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(97.3,0,101,0,113.2,0,101,0,105.7,0,113.9,0,86.4,0,96.5,0,103.3,0,114.9,0,105.8,0,94.2,0,98.4,0,99.4,0,108.8,0,112.6,0,104.4,0,112.2,0,81.1,0,97.1,0,112.6,0,113.8,0,107.8,0,103.2,0,103.3,0,101.2,0,107.7,0,110.4,0,101.9,0,115.9,0,89.9,0,88.6,0,117.2,0,123.9,0,100,0,103.6,0,94.1,0,98.7,0,119.5,0,112.7,0,104.4,0,124.7,0,89.1,0,97,0,121.6,0,118.8,0,114,0,111.5,0,97.2,0,102.5,0,113.4,0,109.8,0,104.9,0,126.1,0,80,0,96.8,0,117.2,1,112.3,1,117.3,1,111.1,1,102.2,1,104.3,1,122.9,1,107.6,1,121.3,1,131.5,1,89,1,104.4,1,128.9,1,135.9,1,133.3,1,121.3,1,120.5,1,120.4,1,137.9,1,126.1,1,133.2,1,146.6,1,103.4,1,117.2,1),dim=c(2,80),dimnames=list(c('y','x'),1:80))
> y <- array(NA,dim=c(2,80),dimnames=list(c('y','x'),1:80))
> 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 97.3 0
2 101.0 0
3 113.2 0
4 101.0 0
5 105.7 0
6 113.9 0
7 86.4 0
8 96.5 0
9 103.3 0
10 114.9 0
11 105.8 0
12 94.2 0
13 98.4 0
14 99.4 0
15 108.8 0
16 112.6 0
17 104.4 0
18 112.2 0
19 81.1 0
20 97.1 0
21 112.6 0
22 113.8 0
23 107.8 0
24 103.2 0
25 103.3 0
26 101.2 0
27 107.7 0
28 110.4 0
29 101.9 0
30 115.9 0
31 89.9 0
32 88.6 0
33 117.2 0
34 123.9 0
35 100.0 0
36 103.6 0
37 94.1 0
38 98.7 0
39 119.5 0
40 112.7 0
41 104.4 0
42 124.7 0
43 89.1 0
44 97.0 0
45 121.6 0
46 118.8 0
47 114.0 0
48 111.5 0
49 97.2 0
50 102.5 0
51 113.4 0
52 109.8 0
53 104.9 0
54 126.1 0
55 80.0 0
56 96.8 0
57 117.2 1
58 112.3 1
59 117.3 1
60 111.1 1
61 102.2 1
62 104.3 1
63 122.9 1
64 107.6 1
65 121.3 1
66 131.5 1
67 89.0 1
68 104.4 1
69 128.9 1
70 135.9 1
71 133.3 1
72 121.3 1
73 120.5 1
74 120.4 1
75 137.9 1
76 126.1 1
77 133.2 1
78 146.6 1
79 103.4 1
80 117.2 1
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) x
105.09 14.32
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-30.4083 -7.8143 -0.4393 8.1607 27.1917
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 105.089 1.538 68.34 < 2e-16 ***
x 14.319 2.808 5.10 2.32e-06 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 11.51 on 78 degrees of freedom
Multiple R-squared: 0.2501, Adjusted R-squared: 0.2405
F-statistic: 26.01 on 1 and 78 DF, p-value: 2.322e-06
> postscript(file="/var/www/html/freestat/rcomp/tmp/1bu5h1227551172.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/freestat/rcomp/tmp/2nig21227551172.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/3cqud1227551172.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/4kyo01227551172.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/5elvw1227551172.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
> grid()
> dev.off()
null device
1
> (myerror <- as.ts(mysum$resid))
Time Series:
Start = 1
End = 80
Frequency = 1
1 2 3 4 5 6
-7.7892857 -4.0892857 8.1107143 -4.0892857 0.6107143 8.8107143
7 8 9 10 11 12
-18.6892857 -8.5892857 -1.7892857 9.8107143 0.7107143 -10.8892857
13 14 15 16 17 18
-6.6892857 -5.6892857 3.7107143 7.5107143 -0.6892857 7.1107143
