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','Correct'),1:68))
> y <- array(NA,dim=c(2,68),dimnames=list(c('T20','Correct'),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 = '1'
> par3 <- 'No Linear Trend'
> par2 <- 'Do not include Seasonal 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, 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
T20 Correct
1 0 0
2 1 0
3 0 0
4 0 0
5 0 0
6 1 0
7 0 0
8 0 0
9 1 0
10 0 0
11 1 0
12 0 0
13 0 0
14 0 0
15 0 0
16 0 0
17 0 0
18 0 0
19 1 0
20 0 0
21 0 0
22 1 0
23 0 0
24 0 0
25 1 0
26 1 0
27 0 0
28 1 0
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 1 0
38 0 0
39 0 0
40 1 0
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 1 0
53 1 0
54 0 0
55 0 1
56 1 0
57 0 0
58 0 0
59 0 0
60 1 0
61 1 0
62 1 0
63 0 0
64 0 0
65 0 0
66 0 1
67 0 1
68 0 0
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Correct
0.2615 -0.2615
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-0.2615 -0.2615 -0.2615 0.1846 0.7385
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.2615 0.0541 4.835 8.32e-06 ***
Correct -0.2615 0.2576 -1.016 0.314
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.4361 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,] 0.7445208 0.5109584 0.2554792
[2,] 0.8569166 0.2861669 0.1430834
[3,] 0.8012853 0.3974294 0.1987147
[4,] 0.7335319 0.5329363 0.2664681
[5,] 0.8310399 0.3379202 0.1689601
[6,] 0.7867521 0.4264958 0.2132479
[7,] 0.8544257 0.2911486 0.1455743
[8,] 0.8228186 0.3543628 0.1771814
[9,] 0.7847460 0.4305079 0.2152540
[10,] 0.7405598 0.5188803 0.2594402
[11,] 0.6909030 0.6181940 0.3090970
[12,] 0.6367302 0.7265396 0.3632698
[13,] 0.5792718 0.8414564 0.4207282
[14,] 0.5199548 0.9600903 0.4800452
[15,] 0.6587914 0.6824173 0.3412086
[16,] 0.6079458 0.7841085 0.3920542
[17,] 0.5549278 0.8901444 0.4450722
[18,] 0.6794491 0.6411018 0.3205509
[19,] 0.6330940 0.7338119 0.3669060
[20,] 0.5844300 0.8311400 0.4155700
[21,] 0.7001097 0.5997805 0.2998903
[22,] 0.7939656 0.4120689 0.2060344
[23,] 0.7595219 0.4809562 0.2404781
[24,] 0.8423708 0.3152585 0.1576292
[25,] 0.8134132 0.3731736 0.1865868
[26,] 0.7808861 0.4382278 0.2191139
[27,] 0.7449257 0.5101486 0.2550743
[28,] 0.7058086 0.5883827 0.2941914
[29,] 0.6639529 0.6720942 0.3360471
[30,] 0.6199081 0.7601838 0.3800919
[31,] 0.5743349 0.8513303 0.4256651
[32,] 0.5279745 0.9440510 0.4720255
[33,] 0.6489185 0.7021629 0.3510815
[34,] 0.6037666 0.7924669 0.3962334
[35,] 0.5574478 0.8851044 0.4425522
[36,] 0.6804990 0.6390021 0.3195010
[37,] 0.6352950 0.7294099 0.3647050
[38,] 0.5884327 0.8231346 0.4115673
[39,] 0.5407807 0.9184386 0.4592193
[40,] 0.4932781 0.9865563 0.5067219
[41,] 0.4468865 0.8937731 0.5531135
[42,] 0.4025432 0.8050865 0.5974568
[43,] 0.3611229 0.7222458 0.6388771
[44,] 0.3234150 0.6468300 0.6765850
[45,] 0.2901263 0.5802527 0.7098737
[46,] 0.2619195 0.5238390 0.7380805
[47,] 0.2395084 0.4790167 0.7604916
[48,] 0.3116902 0.6233805 0.6883098
[49,] 0.4078707 0.8157415 0.5921293
[50,] 0.3666964 0.7333927 0.6333036
[51,] 0.2834260 0.5668520 0.7165740
[52,] 0.3887226 0.7774451 0.6112774
[53,] 0.3360133 0.6720266 0.6639867
[54,] 0.2920907 0.5841814 0.7079093
[55,] 0.2603644 0.5207288 0.7396356
[56,] 0.3444118 0.6888237 0.6555882
[57,] 0.5510067 0.8979867 0.4489933
[58,] 1.0000000 0.0000000 0.0000000
[59,] 1.0000000 0.0000000 0.0000000
