R version 2.9.0 (2009-04-17)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
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Type 'license()' or 'licence()' for distribution details.
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Type 'contributors()' for more information and
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Type 'demo()' for some demos, 'help()' for on-line help, or
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> x <- array(list(8.7
+ ,110.3
+ ,9.3
+ ,9.3
+ ,8.2
+ ,103.9
+ ,8.7
+ ,9.3
+ ,8.3
+ ,101.6
+ ,8.2
+ ,8.7
+ ,8.5
+ ,94.6
+ ,8.3
+ ,8.2
+ ,8.6
+ ,95.9
+ ,8.5
+ ,8.3
+ ,8.5
+ ,104.7
+ ,8.6
+ ,8.5
+ ,8.2
+ ,102.8
+ ,8.5
+ ,8.6
+ ,8.1
+ ,98.1
+ ,8.2
+ ,8.5
+ ,7.9
+ ,113.9
+ ,8.1
+ ,8.2
+ ,8.6
+ ,80.9
+ ,7.9
+ ,8.1
+ ,8.7
+ ,95.7
+ ,8.6
+ ,7.9
+ ,8.7
+ ,113.2
+ ,8.7
+ ,8.6
+ ,8.5
+ ,105.9
+ ,8.7
+ ,8.7
+ ,8.4
+ ,108.8
+ ,8.5
+ ,8.7
+ ,8.5
+ ,102.3
+ ,8.4
+ ,8.5
+ ,8.7
+ ,99
+ ,8.5
+ ,8.4
+ ,8.7
+ ,100.7
+ ,8.7
+ ,8.5
+ ,8.6
+ ,115.5
+ ,8.7
+ ,8.7
+ ,8.5
+ ,100.7
+ ,8.6
+ ,8.7
+ ,8.3
+ ,109.9
+ ,8.5
+ ,8.6
+ ,8
+ ,114.6
+ ,8.3
+ ,8.5
+ ,8.2
+ ,85.4
+ ,8
+ ,8.3
+ ,8.1
+ ,100.5
+ ,8.2
+ ,8
+ ,8.1
+ ,114.8
+ ,8.1
+ ,8.2
+ ,8
+ ,116.5
+ ,8.1
+ ,8.1
+ ,7.9
+ ,112.9
+ ,8
+ ,8.1
+ ,7.9
+ ,102
+ ,7.9
+ ,8
+ ,8
+ ,106
+ ,7.9
+ ,7.9
+ ,8
+ ,105.3
+ ,8
+ ,7.9
+ ,7.9
+ ,118.8
+ ,8
+ ,8
+ ,8
+ ,106.1
+ ,7.9
+ ,8
+ ,7.7
+ ,109.3
+ ,8
+ ,7.9
+ ,7.2
+ ,117.2
+ ,7.7
+ ,8
+ ,7.5
+ ,92.5
+ ,7.2
+ ,7.7
+ ,7.3
+ ,104.2
+ ,7.5
+ ,7.2
+ ,7
+ ,112.5
+ ,7.3
+ ,7.5
+ ,7
+ ,122.4
+ ,7
+ ,7.3
+ ,7
+ ,113.3
+ ,7
+ ,7
+ ,7.2
+ ,100
+ ,7
+ ,7
+ ,7.3
+ ,110.7
+ ,7.2
+ ,7
+ ,7.1
+ ,112.8
+ ,7.3
+ ,7.2
+ ,6.8
+ ,109.8
+ ,7.1
+ ,7.3
+ ,6.4
+ ,117.3
+ ,6.8
+ ,7.1
+ ,6.1
+ ,109.1
+ ,6.4
+ ,6.8
+ ,6.5
+ ,115.9
+ ,6.1
+ ,6.4
+ ,7.7
+ ,96
+ ,6.5
+ ,6.1
+ ,7.9
+ ,99.8
+ ,7.7
+ ,6.5
+ ,7.5
+ ,116.8
+ ,7.9
+ ,7.7
+ ,6.9
+ ,115.7
+ ,7.5
+ ,7.9
+ ,6.6
+ ,99.4
+ ,6.9
+ ,7.5
+ ,6.9
+ ,94.3
+ ,6.6
+ ,6.9
+ ,7.7
+ ,91
+ ,6.9
+ ,6.6
+ ,8
+ ,93.2
+ ,7.7
+ ,6.9
+ ,8
+ ,103.1
+ ,8
+ ,7.7
+ ,7.7
+ ,94.1
+ ,8
+ ,8
+ ,7.3
+ ,91.8
+ ,7.7
+ ,8
+ ,7.4
+ ,102.7
+ ,7.3
+ ,7.7
+ ,8.1
+ ,82.6
+ ,7.4
+ ,7.3)
+ ,dim=c(4
+ ,58)
+ ,dimnames=list(c('Y'
+ ,'X'
+ ,'Y1'
+ ,'Y2')
+ ,1:58))
> y <- array(NA,dim=c(4,58),dimnames=list(c('Y','X','Y1','Y2'),1:58))
> 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 M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 8.7 110.3 9.3 9.3 1 0 0 0 0 0 0 0 0 0 0 1
2 8.2 103.9 8.7 9.3 0 1 0 0 0 0 0 0 0 0 0 2
3 8.3 101.6 8.2 8.7 0 0 1 0 0 0 0 0 0 0 0 3
4 8.5 94.6 8.3 8.2 0 0 0 1 0 0 0 0 0 0 0 4
