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.
Natural language support but running in an English locale
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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(120.3,0,133.4,0,109.4,0,93.2,0,91.2,0,99.2,0,108.2,0,101.5,0,106.9,0,104.4,0,77.9,0,60,0,99.5,0,95,0,105.6,0,102.5,0,93.3,0,97.3,0,127,0,111.7,0,96.4,0,133,0,72.2,0,95.8,0,124.1,0,127.6,0,110.7,0,104.6,0,112.7,0,115.3,0,139.4,0,119,0,97.4,0,154,0,81.5,0,88.8,0,127.7,1,105.1,1,114.9,1,106.4,1,104.5,1,121.6,1,141.4,1,99,1,126.7,1,134.1,1,81.3,1,88.6,1,132.7,1,132.9,1,134.4,1,103.7,1,119.7,1,115,1,132.9,1,108.5,1,113.9,1,142.9,1,95.2,1,93,1),dim=c(2,60),dimnames=list(c('Y','X'),1:60))
> y <- array(NA,dim=c(2,60),dimnames=list(c('Y','X'),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
Y X
1 120.3 0
2 133.4 0
3 109.4 0
4 93.2 0
5 91.2 0
6 99.2 0
7 108.2 0
8 101.5 0
9 106.9 0
10 104.4 0
11 77.9 0
12 60.0 0
13 99.5 0
14 95.0 0
15 105.6 0
16 102.5 0
17 93.3 0
18 97.3 0
19 127.0 0
20 111.7 0
21 96.4 0
22 133.0 0
23 72.2 0
24 95.8 0
25 124.1 0
26 127.6 0
27 110.7 0
28 104.6 0
29 112.7 0
30 115.3 0
31 139.4 0
32 119.0 0
33 97.4 0
34 154.0 0
35 81.5 0
36 88.8 0
37 127.7 1
38 105.1 1
39 114.9 1
40 106.4 1
41 104.5 1
42 121.6 1
43 141.4 1
44 99.0 1
45 126.7 1
46 134.1 1
47 81.3 1
48 88.6 1
49 132.7 1
50 132.9 1
51 134.4 1
52 103.7 1
53 119.7 1
54 115.0 1
55 132.9 1
56 108.5 1
57 113.9 1
58 142.9 1
59 95.2 1
60 93.0 1
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X
105.833 9.838
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-45.833 -10.918 -1.002 13.492 48.167
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 105.833 3.074 34.427 <2e-16 ***
X 9.838 4.861 2.024 0.0476 *
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 18.45 on 58 degrees of freedom
Multiple R-Squared: 0.06596, Adjusted R-squared: 0.04986
F-statistic: 4.096 on 1 and 58 DF, p-value: 0.0476
> postscript(file="/var/www/html/rcomp/tmp/1vk5e1195125119.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/2vvb81195125119.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/39f8l1195125119.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/459s31195125119.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5nd011195125119.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$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
14.4666667 27.5666667 3.5666667 -12.6333333 -14.6333333 -6.6333333
7 8 9 10 11 12
2.3666667 -4.3333333 1.0666667 -1.4333333 -27.9333333 -45.8333333
13 14 15 16 17 18
-6.3333333 -10.8333333 -0.2333333 -3.3333333 -12.5333333 -8.5333333
19 20 21 22 23 24
21.1666667 5.8666667 -9.4333333 27.1666667 -33.6333333 -10.0333333
25 26 27 28 29 30
18.2666667 21.7666667 4.8666667 -1.2333333 6.8666667 9.4666667
31 32 33 34 35 36
33.5666667 13.1666667 -8.4333333 48.1666667 -24.3333333 -17.0333333
37 38 39 40 41 42
12.0291667 -10.5708333 -0.7708333 -9.2708333 -11.1708333 5.9291667
43 44 45 46 47 48
25.7291667 -16.6708333 11.0291667 18.4291667 -34.3708333 -27.0708333
49 50 51 52 53 54
17.0291667 17.2291667 18.7291667 -11.9708333 4.0291667 -0.6708333