> postscript(file="/var/fisher/rcomp/tmp/1sxfq1356132765.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/2dnie1356132765.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3bfr41356132765.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/4opzf1356132765.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/5f3ft1356132765.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
-2.615385e-01 7.384615e-01 -2.615385e-01 -2.615385e-01 -2.615385e-01
6 7 8 9 10
7.384615e-01 -2.615385e-01 -2.615385e-01 7.384615e-01 -2.615385e-01
11 12 13 14 15
7.384615e-01 -2.615385e-01 -2.615385e-01 -2.615385e-01 -2.615385e-01
16 17 18 19 20
-2.615385e-01 -2.615385e-01 -2.615385e-01 7.384615e-01 -2.615385e-01
21 22 23 24 25
-2.615385e-01 7.384615e-01 -2.615385e-01 -2.615385e-01 7.384615e-01
26 27 28 29 30
7.384615e-01 -2.615385e-01 7.384615e-01 -2.615385e-01 -2.615385e-01
31 32 33 34 35
-2.615385e-01 -2.615385e-01 -2.615385e-01 -2.615385e-01 -2.615385e-01
36 37 38 39 40
-2.615385e-01 7.384615e-01 -2.615385e-01 -2.615385e-01 7.384615e-01
41 42 43 44 45
-2.615385e-01 -2.615385e-01 -2.615385e-01 -2.615385e-01 -2.615385e-01
46 47 48 49 50
-2.615385e-01 -2.615385e-01 -2.615385e-01 -2.615385e-01 -2.615385e-01
51 52 53 54 55
-2.615385e-01 7.384615e-01 7.384615e-01 -2.615385e-01 -6.786597e-17
56 57 58 59 60
7.384615e-01 -2.615385e-01 -2.615385e-01 -2.615385e-01 7.384615e-01
61 62 63 64 65
7.384615e-01 7.384615e-01 -2.615385e-01 -2.615385e-01 -2.615385e-01
66 67 68
-6.786597e-17 -6.786597e-17 -2.615385e-01
> postscript(file="/var/fisher/rcomp/tmp/6ccff1356132765.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 -2.615385e-01 NA
1 7.384615e-01 -2.615385e-01
2 -2.615385e-01 7.384615e-01
3 -2.615385e-01 -2.615385e-01
4 -2.615385e-01 -2.615385e-01
5 7.384615e-01 -2.615385e-01
6 -2.615385e-01 7.384615e-01
7 -2.615385e-01 -2.615385e-01
8 7.384615e-01 -2.615385e-01
9 -2.615385e-01 7.384615e-01
10 7.384615e-01 -2.615385e-01
11 -2.615385e-01 7.384615e-01
12 -2.615385e-01 -2.615385e-01
13 -2.615385e-01 -2.615385e-01
14 -2.615385e-01 -2.615385e-01
15 -2.615385e-01 -2.615385e-01
16 -2.615385e-01 -2.615385e-01
17 -2.615385e-01 -2.615385e-01
18 7.384615e-01 -2.615385e-01
19 -2.615385e-01 7.384615e-01
20 -2.615385e-01 -2.615385e-01
21 7.384615e-01 -2.615385e-01
22 -2.615385e-01 7.384615e-01
23 -2.615385e-01 -2.615385e-01
24 7.384615e-01 -2.615385e-01
25 7.384615e-01 7.384615e-01
26 -2.615385e-01 7.384615e-01
27 7.384615e-01 -2.615385e-01
28 -2.615385e-01 7.384615e-01
29 -2.615385e-01 -2.615385e-01
30 -2.615385e-01 -2.615385e-01
31 -2.615385e-01 -2.615385e-01
32 -2.615385e-01 -2.615385e-01
33 -2.615385e-01 -2.615385e-01
34 -2.615385e-01 -2.615385e-01
35 -2.615385e-01 -2.615385e-01
36 7.384615e-01 -2.615385e-01
37 -2.615385e-01 7.384615e-01
38 -2.615385e-01 -2.615385e-01
39 7.384615e-01 -2.615385e-01
40 -2.615385e-01 7.384615e-01
41 -2.615385e-01 -2.615385e-01
42 -2.615385e-01 -2.615385e-01
43 -2.615385e-01 -2.615385e-01
44 -2.615385e-01 -2.615385e-01
45 -2.615385e-01 -2.615385e-01
46 -2.615385e-01 -2.615385e-01
47 -2.615385e-01 -2.615385e-01
48 -2.615385e-01 -2.615385e-01
49 -2.615385e-01 -2.615385e-01
50 -2.615385e-01 -2.615385e-01
51 7.384615e-01 -2.615385e-01
52 7.384615e-01 7.384615e-01
53 -2.615385e-01 7.384615e-01
54 -6.786597e-17 -2.615385e-01
55 7.384615e-01 -6.786597e-17
