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(8
+ ,5560
+ ,0
+ ,0
+ ,0
+ ,0
+ ,8.1
+ ,3922
+ ,8
+ ,0
+ ,0
+ ,0
+ ,7.7
+ ,3759
+ ,8.1
+ ,8
+ ,0
+ ,0
+ ,7.5
+ ,4138
+ ,7.7
+ ,8.1
+ ,8
+ ,0
+ ,7.6
+ ,4634
+ ,7.5
+ ,7.7
+ ,8.1
+ ,8
+ ,7.8
+ ,3996
+ ,7.6
+ ,7.5
+ ,7.7
+ ,8.1
+ ,7.8
+ ,4308
+ ,7.8
+ ,7.6
+ ,7.5
+ ,7.7
+ ,7.8
+ ,4143
+ ,7.8
+ ,7.8
+ ,7.6
+ ,7.5
+ ,7.5
+ ,4429
+ ,7.8
+ ,7.8
+ ,7.8
+ ,7.6
+ ,7.5
+ ,5219
+ ,7.5
+ ,7.8
+ ,7.8
+ ,7.8
+ ,7.1
+ ,4929
+ ,7.5
+ ,7.5
+ ,7.8
+ ,7.8
+ ,7.5
+ ,5755
+ ,7.1
+ ,7.5
+ ,7.5
+ ,7.8
+ ,7.5
+ ,5592
+ ,7.5
+ ,7.1
+ ,7.5
+ ,7.5
+ ,7.6
+ ,4163
+ ,7.5
+ ,7.5
+ ,7.1
+ ,7.5
+ ,7.7
+ ,4962
+ ,7.6
+ ,7.5
+ ,7.5
+ ,7.1
+ ,7.7
+ ,5208
+ ,7.7
+ ,7.6
+ ,7.5
+ ,7.5
+ ,7.9
+ ,4755
+ ,7.7
+ ,7.7
+ ,7.6
+ ,7.5
+ ,8.1
+ ,4491
+ ,7.9
+ ,7.7
+ ,7.7
+ ,7.6
+ ,8.2
+ ,5732
+ ,8.1
+ ,7.9
+ ,7.7
+ ,7.7
+ ,8.2
+ ,5731
+ ,8.2
+ ,8.1
+ ,7.9
+ ,7.7
+ ,8.2
+ ,5040
+ ,8.2
+ ,8.2
+ ,8.1
+ ,7.9
+ ,7.9
+ ,6102
+ ,8.2
+ ,8.2
+ ,8.2
+ ,8.1
+ ,7.3
+ ,4904
+ ,7.9
+ ,8.2
+ ,8.2
+ ,8.2
+ ,6.9
+ ,5369
+ ,7.3
+ ,7.9
+ ,8.2
+ ,8.2
+ ,6.7
+ ,5578
+ ,6.9
+ ,7.3
+ ,7.9
+ ,8.2
+ ,6.7
+ ,4619
+ ,6.7
+ ,6.9
+ ,7.3
+ ,7.9
+ ,6.9
+ ,4731
+ ,6.7
+ ,6.7
+ ,6.9
+ ,7.3
+ ,7
+ ,5011
+ ,6.9
+ ,6.7
+ ,6.7
+ ,6.9
+ ,7.1
+ ,5299
+ ,7
+ ,6.9
+ ,6.7
+ ,6.7
+ ,7.2
+ ,4146
+ ,7.1
+ ,7
+ ,6.9
+ ,6.7
+ ,7.1
+ ,4625
+ ,7.2
+ ,7.1
+ ,7
+ ,6.9
+ ,6.9
+ ,4736
+ ,7.1
+ ,7.2
+ ,7.1
+ ,7
+ ,7
+ ,4219
+ ,6.9
+ ,7.1
+ ,7.2
+ ,7.1
+ ,6.8
+ ,5116
+ ,7
+ ,6.9
+ ,7.1
+ ,7.2
+ ,6.4
+ ,4205
+ ,6.8
+ ,7
+ ,6.9
+ ,7.1
+ ,6.7
+ ,4121
+ ,6.4
+ ,6.8
+ ,7
+ ,6.9
+ ,6.6
+ ,5103
+ ,6.7
+ ,6.4
+ ,6.8
+ ,7
+ ,6.4
+ ,4300
+ ,6.6
+ ,6.7
+ ,6.4
+ ,6.8
+ ,6.3
+ ,4578
+ ,6.4
+ ,6.6
+ ,6.7
+ ,6.4
+ ,6.2
+ ,3809
+ ,6.3
+ ,6.4
+ ,6.6
+ ,6.7
