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(0,0,1,0,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,1,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,1,0,0,0,0,1,1,0,0,0,0,0,0,0,1,0,1,0,1,0,0,0,0,0,0,0,0,1,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,1,1,1,0,0,0,0,0,0,0,0,1,0,0,0,0),dim=c(2,86),dimnames=list(c('T40','CorrectAnalysis'),1:86))
> y <- array(NA,dim=c(2,86),dimnames=list(c('T40','CorrectAnalysis'),1:86))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par20 = ''
> par19 = ''
> par18 = ''
> par17 = ''
> par16 = ''
> par15 = ''
> par14 = ''
> par13 = ''
> par12 = ''
> par11 = ''
> par10 = ''
> par9 = ''
> par8 = ''
> par7 = ''
> par6 = ''
> par5 = ''
> par4 = ''
> par3 = 'No Linear Trend'
> par2 = 'Do not include Seasonal Dummies'
> par1 = '2'
> 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 T40
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
69 0 0
70 0 0
71 0 0
72 0 0
73 0 0
74 0 0
75 0 0
76 0 1
77 0 0
78 0 0
79 1 1
80 0 1
81 0 0
82 0 0
83 0 0
84 1 0
85 0 0
86 0 0
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) T40
0.06061 -0.01061
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-0.06061 -0.06061 -0.06061 -0.05000 0.95000
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.06061 0.02914 2.080 0.0406 *
T40 -0.01061 0.06043 -0.176 0.8611
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.2367 on 84 degrees of freedom
Multiple R-squared: 0.0003666, Adjusted R-squared: -0.01153
F-statistic: 0.03081 on 1 and 84 DF, p-value: 0.8611
> 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,] 2.305469e-09 4.610938e-09 1.0000000
[52,] 9.754064e-10 1.950813e-09 1.0000000
[53,] 3.924317e-10 7.848634e-10 1.0000000
[54,] 1.556046e-10 3.112093e-10 1.0000000
[55,] 6.089040e-11 1.217808e-10 1.0000000
[56,] 2.503710e-11 5.007420e-11 1.0000000
[57,] 1.119544e-11 2.239087e-11 1.0000000
[58,] 6.119341e-12 1.223868e-11 1.0000000
[59,] 2.244797e-12 4.489594e-12 1.0000000
[60,] 8.150383e-13 1.630077e-12 1.0000000
[61,] 2.937080e-13 5.874160e-13 1.0000000
[62,] 3.774961e-06 7.549921e-06 0.9999962
[63,] 1.322413e-02 2.644826e-02 0.9867759
[64,] 8.367799e-03 1.673560e-02 0.9916322
[65,] 5.126721e-03 1.025344e-02 0.9948733
[66,] 3.037622e-03 6.075243e-03 0.9969624
[67,] 1.738641e-03 3.477282e-03 0.9982614
[68,] 9.604325e-04 1.920865e-03 0.9990396
[69,] 5.117623e-04 1.023525e-03 0.9994882
[70,] 2.630871e-04 5.261742e-04 0.9997369
[71,] 1.306975e-04 2.613950e-04 0.9998693
[72,] 1.863824e-04 3.727649e-04 0.9998136
[73,] 8.857170e-05 1.771434e-04 0.9999114
[74,] 4.098613e-05 8.197227e-05 0.9999590
[75,] 8.194490e-03 1.638898e-02 0.9918055
[76,] 3.512225e-03 7.024451e-03 0.9964878
[77,] 1.670738e-03 3.341476e-03 0.9983293
> postscript(file="/var/fisher/rcomp/tmp/19gt21356104931.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/25du11356104931.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/383tc1356104931.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/4u4c71356104931.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/59qlw1356104931.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$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 = 86
Frequency = 1
1 2 3 4 5 6
-0.06060606 -0.05000000 -0.06060606 -0.06060606 -0.06060606 -0.05000000
7 8 9 10 11 12
-0.06060606 -0.06060606 -0.05000000 -0.06060606 -0.05000000 -0.06060606
13 14 15 16 17 18
-0.06060606 -0.06060606 -0.06060606 -0.06060606 -0.06060606 -0.06060606
19 20 21 22 23 24
-0.05000000 -0.06060606 -0.06060606 -0.05000000 -0.06060606 -0.06060606
25 26 27 28 29 30
-0.05000000 -0.05000000 -0.06060606 -0.05000000 -0.06060606 -0.06060606
31 32 33 34 35 36
-0.06060606 -0.06060606 -0.06060606 -0.06060606 -0.06060606 -0.06060606
