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(332,0,0,182,0,0,-303,0,0,-443,0,0,908,0,0,4011,1,0,-2862,0,1,-1126,0,0,-50,0,0,3012,1,0,434,0,0,-273,0,0,-439,0,0,-1203,0,0,137,0,0,-102,0,0,1152,0,0,260,0,0,-1150,0,0,-299,0,0,-922,0,0,-1509,0,0,1152,0,0,-3,0,0,156,0,0,-1131,0,0,-1033,0,0,-130,0,0,-599,0,0,-1633,0,0,527,0,0,112,0,0,-895,0,0,669,0,0,-2126,0,1,-1779,0,0,-129,0,0,1922,0,0,674,0,0,185,0,0,-788,0,0,-696,0,0,-748,0,0,893,0,0,458,0,0,-78,0,0,-280,0,0,-1865,0,0,788,0,0,-916,0,0,1286,0,0,883,0,0,193,0,0,-2527,0,1,-1792,0,0,370,0,0,-2952,0,1,-403,0,0,-1478,0,0),dim=c(3,59),dimnames=list(c('X','Y','Z'),1:59))
> y <- array(NA,dim=c(3,59),dimnames=list(c('X','Y','Z'),1:59))
> 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
X Y Z
1 332 0 0
2 182 0 0
3 -303 0 0
4 -443 0 0
5 908 0 0
6 4011 1 0
7 -2862 0 1
8 -1126 0 0
9 -50 0 0
10 3012 1 0
11 434 0 0
12 -273 0 0
13 -439 0 0
14 -1203 0 0
15 137 0 0
16 -102 0 0
17 1152 0 0
18 260 0 0
19 -1150 0 0
20 -299 0 0
21 -922 0 0
22 -1509 0 0
23 1152 0 0
24 -3 0 0
25 156 0 0
26 -1131 0 0
27 -1033 0 0
28 -130 0 0
29 -599 0 0
30 -1633 0 0
31 527 0 0
32 112 0 0
33 -895 0 0
34 669 0 0
35 -2126 0 1
36 -1779 0 0
37 -129 0 0
38 1922 0 0
39 674 0 0
40 185 0 0
41 -788 0 0
42 -696 0 0
43 -748 0 0
44 893 0 0
45 458 0 0
46 -78 0 0
47 -280 0 0
48 -1865 0 0
49 788 0 0
50 -916 0 0
51 1286 0 0
52 883 0 0
53 193 0 0
54 -2527 0 1
55 -1792 0 0
56 370 0 0
57 -2952 0 1
58 -403 0 0
59 -1478 0 0
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Y Z
-198.5 3710.0 -2418.2
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-1666.47 -569.47 69.53 515.01 2120.53
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -198.5 117.1 -1.695 0.0957 .
Y 3710.0 614.3 6.040 1.31e-07 ***
Z -2418.2 442.2 -5.469 1.09e-06 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 852.8 on 56 degrees of freedom
Multiple R-Squared: 0.5552, Adjusted R-squared: 0.5393
F-statistic: 34.95 on 2 and 56 DF, p-value: 1.409e-10
> postscript(file="/var/www/html/rcomp/tmp/16o971200412749.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/2huca1200412749.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/34lo61200412749.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4amp21200412749.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5cp6y1200412749.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
> grid()
> dev.off()
null device
1
> (myerror <- as.ts(mysum$resid))
Time Series:
Start = 1
End = 59
Frequency = 1
1 2 3 4 5 6 7
530.5283 380.5283 -104.4717 -244.4717 1106.5283 499.5000 -245.2500
8 9 10 11 12 13 14
-927.4717 148.5283 -499.5000 632.5283 -74.4717 -240.4717 -1004.4717
15 16 17 18 19 20 21
335.5283 96.5283 1350.5283 458.5283 -951.4717 -100.4717 -723.4717
22 23 24 25 26 27 28
-1310.4717 1350.5283 195.5283 354.5283 -932.4717 -834.4717 68.5283
29 30 31 32 33 34 35
-400.4717 -1434.4717 725.5283 310.5283 -696.4717 867.5283 490.7500
36 37 38 39 40 41 42