5 8.6 95.9 8.5 8.3 0 0 0 0 1 0 0 0 0 0 0 5
6 8.5 104.7 8.6 8.5 0 0 0 0 0 1 0 0 0 0 0 6
7 8.2 102.8 8.5 8.6 0 0 0 0 0 0 1 0 0 0 0 7
8 8.1 98.1 8.2 8.5 0 0 0 0 0 0 0 1 0 0 0 8
9 7.9 113.9 8.1 8.2 0 0 0 0 0 0 0 0 1 0 0 9
10 8.6 80.9 7.9 8.1 0 0 0 0 0 0 0 0 0 1 0 10
11 8.7 95.7 8.6 7.9 0 0 0 0 0 0 0 0 0 0 1 11
12 8.7 113.2 8.7 8.6 0 0 0 0 0 0 0 0 0 0 0 12
13 8.5 105.9 8.7 8.7 1 0 0 0 0 0 0 0 0 0 0 13
14 8.4 108.8 8.5 8.7 0 1 0 0 0 0 0 0 0 0 0 14
15 8.5 102.3 8.4 8.5 0 0 1 0 0 0 0 0 0 0 0 15
16 8.7 99.0 8.5 8.4 0 0 0 1 0 0 0 0 0 0 0 16
17 8.7 100.7 8.7 8.5 0 0 0 0 1 0 0 0 0 0 0 17
18 8.6 115.5 8.7 8.7 0 0 0 0 0 1 0 0 0 0 0 18
19 8.5 100.7 8.6 8.7 0 0 0 0 0 0 1 0 0 0 0 19
20 8.3 109.9 8.5 8.6 0 0 0 0 0 0 0 1 0 0 0 20
21 8.0 114.6 8.3 8.5 0 0 0 0 0 0 0 0 1 0 0 21
22 8.2 85.4 8.0 8.3 0 0 0 0 0 0 0 0 0 1 0 22
23 8.1 100.5 8.2 8.0 0 0 0 0 0 0 0 0 0 0 1 23
24 8.1 114.8 8.1 8.2 0 0 0 0 0 0 0 0 0 0 0 24
25 8.0 116.5 8.1 8.1 1 0 0 0 0 0 0 0 0 0 0 25
26 7.9 112.9 8.0 8.1 0 1 0 0 0 0 0 0 0 0 0 26
27 7.9 102.0 7.9 8.0 0 0 1 0 0 0 0 0 0 0 0 27
28 8.0 106.0 7.9 7.9 0 0 0 1 0 0 0 0 0 0 0 28
29 8.0 105.3 8.0 7.9 0 0 0 0 1 0 0 0 0 0 0 29
30 7.9 118.8 8.0 8.0 0 0 0 0 0 1 0 0 0 0 0 30
31 8.0 106.1 7.9 8.0 0 0 0 0 0 0 1 0 0 0 0 31
32 7.7 109.3 8.0 7.9 0 0 0 0 0 0 0 1 0 0 0 32
33 7.2 117.2 7.7 8.0 0 0 0 0 0 0 0 0 1 0 0 33
34 7.5 92.5 7.2 7.7 0 0 0 0 0 0 0 0 0 1 0 34
35 7.3 104.2 7.5 7.2 0 0 0 0 0 0 0 0 0 0 1 35
36 7.0 112.5 7.3 7.5 0 0 0 0 0 0 0 0 0 0 0 36
37 7.0 122.4 7.0 7.3 1 0 0 0 0 0 0 0 0 0 0 37
38 7.0 113.3 7.0 7.0 0 1 0 0 0 0 0 0 0 0 0 38
39 7.2 100.0 7.0 7.0 0 0 1 0 0 0 0 0 0 0 0 39
40 7.3 110.7 7.2 7.0 0 0 0 1 0 0 0 0 0 0 0 40
41 7.1 112.8 7.3 7.2 0 0 0 0 1 0 0 0 0 0 0 41
42 6.8 109.8 7.1 7.3 0 0 0 0 0 1 0 0 0 0 0 42
43 6.4 117.3 6.8 7.1 0 0 0 0 0 0 1 0 0 0 0 43
44 6.1 109.1 6.4 6.8 0 0 0 0 0 0 0 1 0 0 0 44
45 6.5 115.9 6.1 6.4 0 0 0 0 0 0 0 0 1 0 0 45
46 7.7 96.0 6.5 6.1 0 0 0 0 0 0 0 0 0 1 0 46
47 7.9 99.8 7.7 6.5 0 0 0 0 0 0 0 0 0 0 1 47
48 7.5 116.8 7.9 7.7 0 0 0 0 0 0 0 0 0 0 0 48
49 6.9 115.7 7.5 7.9 1 0 0 0 0 0 0 0 0 0 0 49
50 6.6 99.4 6.9 7.5 0 1 0 0 0 0 0 0 0 0 0 50
51 6.9 94.3 6.6 6.9 0 0 1 0 0 0 0 0 0 0 0 51
52 7.7 91.0 6.9 6.6 0 0 0 1 0 0 0 0 0 0 0 52
53 8.0 93.2 7.7 6.9 0 0 0 0 1 0 0 0 0 0 0 53
54 8.0 103.1 8.0 7.7 0 0 0 0 0 1 0 0 0 0 0 54
55 7.7 94.1 8.0 8.0 0 0 0 0 0 0 1 0 0 0 0 55
56 7.3 91.8 7.7 8.0 0 0 0 0 0 0 0 1 0 0 0 56
57 7.4 102.7 7.3 7.7 0 0 0 0 0 0 0 0 1 0 0 57
58 8.1 82.6 7.4 7.3 0 0 0 0 0 0 0 0 0 1 0 58
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X Y1 Y2 M1 M2
