R version 2.6.1 (2007-11-26)
Copyright (C) 2007 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.
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(117,0,103.8,0,100.8,0,110.6,0,104,0,112.6,0,107.3,0,98.9,0,109.8,0,104.9,0,102.2,0,123.9,0,124.9,0,112.7,0,121.9,0,100.6,0,104.3,0,120.4,0,107.5,0,102.9,0,125.6,0,107.5,0,108.8,0,128.4,1,121.1,1,119.5,1,128.7,1,108.7,1,105.5,1,119.8,1,111.3,1,110.6,1,120.1,1,97.5,1,107.7,1,127.3,1,117.2,1,119.8,1,116.2,1,111,1,112.4,1,130.6,1,109.1,1,118.8,1,123.9,1,101.6,1,112.8,1,128,1,129.6,1,125.8,1,119.5,1,115.7,1,113.6,1,129.7,1,112,1,116.8,1,127,1,112.9,1,113.3,1,121.7,1),dim=c(2,60),dimnames=list(c('Cons','Wetg'),1:60))
> y <- array(NA,dim=c(2,60),dimnames=list(c('Cons','Wetg'),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 = '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)
> 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
Cons Wetg
1 117.0 0
2 103.8 0
3 100.8 0
4 110.6 0
5 104.0 0
6 112.6 0
7 107.3 0
8 98.9 0
9 109.8 0
10 104.9 0
11 102.2 0
12 123.9 0
13 124.9 0
14 112.7 0
15 121.9 0
16 100.6 0
17 104.3 0
18 120.4 0
19 107.5 0
20 102.9 0
21 125.6 0
22 107.5 0
23 108.8 0
24 128.4 1
25 121.1 1
26 119.5 1
27 128.7 1
28 108.7 1
29 105.5 1
30 119.8 1
31 111.3 1
32 110.6 1
33 120.1 1
34 97.5 1
35 107.7 1
36 127.3 1
37 117.2 1
38 119.8 1
39 116.2 1
40 111.0 1
41 112.4 1
42 130.6 1
43 109.1 1
44 118.8 1
45 123.9 1
46 101.6 1
47 112.8 1
48 128.0 1
49 129.6 1
50 125.8 1
51 119.5 1
52 115.7 1
53 113.6 1
54 129.7 1
55 112.0 1
56 116.8 1
57 127.0 1
58 112.9 1
59 113.3 1
60 121.7 1
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Wetg
110.126 7.312
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-19.9378 -6.1290 -0.9378 6.5651 15.4739
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 110.126 1.735 63.48 < 2e-16 ***
Wetg 7.312 2.209 3.31 0.00161 **
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 8.32 on 58 degrees of freedom
Multiple R-Squared: 0.1589, Adjusted R-squared: 0.1444
F-statistic: 10.95 on 1 and 58 DF, p-value: 0.001610
> postscript(file="/var/www/html/rcomp/tmp/1dgsw1198185364.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
> points(x[,1]-mysum$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2ren01198185364.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/3rulf1198185364.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/47ufr1198185364.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5y03e1198185364.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
> 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
6.8739130 -6.3260870 -9.3260870 0.4739130 -6.1260870 2.4739130
7 8 9 10 11 12
-2.8260870 -11.2260870 -0.3260870 -5.2260870 -7.9260870 13.7739130
13 14 15 16 17 18
14.7739130 2.5739130 11.7739130 -9.5260870 -5.8260870 10.2739130
19 20 21 22 23 24
-2.6260870 -7.2260870 15.4739130 -2.6260870 -1.3260870 10.9621622
25 26 27 28 29 30
3.6621622 2.0621622 11.2621622 -8.7378378 -11.9378378 2.3621622
31 32 33 34 35 36
-6.1378378 -6.8378378 2.6621622 -19.9378378 -9.7378378 9.8621622
37 38 39 40 41 42
-0.2378378 2.3621622 -1.2378378 -6.4378378 -5.0378378 13.1621622
43 44 45 46 47 48
-8.3378378 1.3621622 6.4621622 -15.8378378 -4.6378378 10.5621622
49 50 51 52 53 54
12.1621622 8.3621622 2.0621622 -1.7378378 -3.8378378 12.2621622
55 56 57 58 59 60
-5.4378378 -0.6378378 9.5621622 -4.5378378 -4.1378378 4.2621622
> postscript(file="/var/www/html/rcomp/tmp/6pkhi1198185364.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 6.8739130 NA
1 -6.3260870 6.8739130
2 -9.3260870 -6.3260870
3 0.4739130 -9.3260870
4 -6.1260870 0.4739130
5 2.4739130 -6.1260870
6 -2.8260870 2.4739130
7 -11.2260870 -2.8260870
8 -0.3260870 -11.2260870
9 -5.2260870 -0.3260870
10 -7.9260870 -5.2260870
11 13.7739130 -7.9260870
12 14.7739130 13.7739130
13 2.5739130 14.7739130
14 11.7739130 2.5739130
15 -9.5260870 11.7739130
16 -5.8260870 -9.5260870
17 10.2739130 -5.8260870
