R version 2.6.0 (2007-10-03)
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(106.5,0,112.3,0,102.8,0,96.5,0,101.0,0,98.9,0,105.1,0,103.0,0,99.0,0,104.3,0,94.6,0,90.4,0,108.9,0,111.4,0,100.8,0,102.5,0,98.2,0,98.7,0,113.3,0,104.6,0,99.3,0,111.8,0,97.3,0,97.7,0,115.6,0,111.9,0,107.0,0,107.1,0,100.6,0,99.2,0,108.4,0,103.0,0,99.8,0,115.0,0,90.8,0,95.9,0,114.4,0,108.2,0,112.6,0,109.1,0,105.0,1,105.0,1,118.5,1,103.7,1,112.5,1,116.6,1,96.6,1,101.9,1,116.5,1,119.3,1,115.4,1,108.5,1,111.5,1,108.8,1,121.8,1,109.6,1,112.2,1,119.6,1,103.4,1,105.3,1,113.5,1),dim=c(2,61),dimnames=list(c('Industriële_productie','x'),1:61))
> y <- array(NA,dim=c(2,61),dimnames=list(c('Industriële_productie','x'),1:61))
> 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
Industri\353le_productie x
1 106.5 0
2 112.3 0
3 102.8 0
4 96.5 0
5 101.0 0
6 98.9 0
7 105.1 0
8 103.0 0
9 99.0 0
10 104.3 0
11 94.6 0
12 90.4 0
13 108.9 0
14 111.4 0
15 100.8 0
16 102.5 0
17 98.2 0
18 98.7 0
19 113.3 0
20 104.6 0
21 99.3 0
22 111.8 0
23 97.3 0
24 97.7 0
25 115.6 0
26 111.9 0
27 107.0 0
28 107.1 0
29 100.6 0
30 99.2 0
31 108.4 0
32 103.0 0
33 99.8 0
34 115.0 0
35 90.8 0
36 95.9 0
37 114.4 0
38 108.2 0
39 112.6 0
40 109.1 0
41 105.0 1
42 105.0 1
43 118.5 1
44 103.7 1
45 112.5 1
46 116.6 1
47 96.6 1
48 101.9 1
49 116.5 1
50 119.3 1
51 115.4 1
52 108.5 1
53 111.5 1
54 108.8 1
55 121.8 1
56 109.6 1
57 112.2 1
58 119.6 1
59 103.4 1
60 105.3 1
61 113.5 1
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) x
103.938 6.786
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-14.1238 -5.2375 -0.9375 5.1625 11.6625
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 103.938 1.065 97.64 < 2e-16 ***
x 6.786 1.814 3.74 0.000418 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 6.733 on 59 degrees of freedom
Multiple R-Squared: 0.1917, Adjusted R-squared: 0.178
F-statistic: 13.99 on 1 and 59 DF, p-value: 0.0004179
> postscript(file="/var/www/html/rcomp/tmp/170jh1198326088.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/2r4nk1198326088.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/3rijb1198326088.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4xebd1198326088.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5zkx91198326088.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
> grid()
> dev.off()
null device
1
> (myerror <- as.ts(mysum$resid))
Time Series:
Start = 1
End = 61
Frequency = 1
1 2 3 4 5 6
2.5625000 8.3625000 -1.1375000 -7.4375000 -2.9375000 -5.0375000
7 8 9 10 11 12
1.1625000 -0.9375000 -4.9375000 0.3625000 -9.3375000 -13.5375000
13 14 15 16 17 18
4.9625000 7.4625000 -3.1375000 -1.4375000 -5.7375000 -5.2375000
19 20 21 22 23 24
9.3625000 0.6625000 -4.6375000 7.8625000 -6.6375000 -6.2375000
25 26 27 28 29 30
11.6625000 7.9625000 3.0625000 3.1625000 -3.3375000 -4.7375000
31 32 33 34 35 36
4.4625000 -0.9375000 -4.1375000 11.0625000 -13.1375000 -8.0375000
37 38 39 40 41 42
10.4625000 4.2625000 8.6625000 5.1625000 -5.7238095 -5.7238095
43 44 45 46 47 48
7.7761905 -7.0238095 1.7761905 5.8761905 -14.1238095 -8.8238095
49 50 51 52 53 54