-1580.4717 69.5283 2120.5283 872.5283 383.5283 -589.4717 -497.4717
43 44 45 46 47 48 49
-549.4717 1091.5283 656.5283 120.5283 -81.4717 -1666.4717 986.5283
50 51 52 53 54 55 56
-717.4717 1484.5283 1081.5283 391.5283 89.7500 -1593.4717 568.5283
57 58 59
-335.2500 -204.4717 -1279.4717
> postscript(file="/var/www/html/rcomp/tmp/62u531200412749.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 = 59
Frequency = 1
lag(myerror, k = 1) myerror
0 530.5283 NA
1 380.5283 530.5283
2 -104.4717 380.5283
3 -244.4717 -104.4717
4 1106.5283 -244.4717
5 499.5000 1106.5283
6 -245.2500 499.5000
7 -927.4717 -245.2500
8 148.5283 -927.4717
9 -499.5000 148.5283
10 632.5283 -499.5000
11 -74.4717 632.5283
12 -240.4717 -74.4717
13 -1004.4717 -240.4717
14 335.5283 -1004.4717
15 96.5283 335.5283
16 1350.5283 96.5283
17 458.5283 1350.5283
18 -951.4717 458.5283
19 -100.4717 -951.4717
20 -723.4717 -100.4717
21 -1310.4717 -723.4717
22 1350.5283 -1310.4717
23 195.5283 1350.5283
24 354.5283 195.5283
25 -932.4717 354.5283
26 -834.4717 -932.4717
27 68.5283 -834.4717
28 -400.4717 68.5283
29 -1434.4717 -400.4717
30 725.5283 -1434.4717
31 310.5283 725.5283
32 -696.4717 310.5283
33 867.5283 -696.4717
34 490.7500 867.5283
35 -1580.4717 490.7500
36 69.5283 -1580.4717
37 2120.5283 69.5283
38 872.5283 2120.5283
39 383.5283 872.5283
40 -589.4717 383.5283
41 -497.4717 -589.4717
42 -549.4717 -497.4717
43 1091.5283 -549.4717
44 656.5283 1091.5283
45 120.5283 656.5283
46 -81.4717 120.5283
47 -1666.4717 -81.4717
48 986.5283 -1666.4717
49 -717.4717 986.5283
50 1484.5283 -717.4717
51 1081.5283 1484.5283
52 391.5283 1081.5283
53 89.7500 391.5283
54 -1593.4717 89.7500
55 568.5283 -1593.4717
56 -335.2500 568.5283
57 -204.4717 -335.2500
58 -1279.4717 -204.4717
59 NA -1279.4717
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 380.5283 530.5283
[2,] -104.4717 380.5283
[3,] -244.4717 -104.4717
[4,] 1106.5283 -244.4717
[5,] 499.5000 1106.5283
[6,] -245.2500 499.5000
[7,] -927.4717 -245.2500
[8,] 148.5283 -927.4717
[9,] -499.5000 148.5283
[10,] 632.5283 -499.5000
[11,] -74.4717 632.5283
[12,] -240.4717 -74.4717
[13,] -1004.4717 -240.4717
[14,] 335.5283 -1004.4717
[15,] 96.5283 335.5283
[16,] 1350.5283 96.5283
[17,] 458.5283 1350.5283
[18,] -951.4717 458.5283
[19,] -100.4717 -951.4717
[20,] -723.4717 -100.4717
[21,] -1310.4717 -723.4717
[22,] 1350.5283 -1310.4717
[23,] 195.5283 1350.5283
[24,] 354.5283 195.5283
[25,] -932.4717 354.5283
[26,] -834.4717 -932.4717
[27,] 68.5283 -834.4717
[28,] -400.4717 68.5283
[29,] -1434.4717 -400.4717
[30,] 725.5283 -1434.4717
[31,] 310.5283 725.5283
[32,] -696.4717 310.5283
[33,] 867.5283 -696.4717
[34,] 490.7500 867.5283
[35,] -1580.4717 490.7500
[36,] 69.5283 -1580.4717
[37,] 2120.5283 69.5283
[38,] 872.5283 2120.5283
[39,] 383.5283 872.5283
[40,] -589.4717 383.5283
[41,] -497.4717 -589.4717
[42,] -549.4717 -497.4717
[43,] 1091.5283 -549.4717
[44,] 656.5283 1091.5283
[45,] 120.5283 656.5283