18 -2.6260870 10.2739130
19 -7.2260870 -2.6260870
20 15.4739130 -7.2260870
21 -2.6260870 15.4739130
22 -1.3260870 -2.6260870
23 10.9621622 -1.3260870
24 3.6621622 10.9621622
25 2.0621622 3.6621622
26 11.2621622 2.0621622
27 -8.7378378 11.2621622
28 -11.9378378 -8.7378378
29 2.3621622 -11.9378378
30 -6.1378378 2.3621622
31 -6.8378378 -6.1378378
32 2.6621622 -6.8378378
33 -19.9378378 2.6621622
34 -9.7378378 -19.9378378
35 9.8621622 -9.7378378
36 -0.2378378 9.8621622
37 2.3621622 -0.2378378
38 -1.2378378 2.3621622
39 -6.4378378 -1.2378378
40 -5.0378378 -6.4378378
41 13.1621622 -5.0378378
42 -8.3378378 13.1621622
43 1.3621622 -8.3378378
44 6.4621622 1.3621622
45 -15.8378378 6.4621622
46 -4.6378378 -15.8378378
47 10.5621622 -4.6378378
48 12.1621622 10.5621622
49 8.3621622 12.1621622
50 2.0621622 8.3621622
51 -1.7378378 2.0621622
52 -3.8378378 -1.7378378
53 12.2621622 -3.8378378
54 -5.4378378 12.2621622
55 -0.6378378 -5.4378378
56 9.5621622 -0.6378378
57 -4.5378378 9.5621622
58 -4.1378378 -4.5378378
59 4.2621622 -4.1378378
60 NA 4.2621622
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -6.3260870 6.8739130
[2,] -9.3260870 -6.3260870
[3,] 0.4739130 -9.3260870
[4,] -6.1260870 0.4739130
[5,] 2.4739130 -6.1260870
[6,] -2.8260870 2.4739130
[7,] -11.2260870 -2.8260870
[8,] -0.3260870 -11.2260870
[9,] -5.2260870 -0.3260870
[10,] -7.9260870 -5.2260870
[11,] 13.7739130 -7.9260870
[12,] 14.7739130 13.7739130
[13,] 2.5739130 14.7739130
[14,] 11.7739130 2.5739130
[15,] -9.5260870 11.7739130
[16,] -5.8260870 -9.5260870
[17,] 10.2739130 -5.8260870
[18,] -2.6260870 10.2739130
[19,] -7.2260870 -2.6260870
[20,] 15.4739130 -7.2260870
[21,] -2.6260870 15.4739130
[22,] -1.3260870 -2.6260870
[23,] 10.9621622 -1.3260870
[24,] 3.6621622 10.9621622
[25,] 2.0621622 3.6621622
[26,] 11.2621622 2.0621622
[27,] -8.7378378 11.2621622
[28,] -11.9378378 -8.7378378
[29,] 2.3621622 -11.9378378
[30,] -6.1378378 2.3621622
[31,] -6.8378378 -6.1378378
[32,] 2.6621622 -6.8378378
[33,] -19.9378378 2.6621622
[34,] -9.7378378 -19.9378378
[35,] 9.8621622 -9.7378378
[36,] -0.2378378 9.8621622
[37,] 2.3621622 -0.2378378
[38,] -1.2378378 2.3621622
[39,] -6.4378378 -1.2378378
[40,] -5.0378378 -6.4378378
[41,] 13.1621622 -5.0378378
[42,] -8.3378378 13.1621622
[43,] 1.3621622 -8.3378378
[44,] 6.4621622 1.3621622
[45,] -15.8378378 6.4621622
[46,] -4.6378378 -15.8378378
[47,] 10.5621622 -4.6378378
[48,] 12.1621622 10.5621622
[49,] 8.3621622 12.1621622
[50,] 2.0621622 8.3621622
[51,] -1.7378378 2.0621622
[52,] -3.8378378 -1.7378378
[53,] 12.2621622 -3.8378378
[54,] -5.4378378 12.2621622
[55,] -0.6378378 -5.4378378
[56,] 9.5621622 -0.6378378
[57,] -4.5378378 9.5621622
[58,] -4.1378378 -4.5378378
[59,] 4.2621622 -4.1378378
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -6.3260870 6.8739130
2 -9.3260870 -6.3260870
3 0.4739130 -9.3260870
4 -6.1260870 0.4739130
5 2.4739130 -6.1260870
6 -2.8260870 2.4739130
7 -11.2260870 -2.8260870
8 -0.3260870 -11.2260870
9 -5.2260870 -0.3260870
10 -7.9260870 -5.2260870
11 13.7739130 -7.9260870
12 14.7739130 13.7739130
13 2.5739130 14.7739130
14 11.7739130 2.5739130
15 -9.5260870 11.7739130
16 -5.8260870 -9.5260870
17 10.2739130 -5.8260870
18 -2.6260870 10.2739130
19 -7.2260870 -2.6260870
20 15.4739130 -7.2260870
21 -2.6260870 15.4739130
22 -1.3260870 -2.6260870
23 10.9621622 -1.3260870
24 3.6621622 10.9621622
25 2.0621622 3.6621622
26 11.2621622 2.0621622
27 -8.7378378 11.2621622
28 -11.9378378 -8.7378378
29 2.3621622 -11.9378378
30 -6.1378378 2.3621622
31 -6.8378378 -6.1378378
32 2.6621622 -6.8378378
33 -19.9378378 2.6621622
34 -9.7378378 -19.9378378
35 9.8621622 -9.7378378
36 -0.2378378 9.8621622
37 2.3621622 -0.2378378
38 -1.2378378 2.3621622
39 -6.4378378 -1.2378378
40 -5.0378378 -6.4378378
41 13.1621622 -5.0378378
42 -8.3378378 13.1621622
43 1.3621622 -8.3378378
44 6.4621622 1.3621622
45 -15.8378378 6.4621622
46 -4.6378378 -15.8378378
