R version 2.6.0 (2007-10-03)
Copyright (C) 2007 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
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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
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> x <- array(list(106.8,0,113.7,0,102.5,0,96.6,0,92.1,0,95.6,0,102.3,0,98.6,0,98.2,0,104.5,0,84,0,73.8,0,103.9,0,106,0,97.2,0,102.6,0,89,0,93.8,0,116.7,0,106.8,0,98.5,0,118.7,0,90,0,91.9,0,113.3,0,113.1,1,104.1,1,108.7,1,96.7,1,101,1,116.9,1,105.8,1,99,1,129.4,1,83,1,88.9,1,115.9,1,104.2,1,113.4,1,112.2,1,100.8,1,107.3,1,126.6,1,102.9,1,117.9,1,128.8,1,87.5,1,93.8,1,122.7,1,126.2,1,124.6,1,116.7,1,115.2,1,111.1,1,129.9,1,113.3,1,118.5,1,133.5,1,102.1,1,102.4,1),dim=c(2,60),dimnames=list(c('totmetaal','ramp'),1:60))
> y <- array(NA,dim=c(2,60),dimnames=list(c('totmetaal','ramp'),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
totmetaal ramp
1 106.8 0
2 113.7 0
3 102.5 0
4 96.6 0
5 92.1 0
6 95.6 0
7 102.3 0
8 98.6 0
9 98.2 0
10 104.5 0
11 84.0 0
12 73.8 0
13 103.9 0
14 106.0 0
15 97.2 0
16 102.6 0
17 89.0 0
18 93.8 0
19 116.7 0
20 106.8 0
21 98.5 0
22 118.7 0
23 90.0 0
24 91.9 0
25 113.3 0
26 113.1 1
27 104.1 1
28 108.7 1
29 96.7 1
30 101.0 1
31 116.9 1
32 105.8 1
33 99.0 1
34 129.4 1
35 83.0 1
36 88.9 1
37 115.9 1
38 104.2 1
39 113.4 1
40 112.2 1
41 100.8 1
42 107.3 1
43 126.6 1
44 102.9 1
45 117.9 1
46 128.8 1
47 87.5 1
48 93.8 1
49 122.7 1
50 126.2 1
51 124.6 1
52 116.7 1
53 115.2 1
54 111.1 1
55 129.9 1
56 113.3 1
57 118.5 1
58 133.5 1
59 102.1 1
60 102.4 1
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) ramp
99.88 10.80
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-27.6886 -7.8374 0.9614 6.9160 22.8114
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 99.884 2.367 42.198 < 2e-16 ***
ramp 10.805 3.099 3.486 0.00094 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 11.84 on 58 degrees of freedom
Multiple R-Squared: 0.1732, Adjusted R-squared: 0.159
F-statistic: 12.15 on 1 and 58 DF, p-value: 0.0009405
> postscript(file="/var/www/html/rcomp/tmp/16mv81195468985.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/2cvt01195468985.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/3v5dn1195468985.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4m6un1195468985.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5wwev1195468985.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$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
6.9160000 13.8160000 2.6160000 -3.2840000 -7.7840000 -4.2840000
7 8 9 10 11 12
2.4160000 -1.2840000 -1.6840000 4.6160000 -15.8840000 -26.0840000
13 14 15 16 17 18
4.0160000 6.1160000 -2.6840000 2.7160000 -10.8840000 -6.0840000
19 20 21 22 23 24
16.8160000 6.9160000 -1.3840000 18.8160000 -9.8840000 -7.9840000
25 26 27 28 29 30
13.4160000 2.4114286 -6.5885714 -1.9885714 -13.9885714 -9.6885714
31 32 33 34 35 36
6.2114286 -4.8885714 -11.6885714 18.7114286 -27.6885714 -21.7885714
37 38 39 40 41 42
5.2114286 -6.4885714 2.7114286 1.5114286 -9.8885714 -3.3885714
43 44 45 46 47 48
15.9114286 -7.7885714 7.2114286 18.1114286 -23.1885714 -16.8885714
