R version 2.8.0 (2008-10-20)
Copyright (C) 2008 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(1332.7,0,1343.8,0,1421.6,0,1329.8,0,1306.8,0,1412.8,0,1358.1,0,1163.9,0,1467.9,0,1433.7,0,1362.2,0,1299,0,1291.5,0,1452.7,0,1555.4,0,1402.5,0,1242.9,0,1514.6,0,1308.6,0,1239.3,0,1519.9,0,1659.4,0,1597.6,0,1340.6,0,1427.2,0,1438.1,0,1616.2,0,1392.8,0,1318.7,0,1420.9,0,1221,0,1310,0,1466.7,0,1299.3,0,1640,0,1506.3,0,1530.2,0,1661.9,0,1880.3,1,1230.8,0,1406.5,0,1523.5,0,1323.2,0,1319.2,0,1500.7,0,1483,0,1497,0,1219.8,0,1472.9,0,1423.9,0,1629.6,0,1353.4,0,1366.8,0,1527.1,0,1487.6,0,1478.6,0,1536.7,0,1682.1,0,1576.5,0,1280.5,0),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 1332.7 0
2 1343.8 0
3 1421.6 0
4 1329.8 0
5 1306.8 0
6 1412.8 0
7 1358.1 0
8 1163.9 0
9 1467.9 0
10 1433.7 0
11 1362.2 0
12 1299.0 0
13 1291.5 0
14 1452.7 0
15 1555.4 0
16 1402.5 0
17 1242.9 0
18 1514.6 0
19 1308.6 0
20 1239.3 0
21 1519.9 0
22 1659.4 0
23 1597.6 0
24 1340.6 0
25 1427.2 0
26 1438.1 0
27 1616.2 0
28 1392.8 0
29 1318.7 0
30 1420.9 0
31 1221.0 0
32 1310.0 0
33 1466.7 0
34 1299.3 0
35 1640.0 0
36 1506.3 0
37 1530.2 0
38 1661.9 0
39 1880.3 1
40 1230.8 0
41 1406.5 0
42 1523.5 0
43 1323.2 0
44 1319.2 0
45 1500.7 0
46 1483.0 0
47 1497.0 0
48 1219.8 0
49 1472.9 0
50 1423.9 0
51 1629.6 0
52 1353.4 0
53 1366.8 0
54 1527.1 0
55 1487.6 0
56 1478.6 0
57 1536.7 0
58 1682.1 0
59 1576.5 0
60 1280.5 0
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) x
1422.5 457.8
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-258.5746 -100.2746 -0.4373 85.9004 259.6254
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1422.47 16.38 86.849 < 2e-16 ***
x 457.83 126.87 3.609 0.000642 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 125.8 on 58 degrees of freedom
Multiple R-squared: 0.1834, Adjusted R-squared: 0.1693
F-statistic: 13.02 on 1 and 58 DF, p-value: 0.0006424
> postscript(file="/var/www/html/rcomp/tmp/1l9451227120835.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/2v7hv1227120835.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/3l4xa1227120835.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4w08c1227120835.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5sz2e1227120835.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$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
-8.977458e+01 -7.867458e+01 -8.745763e-01 -9.267458e+01 -1.156746e+02
6 7 8 9 10
-9.674576e+00 -6.437458e+01 -2.585746e+02 4.542542e+01 1.122542e+01
11 12 13 14 15
-6.027458e+01 -1.234746e+02 -1.309746e+02 3.022542e+01 1.329254e+02
16 17 18 19 20
-1.997458e+01 -1.795746e+02 9.212542e+01 -1.138746e+02 -1.831746e+02
21 22 23 24 25
9.742542e+01 2.369254e+02 1.751254e+02 -8.187458e+01 4.725424e+00
26 27 28 29 30
1.562542e+01 1.937254e+02 -2.967458e+01 -1.037746e+02 -1.574576e+00
31 32 33 34 35
-2.014746e+02 -1.124746e+02 4.422542e+01 -1.231746e+02 2.175254e+02
36 37 38 39 40
8.382542e+01 1.077254e+02 2.394254e+02 -1.776357e-15 -1.916746e+02
41 42 43 44 45
-1.597458e+01 1.010254e+02 -9.927458e+01 -1.032746e+02 7.822542e+01
46 47 48 49 50
6.052542e+01 7.452542e+01 -2.026746e+02 5.042542e+01 1.425424e+00
51 52 53 54 55
2.071254e+02 -6.907458e+01 -5.567458e+01 1.046254e+02 6.512542e+01
56 57 58 59 60
5.612542e+01 1.142254e+02 2.596254e+02 1.540254e+02 -1.419746e+02
> postscript(file="/var/www/html/rcomp/tmp/6n66x1227120835.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 -8.977458e+01 NA
1 -7.867458e+01 -8.977458e+01