3.623995 -0.011655 1.339084 -0.619555 -0.043657 0.002999
M3 M4 M5 M6 M7 M8
0.143563 0.122170 -0.103225 0.006676 -0.072454 -0.138085
M9 M10 M11 t
0.101051 0.405496 -0.370534 -0.007426
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-0.278984 -0.116522 -0.007638 0.131314 0.292925
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 3.623995 0.961784 3.768 0.000507 ***
X -0.011655 0.004553 -2.560 0.014151 *
Y1 1.339084 0.117256 11.420 1.84e-14 ***
Y2 -0.619555 0.119921 -5.166 6.19e-06 ***
M1 -0.043657 0.123152 -0.354 0.724742
M2 0.002999 0.131882 0.023 0.981968
M3 0.143563 0.147543 0.973 0.336110
M4 0.122170 0.145720 0.838 0.406558
M5 -0.103225 0.140214 -0.736 0.465703
M6 0.006676 0.123197 0.054 0.957038
M7 -0.072454 0.130933 -0.553 0.582946
M8 -0.138085 0.134657 -1.025 0.311019
M9 0.101051 0.127655 0.792 0.433044
M10 0.405496 0.184213 2.201 0.033267 *
M11 -0.370534 0.164088 -2.258 0.029192 *
t -0.007426 0.002620 -2.834 0.007032 **
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.1819 on 42 degrees of freedom
Multiple R-squared: 0.9451, Adjusted R-squared: 0.9255
F-statistic: 48.18 on 15 and 42 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,] 0.11038668 0.22077337 0.8896133
[2,] 0.04742353 0.09484707 0.9525765
[3,] 0.01992952 0.03985903 0.9800705
[4,] 0.33626285 0.67252570 0.6637371
[5,] 0.25689398 0.51378797 0.7431060
[6,] 0.24342356 0.48684712 0.7565764
[7,] 0.16223536 0.32447072 0.8377646
[8,] 0.14394428 0.28788856 0.8560557
[9,] 0.21225015 0.42450029 0.7877499
[10,] 0.15248221 0.30496443 0.8475178
[11,] 0.11789661 0.23579321 0.8821034
[12,] 0.12760071 0.25520141 0.8723993
[13,] 0.29733512 0.59467024 0.7026649
[14,] 0.44472713 0.88945426 0.5552729
[15,] 0.53764544 0.92470912 0.4623546
[16,] 0.44597673 0.89195345 0.5540233
[17,] 0.46105249 0.92210499 0.5389475
[18,] 0.42475529 0.84951058 0.5752447
[19,] 0.78611622 0.42776757 0.2138838
[20,] 0.69888503 0.60222994 0.3011150
[21,] 0.54475092 0.91049817 0.4552491
> postscript(file="/var/www/html/rcomp/tmp/17tfw1261060986.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2knel1261060986.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/343hx1261060986.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4wnpn1261060986.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5t66q1261060986.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 = 58
Frequency = 1
1 2 3 4 5 6
-0.278984422 -0.089356139 0.148507294 -0.147945007 -0.005833594 -0.115742993
7 8 9 10 11 12
-0.155467900 0.102579784 -0.196939049 0.027286818 0.021967189 0.162601723
13 14 15 16 17 18
