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(1.43,0,0,0,1.43,0,0,0,1.43,0,0,0,1.43,0,0,0,1.43,0,0,0,1.43,0,0,0,1.43,0,0,0,1.43,0,0,0,1.43,0,0,0,1.43,0,0,0,1.43,0,0,0,1.43,0,0,0,1.43,0,0,0,1.43,0,0,0,1.43,0,0,0,1.43,0,0,0,1.43,0,0,0,1.43,0,0,0,1.44,0,0,0,1.48,1,0,0,1.48,1,0,0,1.48,1,0,0,1.48,1,0,0,1.48,1,0,0,1.48,1,0,0,1.48,1,0,0,1.48,1,0,0,1.48,1,0,0,1.48,1,0,0,1.48,1,0,0,1.48,1,0,0,1.48,1,0,0,1.48,1,0,0,1.48,1,0,0,1.48,1,0,0,1.48,1,0,0,1.48,1,0,0,1.48,1,0,0,1.48,1,0,0,1.48,1,0,0,1.48,1,0,0,1.48,1,0,0,1.48,1,0,0,1.48,1,0,0,1.48,1,0,0,1.48,1,0,0,1.48,1,0,0,1.48,1,0,0,1.48,1,0,0,1.57,1,1,0,1.58,1,1,0,1.58,1,1,0,1.58,1,1,0,1.58,1,1,0,1.59,1,1,0,1.6,1,1,1,1.6,1,1,2,1.61,1,1,3,1.61,1,1,4,1.61,1,1,5,1.62,1,1,6,1.63,1,1,7,1.63,1,1,8,1.64,1,1,9,1.64,1,1,10,1.64,1,1,11,1.64,1,1,12,1.64,1,1,13,1.65,1,1,14,1.65,1,1,15,1.65,1,1,16,1.65,1,1,17),dim=c(4,72),dimnames=list(c('Y','x1','x2','x3'),1:72))
> y <- array(NA,dim=c(4,72),dimnames=list(c('Y','x1','x2','x3'),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 x1 x2 x3
1 1.43 0 0 0
2 1.43 0 0 0
3 1.43 0 0 0
4 1.43 0 0 0
5 1.43 0 0 0
6 1.43 0 0 0
7 1.43 0 0 0
8 1.43 0 0 0
9 1.43 0 0 0
10 1.43 0 0 0
11 1.43 0 0 0
12 1.43 0 0 0
13 1.43 0 0 0
14 1.43 0 0 0
15 1.43 0 0 0
16 1.43 0 0 0
17 1.43 0 0 0
18 1.43 0 0 0
19 1.44 0 0 0
20 1.48 1 0 0
21 1.48 1 0 0
22 1.48 1 0 0
23 1.48 1 0 0
24 1.48 1 0 0
25 1.48 1 0 0
26 1.48 1 0 0
27 1.48 1 0 0
28 1.48 1 0 0
29 1.48 1 0 0
30 1.48 1 0 0
31 1.48 1 0 0
32 1.48 1 0 0
33 1.48 1 0 0
34 1.48 1 0 0
35 1.48 1 0 0
36 1.48 1 0 0
37 1.48 1 0 0
38 1.48 1 0 0
39 1.48 1 0 0
40 1.48 1 0 0
41 1.48 1 0 0
42 1.48 1 0 0
43 1.48 1 0 0
44 1.48 1 0 0
45 1.48 1 0 0
46 1.48 1 0 0
47 1.48 1 0 0
48 1.48 1 0 0
49 1.48 1 0 0
50 1.57 1 1 0
51 1.58 1 1 0
52 1.58 1 1 0
53 1.58 1 1 0
54 1.58 1 1 0
55 1.59 1 1 0
56 1.60 1 1 1
57 1.60 1 1 2
58 1.61 1 1 3
59 1.61 1 1 4
60 1.61 1 1 5
61 1.62 1 1 6
62 1.63 1 1 7
63 1.63 1 1 8
64 1.64 1 1 9
65 1.64 1 1 10
66 1.64 1 1 11
67 1.64 1 1 12
68 1.64 1 1 13
69 1.65 1 1 14
70 1.65 1 1 15
71 1.65 1 1 16
72 1.65 1 1 17
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) x1 x2 x3
1.430526 0.049474 0.107514 0.004426
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-1.751e-02 -5.263e-04 1.423e-19 1.423e-19 1.265e-02
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1.4305263 0.0010963 1304.89 <2e-16 ***
x1 0.0494737 0.0014011 35.31 <2e-16 ***
x2 0.1075145 0.0017524 61.35 <2e-16 ***
x3 0.0044259 0.0001725 25.66 <2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.004779 on 68 degrees of freedom
Multiple R-Squared: 0.9964, Adjusted R-squared: 0.9962
F-statistic: 6206 on 3 and 68 DF, p-value: < 2.2e-16
> postscript(file="/var/www/html/rcomp/tmp/1lh831197985636.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/2h7321197985636.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/3sunl1197985636.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4s1yl1197985636.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5091a1197985636.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$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