37 38 39 40 41 42
-0.05000000 -0.06060606 -0.06060606 -0.05000000 -0.06060606 -0.06060606
43 44 45 46 47 48
-0.06060606 -0.06060606 -0.06060606 -0.06060606 -0.06060606 -0.06060606
49 50 51 52 53 54
-0.06060606 -0.06060606 -0.06060606 -0.05000000 -0.05000000 -0.06060606
55 56 57 58 59 60
0.93939394 -0.05000000 -0.06060606 -0.06060606 -0.06060606 -0.05000000
61 62 63 64 65 66
-0.05000000 -0.05000000 -0.06060606 -0.06060606 -0.06060606 0.93939394
67 68 69 70 71 72
0.93939394 -0.06060606 -0.06060606 -0.06060606 -0.06060606 -0.06060606
73 74 75 76 77 78
-0.06060606 -0.06060606 -0.06060606 -0.05000000 -0.06060606 -0.06060606
79 80 81 82 83 84
0.95000000 -0.05000000 -0.06060606 -0.06060606 -0.06060606 0.93939394
85 86
-0.06060606 -0.06060606
> postscript(file="/var/fisher/rcomp/tmp/6sngw1356104931.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 = 86
Frequency = 1
lag(myerror, k = 1) myerror
0 -0.06060606 NA
1 -0.05000000 -0.06060606
2 -0.06060606 -0.05000000
3 -0.06060606 -0.06060606
4 -0.06060606 -0.06060606
5 -0.05000000 -0.06060606
6 -0.06060606 -0.05000000
7 -0.06060606 -0.06060606
8 -0.05000000 -0.06060606
9 -0.06060606 -0.05000000
10 -0.05000000 -0.06060606
11 -0.06060606 -0.05000000
12 -0.06060606 -0.06060606
13 -0.06060606 -0.06060606
14 -0.06060606 -0.06060606
15 -0.06060606 -0.06060606
16 -0.06060606 -0.06060606
17 -0.06060606 -0.06060606
18 -0.05000000 -0.06060606
19 -0.06060606 -0.05000000
20 -0.06060606 -0.06060606
21 -0.05000000 -0.06060606
22 -0.06060606 -0.05000000
23 -0.06060606 -0.06060606
24 -0.05000000 -0.06060606
25 -0.05000000 -0.05000000
26 -0.06060606 -0.05000000
27 -0.05000000 -0.06060606
28 -0.06060606 -0.05000000
29 -0.06060606 -0.06060606
30 -0.06060606 -0.06060606
31 -0.06060606 -0.06060606
32 -0.06060606 -0.06060606
33 -0.06060606 -0.06060606
34 -0.06060606 -0.06060606
35 -0.06060606 -0.06060606
36 -0.05000000 -0.06060606
37 -0.06060606 -0.05000000
38 -0.06060606 -0.06060606
39 -0.05000000 -0.06060606
40 -0.06060606 -0.05000000
41 -0.06060606 -0.06060606
42 -0.06060606 -0.06060606
43 -0.06060606 -0.06060606
44 -0.06060606 -0.06060606
45 -0.06060606 -0.06060606
46 -0.06060606 -0.06060606
47 -0.06060606 -0.06060606
48 -0.06060606 -0.06060606
49 -0.06060606 -0.06060606
50 -0.06060606 -0.06060606
51 -0.05000000 -0.06060606
52 -0.05000000 -0.05000000
53 -0.06060606 -0.05000000
54 0.93939394 -0.06060606
55 -0.05000000 0.93939394
56 -0.06060606 -0.05000000
57 -0.06060606 -0.06060606
58 -0.06060606 -0.06060606
59 -0.05000000 -0.06060606
60 -0.05000000 -0.05000000
61 -0.05000000 -0.05000000
62 -0.06060606 -0.05000000
63 -0.06060606 -0.06060606
64 -0.06060606 -0.06060606
65 0.93939394 -0.06060606
66 0.93939394 0.93939394
67 -0.06060606 0.93939394
68 -0.06060606 -0.06060606
69 -0.06060606 -0.06060606
70 -0.06060606 -0.06060606
71 -0.06060606 -0.06060606
72 -0.06060606 -0.06060606
73 -0.06060606 -0.06060606
74 -0.06060606 -0.06060606
75 -0.05000000 -0.06060606
76 -0.06060606 -0.05000000
77 -0.06060606 -0.06060606
78 0.95000000 -0.06060606
79 -0.05000000 0.95000000
80 -0.06060606 -0.05000000
81 -0.06060606 -0.06060606
82 -0.06060606 -0.06060606
83 0.93939394 -0.06060606
84 -0.06060606 0.93939394
85 -0.06060606 -0.06060606
86 NA -0.06060606
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -0.05000000 -0.06060606
[2,] -0.06060606 -0.05000000
[3,] -0.06060606 -0.06060606
[4,] -0.06060606 -0.06060606
[5,] -0.05000000 -0.06060606
[6,] -0.06060606 -0.05000000
[7,] -0.06060606 -0.06060606
[8,] -0.05000000 -0.06060606
[9,] -0.06060606 -0.05000000
[10,] -0.05000000 -0.06060606
[11,] -0.06060606 -0.05000000
[12,] -0.06060606 -0.06060606
[13,] -0.06060606 -0.06060606
[14,] -0.06060606 -0.06060606
[15,] -0.06060606 -0.06060606