+ ,6.5
+ ,5526
+ ,6.2
+ ,6.3
+ ,6.4
+ ,6.6
+ ,6.8
+ ,4247
+ ,6.5
+ ,6.2
+ ,6.3
+ ,6.4
+ ,6.8
+ ,3830
+ ,6.8
+ ,6.5
+ ,6.2
+ ,6.3
+ ,6.4
+ ,4394
+ ,6.8
+ ,6.8
+ ,6.5
+ ,6.2
+ ,6.1
+ ,4826
+ ,6.4
+ ,6.8
+ ,6.8
+ ,6.5
+ ,5.8
+ ,4409
+ ,6.1
+ ,6.4
+ ,6.8
+ ,6.8
+ ,6.1
+ ,4569
+ ,5.8
+ ,6.1
+ ,6.4
+ ,6.8
+ ,7.2
+ ,4106
+ ,6.1
+ ,5.8
+ ,6.1
+ ,6.4
+ ,7.3
+ ,4794
+ ,7.2
+ ,6.1
+ ,5.8
+ ,6.1
+ ,6.9
+ ,3914
+ ,7.3
+ ,7.2
+ ,6.1
+ ,5.8
+ ,6.1
+ ,3793
+ ,6.9
+ ,7.3
+ ,7.2
+ ,6.1
+ ,5.8
+ ,4405
+ ,6.1
+ ,6.9
+ ,7.3
+ ,7.2
+ ,6.2
+ ,4022
+ ,5.8
+ ,6.1
+ ,6.9
+ ,7.3
+ ,7.1
+ ,4100
+ ,6.2
+ ,5.8
+ ,6.1
+ ,6.9
+ ,7.7
+ ,4788
+ ,7.1
+ ,6.2
+ ,5.8
+ ,6.1
+ ,7.9
+ ,3163
+ ,7.7
+ ,7.1
+ ,6.2
+ ,5.8
+ ,7.7
+ ,3585
+ ,7.9
+ ,7.7
+ ,7.1
+ ,6.2
+ ,7.4
+ ,3903
+ ,7.7
+ ,7.9
+ ,7.7
+ ,7.1
+ ,7.5
+ ,4178
+ ,7.4
+ ,7.7
+ ,7.9
+ ,7.7
+ ,8
+ ,3863
+ ,7.5
+ ,7.4
+ ,7.7
+ ,7.9
+ ,8.1
+ ,4187
+ ,8
+ ,7.5
+ ,7.4
+ ,7.7)
+ ,dim=c(6
+ ,61)
+ ,dimnames=list(c('Y'
+ ,'X'
+ ,'Y1'
+ ,'Y2'
+ ,'Y3'
+ ,'Y4')
+ ,1:61))
> y <- array(NA,dim=c(6,61),dimnames=list(c('Y','X','Y1','Y2','Y3','Y4'),1:61))
> 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 8.0 5560 0.0 0.0 0.0 0.0 1 0 0 0 0 0 0 0 0 0 0 1
2 8.1 3922 8.0 0.0 0.0 0.0 0 1 0 0 0 0 0 0 0 0 0 2
3 7.7 3759 8.1 8.0 0.0 0.0 0 0 1 0 0 0 0 0 0 0 0 3
4 7.5 4138 7.7 8.1 8.0 0.0 0 0 0 1 0 0 0 0 0 0 0 4
5 7.6 4634 7.5 7.7 8.1 8.0 0 0 0 0 1 0 0 0 0 0 0 5
6 7.8 3996 7.6 7.5 7.7 8.1 0 0 0 0 0 1 0 0 0 0 0 6
7 7.8 4308 7.8 7.6 7.5 7.7 0 0 0 0 0 0 1 0 0 0 0 7
8 7.8 4143 7.8 7.8 7.6 7.5 0 0 0 0 0 0 0 1 0 0 0 8
9 7.5 4429 7.8 7.8 7.8 7.6 0 0 0 0 0 0 0 0 1 0 0 9
10 7.5 5219 7.5 7.8 7.8 7.8 0 0 0 0 0 0 0 0 0 1 0 10
11 7.1 4929 7.5 7.5 7.8 7.8 0 0 0 0 0 0 0 0 0 0 1 11
12 7.5 5755 7.1 7.5 7.5 7.8 0 0 0 0 0 0 0 0 0 0 0 12
