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.
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(1.43,0.51,1.43,0.51,1.43,0.51,1.43,0.51,1.43,0.51,1.43,0.51,1.43,0.51,1.43,0.51,1.43,0.5,1.43,0.51,1.43,0.51,1.43,0.5,1.43,0.51,1.43,0.51,1.43,0.51,1.43,0.51,1.43,0.52,1.43,0.52,1.44,0.52,1.48,0.53,1.48,0.53,1.48,0.52,1.48,0.52,1.48,0.52,1.48,0.52,1.48,0.52,1.48,0.52,1.48,0.52,1.48,0.52,1.48,0.52,1.48,0.52,1.48,0.53,1.48,0.53,1.48,0.53,1.48,0.54,1.48,0.54,1.48,0.54,1.48,0.54,1.48,0.54,1.48,0.54,1.48,0.54,1.48,0.54,1.48,0.54,1.48,0.54,1.48,0.53,1.48,0.53,1.48,0.53,1.48,0.53,1.48,0.53,1.57,0.54,1.58,0.55,1.58,0.55,1.58,0.55,1.58,0.55,1.59,0.55,1.6,0.55,1.6,0.55,1.61,0.55,1.61,0.56,1.61,0.56,1.62,0.56,1.63,0.56,1.63,0.56,1.64,0.55,1.64,0.56,1.64,0.55,1.64,0.55,1.64,0.56,1.65,0.55,1.65,0.55,1.65,0.55,1.65,0.55),dim=c(2,72),dimnames=list(c('y','x'),1:72))
> y <- array(NA,dim=c(2,72),dimnames=list(c('y','x'),1:72))
> 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 1.43 0.51
2 1.43 0.51
3 1.43 0.51
4 1.43 0.51
5 1.43 0.51
6 1.43 0.51
7 1.43 0.51
8 1.43 0.51
9 1.43 0.50
10 1.43 0.51
11 1.43 0.51
12 1.43 0.50
13 1.43 0.51
14 1.43 0.51
15 1.43 0.51
16 1.43 0.51
17 1.43 0.52
18 1.43 0.52
19 1.44 0.52
20 1.48 0.53
21 1.48 0.53
22 1.48 0.52
23 1.48 0.52
24 1.48 0.52
25 1.48 0.52
26 1.48 0.52
27 1.48 0.52
28 1.48 0.52
29 1.48 0.52
30 1.48 0.52
31 1.48 0.52
32 1.48 0.53
33 1.48 0.53
34 1.48 0.53
35 1.48 0.54
36 1.48 0.54
37 1.48 0.54
38 1.48 0.54
39 1.48 0.54
40 1.48 0.54
41 1.48 0.54
42 1.48 0.54
43 1.48 0.54
44 1.48 0.54
45 1.48 0.53
46 1.48 0.53
47 1.48 0.53
48 1.48 0.53
49 1.48 0.53
50 1.57 0.54
51 1.58 0.55
52 1.58 0.55
53 1.58 0.55
54 1.58 0.55
55 1.59 0.55
56 1.60 0.55
57 1.60 0.55
58 1.61 0.55
59 1.61 0.56
60 1.61 0.56
61 1.62 0.56
62 1.63 0.56
63 1.63 0.56
64 1.64 0.55
65 1.64 0.56
66 1.64 0.55
67 1.64 0.55
68 1.64 0.56
69 1.65 0.55
70 1.65 0.55
71 1.65 0.55
72 1.65 0.55
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) x
-0.5919 3.9516
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-0.06198 -0.02246 0.00657 0.01705 0.06851
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -0.5919 0.1267 -4.67 1.41e-05 ***
x 3.9516 0.2381 16.60 < 2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.03514 on 70 degrees of freedom
Multiple R-Squared: 0.7974, Adjusted R-squared: 0.7945
F-statistic: 275.5 on 1 and 70 DF, p-value: < 2.2e-16
> postscript(file="/var/www/html/rcomp/tmp/18cou1198159935.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/2eo7y1198159935.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/3hwji1198159935.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/41f021198159935.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5h65l1198159935.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
> grid()
> dev.off()
null device
1
> (myerror <- as.ts(mysum$resid))
Time Series:
Start = 1
End = 72
Frequency = 1
1 2 3 4 5 6
