ,3.87
+ ,3.74
+ ,3.61
+ ,4.19
+ ,1
+ ,4.09
+ ,3.88
+ ,3.87
+ ,3.74
+ ,4.2
+ ,1
+ ,4.19
+ ,4.09
+ ,3.88
+ ,3.87
+ ,4.29
+ ,1
+ ,4.2
+ ,4.19
+ ,4.09
+ ,3.88
+ ,4.37
+ ,1
+ ,4.29
+ ,4.2
+ ,4.19
+ ,4.09
+ ,4.47
+ ,1
+ ,4.37
+ ,4.29
+ ,4.2
+ ,4.19
+ ,4.61
+ ,1
+ ,4.47
+ ,4.37
+ ,4.29
+ ,4.2
+ ,4.65
+ ,1
+ ,4.61
+ ,4.47
+ ,4.37
+ ,4.29
+ ,4.69
+ ,1
+ ,4.65
+ ,4.61
+ ,4.47
+ ,4.37
+ ,4.82
+ ,1
+ ,4.69
+ ,4.65
+ ,4.61
+ ,4.47
+ ,4.86
+ ,1
+ ,4.82
+ ,4.69
+ ,4.65
+ ,4.61
+ ,4.87
+ ,1
+ ,4.86
+ ,4.82
+ ,4.69
+ ,4.65
+ ,5.01
+ ,1
+ ,4.87
+ ,4.86
+ ,4.82
+ ,4.69
+ ,5.03
+ ,1
+ ,5.01
+ ,4.87
+ ,4.86
+ ,4.82
+ ,5.13
+ ,1
+ ,5.03
+ ,5.01
+ ,4.87
+ ,4.86
+ ,5.18
+ ,1
+ ,5.13
+ ,5.03
+ ,5.01
+ ,4.87
+ ,5.21
+ ,1
+ ,5.18
+ ,5.13
+ ,5.03
+ ,5.01
+ ,5.26
+ ,1
+ ,5.21
+ ,5.18
+ ,5.13
+ ,5.03
+ ,5.25
+ ,1
+ ,5.26
+ ,5.21
+ ,5.18
+ ,5.13
+ ,5.2
+ ,1
+ ,5.25
+ ,5.26
+ ,5.21
+ ,5.18
+ ,5.16
+ ,1
+ ,5.2
+ ,5.25
+ ,5.26
+ ,5.21
+ ,5.19
+ ,1
+ ,5.16
+ ,5.2
+ ,5.25
+ ,5.26
+ ,5.39
+ ,1
+ ,5.19
+ ,5.16
+ ,5.2
+ ,5.25
+ ,5.58
+ ,1
+ ,5.39
+ ,5.19
+ ,5.16
+ ,5.2
+ ,5.76
+ ,1
+ ,5.58
+ ,5.39
+ ,5.19
+ ,5.16
+ ,5.89
+ ,1
+ ,5.76
+ ,5.58
+ ,5.39
+ ,5.19
+ ,5.98
+ ,1
+ ,5.89
+ ,5.76
+ ,5.58
+ ,5.39
+ ,6.02
+ ,1
+ ,5.98
+ ,5.89
+ ,5.76
+ ,5.58
+ ,5.62
+ ,1
+ ,6.02
+ ,5.98
+ ,5.89
+ ,5.76
+ ,4.87
+ ,1
+ ,5.62
+ ,6.02
+ ,5.98
+ ,5.89)
+ ,dim=c(6
+ ,68)
+ ,dimnames=list(c('Y'
+ ,'X'
+ ,'Y1'
+ ,'Y2'
+ ,'Y3'
+ ,'Y4')
+ ,1:68))
> y <- array(NA,dim=c(6,68),dimnames=list(c('Y','X','Y1','Y2','Y3','Y4'),1:68))
> 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
Y X Y1 Y2 Y3 Y4 M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 3.70 0 3.70 3.93 4.15 4.24 1 0 0 0 0 0 0 0 0 0 0 1
2 3.65 0 3.70 3.70 3.93 4.15 0 1 0 0 0 0 0 0 0 0 0 2
3 3.55 0 3.65 3.70 3.70 3.93 0 0 1 0 0 0 0 0 0 0 0 3
4 3.43 0 3.55 3.65 3.70 3.70 0 0 0 1 0 0 0 0 0 0 0 4
5 3.47 0 3.43 3.55 3.65 3.70 0 0 0 0 1 0 0 0 0 0 0 5
6 3.58 0 3.47 3.43 3.55 3.65 0 0 0 0 0 1 0 0 0 0 0 6