19 20 21 22 23 24
-23.9892857 -7.9892857 7.5107143 8.7107143 2.7107143 -1.8892857
25 26 27 28 29 30
-1.7892857 -3.8892857 2.6107143 5.3107143 -3.1892857 10.8107143
31 32 33 34 35 36
-15.1892857 -16.4892857 12.1107143 18.8107143 -5.0892857 -1.4892857
37 38 39 40 41 42
-10.9892857 -6.3892857 14.4107143 7.6107143 -0.6892857 19.6107143
43 44 45 46 47 48
-15.9892857 -8.0892857 16.5107143 13.7107143 8.9107143 6.4107143
49 50 51 52 53 54
-7.8892857 -2.5892857 8.3107143 4.7107143 -0.1892857 21.0107143
55 56 57 58 59 60
-25.0892857 -8.2892857 -2.2083333 -7.1083333 -2.1083333 -8.3083333
61 62 63 64 65 66
-17.2083333 -15.1083333 3.4916667 -11.8083333 1.8916667 12.0916667
67 68 69 70 71 72
-30.4083333 -15.0083333 9.4916667 16.4916667 13.8916667 1.8916667
73 74 75 76 77 78
1.0916667 0.9916667 18.4916667 6.6916667 13.7916667 27.1916667
79 80
-16.0083333 -2.2083333
> postscript(file="/var/www/html/freestat/rcomp/tmp/6jl061227551172.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 = 80
Frequency = 1
lag(myerror, k = 1) myerror
0 -7.7892857 NA
1 -4.0892857 -7.7892857
2 8.1107143 -4.0892857
3 -4.0892857 8.1107143
4 0.6107143 -4.0892857
5 8.8107143 0.6107143
6 -18.6892857 8.8107143
7 -8.5892857 -18.6892857
8 -1.7892857 -8.5892857
9 9.8107143 -1.7892857
10 0.7107143 9.8107143
11 -10.8892857 0.7107143
12 -6.6892857 -10.8892857
13 -5.6892857 -6.6892857
14 3.7107143 -5.6892857
15 7.5107143 3.7107143
16 -0.6892857 7.5107143
17 7.1107143 -0.6892857
18 -23.9892857 7.1107143
19 -7.9892857 -23.9892857
20 7.5107143 -7.9892857
21 8.7107143 7.5107143
22 2.7107143 8.7107143
23 -1.8892857 2.7107143
24 -1.7892857 -1.8892857
25 -3.8892857 -1.7892857
26 2.6107143 -3.8892857
27 5.3107143 2.6107143
28 -3.1892857 5.3107143
29 10.8107143 -3.1892857
30 -15.1892857 10.8107143
31 -16.4892857 -15.1892857
32 12.1107143 -16.4892857
33 18.8107143 12.1107143
34 -5.0892857 18.8107143
35 -1.4892857 -5.0892857
36 -10.9892857 -1.4892857
37 -6.3892857 -10.9892857
38 14.4107143 -6.3892857
39 7.6107143 14.4107143
40 -0.6892857 7.6107143
41 19.6107143 -0.6892857
42 -15.9892857 19.6107143
43 -8.0892857 -15.9892857
44 16.5107143 -8.0892857
45 13.7107143 16.5107143
46 8.9107143 13.7107143
47 6.4107143 8.9107143
48 -7.8892857 6.4107143
49 -2.5892857 -7.8892857
50 8.3107143 -2.5892857
51 4.7107143 8.3107143
52 -0.1892857 4.7107143
53 21.0107143 -0.1892857
54 -25.0892857 21.0107143
55 -8.2892857 -25.0892857
56 -2.2083333 -8.2892857
57 -7.1083333 -2.2083333
58 -2.1083333 -7.1083333
59 -8.3083333 -2.1083333
60 -17.2083333 -8.3083333
61 -15.1083333 -17.2083333
62 3.4916667 -15.1083333
63 -11.8083333 3.4916667
64 1.8916667 -11.8083333
65 12.0916667 1.8916667
66 -30.4083333 12.0916667
67 -15.0083333 -30.4083333
68 9.4916667 -15.0083333
69 16.4916667 9.4916667
70 13.8916667 16.4916667
71 1.8916667 13.8916667
72 1.0916667 1.8916667
73 0.9916667 1.0916667
74 18.4916667 0.9916667
