R version 2.8.0 (2008-10-20)
Copyright (C) 2008 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
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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(0,0,9,0,1,0,4,0,6,0,21,0,24,0,23,0,22,0,21,0,20,0,16,0,18,0,18,0,24,0,16,0,15,0,24,0,18,0,15,0,4,0,3,0,6,0,5,0,12,0,12,0,12,0,14,0,12,0,17,0,12,0,20,0,21,0,15,0,22,0,19,0,19,0,26,0,25,0,19,0,20,0,30,0,31,0,35,0,33,0,26,0,25,0,17,0,14,0,8,0,12,0,7,0,4,0,10,0,8,0,16,1,14,1,20,1,9,1,10,1),dim=c(2,60),dimnames=list(c('Spa','Val'),1:60))
> y <- array(NA,dim=c(2,60),dimnames=list(c('Spa','Val'),1:60))
> 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
Spa Val M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 0 0 1 0 0 0 0 0 0 0 0 0 0 1
2 9 0 0 1 0 0 0 0 0 0 0 0 0 2
3 1 0 0 0 1 0 0 0 0 0 0 0 0 3
4 4 0 0 0 0 1 0 0 0 0 0 0 0 4
5 6 0 0 0 0 0 1 0 0 0 0 0 0 5
6 21 0 0 0 0 0 0 1 0 0 0 0 0 6
7 24 0 0 0 0 0 0 0 1 0 0 0 0 7
8 23 0 0 0 0 0 0 0 0 1 0 0 0 8
9 22 0 0 0 0 0 0 0 0 0 1 0 0 9
10 21 0 0 0 0 0 0 0 0 0 0 1 0 10
11 20 0 0 0 0 0 0 0 0 0 0 0 1 11
12 16 0 0 0 0 0 0 0 0 0 0 0 0 12
13 18 0 1 0 0 0 0 0 0 0 0 0 0 13
14 18 0 0 1 0 0 0 0 0 0 0 0 0 14
15 24 0 0 0 1 0 0 0 0 0 0 0 0 15
16 16 0 0 0 0 1 0 0 0 0 0 0 0 16
17 15 0 0 0 0 0 1 0 0 0 0 0 0 17
18 24 0 0 0 0 0 0 1 0 0 0 0 0 18
19 18 0 0 0 0 0 0 0 1 0 0 0 0 19
20 15 0 0 0 0 0 0 0 0 1 0 0 0 20
21 4 0 0 0 0 0 0 0 0 0 1 0 0 21
22 3 0 0 0 0 0 0 0 0 0 0 1 0 22
23 6 0 0 0 0 0 0 0 0 0 0 0 1 23
24 5 0 0 0 0 0 0 0 0 0 0 0 0 24
25 12 0 1 0 0 0 0 0 0 0 0 0 0 25
26 12 0 0 1 0 0 0 0 0 0 0 0 0 26
27 12 0 0 0 1 0 0 0 0 0 0 0 0 27
28 14 0 0 0 0 1 0 0 0 0 0 0 0 28
29 12 0 0 0 0 0 1 0 0 0 0 0 0 29
30 17 0 0 0 0 0 0 1 0 0 0 0 0 30
31 12 0 0 0 0 0 0 0 1 0 0 0 0 31
32 20 0 0 0 0 0 0 0 0 1 0 0 0 32
33 21 0 0 0 0 0 0 0 0 0 1 0 0 33
34 15 0 0 0 0 0 0 0 0 0 0 1 0 34
35 22 0 0 0 0 0 0 0 0 0 0 0 1 35
36 19 0 0 0 0 0 0 0 0 0 0 0 0 36
37 19 0 1 0 0 0 0 0 0 0 0 0 0 37
38 26 0 0 1 0 0 0 0 0 0 0 0 0 38
39 25 0 0 0 1 0 0 0 0 0 0 0 0 39
40 19 0 0 0 0 1 0 0 0 0 0 0 0 40
41 20 0 0 0 0 0 1 0 0 0 0 0 0 41
42 30 0 0 0 0 0 0 1 0 0 0 0 0 42
43 31 0 0 0 0 0 0 0 1 0 0 0 0 43
44 35 0 0 0 0 0 0 0 0 1 0 0 0 44
45 33 0 0 0 0 0 0 0 0 0 1 0 0 45
46 26 0 0 0 0 0 0 0 0 0 0 1 0 46
47 25 0 0 0 0 0 0 0 0 0 0 0 1 47
48 17 0 0 0 0 0 0 0 0 0 0 0 0 48
49 14 0 1 0 0 0 0 0 0 0 0 0 0 49
50 8 0 0 1 0 0 0 0 0 0 0 0 0 50
51 12 0 0 0 1 0 0 0 0 0 0 0 0 51
52 7 0 0 0 0 1 0 0 0 0 0 0 0 52
53 4 0 0 0 0 0 1 0 0 0 0 0 0 53
54 10 0 0 0 0 0 0 1 0 0 0 0 0 54
55 8 0 0 0 0 0 0 0 1 0 0 0 0 55
56 16 1 0 0 0 0 0 0 0 1 0 0 0 56
57 14 1 0 0 0 0 0 0 0 0 1 0 0 57
58 20 1 0 0 0 0 0 0 0 0 0 1 0 58
59 9 1 0 0 0 0 0 0 0 0 0 0 1 59
60 10 1 0 0 0 0 0 0 0 0 0 0 0 60
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Val M1 M2 M3 M4
11.2674 -7.6526 -1.2112 0.6870 0.7853 -2.1165
M5 M6 M7 M8 M9 M10
-2.8182 6.0800 4.1782 8.8070 5.7053 3.8035
M11 t
3.1018 0.1018
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-15.1095 -4.1005 0.6453 5.1895 11.4484
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 11.26737 4.20875 2.677 0.0103 *
Val -7.65263 4.50364 -1.699 0.0960 .