-5.263158e-04 -5.263158e-04 -5.263158e-04 -5.263158e-04 -5.263158e-04
6 7 8 9 10
-5.263158e-04 -5.263158e-04 -5.263158e-04 -5.263158e-04 -5.263158e-04
11 12 13 14 15
-5.263158e-04 -5.263158e-04 -5.263158e-04 -5.263158e-04 -5.263158e-04
16 17 18 19 20
-5.263158e-04 -5.263158e-04 -5.263158e-04 9.473684e-03 1.423015e-19
21 22 23 24 25
1.423015e-19 1.423015e-19 1.423015e-19 1.423015e-19 1.423015e-19
26 27 28 29 30
1.423015e-19 1.423015e-19 1.423015e-19 1.423015e-19 1.423015e-19
31 32 33 34 35
1.423015e-19 1.423015e-19 1.423015e-19 1.423015e-19 1.423015e-19
36 37 38 39 40
1.423015e-19 1.423015e-19 1.423015e-19 1.423015e-19 1.423015e-19
41 42 43 44 45
1.423015e-19 1.423015e-19 1.423015e-19 1.423015e-19 1.423015e-19
46 47 48 49 50
1.423015e-19 1.423015e-19 1.423015e-19 1.423015e-19 -1.751445e-02
51 52 53 54 55
-7.514451e-03 -7.514451e-03 -7.514451e-03 -7.514451e-03 2.485549e-03
56 57 58 59 60
8.059617e-03 3.633685e-03 9.207752e-03 4.781820e-03 3.558880e-04
61 62 63 64 65
5.929956e-03 1.150402e-02 7.078091e-03 1.265216e-02 8.226227e-03
66 67 68 69 70
3.800295e-03 -6.256375e-04 -5.051570e-03 5.224980e-04 -3.903434e-03
71 72
-8.329366e-03 -1.275530e-02
> postscript(file="/var/www/html/rcomp/tmp/6xufa1197985636.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 -5.263158e-04 NA
1 -5.263158e-04 -5.263158e-04
2 -5.263158e-04 -5.263158e-04
3 -5.263158e-04 -5.263158e-04
4 -5.263158e-04 -5.263158e-04
5 -5.263158e-04 -5.263158e-04
6 -5.263158e-04 -5.263158e-04
7 -5.263158e-04 -5.263158e-04
8 -5.263158e-04 -5.263158e-04
9 -5.263158e-04 -5.263158e-04
10 -5.263158e-04 -5.263158e-04
11 -5.263158e-04 -5.263158e-04
12 -5.263158e-04 -5.263158e-04
13 -5.263158e-04 -5.263158e-04
14 -5.263158e-04 -5.263158e-04
15 -5.263158e-04 -5.263158e-04
16 -5.263158e-04 -5.263158e-04
17 -5.263158e-04 -5.263158e-04
18 9.473684e-03 -5.263158e-04
19 1.423015e-19 9.473684e-03
20 1.423015e-19 1.423015e-19
21 1.423015e-19 1.423015e-19
22 1.423015e-19 1.423015e-19
23 1.423015e-19 1.423015e-19
24 1.423015e-19 1.423015e-19
25 1.423015e-19 1.423015e-19
26 1.423015e-19 1.423015e-19
27 1.423015e-19 1.423015e-19
28 1.423015e-19 1.423015e-19
29 1.423015e-19 1.423015e-19
30 1.423015e-19 1.423015e-19
31 1.423015e-19 1.423015e-19
32 1.423015e-19 1.423015e-19
33 1.423015e-19 1.423015e-19
34 1.423015e-19 1.423015e-19
35 1.423015e-19 1.423015e-19
36 1.423015e-19 1.423015e-19
37 1.423015e-19 1.423015e-19
38 1.423015e-19 1.423015e-19
39 1.423015e-19 1.423015e-19
40 1.423015e-19 1.423015e-19
41 1.423015e-19 1.423015e-19
42 1.423015e-19 1.423015e-19
43 1.423015e-19 1.423015e-19
44 1.423015e-19 1.423015e-19
45 1.423015e-19 1.423015e-19
46 1.423015e-19 1.423015e-19
47 1.423015e-19 1.423015e-19
48 1.423015e-19 1.423015e-19
49 -1.751445e-02 1.423015e-19
50 -7.514451e-03 -1.751445e-02
51 -7.514451e-03 -7.514451e-03
52 -7.514451e-03 -7.514451e-03
53 -7.514451e-03 -7.514451e-03
54 2.485549e-03 -7.514451e-03
55 8.059617e-03 2.485549e-03
56 3.633685e-03 8.059617e-03
57 9.207752e-03 3.633685e-03
58 4.781820e-03 9.207752e-03
59 3.558880e-04 4.781820e-03
60 5.929956e-03 3.558880e-04