75 6.6916667 18.4916667
76 13.7916667 6.6916667
77 27.1916667 13.7916667
78 -16.0083333 27.1916667
79 -2.2083333 -16.0083333
80 NA -2.2083333
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -4.0892857 -7.7892857
[2,] 8.1107143 -4.0892857
[3,] -4.0892857 8.1107143
[4,] 0.6107143 -4.0892857
[5,] 8.8107143 0.6107143
[6,] -18.6892857 8.8107143
[7,] -8.5892857 -18.6892857
[8,] -1.7892857 -8.5892857
[9,] 9.8107143 -1.7892857
[10,] 0.7107143 9.8107143
[11,] -10.8892857 0.7107143
[12,] -6.6892857 -10.8892857
[13,] -5.6892857 -6.6892857
[14,] 3.7107143 -5.6892857
[15,] 7.5107143 3.7107143
[16,] -0.6892857 7.5107143
[17,] 7.1107143 -0.6892857
[18,] -23.9892857 7.1107143
[19,] -7.9892857 -23.9892857
[20,] 7.5107143 -7.9892857
[21,] 8.7107143 7.5107143
[22,] 2.7107143 8.7107143
[23,] -1.8892857 2.7107143
[24,] -1.7892857 -1.8892857
[25,] -3.8892857 -1.7892857
[26,] 2.6107143 -3.8892857
[27,] 5.3107143 2.6107143
[28,] -3.1892857 5.3107143
[29,] 10.8107143 -3.1892857
[30,] -15.1892857 10.8107143
[31,] -16.4892857 -15.1892857
[32,] 12.1107143 -16.4892857
[33,] 18.8107143 12.1107143
[34,] -5.0892857 18.8107143
[35,] -1.4892857 -5.0892857
[36,] -10.9892857 -1.4892857
[37,] -6.3892857 -10.9892857
[38,] 14.4107143 -6.3892857
[39,] 7.6107143 14.4107143
[40,] -0.6892857 7.6107143
[41,] 19.6107143 -0.6892857
[42,] -15.9892857 19.6107143
[43,] -8.0892857 -15.9892857
[44,] 16.5107143 -8.0892857
[45,] 13.7107143 16.5107143
[46,] 8.9107143 13.7107143
[47,] 6.4107143 8.9107143
[48,] -7.8892857 6.4107143
[49,] -2.5892857 -7.8892857
[50,] 8.3107143 -2.5892857
[51,] 4.7107143 8.3107143
[52,] -0.1892857 4.7107143
[53,] 21.0107143 -0.1892857
[54,] -25.0892857 21.0107143
[55,] -8.2892857 -25.0892857
[56,] -2.2083333 -8.2892857
[57,] -7.1083333 -2.2083333
[58,] -2.1083333 -7.1083333
[59,] -8.3083333 -2.1083333
[60,] -17.2083333 -8.3083333
[61,] -15.1083333 -17.2083333
[62,] 3.4916667 -15.1083333
[63,] -11.8083333 3.4916667
[64,] 1.8916667 -11.8083333
[65,] 12.0916667 1.8916667
[66,] -30.4083333 12.0916667
[67,] -15.0083333 -30.4083333
[68,] 9.4916667 -15.0083333
[69,] 16.4916667 9.4916667
[70,] 13.8916667 16.4916667
[71,] 1.8916667 13.8916667
[72,] 1.0916667 1.8916667
[73,] 0.9916667 1.0916667
[74,] 18.4916667 0.9916667
[75,] 6.6916667 18.4916667
[76,] 13.7916667 6.6916667
[77,] 27.1916667 13.7916667
[78,] -16.0083333 27.1916667
[79,] -2.2083333 -16.0083333
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -4.0892857 -7.7892857
2 8.1107143 -4.0892857
3 -4.0892857 8.1107143
4 0.6107143 -4.0892857
5 8.8107143 0.6107143
6 -18.6892857 8.8107143
7 -8.5892857 -18.6892857
8 -1.7892857 -8.5892857
9 9.8107143 -1.7892857
10 0.7107143 9.8107143
11 -10.8892857 0.7107143
12 -6.6892857 -10.8892857
13 -5.6892857 -6.6892857
14 3.7107143 -5.6892857
15 7.5107143 3.7107143
16 -0.6892857 7.5107143
17 7.1107143 -0.6892857
18 -23.9892857 7.1107143
19 -7.9892857 -23.9892857