-0.009442027 0.152944445 0.054045160 0.048538305 0.095311726 0.189240826
19 20 21 22 23 24
0.137210687 0.189446405 -0.081623845 -0.241155992 0.164607295 0.225985176
25 26 27 28 29 30
0.134925675 0.087646138 -0.100579769 0.012903401 0.103657681 0.120479786
31 32 33 34 35 36
0.292925190 -0.092585965 -0.268540840 -0.069764111 -0.061447204 -0.174135603
37 38 39 40 41 42
0.270145723 -0.061011205 -0.149162070 -0.163451545 -0.116152272 -0.223821255
43 44 45 46 47 48
-0.172038621 -0.144786068 0.256661197 0.206206645 -0.125127281 -0.214451295
49 50 51 52 53 54
-0.116644948 -0.090223239 0.047189385 0.249954845 -0.076983541 0.029843637
55 56 57 58
-0.102629356 -0.054654155 0.290442537 0.077426640
> postscript(file="/var/www/html/rcomp/tmp/6cpe21261060986.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 = 58
Frequency = 1
lag(myerror, k = 1) myerror
0 -0.278984422 NA
1 -0.089356139 -0.278984422
2 0.148507294 -0.089356139
3 -0.147945007 0.148507294
4 -0.005833594 -0.147945007
5 -0.115742993 -0.005833594
6 -0.155467900 -0.115742993
7 0.102579784 -0.155467900
8 -0.196939049 0.102579784
9 0.027286818 -0.196939049
10 0.021967189 0.027286818
11 0.162601723 0.021967189
12 -0.009442027 0.162601723
13 0.152944445 -0.009442027
14 0.054045160 0.152944445
15 0.048538305 0.054045160
16 0.095311726 0.048538305
17 0.189240826 0.095311726
18 0.137210687 0.189240826
19 0.189446405 0.137210687
20 -0.081623845 0.189446405
21 -0.241155992 -0.081623845
22 0.164607295 -0.241155992
23 0.225985176 0.164607295
24 0.134925675 0.225985176
25 0.087646138 0.134925675
26 -0.100579769 0.087646138
27 0.012903401 -0.100579769
28 0.103657681 0.012903401
29 0.120479786 0.103657681
30 0.292925190 0.120479786
31 -0.092585965 0.292925190
32 -0.268540840 -0.092585965
33 -0.069764111 -0.268540840
34 -0.061447204 -0.069764111
35 -0.174135603 -0.061447204
36 0.270145723 -0.174135603
37 -0.061011205 0.270145723
38 -0.149162070 -0.061011205
39 -0.163451545 -0.149162070
40 -0.116152272 -0.163451545
41 -0.223821255 -0.116152272
42 -0.172038621 -0.223821255
43 -0.144786068 -0.172038621
44 0.256661197 -0.144786068
45 0.206206645 0.256661197
46 -0.125127281 0.206206645
47 -0.214451295 -0.125127281
48 -0.116644948 -0.214451295
49 -0.090223239 -0.116644948
50 0.047189385 -0.090223239
51 0.249954845 0.047189385
52 -0.076983541 0.249954845
53 0.029843637 -0.076983541
54 -0.102629356 0.029843637
55 -0.054654155 -0.102629356
56 0.290442537 -0.054654155
57 0.077426640 0.290442537
58 NA 0.077426640
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -0.089356139 -0.278984422