7 3.67 0 3.58 3.47 3.43 3.55 0 0 0 0 0 0 1 0 0 0 0 7
8 3.72 0 3.67 3.58 3.47 3.43 0 0 0 0 0 0 0 1 0 0 0 8
9 3.80 0 3.72 3.67 3.58 3.47 0 0 0 0 0 0 0 0 1 0 0 9
10 3.76 0 3.80 3.72 3.67 3.58 0 0 0 0 0 0 0 0 0 1 0 10
11 3.63 0 3.76 3.80 3.72 3.67 0 0 0 0 0 0 0 0 0 0 1 11
12 3.48 0 3.63 3.76 3.80 3.72 0 0 0 0 0 0 0 0 0 0 0 12
13 3.41 0 3.48 3.63 3.76 3.80 1 0 0 0 0 0 0 0 0 0 0 13
14 3.43 0 3.41 3.48 3.63 3.76 0 1 0 0 0 0 0 0 0 0 0 14
15 3.50 0 3.43 3.41 3.48 3.63 0 0 1 0 0 0 0 0 0 0 0 15
16 3.62 0 3.50 3.43 3.41 3.48 0 0 0 1 0 0 0 0 0 0 0 16
17 3.58 0 3.62 3.50 3.43 3.41 0 0 0 0 1 0 0 0 0 0 0 17
18 3.52 0 3.58 3.62 3.50 3.43 0 0 0 0 0 1 0 0 0 0 0 18
19 3.45 0 3.52 3.58 3.62 3.50 0 0 0 0 0 0 1 0 0 0 0 19
20 3.36 0 3.45 3.52 3.58 3.62 0 0 0 0 0 0 0 1 0 0 0 20
21 3.27 0 3.36 3.45 3.52 3.58 0 0 0 0 0 0 0 0 1 0 0 21
22 3.21 0 3.27 3.36 3.45 3.52 0 0 0 0 0 0 0 0 0 1 0 22
23 3.19 0 3.21 3.27 3.36 3.45 0 0 0 0 0 0 0 0 0 0 1 23
24 3.16 0 3.19 3.21 3.27 3.36 0 0 0 0 0 0 0 0 0 0 0 24
25 3.12 0 3.16 3.19 3.21 3.27 1 0 0 0 0 0 0 0 0 0 0 25
26 3.06 0 3.12 3.16 3.19 3.21 0 1 0 0 0 0 0 0 0 0 0 26
27 3.01 0 3.06 3.12 3.16 3.19 0 0 1 0 0 0 0 0 0 0 0 27
28 2.98 0 3.01 3.06 3.12 3.16 0 0 0 1 0 0 0 0 0 0 0 28
29 2.97 0 2.98 3.01 3.06 3.12 0 0 0 0 1 0 0 0 0 0 0 29
30 3.02 0 2.97 2.98 3.01 3.06 0 0 0 0 0 1 0 0 0 0 0 30
31 3.07 0 3.02 2.97 2.98 3.01 0 0 0 0 0 0 1 0 0 0 0 31
32 3.18 0 3.07 3.02 2.97 2.98 0 0 0 0 0 0 0 1 0 0 0 32
33 3.29 1 3.18 3.07 3.02 2.97 0 0 0 0 0 0 0 0 1 0 0 33
34 3.43 1 3.29 3.18 3.07 3.02 0 0 0 0 0 0 0 0 0 1 0 34
35 3.61 1 3.43 3.29 3.18 3.07 0 0 0 0 0 0 0 0 0 0 1 35
36 3.74 1 3.61 3.43 3.29 3.18 0 0 0 0 0 0 0 0 0 0 0 36
37 3.87 1 3.74 3.61 3.43 3.29 1 0 0 0 0 0 0 0 0 0 0 37
38 3.88 1 3.87 3.74 3.61 3.43 0 1 0 0 0 0 0 0 0 0 0 38
39 4.09 1 3.88 3.87 3.74 3.61 0 0 1 0 0 0 0 0 0 0 0 39
40 4.19 1 4.09 3.88 3.87 3.74 0 0 0 1 0 0 0 0 0 0 0 40
41 4.20 1 4.19 4.09 3.88 3.87 0 0 0 0 1 0 0 0 0 0 0 41