20 7.5107143 -7.9892857
21 8.7107143 7.5107143
22 2.7107143 8.7107143
23 -1.8892857 2.7107143
24 -1.7892857 -1.8892857
25 -3.8892857 -1.7892857
26 2.6107143 -3.8892857
27 5.3107143 2.6107143
28 -3.1892857 5.3107143
29 10.8107143 -3.1892857
30 -15.1892857 10.8107143
31 -16.4892857 -15.1892857
32 12.1107143 -16.4892857
33 18.8107143 12.1107143
34 -5.0892857 18.8107143
35 -1.4892857 -5.0892857
36 -10.9892857 -1.4892857
37 -6.3892857 -10.9892857
38 14.4107143 -6.3892857
39 7.6107143 14.4107143
40 -0.6892857 7.6107143
41 19.6107143 -0.6892857
42 -15.9892857 19.6107143
43 -8.0892857 -15.9892857
44 16.5107143 -8.0892857
45 13.7107143 16.5107143
46 8.9107143 13.7107143
47 6.4107143 8.9107143
48 -7.8892857 6.4107143
49 -2.5892857 -7.8892857
50 8.3107143 -2.5892857
51 4.7107143 8.3107143
52 -0.1892857 4.7107143
53 21.0107143 -0.1892857
54 -25.0892857 21.0107143
55 -8.2892857 -25.0892857
56 -2.2083333 -8.2892857
57 -7.1083333 -2.2083333
58 -2.1083333 -7.1083333
59 -8.3083333 -2.1083333
60 -17.2083333 -8.3083333
61 -15.1083333 -17.2083333
62 3.4916667 -15.1083333
63 -11.8083333 3.4916667
64 1.8916667 -11.8083333
65 12.0916667 1.8916667
66 -30.4083333 12.0916667
67 -15.0083333 -30.4083333
68 9.4916667 -15.0083333
69 16.4916667 9.4916667
70 13.8916667 16.4916667
71 1.8916667 13.8916667
72 1.0916667 1.8916667
73 0.9916667 1.0916667
74 18.4916667 0.9916667
75 6.6916667 18.4916667
76 13.7916667 6.6916667
77 27.1916667 13.7916667
78 -16.0083333 27.1916667
79 -2.2083333 -16.0083333
> 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/freestat/rcomp/tmp/7iuen1227551172.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/8se401227551172.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/9zsc51227551172.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
>
> #Note: the /var/www/html/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/freestat/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/freestat/rcomp/tmp/10t9aj1227551172.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/freestat/rcomp/tmp/11qsk41227551172.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/freestat/rcomp/tmp/12jmhm1227551172.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/freestat/rcomp/tmp/138qkv1227551172.tab")
>
> system("convert tmp/1bu5h1227551172.ps tmp/1bu5h1227551172.png")
> system("convert tmp/2nig21227551172.ps tmp/2nig21227551172.png")
> system("convert tmp/3cqud1227551172.ps tmp/3cqud1227551172.png")
> system("convert tmp/4kyo01227551172.ps tmp/4kyo01227551172.png")
> system("convert tmp/5elvw1227551172.ps tmp/5elvw1227551172.png")
> system("convert tmp/6jl061227551172.ps tmp/6jl061227551172.png")
> system("convert tmp/7iuen1227551172.ps tmp/7iuen1227551172.png")
> system("convert tmp/8se401227551172.ps tmp/8se401227551172.png")
> system("convert tmp/9zsc51227551172.ps tmp/9zsc51227551172.png")
>
>
> proc.time()
user system elapsed
3.068 2.299 3.369