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(24.67,0,25.59,0,26.09,0,28.37,0,27.34,0,24.46,0,27.46,0,30.23,0,32.33,0,29.87,0,24.87,0,25.48,0,27.28,0,28.24,0,29.58,0,26.95,0,29.08,0,28.76,0,29.59,0,30.7,0,30.52,0,32.67,0,33.19,0,37.13,0,35.54,0,37.75,0,41.84,0,42.94,0,49.14,0,44.61,0,40.22,0,44.23,0,45.85,0,53.38,0,53.26,0,51.8,0,55.3,0,57.81,0,63.96,0,63.77,0,59.15,0,56.12,0,57.42,0,63.52,0,61.71,0,63.01,0,68.18,0,72.03,0,69.75,0,74.41,0,74.33,0,64.24,1,60.03,1,59.44,1,62.5,1,55.04,1,58.34,1,61.92,0,67.65,0,67.68,0),dim=c(2,60),dimnames=list(c('Y','D'),1:60))
> y <- array(NA,dim=c(2,60),dimnames=list(c('Y','D'),1:60))
> 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 = 'Include Monthly 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 D M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 24.67 0 1 0 0 0 0 0 0 0 0 0 0 1
2 25.59 0 0 1 0 0 0 0 0 0 0 0 0 2
3 26.09 0 0 0 1 0 0 0 0 0 0 0 0 3
4 28.37 0 0 0 0 1 0 0 0 0 0 0 0 4
5 27.34 0 0 0 0 0 1 0 0 0 0 0 0 5
6 24.46 0 0 0 0 0 0 1 0 0 0 0 0 6
7 27.46 0 0 0 0 0 0 0 1 0 0 0 0 7
8 30.23 0 0 0 0 0 0 0 0 1 0 0 0 8
9 32.33 0 0 0 0 0 0 0 0 0 1 0 0 9
10 29.87 0 0 0 0 0 0 0 0 0 0 1 0 10
11 24.87 0 0 0 0 0 0 0 0 0 0 0 1 11
12 25.48 0 0 0 0 0 0 0 0 0 0 0 0 12
13 27.28 0 1 0 0 0 0 0 0 0 0 0 0 13
14 28.24 0 0 1 0 0 0 0 0 0 0 0 0 14
15 29.58 0 0 0 1 0 0 0 0 0 0 0 0 15
16 26.95 0 0 0 0 1 0 0 0 0 0 0 0 16
17 29.08 0 0 0 0 0 1 0 0 0 0 0 0 17
18 28.76 0 0 0 0 0 0 1 0 0 0 0 0 18
19 29.59 0 0 0 0 0 0 0 1 0 0 0 0 19
20 30.70 0 0 0 0 0 0 0 0 1 0 0 0 20
21 30.52 0 0 0 0 0 0 0 0 0 1 0 0 21
22 32.67 0 0 0 0 0 0 0 0 0 0 1 0 22
23 33.19 0 0 0 0 0 0 0 0 0 0 0 1 23
24 37.13 0 0 0 0 0 0 0 0 0 0 0 0 24
25 35.54 0 1 0 0 0 0 0 0 0 0 0 0 25
26 37.75 0 0 1 0 0 0 0 0 0 0 0 0 26
27 41.84 0 0 0 1 0 0 0 0 0 0 0 0 27
28 42.94 0 0 0 0 1 0 0 0 0 0 0 0 28
29 49.14 0 0 0 0 0 1 0 0 0 0 0 0 29
30 44.61 0 0 0 0 0 0 1 0 0 0 0 0 30
31 40.22 0 0 0 0 0 0 0 1 0 0 0 0 31
32 44.23 0 0 0 0 0 0 0 0 1 0 0 0 32
33 45.85 0 0 0 0 0 0 0 0 0 1 0 0 33
34 53.38 0 0 0 0 0 0 0 0 0 0 1 0 34
35 53.26 0 0 0 0 0 0 0 0 0 0 0 1 35
36 51.80 0 0 0 0 0 0 0 0 0 0 0 0 36
37 55.30 0 1 0 0 0 0 0 0 0 0 0 0 37
38 57.81 0 0 1 0 0 0 0 0 0 0 0 0 38
39 63.96 0 0 0 1 0 0 0 0 0 0 0 0 39
40 63.77 0 0 0 0 1 0 0 0 0 0 0 0 40
41 59.15 0 0 0 0 0 1 0 0 0 0 0 0 41
42 56.12 0 0 0 0 0 0 1 0 0 0 0 0 42
43 57.42 0 0 0 0 0 0 0 1 0 0 0 0 43
44 63.52 0 0 0 0 0 0 0 0 1 0 0 0 44
45 61.71 0 0 0 0 0 0 0 0 0 1 0 0 45
46 63.01 0 0 0 0 0 0 0 0 0 0 1 0 46
47 68.18 0 0 0 0 0 0 0 0 0 0 0 1 47
48 72.03 0 0 0 0 0 0 0 0 0 0 0 0 48
49 69.75 0 1 0 0 0 0 0 0 0 0 0 0 49
50 74.41 0 0 1 0 0 0 0 0 0 0 0 0 50
51 74.33 0 0 0 1 0 0 0 0 0 0 0 0 51
52 64.24 1 0 0 0 1 0 0 0 0 0 0 0 52
53 60.03 1 0 0 0 0 1 0 0 0 0 0 0 53
54 59.44 1 0 0 0 0 0 1 0 0 0 0 0 54
55 62.50 1 0 0 0 0 0 0 1 0 0 0 0 55
56 55.04 1 0 0 0 0 0 0 0 1 0 0 0 56
57 58.34 1 0 0 0 0 0 0 0 0 1 0 0 57
58 61.92 0 0 0 0 0 0 0 0 0 0 1 0 58
59 67.65 0 0 0 0 0 0 0 0 0 0 0 1 59
60 67.68 0 0 0 0 0 0 0 0 0 0 0 0 60
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) D M1 M2 M3 M4
16.0412 -9.6569 2.3121 3.5979 5.0317 4.0909
M5 M6 M7 M8 M9 M10