[16,] -0.06060606 -0.06060606
[17,] -0.06060606 -0.06060606
[18,] -0.05000000 -0.06060606
[19,] -0.06060606 -0.05000000
[20,] -0.06060606 -0.06060606
[21,] -0.05000000 -0.06060606
[22,] -0.06060606 -0.05000000
[23,] -0.06060606 -0.06060606
[24,] -0.05000000 -0.06060606
[25,] -0.05000000 -0.05000000
[26,] -0.06060606 -0.05000000
[27,] -0.05000000 -0.06060606
[28,] -0.06060606 -0.05000000
[29,] -0.06060606 -0.06060606
[30,] -0.06060606 -0.06060606
[31,] -0.06060606 -0.06060606
[32,] -0.06060606 -0.06060606
[33,] -0.06060606 -0.06060606
[34,] -0.06060606 -0.06060606
[35,] -0.06060606 -0.06060606
[36,] -0.05000000 -0.06060606
[37,] -0.06060606 -0.05000000
[38,] -0.06060606 -0.06060606
[39,] -0.05000000 -0.06060606
[40,] -0.06060606 -0.05000000
[41,] -0.06060606 -0.06060606
[42,] -0.06060606 -0.06060606
[43,] -0.06060606 -0.06060606
[44,] -0.06060606 -0.06060606
[45,] -0.06060606 -0.06060606
[46,] -0.06060606 -0.06060606
[47,] -0.06060606 -0.06060606
[48,] -0.06060606 -0.06060606
[49,] -0.06060606 -0.06060606
[50,] -0.06060606 -0.06060606
[51,] -0.05000000 -0.06060606
[52,] -0.05000000 -0.05000000
[53,] -0.06060606 -0.05000000
[54,] 0.93939394 -0.06060606
[55,] -0.05000000 0.93939394
[56,] -0.06060606 -0.05000000
[57,] -0.06060606 -0.06060606
[58,] -0.06060606 -0.06060606
[59,] -0.05000000 -0.06060606
[60,] -0.05000000 -0.05000000
[61,] -0.05000000 -0.05000000
[62,] -0.06060606 -0.05000000
[63,] -0.06060606 -0.06060606
[64,] -0.06060606 -0.06060606
[65,] 0.93939394 -0.06060606
[66,] 0.93939394 0.93939394
[67,] -0.06060606 0.93939394
[68,] -0.06060606 -0.06060606
[69,] -0.06060606 -0.06060606
[70,] -0.06060606 -0.06060606
[71,] -0.06060606 -0.06060606
[72,] -0.06060606 -0.06060606
[73,] -0.06060606 -0.06060606
[74,] -0.06060606 -0.06060606
[75,] -0.05000000 -0.06060606
[76,] -0.06060606 -0.05000000
[77,] -0.06060606 -0.06060606
[78,] 0.95000000 -0.06060606
[79,] -0.05000000 0.95000000
[80,] -0.06060606 -0.05000000
[81,] -0.06060606 -0.06060606
[82,] -0.06060606 -0.06060606
[83,] 0.93939394 -0.06060606
[84,] -0.06060606 0.93939394
[85,] -0.06060606 -0.06060606
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -0.05000000 -0.06060606
2 -0.06060606 -0.05000000
3 -0.06060606 -0.06060606
4 -0.06060606 -0.06060606
5 -0.05000000 -0.06060606
6 -0.06060606 -0.05000000
7 -0.06060606 -0.06060606
8 -0.05000000 -0.06060606
9 -0.06060606 -0.05000000
10 -0.05000000 -0.06060606
11 -0.06060606 -0.05000000
12 -0.06060606 -0.06060606
13 -0.06060606 -0.06060606
14 -0.06060606 -0.06060606
15 -0.06060606 -0.06060606
16 -0.06060606 -0.06060606
17 -0.06060606 -0.06060606
18 -0.05000000 -0.06060606
19 -0.06060606 -0.05000000
20 -0.06060606 -0.06060606
21 -0.05000000 -0.06060606
22 -0.06060606 -0.05000000
23 -0.06060606 -0.06060606
24 -0.05000000 -0.06060606
25 -0.05000000 -0.05000000
26 -0.06060606 -0.05000000
27 -0.05000000 -0.06060606
28 -0.06060606 -0.05000000
29 -0.06060606 -0.06060606
30 -0.06060606 -0.06060606
31 -0.06060606 -0.06060606
32 -0.06060606 -0.06060606
33 -0.06060606 -0.06060606
34 -0.06060606 -0.06060606
35 -0.06060606 -0.06060606
36 -0.05000000 -0.06060606
37 -0.06060606 -0.05000000
38 -0.06060606 -0.06060606
39 -0.05000000 -0.06060606
40 -0.06060606 -0.05000000
41 -0.06060606 -0.06060606
42 -0.06060606 -0.06060606
43 -0.06060606 -0.06060606
44 -0.06060606 -0.06060606
45 -0.06060606 -0.06060606
46 -0.06060606 -0.06060606
47 -0.06060606 -0.06060606
48 -0.06060606 -0.06060606
49 -0.06060606 -0.06060606
50 -0.06060606 -0.06060606
51 -0.05000000 -0.06060606
52 -0.05000000 -0.05000000
53 -0.06060606 -0.05000000
54 0.93939394 -0.06060606
55 -0.05000000 0.93939394
56 -0.06060606 -0.05000000
57 -0.06060606 -0.06060606
58 -0.06060606 -0.06060606
59 -0.05000000 -0.06060606