0.006570409 0.006570409 0.006570409 0.006570409 0.006570409 0.006570409
7 8 9 10 11 12
0.006570409 0.006570409 0.046086568 0.006570409 0.006570409 0.046086568
13 14 15 16 17 18
0.006570409 0.006570409 0.006570409 0.006570409 -0.032945751 -0.032945751
19 20 21 22 23 24
-0.022945751 -0.022461911 -0.022461911 0.017054249 0.017054249 0.017054249
25 26 27 28 29 30
0.017054249 0.017054249 0.017054249 0.017054249 0.017054249 0.017054249
31 32 33 34 35 36
0.017054249 -0.022461911 -0.022461911 -0.022461911 -0.061978071 -0.061978071
37 38 39 40 41 42
-0.061978071 -0.061978071 -0.061978071 -0.061978071 -0.061978071 -0.061978071
43 44 45 46 47 48
-0.061978071 -0.061978071 -0.022461911 -0.022461911 -0.022461911 -0.022461911
49 50 51 52 53 54
-0.022461911 0.028021929 -0.001494231 -0.001494231 -0.001494231 -0.001494231
55 56 57 58 59 60
0.008505769 0.018505769 0.018505769 0.028505769 -0.011010391 -0.011010391
61 62 63 64 65 66
-0.001010391 0.008989609 0.008989609 0.058505769 0.018989609 0.058505769
67 68 69 70 71 72
0.058505769 0.018989609 0.068505769 0.068505769 0.068505769 0.068505769
> postscript(file="/var/www/html/rcomp/tmp/629801198159935.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 = 72
Frequency = 1
lag(myerror, k = 1) myerror
0 0.006570409 NA
1 0.006570409 0.006570409
2 0.006570409 0.006570409
3 0.006570409 0.006570409
4 0.006570409 0.006570409
5 0.006570409 0.006570409
6 0.006570409 0.006570409
7 0.006570409 0.006570409
8 0.046086568 0.006570409
9 0.006570409 0.046086568
10 0.006570409 0.006570409
11 0.046086568 0.006570409
12 0.006570409 0.046086568
13 0.006570409 0.006570409
14 0.006570409 0.006570409
15 0.006570409 0.006570409
16 -0.032945751 0.006570409
17 -0.032945751 -0.032945751
18 -0.022945751 -0.032945751
19 -0.022461911 -0.022945751
20 -0.022461911 -0.022461911
21 0.017054249 -0.022461911
22 0.017054249 0.017054249
23 0.017054249 0.017054249
24 0.017054249 0.017054249
25 0.017054249 0.017054249
26 0.017054249 0.017054249
27 0.017054249 0.017054249
28 0.017054249 0.017054249
29 0.017054249 0.017054249
30 0.017054249 0.017054249
31 -0.022461911 0.017054249
32 -0.022461911 -0.022461911
33 -0.022461911 -0.022461911
34 -0.061978071 -0.022461911
35 -0.061978071 -0.061978071
36 -0.061978071 -0.061978071
37 -0.061978071 -0.061978071
38 -0.061978071 -0.061978071
39 -0.061978071 -0.061978071
40 -0.061978071 -0.061978071
41 -0.061978071 -0.061978071
42 -0.061978071 -0.061978071
43 -0.061978071 -0.061978071
44 -0.022461911 -0.061978071
45 -0.022461911 -0.022461911
46 -0.022461911 -0.022461911
47 -0.022461911 -0.022461911
48 -0.022461911 -0.022461911
49 0.028021929 -0.022461911
50 -0.001494231 0.028021929
51 -0.001494231 -0.001494231
52 -0.001494231 -0.001494231
53 -0.001494231 -0.001494231
54 0.008505769 -0.001494231
55 0.018505769 0.008505769
56 0.018505769 0.018505769
57 0.028505769 0.018505769
58 -0.011010391 0.028505769
59 -0.011010391 -0.011010391
60 -0.001010391 -0.011010391