[2,] 0.148507294 -0.089356139
[3,] -0.147945007 0.148507294
[4,] -0.005833594 -0.147945007
[5,] -0.115742993 -0.005833594
[6,] -0.155467900 -0.115742993
[7,] 0.102579784 -0.155467900
[8,] -0.196939049 0.102579784
[9,] 0.027286818 -0.196939049
[10,] 0.021967189 0.027286818
[11,] 0.162601723 0.021967189
[12,] -0.009442027 0.162601723
[13,] 0.152944445 -0.009442027
[14,] 0.054045160 0.152944445
[15,] 0.048538305 0.054045160
[16,] 0.095311726 0.048538305
[17,] 0.189240826 0.095311726
[18,] 0.137210687 0.189240826
[19,] 0.189446405 0.137210687
[20,] -0.081623845 0.189446405
[21,] -0.241155992 -0.081623845
[22,] 0.164607295 -0.241155992
[23,] 0.225985176 0.164607295
[24,] 0.134925675 0.225985176
[25,] 0.087646138 0.134925675
[26,] -0.100579769 0.087646138
[27,] 0.012903401 -0.100579769
[28,] 0.103657681 0.012903401
[29,] 0.120479786 0.103657681
[30,] 0.292925190 0.120479786
[31,] -0.092585965 0.292925190
[32,] -0.268540840 -0.092585965
[33,] -0.069764111 -0.268540840
[34,] -0.061447204 -0.069764111
[35,] -0.174135603 -0.061447204
[36,] 0.270145723 -0.174135603
[37,] -0.061011205 0.270145723
[38,] -0.149162070 -0.061011205
[39,] -0.163451545 -0.149162070
[40,] -0.116152272 -0.163451545
[41,] -0.223821255 -0.116152272
[42,] -0.172038621 -0.223821255
[43,] -0.144786068 -0.172038621
[44,] 0.256661197 -0.144786068
[45,] 0.206206645 0.256661197
[46,] -0.125127281 0.206206645
[47,] -0.214451295 -0.125127281
[48,] -0.116644948 -0.214451295
[49,] -0.090223239 -0.116644948
[50,] 0.047189385 -0.090223239
[51,] 0.249954845 0.047189385
[52,] -0.076983541 0.249954845
[53,] 0.029843637 -0.076983541
[54,] -0.102629356 0.029843637
[55,] -0.054654155 -0.102629356
[56,] 0.290442537 -0.054654155
[57,] 0.077426640 0.290442537
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -0.089356139 -0.278984422
2 0.148507294 -0.089356139
3 -0.147945007 0.148507294
4 -0.005833594 -0.147945007
5 -0.115742993 -0.005833594
6 -0.155467900 -0.115742993
7 0.102579784 -0.155467900
8 -0.196939049 0.102579784
9 0.027286818 -0.196939049
10 0.021967189 0.027286818
11 0.162601723 0.021967189
12 -0.009442027 0.162601723
13 0.152944445 -0.009442027
14 0.054045160 0.152944445
15 0.048538305 0.054045160
16 0.095311726 0.048538305
17 0.189240826 0.095311726
18 0.137210687 0.189240826
19 0.189446405 0.137210687
20 -0.081623845 0.189446405
21 -0.241155992 -0.081623845
22 0.164607295 -0.241155992
23 0.225985176 0.164607295
24 0.134925675 0.225985176
25 0.087646138 0.134925675
26 -0.100579769 0.087646138
27 0.012903401 -0.100579769
28 0.103657681 0.012903401