61 1.150402e-02 5.929956e-03
62 7.078091e-03 1.150402e-02
63 1.265216e-02 7.078091e-03
64 8.226227e-03 1.265216e-02
65 3.800295e-03 8.226227e-03
66 -6.256375e-04 3.800295e-03
67 -5.051570e-03 -6.256375e-04
68 5.224980e-04 -5.051570e-03
69 -3.903434e-03 5.224980e-04
70 -8.329366e-03 -3.903434e-03
71 -1.275530e-02 -8.329366e-03
72 NA -1.275530e-02
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -5.263158e-04 -5.263158e-04
[2,] -5.263158e-04 -5.263158e-04
[3,] -5.263158e-04 -5.263158e-04
[4,] -5.263158e-04 -5.263158e-04
[5,] -5.263158e-04 -5.263158e-04
[6,] -5.263158e-04 -5.263158e-04
[7,] -5.263158e-04 -5.263158e-04
[8,] -5.263158e-04 -5.263158e-04
[9,] -5.263158e-04 -5.263158e-04
[10,] -5.263158e-04 -5.263158e-04
[11,] -5.263158e-04 -5.263158e-04
[12,] -5.263158e-04 -5.263158e-04
[13,] -5.263158e-04 -5.263158e-04
[14,] -5.263158e-04 -5.263158e-04
[15,] -5.263158e-04 -5.263158e-04
[16,] -5.263158e-04 -5.263158e-04
[17,] -5.263158e-04 -5.263158e-04
[18,] 9.473684e-03 -5.263158e-04
[19,] 1.423015e-19 9.473684e-03
[20,] 1.423015e-19 1.423015e-19
[21,] 1.423015e-19 1.423015e-19
[22,] 1.423015e-19 1.423015e-19
[23,] 1.423015e-19 1.423015e-19
[24,] 1.423015e-19 1.423015e-19
[25,] 1.423015e-19 1.423015e-19
[26,] 1.423015e-19 1.423015e-19
[27,] 1.423015e-19 1.423015e-19
[28,] 1.423015e-19 1.423015e-19
[29,] 1.423015e-19 1.423015e-19
[30,] 1.423015e-19 1.423015e-19
[31,] 1.423015e-19 1.423015e-19
[32,] 1.423015e-19 1.423015e-19
[33,] 1.423015e-19 1.423015e-19
[34,] 1.423015e-19 1.423015e-19
[35,] 1.423015e-19 1.423015e-19
[36,] 1.423015e-19 1.423015e-19
[37,] 1.423015e-19 1.423015e-19
[38,] 1.423015e-19 1.423015e-19
[39,] 1.423015e-19 1.423015e-19
[40,] 1.423015e-19 1.423015e-19
[41,] 1.423015e-19 1.423015e-19
[42,] 1.423015e-19 1.423015e-19
[43,] 1.423015e-19 1.423015e-19
[44,] 1.423015e-19 1.423015e-19
[45,] 1.423015e-19 1.423015e-19
[46,] 1.423015e-19 1.423015e-19
[47,] 1.423015e-19 1.423015e-19
[48,] 1.423015e-19 1.423015e-19
[49,] -1.751445e-02 1.423015e-19
[50,] -7.514451e-03 -1.751445e-02
[51,] -7.514451e-03 -7.514451e-03
[52,] -7.514451e-03 -7.514451e-03
[53,] -7.514451e-03 -7.514451e-03
[54,] 2.485549e-03 -7.514451e-03
[55,] 8.059617e-03 2.485549e-03
[56,] 3.633685e-03 8.059617e-03
[57,] 9.207752e-03 3.633685e-03
[58,] 4.781820e-03 9.207752e-03
[59,] 3.558880e-04 4.781820e-03
[60,] 5.929956e-03 3.558880e-04
[61,] 1.150402e-02 5.929956e-03
[62,] 7.078091e-03 1.150402e-02
[63,] 1.265216e-02 7.078091e-03
[64,] 8.226227e-03 1.265216e-02
[65,] 3.800295e-03 8.226227e-03
[66,] -6.256375e-04 3.800295e-03
[67,] -5.051570e-03 -6.256375e-04
[68,] 5.224980e-04 -5.051570e-03
[69,] -3.903434e-03 5.224980e-04
[70,] -8.329366e-03 -3.903434e-03
[71,] -1.275530e-02 -8.329366e-03
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -5.263158e-04 -5.263158e-04
2 -5.263158e-04 -5.263158e-04
3 -5.263158e-04 -5.263158e-04
4 -5.263158e-04 -5.263158e-04
5 -5.263158e-04 -5.263158e-04
6 -5.263158e-04 -5.263158e-04
7 -5.263158e-04 -5.263158e-04
8 -5.263158e-04 -5.263158e-04
9 -5.263158e-04 -5.263158e-04
10 -5.263158e-04 -5.263158e-04