56 -2.615385e-01 7.384615e-01
57 -2.615385e-01 -2.615385e-01
58 -2.615385e-01 -2.615385e-01
59 7.384615e-01 -2.615385e-01
60 7.384615e-01 7.384615e-01
61 7.384615e-01 7.384615e-01
62 -2.615385e-01 7.384615e-01
63 -2.615385e-01 -2.615385e-01
64 -2.615385e-01 -2.615385e-01
65 -6.786597e-17 -2.615385e-01
66 -6.786597e-17 -6.786597e-17
67 -2.615385e-01 -6.786597e-17
68 NA -2.615385e-01
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 7.384615e-01 -2.615385e-01
[2,] -2.615385e-01 7.384615e-01
[3,] -2.615385e-01 -2.615385e-01
[4,] -2.615385e-01 -2.615385e-01
[5,] 7.384615e-01 -2.615385e-01
[6,] -2.615385e-01 7.384615e-01
[7,] -2.615385e-01 -2.615385e-01
[8,] 7.384615e-01 -2.615385e-01
[9,] -2.615385e-01 7.384615e-01
[10,] 7.384615e-01 -2.615385e-01
[11,] -2.615385e-01 7.384615e-01
[12,] -2.615385e-01 -2.615385e-01
[13,] -2.615385e-01 -2.615385e-01
[14,] -2.615385e-01 -2.615385e-01
[15,] -2.615385e-01 -2.615385e-01
[16,] -2.615385e-01 -2.615385e-01
[17,] -2.615385e-01 -2.615385e-01
[18,] 7.384615e-01 -2.615385e-01
[19,] -2.615385e-01 7.384615e-01
[20,] -2.615385e-01 -2.615385e-01
[21,] 7.384615e-01 -2.615385e-01
[22,] -2.615385e-01 7.384615e-01
[23,] -2.615385e-01 -2.615385e-01
[24,] 7.384615e-01 -2.615385e-01
[25,] 7.384615e-01 7.384615e-01
[26,] -2.615385e-01 7.384615e-01
[27,] 7.384615e-01 -2.615385e-01
[28,] -2.615385e-01 7.384615e-01
[29,] -2.615385e-01 -2.615385e-01
[30,] -2.615385e-01 -2.615385e-01
[31,] -2.615385e-01 -2.615385e-01
[32,] -2.615385e-01 -2.615385e-01
[33,] -2.615385e-01 -2.615385e-01
[34,] -2.615385e-01 -2.615385e-01
[35,] -2.615385e-01 -2.615385e-01
[36,] 7.384615e-01 -2.615385e-01
[37,] -2.615385e-01 7.384615e-01
[38,] -2.615385e-01 -2.615385e-01
[39,] 7.384615e-01 -2.615385e-01
[40,] -2.615385e-01 7.384615e-01
[41,] -2.615385e-01 -2.615385e-01
[42,] -2.615385e-01 -2.615385e-01
[43,] -2.615385e-01 -2.615385e-01
[44,] -2.615385e-01 -2.615385e-01
[45,] -2.615385e-01 -2.615385e-01
[46,] -2.615385e-01 -2.615385e-01
[47,] -2.615385e-01 -2.615385e-01
[48,] -2.615385e-01 -2.615385e-01
[49,] -2.615385e-01 -2.615385e-01
[50,] -2.615385e-01 -2.615385e-01
[51,] 7.384615e-01 -2.615385e-01
[52,] 7.384615e-01 7.384615e-01
[53,] -2.615385e-01 7.384615e-01
[54,] -6.786597e-17 -2.615385e-01
[55,] 7.384615e-01 -6.786597e-17
[56,] -2.615385e-01 7.384615e-01
[57,] -2.615385e-01 -2.615385e-01
[58,] -2.615385e-01 -2.615385e-01
[59,] 7.384615e-01 -2.615385e-01
[60,] 7.384615e-01 7.384615e-01
[61,] 7.384615e-01 7.384615e-01
[62,] -2.615385e-01 7.384615e-01
[63,] -2.615385e-01 -2.615385e-01
[64,] -2.615385e-01 -2.615385e-01
[65,] -6.786597e-17 -2.615385e-01
[66,] -6.786597e-17 -6.786597e-17
[67,] -2.615385e-01 -6.786597e-17
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 7.384615e-01 -2.615385e-01
2 -2.615385e-01 7.384615e-01
3 -2.615385e-01 -2.615385e-01
4 -2.615385e-01 -2.615385e-01
5 7.384615e-01 -2.615385e-01
6 -2.615385e-01 7.384615e-01
7 -2.615385e-01 -2.615385e-01
8 7.384615e-01 -2.615385e-01
9 -2.615385e-01 7.384615e-01
10 7.384615e-01 -2.615385e-01
11 -2.615385e-01 7.384615e-01
12 -2.615385e-01 -2.615385e-01
13 -2.615385e-01 -2.615385e-01
14 -2.615385e-01 -2.615385e-01
15 -2.615385e-01 -2.615385e-01
16 -2.615385e-01 -2.615385e-01
17 -2.615385e-01 -2.615385e-01
18 7.384615e-01 -2.615385e-01
19 -2.615385e-01 7.384615e-01
20 -2.615385e-01 -2.615385e-01