42 4.29 1 4.20 4.19 4.09 3.88 0 0 0 0 0 1 0 0 0 0 0 42
43 4.37 1 4.29 4.20 4.19 4.09 0 0 0 0 0 0 1 0 0 0 0 43
44 4.47 1 4.37 4.29 4.20 4.19 0 0 0 0 0 0 0 1 0 0 0 44
45 4.61 1 4.47 4.37 4.29 4.20 0 0 0 0 0 0 0 0 1 0 0 45
46 4.65 1 4.61 4.47 4.37 4.29 0 0 0 0 0 0 0 0 0 1 0 46
47 4.69 1 4.65 4.61 4.47 4.37 0 0 0 0 0 0 0 0 0 0 1 47
48 4.82 1 4.69 4.65 4.61 4.47 0 0 0 0 0 0 0 0 0 0 0 48
49 4.86 1 4.82 4.69 4.65 4.61 1 0 0 0 0 0 0 0 0 0 0 49
50 4.87 1 4.86 4.82 4.69 4.65 0 1 0 0 0 0 0 0 0 0 0 50
51 5.01 1 4.87 4.86 4.82 4.69 0 0 1 0 0 0 0 0 0 0 0 51
52 5.03 1 5.01 4.87 4.86 4.82 0 0 0 1 0 0 0 0 0 0 0 52
53 5.13 1 5.03 5.01 4.87 4.86 0 0 0 0 1 0 0 0 0 0 0 53
54 5.18 1 5.13 5.03 5.01 4.87 0 0 0 0 0 1 0 0 0 0 0 54
55 5.21 1 5.18 5.13 5.03 5.01 0 0 0 0 0 0 1 0 0 0 0 55
56 5.26 1 5.21 5.18 5.13 5.03 0 0 0 0 0 0 0 1 0 0 0 56
57 5.25 1 5.26 5.21 5.18 5.13 0 0 0 0 0 0 0 0 1 0 0 57
58 5.20 1 5.25 5.26 5.21 5.18 0 0 0 0 0 0 0 0 0 1 0 58
59 5.16 1 5.20 5.25 5.26 5.21 0 0 0 0 0 0 0 0 0 0 1 59
60 5.19 1 5.16 5.20 5.25 5.26 0 0 0 0 0 0 0 0 0 0 0 60
61 5.39 1 5.19 5.16 5.20 5.25 1 0 0 0 0 0 0 0 0 0 0 61
62 5.58 1 5.39 5.19 5.16 5.20 0 1 0 0 0 0 0 0 0 0 0 62
63 5.76 1 5.58 5.39 5.19 5.16 0 0 1 0 0 0 0 0 0 0 0 63
64 5.89 1 5.76 5.58 5.39 5.19 0 0 0 1 0 0 0 0 0 0 0 64
65 5.98 1 5.89 5.76 5.58 5.39 0 0 0 0 1 0 0 0 0 0 0 65
66 6.02 1 5.98 5.89 5.76 5.58 0 0 0 0 0 1 0 0 0 0 0 66
67 5.62 1 6.02 5.98 5.89 5.76 0 0 0 0 0 0 1 0 0 0 0 67
68 4.87 1 5.62 6.02 5.98 5.89 0 0 0 0 0 0 0 1 0 0 0 68
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X Y1 Y2 Y3 Y4
0.1614445 0.0791593 2.0606456 -1.5124844 0.3994992 0.0095502
M1 M2 M3 M4 M5 M6
0.0378650 -0.0484576 0.0596382 -0.0446391 0.0169784 0.0241710
M7 M8 M9 M10 M11 t
-0.0756530 -0.0303723 -0.0095478 -0.0461532 -0.0003892 -0.0004754
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-0.28159 -0.04843 0.01404 0.05533 0.13770
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.1614445 0.0832036 1.940 0.058 .
