R version 2.15.2 (2012-10-26) -- "Trick or Treat"
Copyright (C) 2012 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i686-pc-linux-gnu (32-bit)
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(0,0,1,0,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,1,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,1,0,0,0,0,1,1,0,0,0,0,0,0,0,1,0,1,0,1,0,0,0,0,0,0,0,0,1,0,1,0,0),dim=c(2,68),dimnames=list(c('T20','CorrectAnalysis'),1:68))
> y <- array(NA,dim=c(2,68),dimnames=list(c('T20','CorrectAnalysis'),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 = 'No Linear Trend'
> par2 = 'Do not include Seasonal Dummies'
> par1 = '2'
> par3 <- 'No Linear Trend'
> par2 <- 'Do not include Seasonal Dummies'
> par1 <- '2'
> #'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, 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
CorrectAnalysis T20
1 0 0
2 0 1
3 0 0
4 0 0
5 0 0
6 0 1
7 0 0
8 0 0
9 0 1
10 0 0
11 0 1
12 0 0
13 0 0
14 0 0
15 0 0
16 0 0
17 0 0
18 0 0
19 0 1
20 0 0
21 0 0
22 0 1
23 0 0
24 0 0
25 0 1
26 0 1
27 0 0
28 0 1
29 0 0
30 0 0
31 0 0
32 0 0
33 0 0
34 0 0
35 0 0
36 0 0
37 0 1
38 0 0
39 0 0
40 0 1
41 0 0
42 0 0
43 0 0
44 0 0
45 0 0
46 0 0
47 0 0
48 0 0
49 0 0
50 0 0
51 0 0
52 0 1
53 0 1
54 0 0
55 1 0
56 0 1
57 0 0
58 0 0
59 0 0
60 0 1
61 0 1
62 0 1
63 0 0
64 0 0
65 0 0
66 1 0
67 1 0
68 0 0
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) T20
0.05882 -0.05882
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-0.05882 -0.05882 -0.05882 0.00000 0.94118
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.05882 0.02896 2.031 0.0463 *
T20 -0.05882 0.05793 -1.016 0.3136
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.2068 on 66 degrees of freedom
Multiple R-squared: 0.01538, Adjusted R-squared: 0.0004662
F-statistic: 1.031 on 1 and 66 DF, p-value: 0.3136
> 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,] 0.000000e+00 0.000000e+00 1.0000000
[2,] 0.000000e+00 0.000000e+00 1.0000000
[3,] 0.000000e+00 0.000000e+00 1.0000000
[4,] 0.000000e+00 0.000000e+00 1.0000000
[5,] 0.000000e+00 0.000000e+00 1.0000000
[6,] 0.000000e+00 0.000000e+00 1.0000000
[7,] 0.000000e+00 0.000000e+00 1.0000000
[8,] 0.000000e+00 0.000000e+00 1.0000000
[9,] 0.000000e+00 0.000000e+00 1.0000000
[10,] 0.000000e+00 0.000000e+00 1.0000000
[11,] 0.000000e+00 0.000000e+00 1.0000000
[12,] 0.000000e+00 0.000000e+00 1.0000000
[13,] 0.000000e+00 0.000000e+00 1.0000000
[14,] 0.000000e+00 0.000000e+00 1.0000000
[15,] 0.000000e+00 0.000000e+00 1.0000000
[16,] 0.000000e+00 0.000000e+00 1.0000000
[17,] 0.000000e+00 0.000000e+00 1.0000000
[18,] 0.000000e+00 0.000000e+00 1.0000000
[19,] 0.000000e+00 0.000000e+00 1.0000000
[20,] 0.000000e+00 0.000000e+00 1.0000000
[21,] 0.000000e+00 0.000000e+00 1.0000000
[22,] 0.000000e+00 0.000000e+00 1.0000000
[23,] 0.000000e+00 0.000000e+00 1.0000000
[24,] 0.000000e+00 0.000000e+00 1.0000000
[25,] 0.000000e+00 0.000000e+00 1.0000000
