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 = '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 t
1 1.43 0 0 0 1
2 1.43 0 0 0 2
3 1.43 0 0 0 3
4 1.43 0 0 0 4
5 1.43 0 0 0 5
6 1.43 0 0 0 6
7 1.43 0 0 0 7
8 1.43 0 0 0 8
9 1.43 0 0 0 9
10 1.43 0 0 0 10
11 1.43 0 0 0 11
12 1.43 0 0 0 12
13 1.43 0 0 0 13
14 1.43 0 0 0 14
15 1.43 0 0 0 15
16 1.43 0 0 0 16
17 1.43 0 0 0 17
18 1.43 0 0 0 18
19 1.44 0 0 0 19
20 1.48 1 0 0 20
21 1.48 1 0 0 21
22 1.48 1 0 0 22
23 1.48 1 0 0 23
24 1.48 1 0 0 24
25 1.48 1 0 0 25
26 1.48 1 0 0 26
27 1.48 1 0 0 27
28 1.48 1 0 0 28
29 1.48 1 0 0 29
30 1.48 1 0 0 30
31 1.48 1 0 0 31
32 1.48 1 0 0 32
33 1.48 1 0 0 33
34 1.48 1 0 0 34
35 1.48 1 0 0 35
36 1.48 1 0 0 36
37 1.48 1 0 0 37
38 1.48 1 0 0 38
39 1.48 1 0 0 39
40 1.48 1 0 0 40
41 1.48 1 0 0 41
42 1.48 1 0 0 42
43 1.48 1 0 0 43
44 1.48 1 0 0 44
45 1.48 1 0 0 45
46 1.48 1 0 0 46
47 1.48 1 0 0 47
48 1.48 1 0 0 48
49 1.48 1 0 0 49
50 1.57 1 1 0 50
51 1.58 1 1 0 51
52 1.58 1 1 0 52
53 1.58 1 1 0 53
54 1.58 1 1 0 54
55 1.59 1 1 0 55
56 1.60 1 1 1 56
57 1.60 1 1 2 57
58 1.61 1 1 3 58
59 1.61 1 1 4 59
60 1.61 1 1 5 60
61 1.62 1 1 6 61
62 1.63 1 1 7 62
63 1.63 1 1 8 63
64 1.64 1 1 9 64
65 1.64 1 1 10 65
66 1.64 1 1 11 66
67 1.64 1 1 12 67
68 1.64 1 1 13 68
69 1.65 1 1 14 69
70 1.65 1 1 15 70
71 1.65 1 1 16 71
72 1.65 1 1 17 72
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) x1 x2 x3 t
1.430e+00 4.730e-02 1.058e-01 4.326e-03 8.868e-05
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-0.0172056 -0.0008936 -0.0001523 0.0007760 0.0126214
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1.430e+00 1.416e-03 1009.979 <2e-16 ***
x1 4.730e-02 2.603e-03 18.173 <2e-16 ***
x2 1.058e-01 2.441e-03 43.350 <2e-16 ***
x3 4.326e-03 2.000e-04 21.627 <2e-16 ***
t 8.868e-05 8.953e-05 0.991 0.325
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.004779 on 67 degrees of freedom
Multiple R-Squared: 0.9964, Adjusted R-squared: 0.9962
F-statistic: 4653 on 4 and 67 DF, p-value: < 2.2e-16
> postscript(file="/var/www/html/rcomp/tmp/1zuzn1197985107.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/2fl6v1197985107.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/30cf81197985107.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4ri111197985107.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5b8pv1197985107.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$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
2.718100e-04 1.831293e-04 9.444871e-05 5.768064e-06 -8.291258e-05
6 7 8 9 10
-1.715932e-04 -2.602739e-04 -3.489545e-04 -4.376351e-04 -5.263158e-04
11 12 13 14 15
-6.149964e-04 -7.036771e-04 -7.923577e-04 -8.810384e-04 -9.697190e-04
16 17 18 19 20
-1.058400e-03 -1.147080e-03 -1.235761e-03 8.675558e-03 1.285869e-03
21 22 23 24 25
1.197189e-03 1.108508e-03 1.019827e-03 9.311467e-04 8.424661e-04
26 27 28 29 30
7.537855e-04 6.651048e-04 5.764242e-04 4.877435e-04 3.990629e-04
31 32 33 34 35