55 56 57 58 59 60
17.2291667 -7.1708333 -1.7708333 27.2291667 -20.4708333 -22.6708333
> postscript(file="/var/www/html/rcomp/tmp/60ou81195125119.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 14.4666667 NA
1 27.5666667 14.4666667
2 3.5666667 27.5666667
3 -12.6333333 3.5666667
4 -14.6333333 -12.6333333
5 -6.6333333 -14.6333333
6 2.3666667 -6.6333333
7 -4.3333333 2.3666667
8 1.0666667 -4.3333333
9 -1.4333333 1.0666667
10 -27.9333333 -1.4333333
11 -45.8333333 -27.9333333
12 -6.3333333 -45.8333333
13 -10.8333333 -6.3333333
14 -0.2333333 -10.8333333
15 -3.3333333 -0.2333333
16 -12.5333333 -3.3333333
17 -8.5333333 -12.5333333
18 21.1666667 -8.5333333
19 5.8666667 21.1666667
20 -9.4333333 5.8666667
21 27.1666667 -9.4333333
22 -33.6333333 27.1666667
23 -10.0333333 -33.6333333
24 18.2666667 -10.0333333
25 21.7666667 18.2666667
26 4.8666667 21.7666667
27 -1.2333333 4.8666667
28 6.8666667 -1.2333333
29 9.4666667 6.8666667
30 33.5666667 9.4666667
31 13.1666667 33.5666667
32 -8.4333333 13.1666667
33 48.1666667 -8.4333333
34 -24.3333333 48.1666667
35 -17.0333333 -24.3333333
36 12.0291667 -17.0333333
37 -10.5708333 12.0291667
38 -0.7708333 -10.5708333
39 -9.2708333 -0.7708333
40 -11.1708333 -9.2708333
41 5.9291667 -11.1708333
42 25.7291667 5.9291667
43 -16.6708333 25.7291667
44 11.0291667 -16.6708333
45 18.4291667 11.0291667
46 -34.3708333 18.4291667
47 -27.0708333 -34.3708333
48 17.0291667 -27.0708333
49 17.2291667 17.0291667
50 18.7291667 17.2291667
51 -11.9708333 18.7291667
52 4.0291667 -11.9708333
53 -0.6708333 4.0291667
54 17.2291667 -0.6708333
55 -7.1708333 17.2291667
56 -1.7708333 -7.1708333
57 27.2291667 -1.7708333
58 -20.4708333 27.2291667
59 -22.6708333 -20.4708333
60 NA -22.6708333
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 27.5666667 14.4666667
[2,] 3.5666667 27.5666667
[3,] -12.6333333 3.5666667
[4,] -14.6333333 -12.6333333
[5,] -6.6333333 -14.6333333
[6,] 2.3666667 -6.6333333
[7,] -4.3333333 2.3666667
[8,] 1.0666667 -4.3333333
[9,] -1.4333333 1.0666667
[10,] -27.9333333 -1.4333333
[11,] -45.8333333 -27.9333333
[12,] -6.3333333 -45.8333333
[13,] -10.8333333 -6.3333333
[14,] -0.2333333 -10.8333333
[15,] -3.3333333 -0.2333333
[16,] -12.5333333 -3.3333333
[17,] -8.5333333 -12.5333333
[18,] 21.1666667 -8.5333333
[19,] 5.8666667 21.1666667
[20,] -9.4333333 5.8666667
[21,] 27.1666667 -9.4333333
[22,] -33.6333333 27.1666667
[23,] -10.0333333 -33.6333333
[24,] 18.2666667 -10.0333333
[25,] 21.7666667 18.2666667
[26,] 4.8666667 21.7666667
[27,] -1.2333333 4.8666667
[28,] 6.8666667 -1.2333333
[29,] 9.4666667 6.8666667
[30,] 33.5666667 9.4666667
[31,] 13.1666667 33.5666667
[32,] -8.4333333 13.1666667
[33,] 48.1666667 -8.4333333
[34,] -24.3333333 48.1666667
[35,] -17.0333333 -24.3333333
[36,] 12.0291667 -17.0333333
[37,] -10.5708333 12.0291667
[38,] -0.7708333 -10.5708333
[39,] -9.2708333 -0.7708333
[40,] -11.1708333 -9.2708333
[41,] 5.9291667 -11.1708333
[42,] 25.7291667 5.9291667
[43,] -16.6708333 25.7291667
[44,] 11.0291667 -16.6708333
[45,] 18.4291667 11.0291667
[46,] -34.3708333 18.4291667
[47,] -27.0708333 -34.3708333
[48,] 17.0291667 -27.0708333
