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(119.5,0,125,0,145,0,105.3,0,116.9,0,120.1,0,88.9,0,78.4,0,114.6,0,113.3,0,117,0,99.6,0,99.4,0,101.9,0,115.2,0,108.5,0,113.8,0,121,0,92.2,0,90.2,0,101.5,0,126.6,0,93.9,0,89.8,0,93.4,0,101.5,0,110.4,0,105.9,0,108.4,0,113.9,0,86.1,0,69.4,0,101.2,0,100.5,0,98,0,106.6,0,90.1,0,96.9,0,125.9,0,112,0,100,0,123.9,0,79.8,0,83.4,0,113.6,0,112.9,0,104,0,109.9,0,99,0,106.3,0,128.9,0,111.1,0,102.9,0,130,0,87,0,87.5,0,117.6,0,103.4,0,110.8,0,112.6,0,102.5,0,112.4,0,135.6,0,105.1,0,127.7,0,137,0,91,0,90.5,0,122.4,1,123.3,1,124.3,1,120,1,118.1,1,119,1,142.7,1,123.6,1,129.6,1,151.6,1,110.4,1,99.2,1,130.5,1,136.2,1,129.7,1,128,1,121.6,1),dim=c(2,85),dimnames=list(c('y','x'),1:85))
> y <- array(NA,dim=c(2,85),dimnames=list(c('y','x'),1:85))
> 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
1 119.5 0
2 125.0 0
3 145.0 0
4 105.3 0
5 116.9 0
6 120.1 0
7 88.9 0
8 78.4 0
9 114.6 0
10 113.3 0
11 117.0 0
12 99.6 0
13 99.4 0
14 101.9 0
15 115.2 0
16 108.5 0
17 113.8 0
18 121.0 0
19 92.2 0
20 90.2 0
21 101.5 0
22 126.6 0
23 93.9 0
24 89.8 0
25 93.4 0
26 101.5 0
27 110.4 0
28 105.9 0
29 108.4 0
30 113.9 0
31 86.1 0
32 69.4 0
33 101.2 0
34 100.5 0
35 98.0 0
36 106.6 0
37 90.1 0
38 96.9 0
39 125.9 0
40 112.0 0
41 100.0 0
42 123.9 0
43 79.8 0
44 83.4 0
45 113.6 0
46 112.9 0
47 104.0 0
48 109.9 0
49 99.0 0
50 106.3 0
51 128.9 0
52 111.1 0
53 102.9 0
54 130.0 0
55 87.0 0
56 87.5 0
57 117.6 0
58 103.4 0
59 110.8 0
60 112.6 0
61 102.5 0
62 112.4 0
63 135.6 0
64 105.1 0
65 127.7 0
66 137.0 0
67 91.0 0
68 90.5 0
69 122.4 1
70 123.3 1
71 124.3 1
72 120.0 1
73 118.1 1
74 119.0 1
75 142.7 1
76 123.6 1
77 129.6 1
78 151.6 1
79 110.4 1
80 99.2 1
81 130.5 1
82 136.2 1
83 129.7 1
84 128.0 1
85 121.6 1
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) x
106.53 18.77
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-37.132 -7.206 -1.006 7.368 38.468
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 106.532 1.744 61.088 < 2e-16 ***
x 18.774 3.899 4.814 6.55e-06 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 14.38 on 83 degrees of freedom
Multiple R-squared: 0.2183, Adjusted R-squared: 0.2089
F-statistic: 23.18 on 1 and 83 DF, p-value: 6.549e-06
> postscript(file="/var/www/html/rcomp/tmp/1jv201227800839.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/2x47h1227800839.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/3hjsm1227800839.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4au4l1227800839.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/55bff1227800839.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
> grid()
> dev.off()
null device
1
> (myerror <- as.ts(mysum$resid))
Time Series:
Start = 1
End = 85
Frequency = 1
1 2 3 4 5 6
12.96764706 18.46764706 38.46764706 -1.23235294 10.36764706 13.56764706
7 8 9 10 11 12
-17.63235294 -28.13235294 8.06764706 6.76764706 10.46764706 -6.93235294
13 14 15 16 17 18
-7.13235294 -4.63235294 8.66764706 1.96764706 7.26764706 14.46764706
19 20 21 22 23 24
-14.33235294 -16.33235294 -5.03235294 20.06764706 -12.63235294 -16.73235294
25 26 27 28 29 30