2 -8.745763e-01 -7.867458e+01
3 -9.267458e+01 -8.745763e-01
4 -1.156746e+02 -9.267458e+01
5 -9.674576e+00 -1.156746e+02
6 -6.437458e+01 -9.674576e+00
7 -2.585746e+02 -6.437458e+01
8 4.542542e+01 -2.585746e+02
9 1.122542e+01 4.542542e+01
10 -6.027458e+01 1.122542e+01
11 -1.234746e+02 -6.027458e+01
12 -1.309746e+02 -1.234746e+02
13 3.022542e+01 -1.309746e+02
14 1.329254e+02 3.022542e+01
15 -1.997458e+01 1.329254e+02
16 -1.795746e+02 -1.997458e+01
17 9.212542e+01 -1.795746e+02
18 -1.138746e+02 9.212542e+01
19 -1.831746e+02 -1.138746e+02
20 9.742542e+01 -1.831746e+02
21 2.369254e+02 9.742542e+01
22 1.751254e+02 2.369254e+02
23 -8.187458e+01 1.751254e+02
24 4.725424e+00 -8.187458e+01
25 1.562542e+01 4.725424e+00
26 1.937254e+02 1.562542e+01
27 -2.967458e+01 1.937254e+02
28 -1.037746e+02 -2.967458e+01
29 -1.574576e+00 -1.037746e+02
30 -2.014746e+02 -1.574576e+00
31 -1.124746e+02 -2.014746e+02
32 4.422542e+01 -1.124746e+02
33 -1.231746e+02 4.422542e+01
34 2.175254e+02 -1.231746e+02
35 8.382542e+01 2.175254e+02
36 1.077254e+02 8.382542e+01
37 2.394254e+02 1.077254e+02
38 -1.776357e-15 2.394254e+02
39 -1.916746e+02 -1.776357e-15
40 -1.597458e+01 -1.916746e+02
41 1.010254e+02 -1.597458e+01
42 -9.927458e+01 1.010254e+02
43 -1.032746e+02 -9.927458e+01
44 7.822542e+01 -1.032746e+02
45 6.052542e+01 7.822542e+01
46 7.452542e+01 6.052542e+01
47 -2.026746e+02 7.452542e+01
48 5.042542e+01 -2.026746e+02
49 1.425424e+00 5.042542e+01
50 2.071254e+02 1.425424e+00
51 -6.907458e+01 2.071254e+02
52 -5.567458e+01 -6.907458e+01
53 1.046254e+02 -5.567458e+01
54 6.512542e+01 1.046254e+02
55 5.612542e+01 6.512542e+01
56 1.142254e+02 5.612542e+01
57 2.596254e+02 1.142254e+02
58 1.540254e+02 2.596254e+02
59 -1.419746e+02 1.540254e+02
60 NA -1.419746e+02
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -7.867458e+01 -8.977458e+01
[2,] -8.745763e-01 -7.867458e+01
[3,] -9.267458e+01 -8.745763e-01
[4,] -1.156746e+02 -9.267458e+01
[5,] -9.674576e+00 -1.156746e+02
[6,] -6.437458e+01 -9.674576e+00
[7,] -2.585746e+02 -6.437458e+01
[8,] 4.542542e+01 -2.585746e+02
[9,] 1.122542e+01 4.542542e+01
[10,] -6.027458e+01 1.122542e+01
[11,] -1.234746e+02 -6.027458e+01
[12,] -1.309746e+02 -1.234746e+02
[13,] 3.022542e+01 -1.309746e+02
[14,] 1.329254e+02 3.022542e+01
[15,] -1.997458e+01 1.329254e+02
[16,] -1.795746e+02 -1.997458e+01
[17,] 9.212542e+01 -1.795746e+02
[18,] -1.138746e+02 9.212542e+01
[19,] -1.831746e+02 -1.138746e+02
[20,] 9.742542e+01 -1.831746e+02
[21,] 2.369254e+02 9.742542e+01
[22,] 1.751254e+02 2.369254e+02
[23,] -8.187458e+01 1.751254e+02
[24,] 4.725424e+00 -8.187458e+01
[25,] 1.562542e+01 4.725424e+00
[26,] 1.937254e+02 1.562542e+01
[27,] -2.967458e+01 1.937254e+02
[28,] -1.037746e+02 -2.967458e+01
[29,] -1.574576e+00 -1.037746e+02
[30,] -2.014746e+02 -1.574576e+00
[31,] -1.124746e+02 -2.014746e+02
[32,] 4.422542e+01 -1.124746e+02
[33,] -1.231746e+02 4.422542e+01
[34,] 2.175254e+02 -1.231746e+02
[35,] 8.382542e+01 2.175254e+02
[36,] 1.077254e+02 8.382542e+01
[37,] 2.394254e+02 1.077254e+02
[38,] -1.776357e-15 2.394254e+02
[39,] -1.916746e+02 -1.776357e-15
[40,] -1.597458e+01 -1.916746e+02
[41,] 1.010254e+02 -1.597458e+01
[42,] -9.927458e+01 1.010254e+02
[43,] -1.032746e+02 -9.927458e+01
[44,] 7.822542e+01 -1.032746e+02
[45,] 6.052542e+01 7.822542e+01
[46,] 7.452542e+01 6.052542e+01
[47,] -2.026746e+02 7.452542e+01
[48,] 5.042542e+01 -2.026746e+02
[49,] 1.425424e+00 5.042542e+01
[50,] 2.071254e+02 1.425424e+00