[49,] 17.2291667 17.0291667
[50,] 18.7291667 17.2291667
[51,] -11.9708333 18.7291667
[52,] 4.0291667 -11.9708333
[53,] -0.6708333 4.0291667
[54,] 17.2291667 -0.6708333
[55,] -7.1708333 17.2291667
[56,] -1.7708333 -7.1708333
[57,] 27.2291667 -1.7708333
[58,] -20.4708333 27.2291667
[59,] -22.6708333 -20.4708333
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 27.5666667 14.4666667
2 3.5666667 27.5666667
3 -12.6333333 3.5666667
4 -14.6333333 -12.6333333
5 -6.6333333 -14.6333333
6 2.3666667 -6.6333333
7 -4.3333333 2.3666667
8 1.0666667 -4.3333333
9 -1.4333333 1.0666667
10 -27.9333333 -1.4333333
11 -45.8333333 -27.9333333
12 -6.3333333 -45.8333333
13 -10.8333333 -6.3333333
14 -0.2333333 -10.8333333
15 -3.3333333 -0.2333333
16 -12.5333333 -3.3333333
17 -8.5333333 -12.5333333
18 21.1666667 -8.5333333
19 5.8666667 21.1666667
20 -9.4333333 5.8666667
21 27.1666667 -9.4333333
22 -33.6333333 27.1666667
23 -10.0333333 -33.6333333
24 18.2666667 -10.0333333
25 21.7666667 18.2666667
26 4.8666667 21.7666667
27 -1.2333333 4.8666667
28 6.8666667 -1.2333333
29 9.4666667 6.8666667
30 33.5666667 9.4666667
31 13.1666667 33.5666667
32 -8.4333333 13.1666667
33 48.1666667 -8.4333333
34 -24.3333333 48.1666667
35 -17.0333333 -24.3333333
36 12.0291667 -17.0333333
37 -10.5708333 12.0291667
38 -0.7708333 -10.5708333
39 -9.2708333 -0.7708333
40 -11.1708333 -9.2708333
41 5.9291667 -11.1708333
42 25.7291667 5.9291667
43 -16.6708333 25.7291667
44 11.0291667 -16.6708333
45 18.4291667 11.0291667
46 -34.3708333 18.4291667
47 -27.0708333 -34.3708333
48 17.0291667 -27.0708333
49 17.2291667 17.0291667
50 18.7291667 17.2291667
51 -11.9708333 18.7291667
52 4.0291667 -11.9708333
53 -0.6708333 4.0291667
54 17.2291667 -0.6708333
55 -7.1708333 17.2291667
56 -1.7708333 -7.1708333
57 27.2291667 -1.7708333
58 -20.4708333 27.2291667
59 -22.6708333 -20.4708333
> 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/7o6131195125119.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8i2jr1195125119.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9a96i1195125119.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> load(file='/var/www/html/rcomp/createtable')
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/10nhrx1195125119.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/11k0b51195125119.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/12dl3h1195125119.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/13sv8g1195125119.tab")
>
> system("convert tmp/1vk5e1195125119.ps tmp/1vk5e1195125119.png")
> system("convert tmp/2vvb81195125119.ps tmp/2vvb81195125119.png")
> system("convert tmp/39f8l1195125119.ps tmp/39f8l1195125119.png")
> system("convert tmp/459s31195125119.ps tmp/459s31195125119.png")
> system("convert tmp/5nd011195125119.ps tmp/5nd011195125119.png")
> system("convert tmp/60ou81195125119.ps tmp/60ou81195125119.png")
> system("convert tmp/7o6131195125119.ps tmp/7o6131195125119.png")
> system("convert tmp/8i2jr1195125119.ps tmp/8i2jr1195125119.png")
> system("convert tmp/9a96i1195125119.ps tmp/9a96i1195125119.png")
>
>
> proc.time()
user system elapsed
7.042 4.186 14.756