13 7.5 5592 7.5 7.1 7.5 7.5 1 0 0 0 0 0 0 0 0 0 0 13
14 7.6 4163 7.5 7.5 7.1 7.5 0 1 0 0 0 0 0 0 0 0 0 14
15 7.7 4962 7.6 7.5 7.5 7.1 0 0 1 0 0 0 0 0 0 0 0 15
16 7.7 5208 7.7 7.6 7.5 7.5 0 0 0 1 0 0 0 0 0 0 0 16
17 7.9 4755 7.7 7.7 7.6 7.5 0 0 0 0 1 0 0 0 0 0 0 17
18 8.1 4491 7.9 7.7 7.7 7.6 0 0 0 0 0 1 0 0 0 0 0 18
19 8.2 5732 8.1 7.9 7.7 7.7 0 0 0 0 0 0 1 0 0 0 0 19
20 8.2 5731 8.2 8.1 7.9 7.7 0 0 0 0 0 0 0 1 0 0 0 20
21 8.2 5040 8.2 8.2 8.1 7.9 0 0 0 0 0 0 0 0 1 0 0 21
22 7.9 6102 8.2 8.2 8.2 8.1 0 0 0 0 0 0 0 0 0 1 0 22
23 7.3 4904 7.9 8.2 8.2 8.2 0 0 0 0 0 0 0 0 0 0 1 23
24 6.9 5369 7.3 7.9 8.2 8.2 0 0 0 0 0 0 0 0 0 0 0 24
25 6.7 5578 6.9 7.3 7.9 8.2 1 0 0 0 0 0 0 0 0 0 0 25
26 6.7 4619 6.7 6.9 7.3 7.9 0 1 0 0 0 0 0 0 0 0 0 26
27 6.9 4731 6.7 6.7 6.9 7.3 0 0 1 0 0 0 0 0 0 0 0 27
28 7.0 5011 6.9 6.7 6.7 6.9 0 0 0 1 0 0 0 0 0 0 0 28
29 7.1 5299 7.0 6.9 6.7 6.7 0 0 0 0 1 0 0 0 0 0 0 29
30 7.2 4146 7.1 7.0 6.9 6.7 0 0 0 0 0 1 0 0 0 0 0 30
31 7.1 4625 7.2 7.1 7.0 6.9 0 0 0 0 0 0 1 0 0 0 0 31
32 6.9 4736 7.1 7.2 7.1 7.0 0 0 0 0 0 0 0 1 0 0 0 32
33 7.0 4219 6.9 7.1 7.2 7.1 0 0 0 0 0 0 0 0 1 0 0 33
34 6.8 5116 7.0 6.9 7.1 7.2 0 0 0 0 0 0 0 0 0 1 0 34
35 6.4 4205 6.8 7.0 6.9 7.1 0 0 0 0 0 0 0 0 0 0 1 35
36 6.7 4121 6.4 6.8 7.0 6.9 0 0 0 0 0 0 0 0 0 0 0 36
37 6.6 5103 6.7 6.4 6.8 7.0 1 0 0 0 0 0 0 0 0 0 0 37
38 6.4 4300 6.6 6.7 6.4 6.8 0 1 0 0 0 0 0 0 0 0 0 38
39 6.3 4578 6.4 6.6 6.7 6.4 0 0 1 0 0 0 0 0 0 0 0 39
40 6.2 3809 6.3 6.4 6.6 6.7 0 0 0 1 0 0 0 0 0 0 0 40
41 6.5 5526 6.2 6.3 6.4 6.6 0 0 0 0 1 0 0 0 0 0 0 41
42 6.8 4247 6.5 6.2 6.3 6.4 0 0 0 0 0 1 0 0 0 0 0 42
43 6.8 3830 6.8 6.5 6.2 6.3 0 0 0 0 0 0 1 0 0 0 0 43
44 6.4 4394 6.8 6.8 6.5 6.2 0 0 0 0 0 0 0 1 0 0 0 44