[26,] 0.000000e+00 0.000000e+00 1.0000000
[27,] 0.000000e+00 0.000000e+00 1.0000000
[28,] 0.000000e+00 0.000000e+00 1.0000000
[29,] 0.000000e+00 0.000000e+00 1.0000000
[30,] 0.000000e+00 0.000000e+00 1.0000000
[31,] 0.000000e+00 0.000000e+00 1.0000000
[32,] 0.000000e+00 0.000000e+00 1.0000000
[33,] 0.000000e+00 0.000000e+00 1.0000000
[34,] 0.000000e+00 0.000000e+00 1.0000000
[35,] 0.000000e+00 0.000000e+00 1.0000000
[36,] 0.000000e+00 0.000000e+00 1.0000000
[37,] 0.000000e+00 0.000000e+00 1.0000000
[38,] 0.000000e+00 0.000000e+00 1.0000000
[39,] 0.000000e+00 0.000000e+00 1.0000000
[40,] 0.000000e+00 0.000000e+00 1.0000000
[41,] 0.000000e+00 0.000000e+00 1.0000000
[42,] 0.000000e+00 0.000000e+00 1.0000000
[43,] 0.000000e+00 0.000000e+00 1.0000000
[44,] 0.000000e+00 0.000000e+00 1.0000000
[45,] 0.000000e+00 0.000000e+00 1.0000000
[46,] 0.000000e+00 0.000000e+00 1.0000000
[47,] 0.000000e+00 0.000000e+00 1.0000000
[48,] 0.000000e+00 0.000000e+00 1.0000000
[49,] 0.000000e+00 0.000000e+00 1.0000000
[50,] 0.000000e+00 0.000000e+00 1.0000000
[51,] 1.006306e-07 2.012613e-07 0.9999999
[52,] 3.284565e-08 6.569130e-08 1.0000000
[53,] 1.782255e-08 3.564510e-08 1.0000000
[54,] 1.121028e-08 2.242056e-08 1.0000000
[55,] 9.179819e-09 1.835964e-08 1.0000000
[56,] 2.382636e-09 4.765271e-09 1.0000000
[57,] 5.555257e-10 1.111051e-09 1.0000000
[58,] 1.135570e-10 2.271139e-10 1.0000000
[59,] 1.181559e-10 2.363118e-10 1.0000000
> postscript(file="/var/fisher/rcomp/tmp/1t4v71356001310.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/2u7b71356001310.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/38ry01356001310.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/40c781356001310.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/51hpf1356001310.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
-5.882353e-02 4.857056e-17 -5.882353e-02 -5.882353e-02 -5.882353e-02
6 7 8 9 10
-1.736418e-18 -5.882353e-02 -5.882353e-02 -1.736418e-18 -5.882353e-02
11 12 13 14 15
-1.736418e-18 -5.882353e-02 -5.882353e-02 -5.882353e-02 -5.882353e-02
16 17 18 19 20
-5.882353e-02 -5.882353e-02 -5.882353e-02 -1.736418e-18 -5.882353e-02
21 22 23 24 25
-5.882353e-02 -1.736418e-18 -5.882353e-02 -5.882353e-02 -1.736418e-18
26 27 28 29 30
-1.736418e-18 -5.882353e-02 -1.736418e-18 -5.882353e-02 -5.882353e-02
31 32 33 34 35
-5.882353e-02 -5.882353e-02 -5.882353e-02 -5.882353e-02 -5.882353e-02
36 37 38 39 40
-5.882353e-02 -1.736418e-18 -5.882353e-02 -5.882353e-02 -1.736418e-18
41 42 43 44 45
-5.882353e-02 -5.882353e-02 -5.882353e-02 -5.882353e-02 -5.882353e-02
46 47 48 49 50
-5.882353e-02 -5.882353e-02 -5.882353e-02 -5.882353e-02 -5.882353e-02
51 52 53 54 55
-5.882353e-02 -1.736418e-18 -1.736418e-18 -5.882353e-02 9.411765e-01
56 57 58 59 60
-1.736418e-18 -5.882353e-02 -5.882353e-02 -5.882353e-02 -1.736418e-18
61 62 63 64 65
-1.736418e-18 -1.736418e-18 -5.882353e-02 -5.882353e-02 -5.882353e-02
66 67 68