3.103822e-04 2.217016e-04 1.330210e-04 4.434032e-05 -4.434032e-05
36 37 38 39 40
-1.330210e-04 -2.217016e-04 -3.103822e-04 -3.990629e-04 -4.877435e-04
41 42 43 44 45
-5.764242e-04 -6.651048e-04 -7.537855e-04 -8.424661e-04 -9.311467e-04
46 47 48 49 50
-1.019827e-03 -1.108508e-03 -1.197189e-03 -1.285869e-03 -1.720561e-02
51 52 53 54 55
-7.294287e-03 -7.382968e-03 -7.471648e-03 -7.560329e-03 2.350990e-03
56 57 58 59 60
7.936592e-03 3.522193e-03 9.107795e-03 4.693396e-03 2.789973e-04
61 62 63 64 65
5.864599e-03 1.145020e-02 7.035801e-03 1.262140e-02 8.207004e-03
66 67 68 69 70
3.792606e-03 -6.217930e-04 -5.036192e-03 5.494098e-04 -3.864989e-03
71 72
-8.279387e-03 -1.269379e-02
> postscript(file="/var/www/html/rcomp/tmp/6f38o1197985107.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 2.718100e-04 NA
1 1.831293e-04 2.718100e-04
2 9.444871e-05 1.831293e-04
3 5.768064e-06 9.444871e-05
4 -8.291258e-05 5.768064e-06
5 -1.715932e-04 -8.291258e-05
6 -2.602739e-04 -1.715932e-04
7 -3.489545e-04 -2.602739e-04
8 -4.376351e-04 -3.489545e-04
9 -5.263158e-04 -4.376351e-04
10 -6.149964e-04 -5.263158e-04
11 -7.036771e-04 -6.149964e-04
12 -7.923577e-04 -7.036771e-04
13 -8.810384e-04 -7.923577e-04
14 -9.697190e-04 -8.810384e-04
15 -1.058400e-03 -9.697190e-04
16 -1.147080e-03 -1.058400e-03
17 -1.235761e-03 -1.147080e-03
18 8.675558e-03 -1.235761e-03
19 1.285869e-03 8.675558e-03
20 1.197189e-03 1.285869e-03
21 1.108508e-03 1.197189e-03
22 1.019827e-03 1.108508e-03
23 9.311467e-04 1.019827e-03
24 8.424661e-04 9.311467e-04
25 7.537855e-04 8.424661e-04
26 6.651048e-04 7.537855e-04
27 5.764242e-04 6.651048e-04
28 4.877435e-04 5.764242e-04
29 3.990629e-04 4.877435e-04
30 3.103822e-04 3.990629e-04
31 2.217016e-04 3.103822e-04
32 1.330210e-04 2.217016e-04
33 4.434032e-05 1.330210e-04
34 -4.434032e-05 4.434032e-05
35 -1.330210e-04 -4.434032e-05
36 -2.217016e-04 -1.330210e-04
37 -3.103822e-04 -2.217016e-04
38 -3.990629e-04 -3.103822e-04
39 -4.877435e-04 -3.990629e-04
40 -5.764242e-04 -4.877435e-04
41 -6.651048e-04 -5.764242e-04
42 -7.537855e-04 -6.651048e-04
43 -8.424661e-04 -7.537855e-04
44 -9.311467e-04 -8.424661e-04
45 -1.019827e-03 -9.311467e-04
46 -1.108508e-03 -1.019827e-03
47 -1.197189e-03 -1.108508e-03
48 -1.285869e-03 -1.197189e-03
49 -1.720561e-02 -1.285869e-03
50 -7.294287e-03 -1.720561e-02
51 -7.382968e-03 -7.294287e-03
52 -7.471648e-03 -7.382968e-03
53 -7.560329e-03 -7.471648e-03
54 2.350990e-03 -7.560329e-03
55 7.936592e-03 2.350990e-03
56 3.522193e-03 7.936592e-03
57 9.107795e-03 3.522193e-03
58 4.693396e-03 9.107795e-03
59 2.789973e-04 4.693396e-03
60 5.864599e-03 2.789973e-04
61 1.145020e-02 5.864599e-03
62 7.035801e-03 1.145020e-02
63 1.262140e-02 7.035801e-03
64 8.207004e-03 1.262140e-02
65 3.792606e-03 8.207004e-03
66 -6.217930e-04 3.792606e-03
67 -5.036192e-03 -6.217930e-04
68 5.494098e-04 -5.036192e-03
69 -3.864989e-03 5.494098e-04
70 -8.279387e-03 -3.864989e-03
71 -1.269379e-02 -8.279387e-03