45 6.1 4826 6.4 6.8 6.8 6.5 0 0 0 0 0 0 0 0 1 0 0 45
46 5.8 4409 6.1 6.4 6.8 6.8 0 0 0 0 0 0 0 0 0 1 0 46
47 6.1 4569 5.8 6.1 6.4 6.8 0 0 0 0 0 0 0 0 0 0 1 47
48 7.2 4106 6.1 5.8 6.1 6.4 0 0 0 0 0 0 0 0 0 0 0 48
49 7.3 4794 7.2 6.1 5.8 6.1 1 0 0 0 0 0 0 0 0 0 0 49
50 6.9 3914 7.3 7.2 6.1 5.8 0 1 0 0 0 0 0 0 0 0 0 50
51 6.1 3793 6.9 7.3 7.2 6.1 0 0 1 0 0 0 0 0 0 0 0 51
52 5.8 4405 6.1 6.9 7.3 7.2 0 0 0 1 0 0 0 0 0 0 0 52
53 6.2 4022 5.8 6.1 6.9 7.3 0 0 0 0 1 0 0 0 0 0 0 53
54 7.1 4100 6.2 5.8 6.1 6.9 0 0 0 0 0 1 0 0 0 0 0 54
55 7.7 4788 7.1 6.2 5.8 6.1 0 0 0 0 0 0 1 0 0 0 0 55
56 7.9 3163 7.7 7.1 6.2 5.8 0 0 0 0 0 0 0 1 0 0 0 56
57 7.7 3585 7.9 7.7 7.1 6.2 0 0 0 0 0 0 0 0 1 0 0 57
58 7.4 3903 7.7 7.9 7.7 7.1 0 0 0 0 0 0 0 0 0 1 0 58
59 7.5 4178 7.4 7.7 7.9 7.7 0 0 0 0 0 0 0 0 0 0 1 59
60 8.0 3863 7.5 7.4 7.7 7.9 0 0 0 0 0 0 0 0 0 0 0 60
61 8.1 4187 8.0 7.5 7.4 7.7 1 0 0 0 0 0 0 0 0 0 0 61
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X Y1 Y2 Y3 Y4
6.453e+00 2.863e-05 3.137e-01 -3.913e-02 -4.754e-02 -5.113e-02
M1 M2 M3 M4 M5 M6
9.765e-02 -5.877e-01 -6.913e-01 -6.342e-01 -3.109e-01 -2.548e-02
M7 M8 M9 M10 M11 t
-1.835e-02 -9.763e-02 -1.667e-01 -3.247e-01 -4.342e-01 -1.333e-02
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-0.8338 -0.3521 -0.1022 0.3823 1.3032
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 6.453e+00 1.010e+00 6.391 9.88e-08 ***
X 2.863e-05 1.630e-04 0.176 0.86141
Y1 3.137e-01 9.637e-02 3.255 0.00221 **
Y2 -3.913e-02 1.069e-01 -0.366 0.71606
Y3 -4.754e-02 1.067e-01 -0.446 0.65815
Y4 -5.113e-02 7.954e-02 -0.643 0.52378
M1 9.765e-02 3.557e-01 0.275 0.78499
M2 -5.877e-01 3.840e-01 -1.530 0.13323
M3 -6.913e-01 3.789e-01 -1.825 0.07500 .
M4 -6.342e-01 3.756e-01 -1.689 0.09853 .