5.7761905 8.5761905 4.6761905 -2.2238095 0.7761905 -1.9238095
55 56 57 58 59 60
11.0761905 -1.1238095 1.4761905 8.8761905 -7.3238095 -5.4238095
61
2.7761905
> postscript(file="/var/www/html/rcomp/tmp/6busm1198326088.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 = 61
Frequency = 1
lag(myerror, k = 1) myerror
0 2.5625000 NA
1 8.3625000 2.5625000
2 -1.1375000 8.3625000
3 -7.4375000 -1.1375000
4 -2.9375000 -7.4375000
5 -5.0375000 -2.9375000
6 1.1625000 -5.0375000
7 -0.9375000 1.1625000
8 -4.9375000 -0.9375000
9 0.3625000 -4.9375000
10 -9.3375000 0.3625000
11 -13.5375000 -9.3375000
12 4.9625000 -13.5375000
13 7.4625000 4.9625000
14 -3.1375000 7.4625000
15 -1.4375000 -3.1375000
16 -5.7375000 -1.4375000
17 -5.2375000 -5.7375000
18 9.3625000 -5.2375000
19 0.6625000 9.3625000
20 -4.6375000 0.6625000
21 7.8625000 -4.6375000
22 -6.6375000 7.8625000
23 -6.2375000 -6.6375000
24 11.6625000 -6.2375000
25 7.9625000 11.6625000
26 3.0625000 7.9625000
27 3.1625000 3.0625000
28 -3.3375000 3.1625000
29 -4.7375000 -3.3375000
30 4.4625000 -4.7375000
31 -0.9375000 4.4625000
32 -4.1375000 -0.9375000
33 11.0625000 -4.1375000
34 -13.1375000 11.0625000
35 -8.0375000 -13.1375000
36 10.4625000 -8.0375000
37 4.2625000 10.4625000
38 8.6625000 4.2625000
39 5.1625000 8.6625000
40 -5.7238095 5.1625000
41 -5.7238095 -5.7238095
42 7.7761905 -5.7238095
43 -7.0238095 7.7761905
44 1.7761905 -7.0238095
45 5.8761905 1.7761905
46 -14.1238095 5.8761905
47 -8.8238095 -14.1238095
48 5.7761905 -8.8238095
49 8.5761905 5.7761905
50 4.6761905 8.5761905
51 -2.2238095 4.6761905
52 0.7761905 -2.2238095
53 -1.9238095 0.7761905
54 11.0761905 -1.9238095
55 -1.1238095 11.0761905
56 1.4761905 -1.1238095
57 8.8761905 1.4761905
58 -7.3238095 8.8761905
59 -5.4238095 -7.3238095
60 2.7761905 -5.4238095
61 NA 2.7761905
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 8.3625000 2.5625000
[2,] -1.1375000 8.3625000
[3,] -7.4375000 -1.1375000
[4,] -2.9375000 -7.4375000
[5,] -5.0375000 -2.9375000
[6,] 1.1625000 -5.0375000
[7,] -0.9375000 1.1625000
[8,] -4.9375000 -0.9375000
[9,] 0.3625000 -4.9375000
[10,] -9.3375000 0.3625000
[11,] -13.5375000 -9.3375000
[12,] 4.9625000 -13.5375000
[13,] 7.4625000 4.9625000
[14,] -3.1375000 7.4625000
[15,] -1.4375000 -3.1375000
[16,] -5.7375000 -1.4375000
[17,] -5.2375000 -5.7375000
[18,] 9.3625000 -5.2375000
[19,] 0.6625000 9.3625000
[20,] -4.6375000 0.6625000
[21,] 7.8625000 -4.6375000
[22,] -6.6375000 7.8625000
[23,] -6.2375000 -6.6375000
[24,] 11.6625000 -6.2375000
[25,] 7.9625000 11.6625000
[26,] 3.0625000 7.9625000
[27,] 3.1625000 3.0625000
[28,] -3.3375000 3.1625000
[29,] -4.7375000 -3.3375000
[30,] 4.4625000 -4.7375000
[31,] -0.9375000 4.4625000
[32,] -4.1375000 -0.9375000
[33,] 11.0625000 -4.1375000
[34,] -13.1375000 11.0625000
[35,] -8.0375000 -13.1375000
[36,] 10.4625000 -8.0375000
[37,] 4.2625000 10.4625000
[38,] 8.6625000 4.2625000
[39,] 5.1625000 8.6625000
[40,] -5.7238095 5.1625000
[41,] -5.7238095 -5.7238095
[42,] 7.7761905 -5.7238095
[43,] -7.0238095 7.7761905
[44,] 1.7761905 -7.0238095
[45,] 5.8761905 1.7761905
[46,] -14.1238095 5.8761905
[47,] -8.8238095 -14.1238095
