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 'demo()' for some demos, 'help()' for on-line help, or
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> x <- array(list(588261,1,596397,1,576612,0,538141,0,491481,0,469740,0,474427,0,507632,0,541047,0,570046,0,588251,0,596872,0,588676,0,549738,0,472907,0,429496,0,402790,0,419304,0,459425,0,500845,0,516761,0,557423,0,595042,0,589496,0,535029,0),dim=c(2,25),dimnames=list(c('y','x'),1:25))
> y <- array(NA,dim=c(2,25),dimnames=list(c('y','x'),1:25))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par3 = '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 t
1 588261 1 1
2 596397 1 2
3 576612 0 3
4 538141 0 4
5 491481 0 5
6 469740 0 6
7 474427 0 7
8 507632 0 8
9 541047 0 9
10 570046 0 10
11 588251 0 11
12 596872 0 12
13 588676 0 13
14 549738 0 14
15 472907 0 15
16 429496 0 16
17 402790 0 17
18 419304 0 18
19 459425 0 19
20 500845 0 20
21 516761 0 21
22 557423 0 22
23 595042 0 23
24 589496 0 24
25 535029 0 25
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) x t
521435.3 70995.4 -67.8
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-117493 -46534 4102 49289 76250
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 521435.3 29114.0 17.910 1.32e-14 ***
x 70995.4 49950.3 1.421 0.169
t -67.8 1879.2 -0.036 0.972
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 59800 on 22 degrees of freedom
Multiple R-Squared: 0.1078, Adjusted R-squared: 0.02666
F-statistic: 1.329 on 2 and 22 DF, p-value: 0.2853
> postscript(file="/var/www/html/rcomp/tmp/1gw6l1195648326.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/2sqir1195648326.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/36ewg1195648326.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/48rp81195648327.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5e7cb1195648327.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
> grid()
> dev.off()
null device
1
> (myerror <- as.ts(mysum$resid))
Time Series:
Start = 1
End = 25
Frequency = 1
1 2 3 4 5 6
-4101.900 4101.900 55380.064 16976.865 -29615.335 -51288.534
7 8 9 10 11 12
-46533.734 -13260.933 20221.867 49288.668 67561.468 76250.269
13 14 15 16 17 18
68122.069 29251.870 -47511.330 -90854.529 -117492.729 -100910.928
19 20 21 22 23 24
-60722.128 -19234.327 -3250.527 37479.274 75166.074 69687.875
25
15288.675
> postscript(file="/var/www/html/rcomp/tmp/6xiha1195648327.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 = 25
Frequency = 1
lag(myerror, k = 1) myerror
0 -4101.900 NA
1 4101.900 -4101.900
2 55380.064 4101.900
3 16976.865 55380.064
4 -29615.335 16976.865
5 -51288.534 -29615.335
6 -46533.734 -51288.534
7 -13260.933 -46533.734
8 20221.867 -13260.933
9 49288.668 20221.867
10 67561.468 49288.668
11 76250.269 67561.468
12 68122.069 76250.269
13 29251.870 68122.069
14 -47511.330 29251.870
15 -90854.529 -47511.330
16 -117492.729 -90854.529
17 -100910.928 -117492.729
18 -60722.128 -100910.928
19 -19234.327 -60722.128
20 -3250.527 -19234.327
21 37479.274 -3250.527
22 75166.074 37479.274
23 69687.875 75166.074
24 15288.675 69687.875
25 NA 15288.675
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 4101.900 -4101.900
[2,] 55380.064 4101.900
[3,] 16976.865 55380.064
[4,] -29615.335 16976.865
[5,] -51288.534 -29615.335
[6,] -46533.734 -51288.534
[7,] -13260.933 -46533.734
[8,] 20221.867 -13260.933
[9,] 49288.668 20221.867
[10,] 67561.468 49288.668
[11,] 76250.269 67561.468
[12,] 68122.069 76250.269
[13,] 29251.870 68122.069
[14,] -47511.330 29251.870
[15,] -90854.529 -47511.330
[16,] -117492.729 -90854.529
[17,] -100910.928 -117492.729
[18,] -60722.128 -100910.928
[19,] -19234.327 -60722.128
[20,] -3250.527 -19234.327
[21,] 37479.274 -3250.527
[22,] 75166.074 37479.274
[23,] 69687.875 75166.074
[24,] 15288.675 69687.875
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 4101.900 -4101.900
2 55380.064 4101.900
3 16976.865 55380.064
4 -29615.335 16976.865
5 -51288.534 -29615.335
6 -46533.734 -51288.534
7 -13260.933 -46533.734
8 20221.867 -13260.933
9 49288.668 20221.867
10 67561.468 49288.668
11 76250.269 67561.468
12 68122.069 76250.269
13 29251.870 68122.069
14 -47511.330 29251.870
15 -90854.529 -47511.330
16 -117492.729 -90854.529
17 -100910.928 -117492.729
18 -60722.128 -100910.928
19 -19234.327 -60722.128
20 -3250.527 -19234.327
21 37479.274 -3250.527
22 75166.074 37479.274
23 69687.875 75166.074
24 15288.675 69687.875
> 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/7sp2w1195648327.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8ux931195648327.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/99lv21195648327.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> load(file='/var/www/html/rcomp/createtable')
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/10mnms1195648327.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/11ivyf1195648327.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/12cr9r1195648328.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/13uypl1195648328.tab")
>
> system("convert tmp/1gw6l1195648326.ps tmp/1gw6l1195648326.png")
> system("convert tmp/2sqir1195648326.ps tmp/2sqir1195648326.png")
> system("convert tmp/36ewg1195648326.ps tmp/36ewg1195648326.png")
> system("convert tmp/48rp81195648327.ps tmp/48rp81195648327.png")
> system("convert tmp/5e7cb1195648327.ps tmp/5e7cb1195648327.png")
> system("convert tmp/6xiha1195648327.ps tmp/6xiha1195648327.png")
> system("convert tmp/7sp2w1195648327.ps tmp/7sp2w1195648327.png")
> system("convert tmp/8ux931195648327.ps tmp/8ux931195648327.png")
> system("convert tmp/99lv21195648327.ps tmp/99lv21195648327.png")
>
>
> proc.time()
user system elapsed
2.196 1.405 2.741