M5 -3.109e-01 3.545e-01 -0.877 0.38531
M6 -2.548e-02 3.645e-01 -0.070 0.94460
M7 -1.835e-02 3.576e-01 -0.051 0.95931
M8 -9.763e-02 3.590e-01 -0.272 0.78696
M9 -1.667e-01 3.578e-01 -0.466 0.64363
M10 -3.247e-01 3.584e-01 -0.906 0.37001
M11 -4.342e-01 3.535e-01 -1.228 0.22600
t -1.333e-02 5.246e-03 -2.540 0.01477 *
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.558 on 43 degrees of freedom
Multiple R-squared: 0.4902, Adjusted R-squared: 0.2887
F-statistic: 2.433 on 17 and 43 DF, p-value: 0.00949
> 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,] 0.3525572 0.70511444 0.64744278
[2,] 0.2036791 0.40735817 0.79632092
[3,] 0.1228447 0.24568939 0.87715531
[4,] 0.7203727 0.55925454 0.27962727
[5,] 0.9427510 0.11449801 0.05724900
[6,] 0.9866735 0.02665291 0.01332646
[7,] 0.9790406 0.04191878 0.02095939
[8,] 0.9646737 0.07065252 0.03532626
[9,] 0.9632443 0.07351133 0.03675567
[10,] 0.9383472 0.12330559 0.06165280
[11,] 0.9003544 0.19929111 0.09964556
[12,] 0.8593377 0.28132453 0.14066227
[13,] 0.8714096 0.25718071 0.12859036
[14,] 0.7972783 0.40544331 0.20272165
[15,] 0.8602413 0.27951750 0.13975875
[16,] 0.8757953 0.24840941 0.12420470
[17,] 0.8753871 0.24922577 0.12461288
[18,] 0.8038125 0.39237493 0.19618747
[19,] 0.8496424 0.30071525 0.15035763
[20,] 0.8735166 0.25296688 0.12648344
> postscript(file="/var/www/html/rcomp/tmp/1sspn1258738589.ps",horizontal=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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2i7o81258738589.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3de0y1258738589.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/41g4r1258738589.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5xf031258738589.ps",horizontal=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 = 61
Frequency = 1
1 2 3 4 5 6
1.30316830 -0.36058650 -0.35725445 -0.10222687 0.13447616 0.02752082
7 8 9 10 11 12
-0.06398750 0.03569040 -0.17546575 0.07754548 -0.20299707 -0.13636063
13 14 15 16 17 18
-0.37247045 0.46374140 0.62504661 0.56721014 0.47887889 0.36144509
19 20 21 22 23 24
0.38232727 0.46092343 0.58676199 0.44264110 0.09904345 -0.55873142
25 26 27 28 29 30
-0.76130773 -0.03196893 0.22428825 0.17978823 -0.07218844 -0.22925253
31 32 33 34 35 36
-0.34923669 -0.41466781 -0.14877040 -0.24198068 -0.44098070 -0.44733118
37 38 39 40 41 42
-0.77390817 -0.23838947 -0.17673713 -0.26439028 -0.31067600 -0.35917891
43 44 45 46 47 48
-0.43326580 -0.73592370 -0.81081432 -0.83378980 -0.35212990 0.19965096
49 50 51 52 53 54
-0.16725428 0.16720350 -0.31534328 -0.38038121 -0.23049061 0.19946554
55 56 57 58 59 60
0.46416271 0.65397767 0.54828848 0.55558390 0.89706422 0.94277227
61
0.77177233
> postscript(file="/var/www/html/rcomp/tmp/6wc761258738589.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> dum <- cbind(lag(myerror,k=1),myerror)
> dum
Time Series:
Start = 0
End = 61
Frequency = 1
lag(myerror, k = 1) myerror
0 1.30316830 NA
1 -0.36058650 1.30316830
2 -0.35725445 -0.36058650
3 -0.10222687 -0.35725445
4 0.13447616 -0.10222687
5 0.02752082 0.13447616
6 -0.06398750 0.02752082
7 0.03569040 -0.06398750