-13.13235294 -5.03235294 3.86764706 -0.63235294 1.86764706 7.36764706
31 32 33 34 35 36
-20.43235294 -37.13235294 -5.33235294 -6.03235294 -8.53235294 0.06764706
37 38 39 40 41 42
-16.43235294 -9.63235294 19.36764706 5.46764706 -6.53235294 17.36764706
43 44 45 46 47 48
-26.73235294 -23.13235294 7.06764706 6.36764706 -2.53235294 3.36764706
49 50 51 52 53 54
-7.53235294 -0.23235294 22.36764706 4.56764706 -3.63235294 23.46764706
55 56 57 58 59 60
-19.53235294 -19.03235294 11.06764706 -3.13235294 4.26764706 6.06764706
61 62 63 64 65 66
-4.03235294 5.86764706 29.06764706 -1.43235294 21.16764706 30.46764706
67 68 69 70 71 72
-15.53235294 -16.03235294 -2.90588235 -2.00588235 -1.00588235 -5.30588235
73 74 75 76 77 78
-7.20588235 -6.30588235 17.39411765 -1.70588235 4.29411765 26.29411765
79 80 81 82 83 84
-14.90588235 -26.10588235 5.19411765 10.89411765 4.39411765 2.69411765
85
-3.70588235
> postscript(file="/var/www/html/rcomp/tmp/6buis1227800840.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 = 85
Frequency = 1
lag(myerror, k = 1) myerror
0 12.96764706 NA
1 18.46764706 12.96764706
2 38.46764706 18.46764706
3 -1.23235294 38.46764706
4 10.36764706 -1.23235294
5 13.56764706 10.36764706
6 -17.63235294 13.56764706
7 -28.13235294 -17.63235294
8 8.06764706 -28.13235294
9 6.76764706 8.06764706
10 10.46764706 6.76764706
11 -6.93235294 10.46764706
12 -7.13235294 -6.93235294
13 -4.63235294 -7.13235294
14 8.66764706 -4.63235294
15 1.96764706 8.66764706
16 7.26764706 1.96764706
17 14.46764706 7.26764706
18 -14.33235294 14.46764706
19 -16.33235294 -14.33235294
20 -5.03235294 -16.33235294
21 20.06764706 -5.03235294
22 -12.63235294 20.06764706
23 -16.73235294 -12.63235294
24 -13.13235294 -16.73235294
25 -5.03235294 -13.13235294
26 3.86764706 -5.03235294
27 -0.63235294 3.86764706
28 1.86764706 -0.63235294
29 7.36764706 1.86764706
30 -20.43235294 7.36764706
31 -37.13235294 -20.43235294
32 -5.33235294 -37.13235294
33 -6.03235294 -5.33235294
34 -8.53235294 -6.03235294
35 0.06764706 -8.53235294
36 -16.43235294 0.06764706
37 -9.63235294 -16.43235294
38 19.36764706 -9.63235294
39 5.46764706 19.36764706
40 -6.53235294 5.46764706
41 17.36764706 -6.53235294
42 -26.73235294 17.36764706
43 -23.13235294 -26.73235294
44 7.06764706 -23.13235294
45 6.36764706 7.06764706
46 -2.53235294 6.36764706
47 3.36764706 -2.53235294
48 -7.53235294 3.36764706
49 -0.23235294 -7.53235294
50 22.36764706 -0.23235294
51 4.56764706 22.36764706
52 -3.63235294 4.56764706
53 23.46764706 -3.63235294
54 -19.53235294 23.46764706
55 -19.03235294 -19.53235294
56 11.06764706 -19.03235294
57 -3.13235294 11.06764706
58 4.26764706 -3.13235294
59 6.06764706 4.26764706
60 -4.03235294 6.06764706
61 5.86764706 -4.03235294
62 29.06764706 5.86764706
63 -1.43235294 29.06764706
64 21.16764706 -1.43235294
65 30.46764706 21.16764706
66 -15.53235294 30.46764706
67 -16.03235294 -15.53235294
68 -2.90588235 -16.03235294
69 -2.00588235 -2.90588235
70 -1.00588235 -2.00588235
71 -5.30588235 -1.00588235
72 -7.20588235 -5.30588235
73 -6.30588235 -7.20588235
74 17.39411765 -6.30588235
75 -1.70588235 17.39411765
76 4.29411765 -1.70588235
77 26.29411765 4.29411765