47 10.5621622 -4.6378378
48 12.1621622 10.5621622
49 8.3621622 12.1621622
50 2.0621622 8.3621622
51 -1.7378378 2.0621622
52 -3.8378378 -1.7378378
53 12.2621622 -3.8378378
54 -5.4378378 12.2621622
55 -0.6378378 -5.4378378
56 9.5621622 -0.6378378
57 -4.5378378 9.5621622
58 -4.1378378 -4.5378378
59 4.2621622 -4.1378378
> plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
> lines(lowess(z))
> abline(lm(z))
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/7xtah1198185364.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8zfp91198185364.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9tmxu1198185364.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> load(file='/var/www/html/rcomp/createtable')
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
+ myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ')
+ if (rownames(mysum$coefficients)[i] != '(Intercept)') {
+ myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
+ if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
+ }
+ }
> myeq <- paste(myeq, ' + e[t]')
> a<-table.row.start(a)
> a<-table.element(a, myeq)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/10kn841198185364.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Variable',header=TRUE)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
> a<-table.element(a,'2-tail p-value',header=TRUE)
> a<-table.element(a,'1-tail p-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:k){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
+ a<-table.element(a,mysum$coefficients[i,1])
+ a<-table.element(a, round(mysum$coefficients[i,2],6))
+ a<-table.element(a, round(mysum$coefficients[i,3],4))
+ a<-table.element(a, round(mysum$coefficients[i,4],6))
+ a<-table.element(a, round(mysum$coefficients[i,4]/2,6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/11vcev1198185364.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple R',1,TRUE)
> a<-table.element(a, sqrt(mysum$r.squared))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'R-squared',1,TRUE)
> a<-table.element(a, mysum$r.squared)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Adjusted R-squared',1,TRUE)
> a<-table.element(a, mysum$adj.r.squared)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (value)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[1])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[2])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[3])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'p-value',1,TRUE)
> a<-table.element(a, 1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
> a<-table.element(a, mysum$sigma)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a, sum(myerror*myerror))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/120oom1198185365.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Time or Index', 1, TRUE)
> a<-table.element(a, 'Actuals', 1, TRUE)
> a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
> a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
> a<-table.row.end(a)
> for (i in 1:n) {
+ a<-table.row.start(a)
+ a<-table.element(a,i, 1, TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]-mysum$resid[i])
+ a<-table.element(a,mysum$resid[i])
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/13kpza1198185365.tab")
>
> system("convert tmp/1dgsw1198185364.ps tmp/1dgsw1198185364.png")
> system("convert tmp/2ren01198185364.ps tmp/2ren01198185364.png")
> system("convert tmp/3rulf1198185364.ps tmp/3rulf1198185364.png")
> system("convert tmp/47ufr1198185364.ps tmp/47ufr1198185364.png")
> system("convert tmp/5y03e1198185364.ps tmp/5y03e1198185364.png")
> system("convert tmp/6pkhi1198185364.ps tmp/6pkhi1198185364.png")
> system("convert tmp/7xtah1198185364.ps tmp/7xtah1198185364.png")
> system("convert tmp/8zfp91198185364.ps tmp/8zfp91198185364.png")
> system("convert tmp/9tmxu1198185364.ps tmp/9tmxu1198185364.png")
>
>
> proc.time()
user system elapsed
4.006 2.503 4.341