8 -0.17546575 0.03569040
9 0.07754548 -0.17546575
10 -0.20299707 0.07754548
11 -0.13636063 -0.20299707
12 -0.37247045 -0.13636063
13 0.46374140 -0.37247045
14 0.62504661 0.46374140
15 0.56721014 0.62504661
16 0.47887889 0.56721014
17 0.36144509 0.47887889
18 0.38232727 0.36144509
19 0.46092343 0.38232727
20 0.58676199 0.46092343
21 0.44264110 0.58676199
22 0.09904345 0.44264110
23 -0.55873142 0.09904345
24 -0.76130773 -0.55873142
25 -0.03196893 -0.76130773
26 0.22428825 -0.03196893
27 0.17978823 0.22428825
28 -0.07218844 0.17978823
29 -0.22925253 -0.07218844
30 -0.34923669 -0.22925253
31 -0.41466781 -0.34923669
32 -0.14877040 -0.41466781
33 -0.24198068 -0.14877040
34 -0.44098070 -0.24198068
35 -0.44733118 -0.44098070
36 -0.77390817 -0.44733118
37 -0.23838947 -0.77390817
38 -0.17673713 -0.23838947
39 -0.26439028 -0.17673713
40 -0.31067600 -0.26439028
41 -0.35917891 -0.31067600
42 -0.43326580 -0.35917891
43 -0.73592370 -0.43326580
44 -0.81081432 -0.73592370
45 -0.83378980 -0.81081432
46 -0.35212990 -0.83378980
47 0.19965096 -0.35212990
48 -0.16725428 0.19965096
49 0.16720350 -0.16725428
50 -0.31534328 0.16720350
51 -0.38038121 -0.31534328
52 -0.23049061 -0.38038121
53 0.19946554 -0.23049061
54 0.46416271 0.19946554
55 0.65397767 0.46416271
56 0.54828848 0.65397767
57 0.55558390 0.54828848
58 0.89706422 0.55558390
59 0.94277227 0.89706422
60 0.77177233 0.94277227
61 NA 0.77177233
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -0.36058650 1.30316830
[2,] -0.35725445 -0.36058650
[3,] -0.10222687 -0.35725445
[4,] 0.13447616 -0.10222687
[5,] 0.02752082 0.13447616
[6,] -0.06398750 0.02752082
[7,] 0.03569040 -0.06398750
[8,] -0.17546575 0.03569040
[9,] 0.07754548 -0.17546575
[10,] -0.20299707 0.07754548
[11,] -0.13636063 -0.20299707
[12,] -0.37247045 -0.13636063
[13,] 0.46374140 -0.37247045
[14,] 0.62504661 0.46374140
[15,] 0.56721014 0.62504661
[16,] 0.47887889 0.56721014
[17,] 0.36144509 0.47887889
[18,] 0.38232727 0.36144509
[19,] 0.46092343 0.38232727
[20,] 0.58676199 0.46092343
[21,] 0.44264110 0.58676199
[22,] 0.09904345 0.44264110
[23,] -0.55873142 0.09904345
[24,] -0.76130773 -0.55873142
[25,] -0.03196893 -0.76130773
[26,] 0.22428825 -0.03196893
[27,] 0.17978823 0.22428825
[28,] -0.07218844 0.17978823
[29,] -0.22925253 -0.07218844
[30,] -0.34923669 -0.22925253
[31,] -0.41466781 -0.34923669
[32,] -0.14877040 -0.41466781
[33,] -0.24198068 -0.14877040
[34,] -0.44098070 -0.24198068
[35,] -0.44733118 -0.44098070
[36,] -0.77390817 -0.44733118
[37,] -0.23838947 -0.77390817
[38,] -0.17673713 -0.23838947
[39,] -0.26439028 -0.17673713
[40,] -0.31067600 -0.26439028
[41,] -0.35917891 -0.31067600
[42,] -0.43326580 -0.35917891
[43,] -0.73592370 -0.43326580
[44,] -0.81081432 -0.73592370
[45,] -0.83378980 -0.81081432
[46,] -0.35212990 -0.83378980
[47,] 0.19965096 -0.35212990
[48,] -0.16725428 0.19965096
[49,] 0.16720350 -0.16725428
[50,] -0.31534328 0.16720350
[51,] -0.38038121 -0.31534328
[52,] -0.23049061 -0.38038121
[53,] 0.19946554 -0.23049061
[54,] 0.46416271 0.19946554
[55,] 0.65397767 0.46416271
[56,] 0.54828848 0.65397767
[57,] 0.55558390 0.54828848
[58,] 0.89706422 0.55558390