78 -14.90588235 26.29411765
79 -26.10588235 -14.90588235
80 5.19411765 -26.10588235
81 10.89411765 5.19411765
82 4.39411765 10.89411765
83 2.69411765 4.39411765
84 -3.70588235 2.69411765
85 NA -3.70588235
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 18.46764706 12.96764706
[2,] 38.46764706 18.46764706
[3,] -1.23235294 38.46764706
[4,] 10.36764706 -1.23235294
[5,] 13.56764706 10.36764706
[6,] -17.63235294 13.56764706
[7,] -28.13235294 -17.63235294
[8,] 8.06764706 -28.13235294
[9,] 6.76764706 8.06764706
[10,] 10.46764706 6.76764706
[11,] -6.93235294 10.46764706
[12,] -7.13235294 -6.93235294
[13,] -4.63235294 -7.13235294
[14,] 8.66764706 -4.63235294
[15,] 1.96764706 8.66764706
[16,] 7.26764706 1.96764706
[17,] 14.46764706 7.26764706
[18,] -14.33235294 14.46764706
[19,] -16.33235294 -14.33235294
[20,] -5.03235294 -16.33235294
[21,] 20.06764706 -5.03235294
[22,] -12.63235294 20.06764706
[23,] -16.73235294 -12.63235294
[24,] -13.13235294 -16.73235294
[25,] -5.03235294 -13.13235294
[26,] 3.86764706 -5.03235294
[27,] -0.63235294 3.86764706
[28,] 1.86764706 -0.63235294
[29,] 7.36764706 1.86764706
[30,] -20.43235294 7.36764706
[31,] -37.13235294 -20.43235294
[32,] -5.33235294 -37.13235294
[33,] -6.03235294 -5.33235294
[34,] -8.53235294 -6.03235294
[35,] 0.06764706 -8.53235294
[36,] -16.43235294 0.06764706
[37,] -9.63235294 -16.43235294
[38,] 19.36764706 -9.63235294
[39,] 5.46764706 19.36764706
[40,] -6.53235294 5.46764706
[41,] 17.36764706 -6.53235294
[42,] -26.73235294 17.36764706
[43,] -23.13235294 -26.73235294
[44,] 7.06764706 -23.13235294
[45,] 6.36764706 7.06764706
[46,] -2.53235294 6.36764706
[47,] 3.36764706 -2.53235294
[48,] -7.53235294 3.36764706
[49,] -0.23235294 -7.53235294
[50,] 22.36764706 -0.23235294
[51,] 4.56764706 22.36764706
[52,] -3.63235294 4.56764706
[53,] 23.46764706 -3.63235294
[54,] -19.53235294 23.46764706
[55,] -19.03235294 -19.53235294
[56,] 11.06764706 -19.03235294
[57,] -3.13235294 11.06764706
[58,] 4.26764706 -3.13235294
[59,] 6.06764706 4.26764706
[60,] -4.03235294 6.06764706
[61,] 5.86764706 -4.03235294
[62,] 29.06764706 5.86764706
[63,] -1.43235294 29.06764706
[64,] 21.16764706 -1.43235294
[65,] 30.46764706 21.16764706
[66,] -15.53235294 30.46764706
[67,] -16.03235294 -15.53235294
[68,] -2.90588235 -16.03235294
[69,] -2.00588235 -2.90588235
[70,] -1.00588235 -2.00588235
[71,] -5.30588235 -1.00588235
[72,] -7.20588235 -5.30588235
[73,] -6.30588235 -7.20588235
[74,] 17.39411765 -6.30588235
[75,] -1.70588235 17.39411765
[76,] 4.29411765 -1.70588235
[77,] 26.29411765 4.29411765
[78,] -14.90588235 26.29411765
[79,] -26.10588235 -14.90588235
[80,] 5.19411765 -26.10588235
[81,] 10.89411765 5.19411765
[82,] 4.39411765 10.89411765
[83,] 2.69411765 4.39411765
[84,] -3.70588235 2.69411765
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 18.46764706 12.96764706
2 38.46764706 18.46764706
3 -1.23235294 38.46764706
4 10.36764706 -1.23235294
5 13.56764706 10.36764706
6 -17.63235294 13.56764706
7 -28.13235294 -17.63235294
8 8.06764706 -28.13235294
9 6.76764706 8.06764706
10 10.46764706 6.76764706
11 -6.93235294 10.46764706