60 -0.05000000 -0.05000000
61 -0.05000000 -0.05000000
62 -0.06060606 -0.05000000
63 -0.06060606 -0.06060606
64 -0.06060606 -0.06060606
65 0.93939394 -0.06060606
66 0.93939394 0.93939394
67 -0.06060606 0.93939394
68 -0.06060606 -0.06060606
69 -0.06060606 -0.06060606
70 -0.06060606 -0.06060606
71 -0.06060606 -0.06060606
72 -0.06060606 -0.06060606
73 -0.06060606 -0.06060606
74 -0.06060606 -0.06060606
75 -0.05000000 -0.06060606
76 -0.06060606 -0.05000000
77 -0.06060606 -0.06060606
78 0.95000000 -0.06060606
79 -0.05000000 0.95000000
80 -0.06060606 -0.05000000
81 -0.06060606 -0.06060606
82 -0.06060606 -0.06060606
83 0.93939394 -0.06060606
84 -0.06060606 0.93939394
85 -0.06060606 -0.06060606
> 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/7jikc1356104931.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/8leus1356104931.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/9hki21356104931.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/10zdpq1356104931.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$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
+ }
+ }
> myeq <- paste(myeq, ' + e[t]')
> a<-table.row.start(a)
> a<-table.element(a, myeq)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/fisher/rcomp/tmp/119itn1356104932.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Variable',header=TRUE)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
> a<-table.element(a,'2-tail p-value',header=TRUE)
> a<-table.element(a,'1-tail p-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:k){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(mysum$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$coefficients[i,4]/2,6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/fisher/rcomp/tmp/129v991356104932.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple R',1,TRUE)
> a<-table.element(a, sqrt(mysum$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$sigma)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a, sum(myerror*myerror))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/fisher/rcomp/tmp/13gjv71356104932.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Time or Index', 1, TRUE)
> a<-table.element(a, 'Actuals', 1, TRUE)
> a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
> a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
> a<-table.row.end(a)
> for (i in 1:n) {
+ a<-table.row.start(a)
+ a<-table.element(a,i, 1, TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]-mysum$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/14jnlb1356104932.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/15coch1356104932.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/16bipk1356104932.tab")
+ }
>
> try(system("convert tmp/19gt21356104931.ps tmp/19gt21356104931.png",intern=TRUE))
character(0)
> try(system("convert tmp/25du11356104931.ps tmp/25du11356104931.png",intern=TRUE))
character(0)
> try(system("convert tmp/383tc1356104931.ps tmp/383tc1356104931.png",intern=TRUE))
character(0)
> try(system("convert tmp/4u4c71356104931.ps tmp/4u4c71356104931.png",intern=TRUE))
character(0)
> try(system("convert tmp/59qlw1356104931.ps tmp/59qlw1356104931.png",intern=TRUE))
character(0)
> try(system("convert tmp/6sngw1356104931.ps tmp/6sngw1356104931.png",intern=TRUE))
character(0)
> try(system("convert tmp/7jikc1356104931.ps tmp/7jikc1356104931.png",intern=TRUE))
character(0)
> try(system("convert tmp/8leus1356104931.ps tmp/8leus1356104931.png",intern=TRUE))
character(0)
> try(system("convert tmp/9hki21356104931.ps tmp/9hki21356104931.png",intern=TRUE))
character(0)
> try(system("convert tmp/10zdpq1356104931.ps tmp/10zdpq1356104931.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
6.436 1.759 8.209