[59,] 0.94277227 0.89706422
[60,] 0.77177233 0.94277227
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -0.36058650 1.30316830
2 -0.35725445 -0.36058650
3 -0.10222687 -0.35725445
4 0.13447616 -0.10222687
5 0.02752082 0.13447616
6 -0.06398750 0.02752082
7 0.03569040 -0.06398750
8 -0.17546575 0.03569040
9 0.07754548 -0.17546575
10 -0.20299707 0.07754548
11 -0.13636063 -0.20299707
12 -0.37247045 -0.13636063
13 0.46374140 -0.37247045
14 0.62504661 0.46374140
15 0.56721014 0.62504661
16 0.47887889 0.56721014
17 0.36144509 0.47887889
18 0.38232727 0.36144509
19 0.46092343 0.38232727
20 0.58676199 0.46092343
21 0.44264110 0.58676199
22 0.09904345 0.44264110
23 -0.55873142 0.09904345
24 -0.76130773 -0.55873142
25 -0.03196893 -0.76130773
26 0.22428825 -0.03196893
27 0.17978823 0.22428825
28 -0.07218844 0.17978823
29 -0.22925253 -0.07218844
30 -0.34923669 -0.22925253
31 -0.41466781 -0.34923669
32 -0.14877040 -0.41466781
33 -0.24198068 -0.14877040
34 -0.44098070 -0.24198068
35 -0.44733118 -0.44098070
36 -0.77390817 -0.44733118
37 -0.23838947 -0.77390817
38 -0.17673713 -0.23838947
39 -0.26439028 -0.17673713
40 -0.31067600 -0.26439028
41 -0.35917891 -0.31067600
42 -0.43326580 -0.35917891
43 -0.73592370 -0.43326580
44 -0.81081432 -0.73592370
45 -0.83378980 -0.81081432
46 -0.35212990 -0.83378980
47 0.19965096 -0.35212990
48 -0.16725428 0.19965096
49 0.16720350 -0.16725428
50 -0.31534328 0.16720350
51 -0.38038121 -0.31534328
52 -0.23049061 -0.38038121
53 0.19946554 -0.23049061
54 0.46416271 0.19946554
55 0.65397767 0.46416271
56 0.54828848 0.65397767
57 0.55558390 0.54828848
58 0.89706422 0.55558390
59 0.94277227 0.89706422
60 0.77177233 0.94277227
> 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/726rp1258738589.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8xqta1258738589.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/920oh1258738589.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/1006n21258738589.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11nv4t1258738589.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/12i7dd1258738589.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/134oc01258738589.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/14wcnb1258738589.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/15fpdm1258738589.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/16wniq1258738589.tab")
+ }
>
> system("convert tmp/1sspn1258738589.ps tmp/1sspn1258738589.png")
> system("convert tmp/2i7o81258738589.ps tmp/2i7o81258738589.png")
> system("convert tmp/3de0y1258738589.ps tmp/3de0y1258738589.png")
> system("convert tmp/41g4r1258738589.ps tmp/41g4r1258738589.png")
> system("convert tmp/5xf031258738589.ps tmp/5xf031258738589.png")
> system("convert tmp/6wc761258738589.ps tmp/6wc761258738589.png")
> system("convert tmp/726rp1258738589.ps tmp/726rp1258738589.png")
> system("convert tmp/8xqta1258738589.ps tmp/8xqta1258738589.png")
> system("convert tmp/920oh1258738589.ps tmp/920oh1258738589.png")
> system("convert tmp/1006n21258738589.ps tmp/1006n21258738589.png")
>
>
> proc.time()
user system elapsed
2.412 1.569 4.927