[46,] -81.4717 120.5283
[47,] -1666.4717 -81.4717
[48,] 986.5283 -1666.4717
[49,] -717.4717 986.5283
[50,] 1484.5283 -717.4717
[51,] 1081.5283 1484.5283
[52,] 391.5283 1081.5283
[53,] 89.7500 391.5283
[54,] -1593.4717 89.7500
[55,] 568.5283 -1593.4717
[56,] -335.2500 568.5283
[57,] -204.4717 -335.2500
[58,] -1279.4717 -204.4717
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 380.5283 530.5283
2 -104.4717 380.5283
3 -244.4717 -104.4717
4 1106.5283 -244.4717
5 499.5000 1106.5283
6 -245.2500 499.5000
7 -927.4717 -245.2500
8 148.5283 -927.4717
9 -499.5000 148.5283
10 632.5283 -499.5000
11 -74.4717 632.5283
12 -240.4717 -74.4717
13 -1004.4717 -240.4717
14 335.5283 -1004.4717
15 96.5283 335.5283
16 1350.5283 96.5283
17 458.5283 1350.5283
18 -951.4717 458.5283
19 -100.4717 -951.4717
20 -723.4717 -100.4717
21 -1310.4717 -723.4717
22 1350.5283 -1310.4717
23 195.5283 1350.5283
24 354.5283 195.5283
25 -932.4717 354.5283
26 -834.4717 -932.4717
27 68.5283 -834.4717
28 -400.4717 68.5283
29 -1434.4717 -400.4717
30 725.5283 -1434.4717
31 310.5283 725.5283
32 -696.4717 310.5283
33 867.5283 -696.4717
34 490.7500 867.5283
35 -1580.4717 490.7500
36 69.5283 -1580.4717
37 2120.5283 69.5283
38 872.5283 2120.5283
39 383.5283 872.5283
40 -589.4717 383.5283
41 -497.4717 -589.4717
42 -549.4717 -497.4717
43 1091.5283 -549.4717
44 656.5283 1091.5283
45 120.5283 656.5283
46 -81.4717 120.5283
47 -1666.4717 -81.4717
48 986.5283 -1666.4717
49 -717.4717 986.5283
50 1484.5283 -717.4717
51 1081.5283 1484.5283
52 391.5283 1081.5283
53 89.7500 391.5283
54 -1593.4717 89.7500
55 568.5283 -1593.4717
56 -335.2500 568.5283
57 -204.4717 -335.2500
58 -1279.4717 -204.4717
> 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/7lepb1200412749.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8mc5s1200412749.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9yiqf1200412749.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> load(file='/var/www/html/rcomp/createtable')
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/1096kz1200412749.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/11jnsa1200412749.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/12e4md1200412749.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/13xltg1200412749.tab")
>
> system("convert tmp/16o971200412749.ps tmp/16o971200412749.png")
> system("convert tmp/2huca1200412749.ps tmp/2huca1200412749.png")
> system("convert tmp/34lo61200412749.ps tmp/34lo61200412749.png")
> system("convert tmp/4amp21200412749.ps tmp/4amp21200412749.png")
> system("convert tmp/5cp6y1200412749.ps tmp/5cp6y1200412749.png")
> system("convert tmp/62u531200412749.ps tmp/62u531200412749.png")
> system("convert tmp/7lepb1200412749.ps tmp/7lepb1200412749.png")
> system("convert tmp/8mc5s1200412749.ps tmp/8mc5s1200412749.png")
> system("convert tmp/9yiqf1200412749.ps tmp/9yiqf1200412749.png")
>
>
> proc.time()
user system elapsed
2.290 1.513 2.747