9.411765e-01 9.411765e-01 -5.882353e-02
> postscript(file="/var/fisher/rcomp/tmp/6ivgf1356001310.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 -5.882353e-02 NA
1 4.857056e-17 -5.882353e-02
2 -5.882353e-02 4.857056e-17
3 -5.882353e-02 -5.882353e-02
4 -5.882353e-02 -5.882353e-02
5 -1.736418e-18 -5.882353e-02
6 -5.882353e-02 -1.736418e-18
7 -5.882353e-02 -5.882353e-02
8 -1.736418e-18 -5.882353e-02
9 -5.882353e-02 -1.736418e-18
10 -1.736418e-18 -5.882353e-02
11 -5.882353e-02 -1.736418e-18
12 -5.882353e-02 -5.882353e-02
13 -5.882353e-02 -5.882353e-02
14 -5.882353e-02 -5.882353e-02
15 -5.882353e-02 -5.882353e-02
16 -5.882353e-02 -5.882353e-02
17 -5.882353e-02 -5.882353e-02
18 -1.736418e-18 -5.882353e-02
19 -5.882353e-02 -1.736418e-18
20 -5.882353e-02 -5.882353e-02
21 -1.736418e-18 -5.882353e-02
22 -5.882353e-02 -1.736418e-18
23 -5.882353e-02 -5.882353e-02
24 -1.736418e-18 -5.882353e-02
25 -1.736418e-18 -1.736418e-18
26 -5.882353e-02 -1.736418e-18
27 -1.736418e-18 -5.882353e-02
28 -5.882353e-02 -1.736418e-18
29 -5.882353e-02 -5.882353e-02
30 -5.882353e-02 -5.882353e-02
31 -5.882353e-02 -5.882353e-02
32 -5.882353e-02 -5.882353e-02
33 -5.882353e-02 -5.882353e-02
34 -5.882353e-02 -5.882353e-02
35 -5.882353e-02 -5.882353e-02
36 -1.736418e-18 -5.882353e-02
37 -5.882353e-02 -1.736418e-18
38 -5.882353e-02 -5.882353e-02
39 -1.736418e-18 -5.882353e-02
40 -5.882353e-02 -1.736418e-18
41 -5.882353e-02 -5.882353e-02
42 -5.882353e-02 -5.882353e-02
43 -5.882353e-02 -5.882353e-02
44 -5.882353e-02 -5.882353e-02
45 -5.882353e-02 -5.882353e-02
46 -5.882353e-02 -5.882353e-02
47 -5.882353e-02 -5.882353e-02
48 -5.882353e-02 -5.882353e-02
49 -5.882353e-02 -5.882353e-02
50 -5.882353e-02 -5.882353e-02
51 -1.736418e-18 -5.882353e-02
52 -1.736418e-18 -1.736418e-18
53 -5.882353e-02 -1.736418e-18
54 9.411765e-01 -5.882353e-02
55 -1.736418e-18 9.411765e-01
56 -5.882353e-02 -1.736418e-18
57 -5.882353e-02 -5.882353e-02
58 -5.882353e-02 -5.882353e-02
59 -1.736418e-18 -5.882353e-02
60 -1.736418e-18 -1.736418e-18
61 -1.736418e-18 -1.736418e-18
62 -5.882353e-02 -1.736418e-18
63 -5.882353e-02 -5.882353e-02
64 -5.882353e-02 -5.882353e-02
65 9.411765e-01 -5.882353e-02
66 9.411765e-01 9.411765e-01
67 -5.882353e-02 9.411765e-01
68 NA -5.882353e-02
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 4.857056e-17 -5.882353e-02
[2,] -5.882353e-02 4.857056e-17
[3,] -5.882353e-02 -5.882353e-02
[4,] -5.882353e-02 -5.882353e-02
[5,] -1.736418e-18 -5.882353e-02
[6,] -5.882353e-02 -1.736418e-18
[7,] -5.882353e-02 -5.882353e-02
[8,] -1.736418e-18 -5.882353e-02
[9,] -5.882353e-02 -1.736418e-18
[10,] -1.736418e-18 -5.882353e-02
[11,] -5.882353e-02 -1.736418e-18
[12,] -5.882353e-02 -5.882353e-02
[13,] -5.882353e-02 -5.882353e-02
[14,] -5.882353e-02 -5.882353e-02
[15,] -5.882353e-02 -5.882353e-02
[16,] -5.882353e-02 -5.882353e-02
[17,] -5.882353e-02 -5.882353e-02
[18,] -1.736418e-18 -5.882353e-02
[19,] -5.882353e-02 -1.736418e-18