61 0.008989609 -0.001010391
62 0.008989609 0.008989609
63 0.058505769 0.008989609
64 0.018989609 0.058505769
65 0.058505769 0.018989609
66 0.058505769 0.058505769
67 0.018989609 0.058505769
68 0.068505769 0.018989609
69 0.068505769 0.068505769
70 0.068505769 0.068505769
71 0.068505769 0.068505769
72 NA 0.068505769
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 0.006570409 0.006570409
[2,] 0.006570409 0.006570409
[3,] 0.006570409 0.006570409
[4,] 0.006570409 0.006570409
[5,] 0.006570409 0.006570409
[6,] 0.006570409 0.006570409
[7,] 0.006570409 0.006570409
[8,] 0.046086568 0.006570409
[9,] 0.006570409 0.046086568
[10,] 0.006570409 0.006570409
[11,] 0.046086568 0.006570409
[12,] 0.006570409 0.046086568
[13,] 0.006570409 0.006570409
[14,] 0.006570409 0.006570409
[15,] 0.006570409 0.006570409
[16,] -0.032945751 0.006570409
[17,] -0.032945751 -0.032945751
[18,] -0.022945751 -0.032945751
[19,] -0.022461911 -0.022945751
[20,] -0.022461911 -0.022461911
[21,] 0.017054249 -0.022461911
[22,] 0.017054249 0.017054249
[23,] 0.017054249 0.017054249
[24,] 0.017054249 0.017054249
[25,] 0.017054249 0.017054249
[26,] 0.017054249 0.017054249
[27,] 0.017054249 0.017054249
[28,] 0.017054249 0.017054249
[29,] 0.017054249 0.017054249
[30,] 0.017054249 0.017054249
[31,] -0.022461911 0.017054249
[32,] -0.022461911 -0.022461911
[33,] -0.022461911 -0.022461911
[34,] -0.061978071 -0.022461911
[35,] -0.061978071 -0.061978071
[36,] -0.061978071 -0.061978071
[37,] -0.061978071 -0.061978071
[38,] -0.061978071 -0.061978071
[39,] -0.061978071 -0.061978071
[40,] -0.061978071 -0.061978071
[41,] -0.061978071 -0.061978071
[42,] -0.061978071 -0.061978071
[43,] -0.061978071 -0.061978071
[44,] -0.022461911 -0.061978071
[45,] -0.022461911 -0.022461911
[46,] -0.022461911 -0.022461911
[47,] -0.022461911 -0.022461911
[48,] -0.022461911 -0.022461911
[49,] 0.028021929 -0.022461911
[50,] -0.001494231 0.028021929
[51,] -0.001494231 -0.001494231
[52,] -0.001494231 -0.001494231
[53,] -0.001494231 -0.001494231
[54,] 0.008505769 -0.001494231
[55,] 0.018505769 0.008505769
[56,] 0.018505769 0.018505769
[57,] 0.028505769 0.018505769
[58,] -0.011010391 0.028505769
[59,] -0.011010391 -0.011010391
[60,] -0.001010391 -0.011010391
[61,] 0.008989609 -0.001010391
[62,] 0.008989609 0.008989609
[63,] 0.058505769 0.008989609
[64,] 0.018989609 0.058505769
[65,] 0.058505769 0.018989609
[66,] 0.058505769 0.058505769
[67,] 0.018989609 0.058505769
[68,] 0.068505769 0.018989609
[69,] 0.068505769 0.068505769
[70,] 0.068505769 0.068505769
[71,] 0.068505769 0.068505769
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 0.006570409 0.006570409
2 0.006570409 0.006570409
3 0.006570409 0.006570409
4 0.006570409 0.006570409
5 0.006570409 0.006570409
6 0.006570409 0.006570409
7 0.006570409 0.006570409
8 0.046086568 0.006570409
9 0.006570409 0.046086568
10 0.006570409 0.006570409
11 0.046086568 0.006570409
12 0.006570409 0.046086568