12 -7.13235294 -6.93235294
13 -4.63235294 -7.13235294
14 8.66764706 -4.63235294
15 1.96764706 8.66764706
16 7.26764706 1.96764706
17 14.46764706 7.26764706
18 -14.33235294 14.46764706
19 -16.33235294 -14.33235294
20 -5.03235294 -16.33235294
21 20.06764706 -5.03235294
22 -12.63235294 20.06764706
23 -16.73235294 -12.63235294
24 -13.13235294 -16.73235294
25 -5.03235294 -13.13235294
26 3.86764706 -5.03235294
27 -0.63235294 3.86764706
28 1.86764706 -0.63235294
29 7.36764706 1.86764706
30 -20.43235294 7.36764706
31 -37.13235294 -20.43235294
32 -5.33235294 -37.13235294
33 -6.03235294 -5.33235294
34 -8.53235294 -6.03235294
35 0.06764706 -8.53235294
36 -16.43235294 0.06764706
37 -9.63235294 -16.43235294
38 19.36764706 -9.63235294
39 5.46764706 19.36764706
40 -6.53235294 5.46764706
41 17.36764706 -6.53235294
42 -26.73235294 17.36764706
43 -23.13235294 -26.73235294
44 7.06764706 -23.13235294
45 6.36764706 7.06764706
46 -2.53235294 6.36764706
47 3.36764706 -2.53235294
48 -7.53235294 3.36764706
49 -0.23235294 -7.53235294
50 22.36764706 -0.23235294
51 4.56764706 22.36764706
52 -3.63235294 4.56764706
53 23.46764706 -3.63235294
54 -19.53235294 23.46764706
55 -19.03235294 -19.53235294
56 11.06764706 -19.03235294
57 -3.13235294 11.06764706
58 4.26764706 -3.13235294
59 6.06764706 4.26764706
60 -4.03235294 6.06764706
61 5.86764706 -4.03235294
62 29.06764706 5.86764706
63 -1.43235294 29.06764706
64 21.16764706 -1.43235294
65 30.46764706 21.16764706
66 -15.53235294 30.46764706
67 -16.03235294 -15.53235294
68 -2.90588235 -16.03235294
69 -2.00588235 -2.90588235
70 -1.00588235 -2.00588235
71 -5.30588235 -1.00588235
72 -7.20588235 -5.30588235
73 -6.30588235 -7.20588235
74 17.39411765 -6.30588235
75 -1.70588235 17.39411765
76 4.29411765 -1.70588235
77 26.29411765 4.29411765
78 -14.90588235 26.29411765
79 -26.10588235 -14.90588235
80 5.19411765 -26.10588235
81 10.89411765 5.19411765
82 4.39411765 10.89411765
83 2.69411765 4.39411765
84 -3.70588235 2.69411765
> 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/7xhgo1227800840.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/80n0x1227800840.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9io8e1227800840.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/107jx61227800840.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/11hnnn1227800840.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/1233d61227800840.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/13crf71227800840.tab")
>
> system("convert tmp/1jv201227800839.ps tmp/1jv201227800839.png")
> system("convert tmp/2x47h1227800839.ps tmp/2x47h1227800839.png")
> system("convert tmp/3hjsm1227800839.ps tmp/3hjsm1227800839.png")
> system("convert tmp/4au4l1227800839.ps tmp/4au4l1227800839.png")
> system("convert tmp/55bff1227800839.ps tmp/55bff1227800839.png")
> system("convert tmp/6buis1227800840.ps tmp/6buis1227800840.png")
> system("convert tmp/7xhgo1227800840.ps tmp/7xhgo1227800840.png")
> system("convert tmp/80n0x1227800840.ps tmp/80n0x1227800840.png")
> system("convert tmp/9io8e1227800840.ps tmp/9io8e1227800840.png")
>
>
> proc.time()
user system elapsed
1.976 1.415 2.821