[20,] -5.882353e-02 -5.882353e-02
[21,] -1.736418e-18 -5.882353e-02
[22,] -5.882353e-02 -1.736418e-18
[23,] -5.882353e-02 -5.882353e-02
[24,] -1.736418e-18 -5.882353e-02
[25,] -1.736418e-18 -1.736418e-18
[26,] -5.882353e-02 -1.736418e-18
[27,] -1.736418e-18 -5.882353e-02
[28,] -5.882353e-02 -1.736418e-18
[29,] -5.882353e-02 -5.882353e-02
[30,] -5.882353e-02 -5.882353e-02
[31,] -5.882353e-02 -5.882353e-02
[32,] -5.882353e-02 -5.882353e-02
[33,] -5.882353e-02 -5.882353e-02
[34,] -5.882353e-02 -5.882353e-02
[35,] -5.882353e-02 -5.882353e-02
[36,] -1.736418e-18 -5.882353e-02
[37,] -5.882353e-02 -1.736418e-18
[38,] -5.882353e-02 -5.882353e-02
[39,] -1.736418e-18 -5.882353e-02
[40,] -5.882353e-02 -1.736418e-18
[41,] -5.882353e-02 -5.882353e-02
[42,] -5.882353e-02 -5.882353e-02
[43,] -5.882353e-02 -5.882353e-02
[44,] -5.882353e-02 -5.882353e-02
[45,] -5.882353e-02 -5.882353e-02
[46,] -5.882353e-02 -5.882353e-02
[47,] -5.882353e-02 -5.882353e-02
[48,] -5.882353e-02 -5.882353e-02
[49,] -5.882353e-02 -5.882353e-02
[50,] -5.882353e-02 -5.882353e-02
[51,] -1.736418e-18 -5.882353e-02
[52,] -1.736418e-18 -1.736418e-18
[53,] -5.882353e-02 -1.736418e-18
[54,] 9.411765e-01 -5.882353e-02
[55,] -1.736418e-18 9.411765e-01
[56,] -5.882353e-02 -1.736418e-18
[57,] -5.882353e-02 -5.882353e-02
[58,] -5.882353e-02 -5.882353e-02
[59,] -1.736418e-18 -5.882353e-02
[60,] -1.736418e-18 -1.736418e-18
[61,] -1.736418e-18 -1.736418e-18
[62,] -5.882353e-02 -1.736418e-18
[63,] -5.882353e-02 -5.882353e-02
[64,] -5.882353e-02 -5.882353e-02
[65,] 9.411765e-01 -5.882353e-02
[66,] 9.411765e-01 9.411765e-01
[67,] -5.882353e-02 9.411765e-01
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 4.857056e-17 -5.882353e-02
2 -5.882353e-02 4.857056e-17
3 -5.882353e-02 -5.882353e-02
4 -5.882353e-02 -5.882353e-02
5 -1.736418e-18 -5.882353e-02
6 -5.882353e-02 -1.736418e-18
7 -5.882353e-02 -5.882353e-02
8 -1.736418e-18 -5.882353e-02
9 -5.882353e-02 -1.736418e-18
10 -1.736418e-18 -5.882353e-02
11 -5.882353e-02 -1.736418e-18
12 -5.882353e-02 -5.882353e-02
13 -5.882353e-02 -5.882353e-02
14 -5.882353e-02 -5.882353e-02
15 -5.882353e-02 -5.882353e-02
16 -5.882353e-02 -5.882353e-02
17 -5.882353e-02 -5.882353e-02
18 -1.736418e-18 -5.882353e-02
19 -5.882353e-02 -1.736418e-18
20 -5.882353e-02 -5.882353e-02
21 -1.736418e-18 -5.882353e-02
22 -5.882353e-02 -1.736418e-18
23 -5.882353e-02 -5.882353e-02
24 -1.736418e-18 -5.882353e-02
25 -1.736418e-18 -1.736418e-18
26 -5.882353e-02 -1.736418e-18
27 -1.736418e-18 -5.882353e-02
28 -5.882353e-02 -1.736418e-18
29 -5.882353e-02 -5.882353e-02
30 -5.882353e-02 -5.882353e-02
31 -5.882353e-02 -5.882353e-02
32 -5.882353e-02 -5.882353e-02
33 -5.882353e-02 -5.882353e-02
34 -5.882353e-02 -5.882353e-02
35 -5.882353e-02 -5.882353e-02
36 -1.736418e-18 -5.882353e-02
37 -5.882353e-02 -1.736418e-18
38 -5.882353e-02 -5.882353e-02
39 -1.736418e-18 -5.882353e-02
40 -5.882353e-02 -1.736418e-18