M1 -1.21123 5.14307 -0.236 0.8149
M2 0.68702 5.13896 0.134 0.8942
M3 0.78526 5.13576 0.153 0.8791
M4 -2.11649 5.13347 -0.412 0.6820
M5 -2.81825 5.13210 -0.549 0.5856
M6 6.08000 5.13164 1.185 0.2422
M7 4.17825 5.13210 0.814 0.4198
M8 8.80702 5.07608 1.735 0.0894 .
M9 5.70526 5.07284 1.125 0.2666
M10 3.80351 5.07053 0.750 0.4570
M11 3.10175 5.06914 0.612 0.5436
t 0.10175 0.06852 1.485 0.1444
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 8.014 on 46 degrees of freedom
Multiple R-squared: 0.2264, Adjusted R-squared: 0.007723
F-statistic: 1.035 on 13 and 46 DF, p-value: 0.4361
> 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,] 0.1950132 0.39002649 0.80498675
[2,] 0.2044783 0.40895651 0.79552175
[3,] 0.3679858 0.73597162 0.63201419
[4,] 0.4564016 0.91280325 0.54359837
[5,] 0.7243949 0.55121028 0.27560514
[6,] 0.8492259 0.30154812 0.15077406
[7,] 0.8773247 0.24535062 0.12267531
[8,] 0.8819789 0.23604220 0.11802110
[9,] 0.8303583 0.33928334 0.16964167
[10,] 0.7699856 0.46002880 0.23001440
[11,] 0.7126161 0.57476789 0.28738395
[12,] 0.6266157 0.74676853 0.37338426
[13,] 0.5319251 0.93614974 0.46807487
[14,] 0.4697934 0.93958684 0.53020658
[15,] 0.4949840 0.98996801 0.50501600
[16,] 0.5186880 0.96262395 0.48131198
[17,] 0.5683564 0.86328711 0.43164356
[18,] 0.8363567 0.32728655 0.16364328
[19,] 0.8916098 0.21678037 0.10839019
[20,] 0.9708853 0.05822947 0.02911473
[21,] 0.9854484 0.02910326 0.01455163
[22,] 0.9728729 0.05425420 0.02712710
[23,] 0.9571503 0.08569931 0.04284966
[24,] 0.9453045 0.10939094 0.05469547
[25,] 0.9086668 0.18266643 0.09133322
[26,] 0.8243771 0.35124583 0.17562292
[27,] 0.6821565 0.63568691 0.31784345
> postscript(file="/var/www/html/freestat/rcomp/tmp/1kkvb1228496783.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/2btpy1228496783.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/freestat/rcomp/tmp/3koz31228496783.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/4f7yn1228496783.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/5l1d21228496783.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 = 60
Frequency = 1
1 2 3 4 5 6
-10.1578947 -3.1578947 -11.3578947 -5.5578947 -2.9578947 3.0421053
7 8 9 10 11 12
7.8421053 2.1115789 4.1115789 4.9115789 4.5115789 3.5115789
13 14 15 16 17 18
6.6210526 4.6210526 10.4210526 5.2210526 4.8210526 4.8210526
19 20 21 22 23 24
0.6210526 -7.1094737 -15.1094737 -14.3094737 -10.7094737 -8.7094737
25 26 27 28 29 30
-0.6000000 -2.6000000 -2.8000000 2.0000000 0.6000000 -3.4000000
31 32 33 34 35 36
-6.6000000 -3.3305263 0.6694737 -3.5305263 4.0694737 4.0694737
37 38 39 40 41 42
5.1789474 10.1789474 8.9789474 5.7789474 7.3789474 8.3789474
43 44 45 46 47 48
11.1789474 10.4484211 11.4484211 6.2484211 5.8484211 0.8484211
49 50 51 52 53 54
-1.0421053 -9.0421053 -5.2421053 -7.4421053 -9.8421053 -12.8421053
55 56 57 58 59 60
-13.0421053 -2.1200000 -1.1200000 6.6800000 -3.7200000 0.2800000
> postscript(file="/var/www/html/freestat/rcomp/tmp/6ac7q1228496783.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 = 60
Frequency = 1
lag(myerror, k = 1) myerror
0 -10.1578947 NA
1 -3.1578947 -10.1578947