21 7.384615e-01 -2.615385e-01
22 -2.615385e-01 7.384615e-01
23 -2.615385e-01 -2.615385e-01
24 7.384615e-01 -2.615385e-01
25 7.384615e-01 7.384615e-01
26 -2.615385e-01 7.384615e-01
27 7.384615e-01 -2.615385e-01
28 -2.615385e-01 7.384615e-01
29 -2.615385e-01 -2.615385e-01
30 -2.615385e-01 -2.615385e-01
31 -2.615385e-01 -2.615385e-01
32 -2.615385e-01 -2.615385e-01
33 -2.615385e-01 -2.615385e-01
34 -2.615385e-01 -2.615385e-01
35 -2.615385e-01 -2.615385e-01
36 7.384615e-01 -2.615385e-01
37 -2.615385e-01 7.384615e-01
38 -2.615385e-01 -2.615385e-01
39 7.384615e-01 -2.615385e-01
40 -2.615385e-01 7.384615e-01
41 -2.615385e-01 -2.615385e-01
42 -2.615385e-01 -2.615385e-01
43 -2.615385e-01 -2.615385e-01
44 -2.615385e-01 -2.615385e-01
45 -2.615385e-01 -2.615385e-01
46 -2.615385e-01 -2.615385e-01
47 -2.615385e-01 -2.615385e-01
48 -2.615385e-01 -2.615385e-01
49 -2.615385e-01 -2.615385e-01
50 -2.615385e-01 -2.615385e-01
51 7.384615e-01 -2.615385e-01
52 7.384615e-01 7.384615e-01
53 -2.615385e-01 7.384615e-01
54 -6.786597e-17 -2.615385e-01
55 7.384615e-01 -6.786597e-17
56 -2.615385e-01 7.384615e-01
57 -2.615385e-01 -2.615385e-01
58 -2.615385e-01 -2.615385e-01
59 7.384615e-01 -2.615385e-01
60 7.384615e-01 7.384615e-01
61 7.384615e-01 7.384615e-01
62 -2.615385e-01 7.384615e-01
63 -2.615385e-01 -2.615385e-01
64 -2.615385e-01 -2.615385e-01
65 -6.786597e-17 -2.615385e-01
66 -6.786597e-17 -6.786597e-17
67 -2.615385e-01 -6.786597e-17
> 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/7ri081356132765.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/8k3631356132765.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/9vdnn1356132765.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/fisher/rcomp/tmp/10q2vc1356132765.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/fisher/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/fisher/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11h8c11356132766.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/123pmg1356132766.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/13ly5f1356132766.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/14afcp1356132766.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/15o21e1356132766.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/168d4n1356132766.tab")
+ }
>
> try(system("convert tmp/1sxfq1356132765.ps tmp/1sxfq1356132765.png",intern=TRUE))
character(0)
> try(system("convert tmp/2dnie1356132765.ps tmp/2dnie1356132765.png",intern=TRUE))
character(0)
> try(system("convert tmp/3bfr41356132765.ps tmp/3bfr41356132765.png",intern=TRUE))
character(0)
> try(system("convert tmp/4opzf1356132765.ps tmp/4opzf1356132765.png",intern=TRUE))
character(0)
> try(system("convert tmp/5f3ft1356132765.ps tmp/5f3ft1356132765.png",intern=TRUE))
character(0)
> try(system("convert tmp/6ccff1356132765.ps tmp/6ccff1356132765.png",intern=TRUE))
character(0)
> try(system("convert tmp/7ri081356132765.ps tmp/7ri081356132765.png",intern=TRUE))
character(0)
> try(system("convert tmp/8k3631356132765.ps tmp/8k3631356132765.png",intern=TRUE))
character(0)
> try(system("convert tmp/9vdnn1356132765.ps tmp/9vdnn1356132765.png",intern=TRUE))
character(0)
> try(system("convert tmp/10q2vc1356132765.ps tmp/10q2vc1356132765.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
5.819 1.719 7.535