72 NA -1.269379e-02
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 1.831293e-04 2.718100e-04
[2,] 9.444871e-05 1.831293e-04
[3,] 5.768064e-06 9.444871e-05
[4,] -8.291258e-05 5.768064e-06
[5,] -1.715932e-04 -8.291258e-05
[6,] -2.602739e-04 -1.715932e-04
[7,] -3.489545e-04 -2.602739e-04
[8,] -4.376351e-04 -3.489545e-04
[9,] -5.263158e-04 -4.376351e-04
[10,] -6.149964e-04 -5.263158e-04
[11,] -7.036771e-04 -6.149964e-04
[12,] -7.923577e-04 -7.036771e-04
[13,] -8.810384e-04 -7.923577e-04
[14,] -9.697190e-04 -8.810384e-04
[15,] -1.058400e-03 -9.697190e-04
[16,] -1.147080e-03 -1.058400e-03
[17,] -1.235761e-03 -1.147080e-03
[18,] 8.675558e-03 -1.235761e-03
[19,] 1.285869e-03 8.675558e-03
[20,] 1.197189e-03 1.285869e-03
[21,] 1.108508e-03 1.197189e-03
[22,] 1.019827e-03 1.108508e-03
[23,] 9.311467e-04 1.019827e-03
[24,] 8.424661e-04 9.311467e-04
[25,] 7.537855e-04 8.424661e-04
[26,] 6.651048e-04 7.537855e-04
[27,] 5.764242e-04 6.651048e-04
[28,] 4.877435e-04 5.764242e-04
[29,] 3.990629e-04 4.877435e-04
[30,] 3.103822e-04 3.990629e-04
[31,] 2.217016e-04 3.103822e-04
[32,] 1.330210e-04 2.217016e-04
[33,] 4.434032e-05 1.330210e-04
[34,] -4.434032e-05 4.434032e-05
[35,] -1.330210e-04 -4.434032e-05
[36,] -2.217016e-04 -1.330210e-04
[37,] -3.103822e-04 -2.217016e-04
[38,] -3.990629e-04 -3.103822e-04
[39,] -4.877435e-04 -3.990629e-04
[40,] -5.764242e-04 -4.877435e-04
[41,] -6.651048e-04 -5.764242e-04
[42,] -7.537855e-04 -6.651048e-04
[43,] -8.424661e-04 -7.537855e-04
[44,] -9.311467e-04 -8.424661e-04
[45,] -1.019827e-03 -9.311467e-04
[46,] -1.108508e-03 -1.019827e-03
[47,] -1.197189e-03 -1.108508e-03
[48,] -1.285869e-03 -1.197189e-03
[49,] -1.720561e-02 -1.285869e-03
[50,] -7.294287e-03 -1.720561e-02
[51,] -7.382968e-03 -7.294287e-03
[52,] -7.471648e-03 -7.382968e-03
[53,] -7.560329e-03 -7.471648e-03
[54,] 2.350990e-03 -7.560329e-03
[55,] 7.936592e-03 2.350990e-03
[56,] 3.522193e-03 7.936592e-03
[57,] 9.107795e-03 3.522193e-03
[58,] 4.693396e-03 9.107795e-03
[59,] 2.789973e-04 4.693396e-03
[60,] 5.864599e-03 2.789973e-04
[61,] 1.145020e-02 5.864599e-03
[62,] 7.035801e-03 1.145020e-02
[63,] 1.262140e-02 7.035801e-03
[64,] 8.207004e-03 1.262140e-02
[65,] 3.792606e-03 8.207004e-03
[66,] -6.217930e-04 3.792606e-03
[67,] -5.036192e-03 -6.217930e-04
[68,] 5.494098e-04 -5.036192e-03
[69,] -3.864989e-03 5.494098e-04
[70,] -8.279387e-03 -3.864989e-03
[71,] -1.269379e-02 -8.279387e-03
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 1.831293e-04 2.718100e-04
2 9.444871e-05 1.831293e-04
3 5.768064e-06 9.444871e-05
4 -8.291258e-05 5.768064e-06
5 -1.715932e-04 -8.291258e-05
6 -2.602739e-04 -1.715932e-04
7 -3.489545e-04 -2.602739e-04
8 -4.376351e-04 -3.489545e-04
9 -5.263158e-04 -4.376351e-04
10 -6.149964e-04 -5.263158e-04
11 -7.036771e-04 -6.149964e-04
12 -7.923577e-04 -7.036771e-04
13 -8.810384e-04 -7.923577e-04
14 -9.697190e-04 -8.810384e-04
15 -1.058400e-03 -9.697190e-04