X 0.0791593 0.0568823 1.392 0.170
Y1 2.0606456 0.1635501 12.599 < 2e-16 ***
Y2 -1.5124844 0.3335304 -4.535 3.62e-05 ***
Y3 0.3994992 0.3711067 1.077 0.287
Y4 0.0095502 0.1991501 0.048 0.962
M1 0.0378650 0.0583309 0.649 0.519
M2 -0.0484576 0.0593709 -0.816 0.418
M3 0.0596382 0.0605241 0.985 0.329
M4 -0.0446391 0.0591251 -0.755 0.454
M5 0.0169784 0.0606204 0.280 0.781
M6 0.0241710 0.0587947 0.411 0.683
M7 -0.0756530 0.0589395 -1.284 0.205
M8 -0.0303723 0.0599551 -0.507 0.615
M9 -0.0095478 0.0606229 -0.157 0.875
M10 -0.0461532 0.0608884 -0.758 0.452
M11 -0.0003892 0.0609417 -0.006 0.995
t -0.0004754 0.0014293 -0.333 0.741
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.09522 on 50 degrees of freedom
Multiple R-squared: 0.9916, Adjusted R-squared: 0.9887
F-statistic: 345.3 on 17 and 50 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,] 0.7416642938 0.516671412 0.2583357
[2,] 0.5960348914 0.807930217 0.4039651
[3,] 0.4440571051 0.888114210 0.5559429
[4,] 0.3205676377 0.641135275 0.6794324
[5,] 0.3104978709 0.620995742 0.6895021
[6,] 0.2101151021 0.420230204 0.7898849
[7,] 0.1640278794 0.328055759 0.8359721
[8,] 0.1049880316 0.209976063 0.8950120
[9,] 0.0673906417 0.134781283 0.9326094
[10,] 0.0416630941 0.083326188 0.9583369
[11,] 0.0222568890 0.044513778 0.9777431
[12,] 0.0176115951 0.035223190 0.9823884
[13,] 0.0092342053 0.018468411 0.9907658
[14,] 0.0070902134 0.014180427 0.9929098
[15,] 0.0047942124 0.009588425 0.9952058
[16,] 0.0039826896 0.007965379 0.9960173
[17,] 0.0019296501 0.003859300 0.9980703
[18,] 0.0012938496 0.002587699 0.9987062
[19,] 0.0045137117 0.009027423 0.9954863
[20,] 0.0054343667 0.010868733 0.9945656
[21,] 0.0108542905 0.021708581 0.9891457
[22,] 0.0056801989 0.011360398 0.9943198
[23,] 0.0025247135 0.005049427 0.9974753
[24,] 0.0011539380 0.002307876 0.9988461
[25,] 0.0006462639 0.001292528 0.9993537
[26,] 0.0010145078 0.002029016 0.9989855
[27,] 0.0006017256 0.001203451 0.9993983
> postscript(file="/var/www/html/rcomp/tmp/180ls1293570695.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/280ls1293570695.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3ia3v1293570695.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4ia3v1293570695.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5ia3v1293570695.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 = 68
Frequency = 1
1 2 3 4 5 6
0.122426385 -0.099897664 -0.110500016 0.006889562 0.101751387 -0.018462341
7 8 9 10 11 12
0.054560300 0.025836246 0.074251519 -0.054900592 -0.047599135 -0.022565892
13 14 15 16 17 18
-0.002265752 0.074221702 -0.049319196 0.090835464 -0.159031729 0.010019061
19 20 21 22 23 24
0.054849364 -0.011625861 -0.018038834 0.036914393 -0.004235663 -0.046871231
25 26 27 28 29 30
-0.067861758 0.004550549 -0.077754597 0.025547781 -0.035047275 0.004015411
31 32 33 34 35 36
0.048620132 0.090688278 -0.069746376 0.026584188 -0.005243966 -0.079321650
37 38 39 40 41 42
-0.039328470 -0.087038286 0.137703811 -0.128330643 -0.073152168 0.056782278
43 44 45 46 47 48
0.024792916 0.046309558 0.044844198 -0.048136433 0.035182986 0.086457772
49 50 51 52 53 54
-0.135633450 0.058999739 0.078955274 -0.086879067 0.118136668 -0.070420794
55 56 57 58 59 60
0.098767707 0.077626345 -0.031310508 0.039538445 0.021895778 0.062301001
61 62 63 64 65 66
0.122663044 0.049163960 0.020914724 0.091936903 0.047343117 0.018066384
67 68
-0.281590419 -0.228834566
> postscript(file="/var/www/html/rcomp/tmp/6b1ky1293570695.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 = 68
Frequency = 1
lag(myerror, k = 1) myerror
0 0.122426385 NA
1 -0.099897664 0.122426385
2 -0.110500016 -0.099897664
3 0.006889562 -0.110500016
4 0.101751387 0.006889562
5 -0.018462341 0.101751387
6 0.054560300 -0.018462341