49 50 51 52 53 54
12.0114286 15.5114286 13.9114286 6.0114286 4.5114286 0.4114286
55 56 57 58 59 60
19.2114286 2.6114286 7.8114286 22.8114286 -8.5885714 -8.2885714
> postscript(file="/var/www/html/rcomp/tmp/6vvz71195468985.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 6.9160000 NA
1 13.8160000 6.9160000
2 2.6160000 13.8160000
3 -3.2840000 2.6160000
4 -7.7840000 -3.2840000
5 -4.2840000 -7.7840000
6 2.4160000 -4.2840000
7 -1.2840000 2.4160000
8 -1.6840000 -1.2840000
9 4.6160000 -1.6840000
10 -15.8840000 4.6160000
11 -26.0840000 -15.8840000
12 4.0160000 -26.0840000
13 6.1160000 4.0160000
14 -2.6840000 6.1160000
15 2.7160000 -2.6840000
16 -10.8840000 2.7160000
17 -6.0840000 -10.8840000
18 16.8160000 -6.0840000
19 6.9160000 16.8160000
20 -1.3840000 6.9160000
21 18.8160000 -1.3840000
22 -9.8840000 18.8160000
23 -7.9840000 -9.8840000
24 13.4160000 -7.9840000
25 2.4114286 13.4160000
26 -6.5885714 2.4114286
27 -1.9885714 -6.5885714
28 -13.9885714 -1.9885714
29 -9.6885714 -13.9885714
30 6.2114286 -9.6885714
31 -4.8885714 6.2114286
32 -11.6885714 -4.8885714
33 18.7114286 -11.6885714
34 -27.6885714 18.7114286
35 -21.7885714 -27.6885714
36 5.2114286 -21.7885714
37 -6.4885714 5.2114286
38 2.7114286 -6.4885714
39 1.5114286 2.7114286
40 -9.8885714 1.5114286
41 -3.3885714 -9.8885714
42 15.9114286 -3.3885714
43 -7.7885714 15.9114286
44 7.2114286 -7.7885714
45 18.1114286 7.2114286
46 -23.1885714 18.1114286
47 -16.8885714 -23.1885714
48 12.0114286 -16.8885714
49 15.5114286 12.0114286
50 13.9114286 15.5114286
51 6.0114286 13.9114286
52 4.5114286 6.0114286
53 0.4114286 4.5114286
54 19.2114286 0.4114286
55 2.6114286 19.2114286
56 7.8114286 2.6114286
57 22.8114286 7.8114286
58 -8.5885714 22.8114286
59 -8.2885714 -8.5885714
60 NA -8.2885714
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 13.8160000 6.9160000
[2,] 2.6160000 13.8160000
[3,] -3.2840000 2.6160000
[4,] -7.7840000 -3.2840000
[5,] -4.2840000 -7.7840000
[6,] 2.4160000 -4.2840000
[7,] -1.2840000 2.4160000
[8,] -1.6840000 -1.2840000
[9,] 4.6160000 -1.6840000
[10,] -15.8840000 4.6160000
[11,] -26.0840000 -15.8840000
[12,] 4.0160000 -26.0840000
[13,] 6.1160000 4.0160000
[14,] -2.6840000 6.1160000
[15,] 2.7160000 -2.6840000
[16,] -10.8840000 2.7160000
[17,] -6.0840000 -10.8840000
[18,] 16.8160000 -6.0840000
[19,] 6.9160000 16.8160000
[20,] -1.3840000 6.9160000
[21,] 18.8160000 -1.3840000
[22,] -9.8840000 18.8160000
[23,] -7.9840000 -9.8840000
[24,] 13.4160000 -7.9840000
[25,] 2.4114286 13.4160000
[26,] -6.5885714 2.4114286
[27,] -1.9885714 -6.5885714
[28,] -13.9885714 -1.9885714
[29,] -9.6885714 -13.9885714
[30,] 6.2114286 -9.6885714
[31,] -4.8885714 6.2114286
[32,] -11.6885714 -4.8885714
[33,] 18.7114286 -11.6885714
[34,] -27.6885714 18.7114286
[35,] -21.7885714 -27.6885714
[36,] 5.2114286 -21.7885714
[37,] -6.4885714 5.2114286
[38,] 2.7114286 -6.4885714
[39,] 1.5114286 2.7114286
[40,] -9.8885714 1.5114286
[41,] -3.3885714 -9.8885714
[42,] 15.9114286 -3.3885714
[43,] -7.7885714 15.9114286
[44,] 7.2114286 -7.7885714
[45,] 18.1114286 7.2114286
[46,] -23.1885714 18.1114286
[47,] -16.8885714 -23.1885714