16 -1.147080e-03 -1.058400e-03
17 -1.235761e-03 -1.147080e-03
18 8.675558e-03 -1.235761e-03
19 1.285869e-03 8.675558e-03
20 1.197189e-03 1.285869e-03
21 1.108508e-03 1.197189e-03
22 1.019827e-03 1.108508e-03
23 9.311467e-04 1.019827e-03
24 8.424661e-04 9.311467e-04
25 7.537855e-04 8.424661e-04
26 6.651048e-04 7.537855e-04
27 5.764242e-04 6.651048e-04
28 4.877435e-04 5.764242e-04
29 3.990629e-04 4.877435e-04
30 3.103822e-04 3.990629e-04
31 2.217016e-04 3.103822e-04
32 1.330210e-04 2.217016e-04
33 4.434032e-05 1.330210e-04
34 -4.434032e-05 4.434032e-05
35 -1.330210e-04 -4.434032e-05
36 -2.217016e-04 -1.330210e-04
37 -3.103822e-04 -2.217016e-04
38 -3.990629e-04 -3.103822e-04
39 -4.877435e-04 -3.990629e-04
40 -5.764242e-04 -4.877435e-04
41 -6.651048e-04 -5.764242e-04
42 -7.537855e-04 -6.651048e-04
43 -8.424661e-04 -7.537855e-04
44 -9.311467e-04 -8.424661e-04
45 -1.019827e-03 -9.311467e-04
46 -1.108508e-03 -1.019827e-03
47 -1.197189e-03 -1.108508e-03
48 -1.285869e-03 -1.197189e-03
49 -1.720561e-02 -1.285869e-03
50 -7.294287e-03 -1.720561e-02
51 -7.382968e-03 -7.294287e-03
52 -7.471648e-03 -7.382968e-03
53 -7.560329e-03 -7.471648e-03
54 2.350990e-03 -7.560329e-03
55 7.936592e-03 2.350990e-03
56 3.522193e-03 7.936592e-03
57 9.107795e-03 3.522193e-03
58 4.693396e-03 9.107795e-03
59 2.789973e-04 4.693396e-03
60 5.864599e-03 2.789973e-04
61 1.145020e-02 5.864599e-03
62 7.035801e-03 1.145020e-02
63 1.262140e-02 7.035801e-03
64 8.207004e-03 1.262140e-02
65 3.792606e-03 8.207004e-03
66 -6.217930e-04 3.792606e-03
67 -5.036192e-03 -6.217930e-04
68 5.494098e-04 -5.036192e-03
69 -3.864989e-03 5.494098e-04
70 -8.279387e-03 -3.864989e-03
71 -1.269379e-02 -8.279387e-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/7bglz1197985107.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8adiu1197985107.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/98hni1197985107.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> load(file='/var/www/html/rcomp/createtable')
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/10k4871197985108.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/11lz2a1197985108.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/12ldbb1197985108.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/13buo21197985108.tab")
>
> system("convert tmp/1zuzn1197985107.ps tmp/1zuzn1197985107.png")
> system("convert tmp/2fl6v1197985107.ps tmp/2fl6v1197985107.png")
> system("convert tmp/30cf81197985107.ps tmp/30cf81197985107.png")
> system("convert tmp/4ri111197985107.ps tmp/4ri111197985107.png")
> system("convert tmp/5b8pv1197985107.ps tmp/5b8pv1197985107.png")
> system("convert tmp/6f38o1197985107.ps tmp/6f38o1197985107.png")
> system("convert tmp/7bglz1197985107.ps tmp/7bglz1197985107.png")
> system("convert tmp/8adiu1197985107.ps tmp/8adiu1197985107.png")
> system("convert tmp/98hni1197985107.ps tmp/98hni1197985107.png")
>
>
> proc.time()
user system elapsed
2.263 1.445 2.569