2 -11.3578947 -3.1578947
3 -5.5578947 -11.3578947
4 -2.9578947 -5.5578947
5 3.0421053 -2.9578947
6 7.8421053 3.0421053
7 2.1115789 7.8421053
8 4.1115789 2.1115789
9 4.9115789 4.1115789
10 4.5115789 4.9115789
11 3.5115789 4.5115789
12 6.6210526 3.5115789
13 4.6210526 6.6210526
14 10.4210526 4.6210526
15 5.2210526 10.4210526
16 4.8210526 5.2210526
17 4.8210526 4.8210526
18 0.6210526 4.8210526
19 -7.1094737 0.6210526
20 -15.1094737 -7.1094737
21 -14.3094737 -15.1094737
22 -10.7094737 -14.3094737
23 -8.7094737 -10.7094737
24 -0.6000000 -8.7094737
25 -2.6000000 -0.6000000
26 -2.8000000 -2.6000000
27 2.0000000 -2.8000000
28 0.6000000 2.0000000
29 -3.4000000 0.6000000
30 -6.6000000 -3.4000000
31 -3.3305263 -6.6000000
32 0.6694737 -3.3305263
33 -3.5305263 0.6694737
34 4.0694737 -3.5305263
35 4.0694737 4.0694737
36 5.1789474 4.0694737
37 10.1789474 5.1789474
38 8.9789474 10.1789474
39 5.7789474 8.9789474
40 7.3789474 5.7789474
41 8.3789474 7.3789474
42 11.1789474 8.3789474
43 10.4484211 11.1789474
44 11.4484211 10.4484211
45 6.2484211 11.4484211
46 5.8484211 6.2484211
47 0.8484211 5.8484211
48 -1.0421053 0.8484211
49 -9.0421053 -1.0421053
50 -5.2421053 -9.0421053
51 -7.4421053 -5.2421053
52 -9.8421053 -7.4421053
53 -12.8421053 -9.8421053
54 -13.0421053 -12.8421053
55 -2.1200000 -13.0421053
56 -1.1200000 -2.1200000
57 6.6800000 -1.1200000
58 -3.7200000 6.6800000
59 0.2800000 -3.7200000
60 NA 0.2800000
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -3.1578947 -10.1578947
[2,] -11.3578947 -3.1578947
[3,] -5.5578947 -11.3578947
[4,] -2.9578947 -5.5578947
[5,] 3.0421053 -2.9578947
[6,] 7.8421053 3.0421053
[7,] 2.1115789 7.8421053
[8,] 4.1115789 2.1115789
[9,] 4.9115789 4.1115789
[10,] 4.5115789 4.9115789
[11,] 3.5115789 4.5115789
[12,] 6.6210526 3.5115789
[13,] 4.6210526 6.6210526
[14,] 10.4210526 4.6210526
[15,] 5.2210526 10.4210526
[16,] 4.8210526 5.2210526
[17,] 4.8210526 4.8210526
[18,] 0.6210526 4.8210526
[19,] -7.1094737 0.6210526
[20,] -15.1094737 -7.1094737
[21,] -14.3094737 -15.1094737
[22,] -10.7094737 -14.3094737
[23,] -8.7094737 -10.7094737
[24,] -0.6000000 -8.7094737
[25,] -2.6000000 -0.6000000
[26,] -2.8000000 -2.6000000
[27,] 2.0000000 -2.8000000
[28,] 0.6000000 2.0000000
[29,] -3.4000000 0.6000000
[30,] -6.6000000 -3.4000000
[31,] -3.3305263 -6.6000000
[32,] 0.6694737 -3.3305263
[33,] -3.5305263 0.6694737
[34,] 4.0694737 -3.5305263
[35,] 4.0694737 4.0694737
[36,] 5.1789474 4.0694737
[37,] 10.1789474 5.1789474
[38,] 8.9789474 10.1789474
[39,] 5.7789474 8.9789474
[40,] 7.3789474 5.7789474
[41,] 8.3789474 7.3789474
[42,] 11.1789474 8.3789474
[43,] 10.4484211 11.1789474
[44,] 11.4484211 10.4484211
[45,] 6.2484211 11.4484211
[46,] 5.8484211 6.2484211
[47,] 0.8484211 5.8484211
[48,] -1.0421053 0.8484211
[49,] -9.0421053 -1.0421053
[50,] -5.2421053 -9.0421053
[51,] -7.4421053 -5.2421053
[52,] -9.8421053 -7.4421053
[53,] -12.8421053 -9.8421053
[54,] -13.0421053 -12.8421053
[55,] -2.1200000 -13.0421053
[56,] -1.1200000 -2.1200000
[57,] 6.6800000 -1.1200000
[58,] -3.7200000 6.6800000
[59,] 0.2800000 -3.7200000