[48,] 12.0114286 -16.8885714
[49,] 15.5114286 12.0114286
[50,] 13.9114286 15.5114286
[51,] 6.0114286 13.9114286
[52,] 4.5114286 6.0114286
[53,] 0.4114286 4.5114286
[54,] 19.2114286 0.4114286
[55,] 2.6114286 19.2114286
[56,] 7.8114286 2.6114286
[57,] 22.8114286 7.8114286
[58,] -8.5885714 22.8114286
[59,] -8.2885714 -8.5885714
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 13.8160000 6.9160000
2 2.6160000 13.8160000
3 -3.2840000 2.6160000
4 -7.7840000 -3.2840000
5 -4.2840000 -7.7840000
6 2.4160000 -4.2840000
7 -1.2840000 2.4160000
8 -1.6840000 -1.2840000
9 4.6160000 -1.6840000
10 -15.8840000 4.6160000
11 -26.0840000 -15.8840000
12 4.0160000 -26.0840000
13 6.1160000 4.0160000
14 -2.6840000 6.1160000
15 2.7160000 -2.6840000
16 -10.8840000 2.7160000
17 -6.0840000 -10.8840000
18 16.8160000 -6.0840000
19 6.9160000 16.8160000
20 -1.3840000 6.9160000
21 18.8160000 -1.3840000
22 -9.8840000 18.8160000
23 -7.9840000 -9.8840000
24 13.4160000 -7.9840000
25 2.4114286 13.4160000
26 -6.5885714 2.4114286
27 -1.9885714 -6.5885714
28 -13.9885714 -1.9885714
29 -9.6885714 -13.9885714
30 6.2114286 -9.6885714
31 -4.8885714 6.2114286
32 -11.6885714 -4.8885714
33 18.7114286 -11.6885714
34 -27.6885714 18.7114286
35 -21.7885714 -27.6885714
36 5.2114286 -21.7885714
37 -6.4885714 5.2114286
38 2.7114286 -6.4885714
39 1.5114286 2.7114286
40 -9.8885714 1.5114286
41 -3.3885714 -9.8885714
42 15.9114286 -3.3885714
43 -7.7885714 15.9114286
44 7.2114286 -7.7885714
45 18.1114286 7.2114286
46 -23.1885714 18.1114286
47 -16.8885714 -23.1885714
48 12.0114286 -16.8885714
49 15.5114286 12.0114286
50 13.9114286 15.5114286
51 6.0114286 13.9114286
52 4.5114286 6.0114286
53 0.4114286 4.5114286
54 19.2114286 0.4114286
55 2.6114286 19.2114286
56 7.8114286 2.6114286
57 22.8114286 7.8114286
58 -8.5885714 22.8114286
59 -8.2885714 -8.5885714
> 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/7t2in1195468985.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8lxmv1195468985.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9ko911195468985.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> load(file='/var/www/html/rcomp/createtable')
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/1012a71195468985.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/11buhk1195468985.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/12h19u1195468986.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/13h9uc1195468986.tab")
>
> system("convert tmp/16mv81195468985.ps tmp/16mv81195468985.png")
> system("convert tmp/2cvt01195468985.ps tmp/2cvt01195468985.png")
> system("convert tmp/3v5dn1195468985.ps tmp/3v5dn1195468985.png")
> system("convert tmp/4m6un1195468985.ps tmp/4m6un1195468985.png")
> system("convert tmp/5wwev1195468985.ps tmp/5wwev1195468985.png")
> system("convert tmp/6vvz71195468985.ps tmp/6vvz71195468985.png")
> system("convert tmp/7t2in1195468985.ps tmp/7t2in1195468985.png")
> system("convert tmp/8lxmv1195468985.ps tmp/8lxmv1195468985.png")
> system("convert tmp/9ko911195468985.ps tmp/9ko911195468985.png")
>
>
> proc.time()
user system elapsed
2.225 1.423 2.594