13 0.006570409 0.006570409
14 0.006570409 0.006570409
15 0.006570409 0.006570409
16 -0.032945751 0.006570409
17 -0.032945751 -0.032945751
18 -0.022945751 -0.032945751
19 -0.022461911 -0.022945751
20 -0.022461911 -0.022461911
21 0.017054249 -0.022461911
22 0.017054249 0.017054249
23 0.017054249 0.017054249
24 0.017054249 0.017054249
25 0.017054249 0.017054249
26 0.017054249 0.017054249
27 0.017054249 0.017054249
28 0.017054249 0.017054249
29 0.017054249 0.017054249
30 0.017054249 0.017054249
31 -0.022461911 0.017054249
32 -0.022461911 -0.022461911
33 -0.022461911 -0.022461911
34 -0.061978071 -0.022461911
35 -0.061978071 -0.061978071
36 -0.061978071 -0.061978071
37 -0.061978071 -0.061978071
38 -0.061978071 -0.061978071
39 -0.061978071 -0.061978071
40 -0.061978071 -0.061978071
41 -0.061978071 -0.061978071
42 -0.061978071 -0.061978071
43 -0.061978071 -0.061978071
44 -0.022461911 -0.061978071
45 -0.022461911 -0.022461911
46 -0.022461911 -0.022461911
47 -0.022461911 -0.022461911
48 -0.022461911 -0.022461911
49 0.028021929 -0.022461911
50 -0.001494231 0.028021929
51 -0.001494231 -0.001494231
52 -0.001494231 -0.001494231
53 -0.001494231 -0.001494231
54 0.008505769 -0.001494231
55 0.018505769 0.008505769
56 0.018505769 0.018505769
57 0.028505769 0.018505769
58 -0.011010391 0.028505769
59 -0.011010391 -0.011010391
60 -0.001010391 -0.011010391
61 0.008989609 -0.001010391
62 0.008989609 0.008989609
63 0.058505769 0.008989609
64 0.018989609 0.058505769
65 0.058505769 0.018989609
66 0.058505769 0.058505769
67 0.018989609 0.058505769
68 0.068505769 0.018989609
69 0.068505769 0.068505769
70 0.068505769 0.068505769
71 0.068505769 0.068505769
> 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/76ylf1198159935.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8zg5x1198159935.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9kksw1198159935.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> load(file='/var/www/html/rcomp/createtable')
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/105db01198159935.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/11m2621198159935.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/12ju8w1198159935.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/13h6n91198159935.tab")
>
> system("convert tmp/18cou1198159935.ps tmp/18cou1198159935.png")
> system("convert tmp/2eo7y1198159935.ps tmp/2eo7y1198159935.png")
> system("convert tmp/3hwji1198159935.ps tmp/3hwji1198159935.png")
> system("convert tmp/41f021198159935.ps tmp/41f021198159935.png")
> system("convert tmp/5h65l1198159935.ps tmp/5h65l1198159935.png")
> system("convert tmp/629801198159935.ps tmp/629801198159935.png")
> system("convert tmp/76ylf1198159935.ps tmp/76ylf1198159935.png")
> system("convert tmp/8zg5x1198159935.ps tmp/8zg5x1198159935.png")
> system("convert tmp/9kksw1198159935.ps tmp/9kksw1198159935.png")
>
>
> proc.time()
user system elapsed
2.266 1.482 2.805