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -3.1578947 -10.1578947
2 -11.3578947 -3.1578947
3 -5.5578947 -11.3578947
4 -2.9578947 -5.5578947
5 3.0421053 -2.9578947
6 7.8421053 3.0421053
7 2.1115789 7.8421053
8 4.1115789 2.1115789
9 4.9115789 4.1115789
10 4.5115789 4.9115789
11 3.5115789 4.5115789
12 6.6210526 3.5115789
13 4.6210526 6.6210526
14 10.4210526 4.6210526
15 5.2210526 10.4210526
16 4.8210526 5.2210526
17 4.8210526 4.8210526
18 0.6210526 4.8210526
19 -7.1094737 0.6210526
20 -15.1094737 -7.1094737
21 -14.3094737 -15.1094737
22 -10.7094737 -14.3094737
23 -8.7094737 -10.7094737
24 -0.6000000 -8.7094737
25 -2.6000000 -0.6000000
26 -2.8000000 -2.6000000
27 2.0000000 -2.8000000
28 0.6000000 2.0000000
29 -3.4000000 0.6000000
30 -6.6000000 -3.4000000
31 -3.3305263 -6.6000000
32 0.6694737 -3.3305263
33 -3.5305263 0.6694737
34 4.0694737 -3.5305263
35 4.0694737 4.0694737
36 5.1789474 4.0694737
37 10.1789474 5.1789474
38 8.9789474 10.1789474
39 5.7789474 8.9789474
40 7.3789474 5.7789474
41 8.3789474 7.3789474
42 11.1789474 8.3789474
43 10.4484211 11.1789474
44 11.4484211 10.4484211
45 6.2484211 11.4484211
46 5.8484211 6.2484211
47 0.8484211 5.8484211
48 -1.0421053 0.8484211
49 -9.0421053 -1.0421053
50 -5.2421053 -9.0421053
51 -7.4421053 -5.2421053
52 -9.8421053 -7.4421053
53 -12.8421053 -9.8421053
54 -13.0421053 -12.8421053
55 -2.1200000 -13.0421053
56 -1.1200000 -2.1200000
57 6.6800000 -1.1200000
58 -3.7200000 6.6800000
59 0.2800000 -3.7200000
> 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/freestat/rcomp/tmp/7g5p11228496783.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/832ad1228496783.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/921tc1228496783.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/freestat/rcomp/tmp/10l3th1228496783.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/freestat/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/freestat/rcomp/tmp/11ni761228496783.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/freestat/rcomp/tmp/12a3ot1228496783.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/freestat/rcomp/tmp/13rja91228496783.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/freestat/rcomp/tmp/14sqyg1228496783.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/freestat/rcomp/tmp/15t3s61228496783.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/freestat/rcomp/tmp/163q9p1228496784.tab")
+ }
>
> system("convert tmp/1kkvb1228496783.ps tmp/1kkvb1228496783.png")
> system("convert tmp/2btpy1228496783.ps tmp/2btpy1228496783.png")
> system("convert tmp/3koz31228496783.ps tmp/3koz31228496783.png")
> system("convert tmp/4f7yn1228496783.ps tmp/4f7yn1228496783.png")
> system("convert tmp/5l1d21228496783.ps tmp/5l1d21228496783.png")
> system("convert tmp/6ac7q1228496783.ps tmp/6ac7q1228496783.png")
> system("convert tmp/7g5p11228496783.ps tmp/7g5p11228496783.png")
> system("convert tmp/832ad1228496783.ps tmp/832ad1228496783.png")
> system("convert tmp/921tc1228496783.ps tmp/921tc1228496783.png")
> system("convert tmp/10l3th1228496783.ps tmp/10l3th1228496783.png")
>
>
> proc.time()
user system elapsed
3.651 2.502 4.102