29 0.120479786 0.103657681
30 0.292925190 0.120479786
31 -0.092585965 0.292925190
32 -0.268540840 -0.092585965
33 -0.069764111 -0.268540840
34 -0.061447204 -0.069764111
35 -0.174135603 -0.061447204
36 0.270145723 -0.174135603
37 -0.061011205 0.270145723
38 -0.149162070 -0.061011205
39 -0.163451545 -0.149162070
40 -0.116152272 -0.163451545
41 -0.223821255 -0.116152272
42 -0.172038621 -0.223821255
43 -0.144786068 -0.172038621
44 0.256661197 -0.144786068
45 0.206206645 0.256661197
46 -0.125127281 0.206206645
47 -0.214451295 -0.125127281
48 -0.116644948 -0.214451295
49 -0.090223239 -0.116644948
50 0.047189385 -0.090223239
51 0.249954845 0.047189385
52 -0.076983541 0.249954845
53 0.029843637 -0.076983541
54 -0.102629356 0.029843637
55 -0.054654155 -0.102629356
56 0.290442537 -0.054654155
57 0.077426640 0.290442537
> 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/74q7v1261060986.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/83k621261060986.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9mqez1261060986.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10dcvn1261060986.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11mfs21261060986.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/12dd6n1261060986.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/13bovo1261060986.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/14bbjx1261060986.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/15a8vz1261060986.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/16e31a1261060986.tab")
+ }
>
> try(system("convert tmp/17tfw1261060986.ps tmp/17tfw1261060986.png",intern=TRUE))
character(0)
> try(system("convert tmp/2knel1261060986.ps tmp/2knel1261060986.png",intern=TRUE))
character(0)
> try(system("convert tmp/343hx1261060986.ps tmp/343hx1261060986.png",intern=TRUE))
character(0)
> try(system("convert tmp/4wnpn1261060986.ps tmp/4wnpn1261060986.png",intern=TRUE))
character(0)
> try(system("convert tmp/5t66q1261060986.ps tmp/5t66q1261060986.png",intern=TRUE))
character(0)
> try(system("convert tmp/6cpe21261060986.ps tmp/6cpe21261060986.png",intern=TRUE))
character(0)
> try(system("convert tmp/74q7v1261060986.ps tmp/74q7v1261060986.png",intern=TRUE))
character(0)
> try(system("convert tmp/83k621261060986.ps tmp/83k621261060986.png",intern=TRUE))
character(0)
> try(system("convert tmp/9mqez1261060986.ps tmp/9mqez1261060986.png",intern=TRUE))
character(0)
> try(system("convert tmp/10dcvn1261060986.ps tmp/10dcvn1261060986.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
2.405 1.583 3.719