[51,] -6.907458e+01 2.071254e+02
[52,] -5.567458e+01 -6.907458e+01
[53,] 1.046254e+02 -5.567458e+01
[54,] 6.512542e+01 1.046254e+02
[55,] 5.612542e+01 6.512542e+01
[56,] 1.142254e+02 5.612542e+01
[57,] 2.596254e+02 1.142254e+02
[58,] 1.540254e+02 2.596254e+02
[59,] -1.419746e+02 1.540254e+02
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -7.867458e+01 -8.977458e+01
2 -8.745763e-01 -7.867458e+01
3 -9.267458e+01 -8.745763e-01
4 -1.156746e+02 -9.267458e+01
5 -9.674576e+00 -1.156746e+02
6 -6.437458e+01 -9.674576e+00
7 -2.585746e+02 -6.437458e+01
8 4.542542e+01 -2.585746e+02
9 1.122542e+01 4.542542e+01
10 -6.027458e+01 1.122542e+01
11 -1.234746e+02 -6.027458e+01
12 -1.309746e+02 -1.234746e+02
13 3.022542e+01 -1.309746e+02
14 1.329254e+02 3.022542e+01
15 -1.997458e+01 1.329254e+02
16 -1.795746e+02 -1.997458e+01
17 9.212542e+01 -1.795746e+02
18 -1.138746e+02 9.212542e+01
19 -1.831746e+02 -1.138746e+02
20 9.742542e+01 -1.831746e+02
21 2.369254e+02 9.742542e+01
22 1.751254e+02 2.369254e+02
23 -8.187458e+01 1.751254e+02
24 4.725424e+00 -8.187458e+01
25 1.562542e+01 4.725424e+00
26 1.937254e+02 1.562542e+01
27 -2.967458e+01 1.937254e+02
28 -1.037746e+02 -2.967458e+01
29 -1.574576e+00 -1.037746e+02
30 -2.014746e+02 -1.574576e+00
31 -1.124746e+02 -2.014746e+02
32 4.422542e+01 -1.124746e+02
33 -1.231746e+02 4.422542e+01
34 2.175254e+02 -1.231746e+02
35 8.382542e+01 2.175254e+02
36 1.077254e+02 8.382542e+01
37 2.394254e+02 1.077254e+02
38 -1.776357e-15 2.394254e+02
39 -1.916746e+02 -1.776357e-15
40 -1.597458e+01 -1.916746e+02
41 1.010254e+02 -1.597458e+01
42 -9.927458e+01 1.010254e+02
43 -1.032746e+02 -9.927458e+01
44 7.822542e+01 -1.032746e+02
45 6.052542e+01 7.822542e+01
46 7.452542e+01 6.052542e+01
47 -2.026746e+02 7.452542e+01
48 5.042542e+01 -2.026746e+02
49 1.425424e+00 5.042542e+01
50 2.071254e+02 1.425424e+00
51 -6.907458e+01 2.071254e+02
52 -5.567458e+01 -6.907458e+01
53 1.046254e+02 -5.567458e+01
54 6.512542e+01 1.046254e+02
55 5.612542e+01 6.512542e+01
56 1.142254e+02 5.612542e+01
57 2.596254e+02 1.142254e+02
58 1.540254e+02 2.596254e+02
59 -1.419746e+02 1.540254e+02
> 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/7ke3f1227120835.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8vldl1227120835.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9meck1227120835.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
Warning message:
In dropInf(r.w/(s * sqrt(1 - hii))) :
Not plotting observations with leverage one:
39
> par(opar)
> dev.off()
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/10a1841227120835.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/11vpke1227120835.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/12lb2a1227120835.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/13gzpf1227120835.tab")
>
> system("convert tmp/1l9451227120835.ps tmp/1l9451227120835.png")
> system("convert tmp/2v7hv1227120835.ps tmp/2v7hv1227120835.png")
> system("convert tmp/3l4xa1227120835.ps tmp/3l4xa1227120835.png")
> system("convert tmp/4w08c1227120835.ps tmp/4w08c1227120835.png")
> system("convert tmp/5sz2e1227120835.ps tmp/5sz2e1227120835.png")
> system("convert tmp/6n66x1227120835.ps tmp/6n66x1227120835.png")
> system("convert tmp/7ke3f1227120835.ps tmp/7ke3f1227120835.png")
> system("convert tmp/8vldl1227120835.ps tmp/8vldl1227120835.png")
> system("convert tmp/9meck1227120835.ps tmp/9meck1227120835.png")
>
>
> proc.time()
user system elapsed
1.906 1.393 2.298