[48,] 5.7761905 -8.8238095
[49,] 8.5761905 5.7761905
[50,] 4.6761905 8.5761905
[51,] -2.2238095 4.6761905
[52,] 0.7761905 -2.2238095
[53,] -1.9238095 0.7761905
[54,] 11.0761905 -1.9238095
[55,] -1.1238095 11.0761905
[56,] 1.4761905 -1.1238095
[57,] 8.8761905 1.4761905
[58,] -7.3238095 8.8761905
[59,] -5.4238095 -7.3238095
[60,] 2.7761905 -5.4238095
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 8.3625000 2.5625000
2 -1.1375000 8.3625000
3 -7.4375000 -1.1375000
4 -2.9375000 -7.4375000
5 -5.0375000 -2.9375000
6 1.1625000 -5.0375000
7 -0.9375000 1.1625000
8 -4.9375000 -0.9375000
9 0.3625000 -4.9375000
10 -9.3375000 0.3625000
11 -13.5375000 -9.3375000
12 4.9625000 -13.5375000
13 7.4625000 4.9625000
14 -3.1375000 7.4625000
15 -1.4375000 -3.1375000
16 -5.7375000 -1.4375000
17 -5.2375000 -5.7375000
18 9.3625000 -5.2375000
19 0.6625000 9.3625000
20 -4.6375000 0.6625000
21 7.8625000 -4.6375000
22 -6.6375000 7.8625000
23 -6.2375000 -6.6375000
24 11.6625000 -6.2375000
25 7.9625000 11.6625000
26 3.0625000 7.9625000
27 3.1625000 3.0625000
28 -3.3375000 3.1625000
29 -4.7375000 -3.3375000
30 4.4625000 -4.7375000
31 -0.9375000 4.4625000
32 -4.1375000 -0.9375000
33 11.0625000 -4.1375000
34 -13.1375000 11.0625000
35 -8.0375000 -13.1375000
36 10.4625000 -8.0375000
37 4.2625000 10.4625000
38 8.6625000 4.2625000
39 5.1625000 8.6625000
40 -5.7238095 5.1625000
41 -5.7238095 -5.7238095
42 7.7761905 -5.7238095
43 -7.0238095 7.7761905
44 1.7761905 -7.0238095
45 5.8761905 1.7761905
46 -14.1238095 5.8761905
47 -8.8238095 -14.1238095
48 5.7761905 -8.8238095
49 8.5761905 5.7761905
50 4.6761905 8.5761905
51 -2.2238095 4.6761905
52 0.7761905 -2.2238095
53 -1.9238095 0.7761905
54 11.0761905 -1.9238095
55 -1.1238095 11.0761905
56 1.4761905 -1.1238095
57 8.8761905 1.4761905
58 -7.3238095 8.8761905
59 -5.4238095 -7.3238095
60 2.7761905 -5.4238095
> 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/7os5z1198326088.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8xhem1198326088.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/96sm01198326089.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> load(file='/var/www/html/rcomp/createtable')
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/109fcu1198326089.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/11irpe1198326089.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/1215go1198326089.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/13jusd1198326090.tab")
>
> system("convert tmp/170jh1198326088.ps tmp/170jh1198326088.png")
> system("convert tmp/2r4nk1198326088.ps tmp/2r4nk1198326088.png")
> system("convert tmp/3rijb1198326088.ps tmp/3rijb1198326088.png")
> system("convert tmp/4xebd1198326088.ps tmp/4xebd1198326088.png")
> system("convert tmp/5zkx91198326088.ps tmp/5zkx91198326088.png")
> system("convert tmp/6busm1198326088.ps tmp/6busm1198326088.png")
> system("convert tmp/7os5z1198326088.ps tmp/7os5z1198326088.png")
> system("convert tmp/8xhem1198326088.ps tmp/8xhem1198326088.png")
> system("convert tmp/96sm01198326089.ps tmp/96sm01198326089.png")
>
>
> proc.time()
user system elapsed
2.229 1.456 2.898