7 0.025836246 0.054560300
8 0.074251519 0.025836246
9 -0.054900592 0.074251519
10 -0.047599135 -0.054900592
11 -0.022565892 -0.047599135
12 -0.002265752 -0.022565892
13 0.074221702 -0.002265752
14 -0.049319196 0.074221702
15 0.090835464 -0.049319196
16 -0.159031729 0.090835464
17 0.010019061 -0.159031729
18 0.054849364 0.010019061
19 -0.011625861 0.054849364
20 -0.018038834 -0.011625861
21 0.036914393 -0.018038834
22 -0.004235663 0.036914393
23 -0.046871231 -0.004235663
24 -0.067861758 -0.046871231
25 0.004550549 -0.067861758
26 -0.077754597 0.004550549
27 0.025547781 -0.077754597
28 -0.035047275 0.025547781
29 0.004015411 -0.035047275
30 0.048620132 0.004015411
31 0.090688278 0.048620132
32 -0.069746376 0.090688278
33 0.026584188 -0.069746376
34 -0.005243966 0.026584188
35 -0.079321650 -0.005243966
36 -0.039328470 -0.079321650
37 -0.087038286 -0.039328470
38 0.137703811 -0.087038286
39 -0.128330643 0.137703811
40 -0.073152168 -0.128330643
41 0.056782278 -0.073152168
42 0.024792916 0.056782278
43 0.046309558 0.024792916
44 0.044844198 0.046309558
45 -0.048136433 0.044844198
46 0.035182986 -0.048136433
47 0.086457772 0.035182986
48 -0.135633450 0.086457772
49 0.058999739 -0.135633450
50 0.078955274 0.058999739
51 -0.086879067 0.078955274
52 0.118136668 -0.086879067
53 -0.070420794 0.118136668
54 0.098767707 -0.070420794
55 0.077626345 0.098767707
56 -0.031310508 0.077626345
57 0.039538445 -0.031310508
58 0.021895778 0.039538445
59 0.062301001 0.021895778
60 0.122663044 0.062301001
61 0.049163960 0.122663044
62 0.020914724 0.049163960
63 0.091936903 0.020914724
64 0.047343117 0.091936903
65 0.018066384 0.047343117
66 -0.281590419 0.018066384
67 -0.228834566 -0.281590419
68 NA -0.228834566
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -0.099897664 0.122426385
[2,] -0.110500016 -0.099897664
[3,] 0.006889562 -0.110500016
[4,] 0.101751387 0.006889562
[5,] -0.018462341 0.101751387
[6,] 0.054560300 -0.018462341
[7,] 0.025836246 0.054560300
[8,] 0.074251519 0.025836246
[9,] -0.054900592 0.074251519
[10,] -0.047599135 -0.054900592
[11,] -0.022565892 -0.047599135
[12,] -0.002265752 -0.022565892
[13,] 0.074221702 -0.002265752
[14,] -0.049319196 0.074221702
[15,] 0.090835464 -0.049319196
[16,] -0.159031729 0.090835464
[17,] 0.010019061 -0.159031729
[18,] 0.054849364 0.010019061
[19,] -0.011625861 0.054849364
[20,] -0.018038834 -0.011625861
[21,] 0.036914393 -0.018038834
[22,] -0.004235663 0.036914393
[23,] -0.046871231 -0.004235663
[24,] -0.067861758 -0.046871231
[25,] 0.004550549 -0.067861758
[26,] -0.077754597 0.004550549
[27,] 0.025547781 -0.077754597
[28,] -0.035047275 0.025547781
[29,] 0.004015411 -0.035047275
[30,] 0.048620132 0.004015411
[31,] 0.090688278 0.048620132
[32,] -0.069746376 0.090688278
[33,] 0.026584188 -0.069746376
[34,] -0.005243966 0.026584188
[35,] -0.079321650 -0.005243966
[36,] -0.039328470 -0.079321650
[37,] -0.087038286 -0.039328470
[38,] 0.137703811 -0.087038286
[39,] -0.128330643 0.137703811
[40,] -0.073152168 -0.128330643
[41,] 0.056782278 -0.073152168
[42,] 0.024792916 0.056782278
[43,] 0.046309558 0.024792916
[44,] 0.044844198 0.046309558
[45,] -0.048136433 0.044844198
[46,] 0.035182986 -0.048136433
[47,] 0.086457772 0.035182986
[48,] -0.135633450 0.086457772
[49,] 0.058999739 -0.135633450
[50,] 0.078955274 0.058999739
[51,] -0.086879067 0.078955274
[52,] 0.118136668 -0.086879067
[53,] -0.070420794 0.118136668
[54,] 0.098767707 -0.070420794
[55,] 0.077626345 0.098767707
[56,] -0.031310508 0.077626345
[57,] 0.039538445 -0.031310508
[58,] 0.021895778 0.039538445
[59,] 0.062301001 0.021895778
[60,] 0.122663044 0.062301001
[61,] 0.049163960 0.122663044
[62,] 0.020914724 0.049163960
[63,] 0.091936903 0.020914724
[64,] 0.047343117 0.091936903