11 -5.263158e-04 -5.263158e-04
12 -5.263158e-04 -5.263158e-04
13 -5.263158e-04 -5.263158e-04
14 -5.263158e-04 -5.263158e-04
15 -5.263158e-04 -5.263158e-04
16 -5.263158e-04 -5.263158e-04
17 -5.263158e-04 -5.263158e-04
18 9.473684e-03 -5.263158e-04
19 1.423015e-19 9.473684e-03
20 1.423015e-19 1.423015e-19
21 1.423015e-19 1.423015e-19
22 1.423015e-19 1.423015e-19
23 1.423015e-19 1.423015e-19
24 1.423015e-19 1.423015e-19
25 1.423015e-19 1.423015e-19
26 1.423015e-19 1.423015e-19
27 1.423015e-19 1.423015e-19
28 1.423015e-19 1.423015e-19
29 1.423015e-19 1.423015e-19
30 1.423015e-19 1.423015e-19
31 1.423015e-19 1.423015e-19
32 1.423015e-19 1.423015e-19
33 1.423015e-19 1.423015e-19
34 1.423015e-19 1.423015e-19
35 1.423015e-19 1.423015e-19
36 1.423015e-19 1.423015e-19
37 1.423015e-19 1.423015e-19
38 1.423015e-19 1.423015e-19
39 1.423015e-19 1.423015e-19
40 1.423015e-19 1.423015e-19
41 1.423015e-19 1.423015e-19
42 1.423015e-19 1.423015e-19
43 1.423015e-19 1.423015e-19
44 1.423015e-19 1.423015e-19
45 1.423015e-19 1.423015e-19
46 1.423015e-19 1.423015e-19
47 1.423015e-19 1.423015e-19
48 1.423015e-19 1.423015e-19
49 -1.751445e-02 1.423015e-19
50 -7.514451e-03 -1.751445e-02
51 -7.514451e-03 -7.514451e-03
52 -7.514451e-03 -7.514451e-03
53 -7.514451e-03 -7.514451e-03
54 2.485549e-03 -7.514451e-03
55 8.059617e-03 2.485549e-03
56 3.633685e-03 8.059617e-03
57 9.207752e-03 3.633685e-03
58 4.781820e-03 9.207752e-03
59 3.558880e-04 4.781820e-03
60 5.929956e-03 3.558880e-04
61 1.150402e-02 5.929956e-03
62 7.078091e-03 1.150402e-02
63 1.265216e-02 7.078091e-03
64 8.226227e-03 1.265216e-02
65 3.800295e-03 8.226227e-03
66 -6.256375e-04 3.800295e-03
67 -5.051570e-03 -6.256375e-04
68 5.224980e-04 -5.051570e-03
69 -3.903434e-03 5.224980e-04
70 -8.329366e-03 -3.903434e-03
71 -1.275530e-02 -8.329366e-03
> 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/7st8b1197985636.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8xz1w1197985636.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/99eib1197985636.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> load(file='/var/www/html/rcomp/createtable')
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/108qns1197985636.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/11ygl11197985636.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/12mnfk1197985636.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/13r0mf1197985637.tab")
>
> system("convert tmp/1lh831197985636.ps tmp/1lh831197985636.png")
> system("convert tmp/2h7321197985636.ps tmp/2h7321197985636.png")
> system("convert tmp/3sunl1197985636.ps tmp/3sunl1197985636.png")
> system("convert tmp/4s1yl1197985636.ps tmp/4s1yl1197985636.png")
> system("convert tmp/5091a1197985636.ps tmp/5091a1197985636.png")
> system("convert tmp/6xufa1197985636.ps tmp/6xufa1197985636.png")
> system("convert tmp/7st8b1197985636.ps tmp/7st8b1197985636.png")
> system("convert tmp/8xz1w1197985636.ps tmp/8xz1w1197985636.png")
> system("convert tmp/99eib1197985636.ps tmp/99eib1197985636.png")
>
>
> proc.time()
user system elapsed
2.240 1.454 2.563