41 -5.882353e-02 -5.882353e-02
42 -5.882353e-02 -5.882353e-02
43 -5.882353e-02 -5.882353e-02
44 -5.882353e-02 -5.882353e-02
45 -5.882353e-02 -5.882353e-02
46 -5.882353e-02 -5.882353e-02
47 -5.882353e-02 -5.882353e-02
48 -5.882353e-02 -5.882353e-02
49 -5.882353e-02 -5.882353e-02
50 -5.882353e-02 -5.882353e-02
51 -1.736418e-18 -5.882353e-02
52 -1.736418e-18 -1.736418e-18
53 -5.882353e-02 -1.736418e-18
54 9.411765e-01 -5.882353e-02
55 -1.736418e-18 9.411765e-01
56 -5.882353e-02 -1.736418e-18
57 -5.882353e-02 -5.882353e-02
58 -5.882353e-02 -5.882353e-02
59 -1.736418e-18 -5.882353e-02
60 -1.736418e-18 -1.736418e-18
61 -1.736418e-18 -1.736418e-18
62 -5.882353e-02 -1.736418e-18
63 -5.882353e-02 -5.882353e-02
64 -5.882353e-02 -5.882353e-02
65 9.411765e-01 -5.882353e-02
66 9.411765e-01 9.411765e-01
67 -5.882353e-02 9.411765e-01
> plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
> lines(lowess(z))
> abline(lm(z))
> grid()
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/7d5lk1356001310.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/887h41356001310.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/94qxd1356001310.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/fisher/rcomp/tmp/10rggc1356001310.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/fisher/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/fisher/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/fisher/rcomp/tmp/11ol9h1356001310.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/fisher/rcomp/tmp/12ylpo1356001310.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/fisher/rcomp/tmp/132up31356001311.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/fisher/rcomp/tmp/14ief61356001311.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/fisher/rcomp/tmp/15f0j61356001311.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/fisher/rcomp/tmp/16vt761356001311.tab")
+ }
>
> try(system("convert tmp/1t4v71356001310.ps tmp/1t4v71356001310.png",intern=TRUE))
character(0)
> try(system("convert tmp/2u7b71356001310.ps tmp/2u7b71356001310.png",intern=TRUE))
character(0)
> try(system("convert tmp/38ry01356001310.ps tmp/38ry01356001310.png",intern=TRUE))
character(0)
> try(system("convert tmp/40c781356001310.ps tmp/40c781356001310.png",intern=TRUE))
character(0)
> try(system("convert tmp/51hpf1356001310.ps tmp/51hpf1356001310.png",intern=TRUE))
character(0)
> try(system("convert tmp/6ivgf1356001310.ps tmp/6ivgf1356001310.png",intern=TRUE))
character(0)
> try(system("convert tmp/7d5lk1356001310.ps tmp/7d5lk1356001310.png",intern=TRUE))
character(0)
> try(system("convert tmp/887h41356001310.ps tmp/887h41356001310.png",intern=TRUE))
character(0)
> try(system("convert tmp/94qxd1356001310.ps tmp/94qxd1356001310.png",intern=TRUE))
character(0)
> try(system("convert tmp/10rggc1356001310.ps tmp/10rggc1356001310.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
6.243 1.722 7.979