[65,] 0.018066384 0.047343117
[66,] -0.281590419 0.018066384
[67,] -0.228834566 -0.281590419
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -0.099897664 0.122426385
2 -0.110500016 -0.099897664
3 0.006889562 -0.110500016
4 0.101751387 0.006889562
5 -0.018462341 0.101751387
6 0.054560300 -0.018462341
7 0.025836246 0.054560300
8 0.074251519 0.025836246
9 -0.054900592 0.074251519
10 -0.047599135 -0.054900592
11 -0.022565892 -0.047599135
12 -0.002265752 -0.022565892
13 0.074221702 -0.002265752
14 -0.049319196 0.074221702
15 0.090835464 -0.049319196
16 -0.159031729 0.090835464
17 0.010019061 -0.159031729
18 0.054849364 0.010019061
19 -0.011625861 0.054849364
20 -0.018038834 -0.011625861
21 0.036914393 -0.018038834
22 -0.004235663 0.036914393
23 -0.046871231 -0.004235663
24 -0.067861758 -0.046871231
25 0.004550549 -0.067861758
26 -0.077754597 0.004550549
27 0.025547781 -0.077754597
28 -0.035047275 0.025547781
29 0.004015411 -0.035047275
30 0.048620132 0.004015411
31 0.090688278 0.048620132
32 -0.069746376 0.090688278
33 0.026584188 -0.069746376
34 -0.005243966 0.026584188
35 -0.079321650 -0.005243966
36 -0.039328470 -0.079321650
37 -0.087038286 -0.039328470
38 0.137703811 -0.087038286
39 -0.128330643 0.137703811
40 -0.073152168 -0.128330643
41 0.056782278 -0.073152168
42 0.024792916 0.056782278
43 0.046309558 0.024792916
44 0.044844198 0.046309558
45 -0.048136433 0.044844198
46 0.035182986 -0.048136433
47 0.086457772 0.035182986
48 -0.135633450 0.086457772
49 0.058999739 -0.135633450
50 0.078955274 0.058999739
51 -0.086879067 0.078955274
52 0.118136668 -0.086879067
53 -0.070420794 0.118136668
54 0.098767707 -0.070420794
55 0.077626345 0.098767707
56 -0.031310508 0.077626345
57 0.039538445 -0.031310508
58 0.021895778 0.039538445
59 0.062301001 0.021895778
60 0.122663044 0.062301001
61 0.049163960 0.122663044
62 0.020914724 0.049163960
63 0.091936903 0.020914724
64 0.047343117 0.091936903
65 0.018066384 0.047343117
66 -0.281590419 0.018066384
67 -0.228834566 -0.281590419
> 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/7ma111293570695.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8ma111293570695.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9ma111293570695.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10e1141293570695.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11au251293570696.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/123l1q1293570696.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/13a4y11293570696.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/14kvfm1293570696.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/15owea1293570696.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/1626bj1293570696.tab")
+ }
>
> try(system("convert tmp/180ls1293570695.ps tmp/180ls1293570695.png",intern=TRUE))
character(0)
> try(system("convert tmp/280ls1293570695.ps tmp/280ls1293570695.png",intern=TRUE))
character(0)
> try(system("convert tmp/3ia3v1293570695.ps tmp/3ia3v1293570695.png",intern=TRUE))
character(0)
> try(system("convert tmp/4ia3v1293570695.ps tmp/4ia3v1293570695.png",intern=TRUE))
character(0)
> try(system("convert tmp/5ia3v1293570695.ps tmp/5ia3v1293570695.png",intern=TRUE))
character(0)
> try(system("convert tmp/6b1ky1293570695.ps tmp/6b1ky1293570695.png",intern=TRUE))
character(0)
> try(system("convert tmp/7ma111293570695.ps tmp/7ma111293570695.png",intern=TRUE))
character(0)
> try(system("convert tmp/8ma111293570695.ps tmp/8ma111293570695.png",intern=TRUE))
character(0)
> try(system("convert tmp/9ma111293570695.ps tmp/9ma111293570695.png",intern=TRUE))
character(0)
> try(system("convert tmp/10e1141293570695.ps tmp/10e1141293570695.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
2.526 1.640 8.229