2.8187 -0.4175 -0.6237 -0.2839 -0.2440 -0.7216
M11 t
-0.4278 0.9662
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-9.4386 -4.2866 0.5663 3.9907 9.6117
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 16.04117 2.94659 5.444 1.95e-06 ***
D -9.65694 2.83535 -3.406 0.00138 **
M1 2.31209 3.44190 0.672 0.50510
M2 3.59790 3.43508 1.047 0.30039
M3 5.03171 3.42890 1.467 0.14906
M4 4.09091 3.50077 1.169 0.24860
M5 2.81872 3.49214 0.807 0.42373
M6 -0.41747 3.48414 -0.120 0.90515
M7 -0.62366 3.47676 -0.179 0.85843
M8 -0.28385 3.47001 -0.082 0.93516
M9 -0.24404 3.46389 -0.070 0.94414
M10 -0.72162 3.40374 -0.212 0.83304
M11 -0.42781 3.40275 -0.126 0.90050
t 0.96619 0.04726 20.446 < 2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 5.38 on 46 degrees of freedom
Multiple R-squared: 0.9147, Adjusted R-squared: 0.8905
F-statistic: 37.92 on 13 and 46 DF, p-value: < 2.2e-16
> postscript(file="/var/www/html/freestat/rcomp/tmp/1wup71227481052.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/28pv51227481052.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/331qv1227481052.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/41n461227481052.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/5snoi1227481052.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
> grid()
> dev.off()
null device
1
> (myerror <- as.ts(mysum$resid))
Time Series:
Start = 1
End = 60
Frequency = 1
1 2 3 4 5
5.3505555556 4.0185555556 2.1185555556 4.3731666667 3.6491666667
6 7 8 9 10
3.0391666667 5.2791666667 6.7431666667 7.8371666667 4.8885555556
11 12 13 14 15
-1.3714444444 -2.1554444444 -3.6337222222 -4.9257222222 -5.9857222222
16 17 18 19 20
-8.6411111111 -6.2051111111 -4.2551111111 -4.1851111111 -4.3811111111
21 22 23 24 25
-5.5671111111 -3.9057222222 -4.6457222222 -2.0997222222 -6.9680000000
26 27 28 29 30
-7.0100000000 -5.3200000000 -4.2453888889 2.2606111111 0.0006111111
31 32 33 34 35
-5.1493888889 -2.4453888889 -1.8313888889 5.2100000000 3.8300000000
36 37 38 39 40
0.9760000000 1.1977222222 1.4557222222 5.2057222222 4.9903333333
41 42 43 44 45
0.6763333333 -0.0836666667 0.4563333333 5.2503333333 2.4343333333
46 47 48 49 50
3.2457222222 7.1557222222 9.6117222222 4.0534444444 6.4614444444
51 52 53 54 55
3.9814444444 3.5230000000 -0.3810000000 1.2990000000 3.5990000000
56 57 58 59 60
-5.1670000000 -2.8730000000 -9.4385555556 -4.9685555556 -6.3325555556
> postscript(file="/var/www/html/freestat/rcomp/tmp/61y9h1227481052.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 = 60
Frequency = 1
lag(myerror, k = 1) myerror
0 5.3505555556 NA
1 4.0185555556 5.3505555556
2 2.1185555556 4.0185555556
3 4.3731666667 2.1185555556
4 3.6491666667 4.3731666667
5 3.0391666667 3.6491666667
6 5.2791666667 3.0391666667
7 6.7431666667 5.2791666667
8 7.8371666667 6.7431666667
9 4.8885555556 7.8371666667
10 -1.3714444444 4.8885555556
11 -2.1554444444 -1.3714444444
12 -3.6337222222 -2.1554444444
13 -4.9257222222 -3.6337222222
14 -5.9857222222 -4.9257222222
15 -8.6411111111 -5.9857222222
16 -6.2051111111 -8.6411111111
17 -4.2551111111 -6.2051111111
18 -4.1851111111 -4.2551111111
19 -4.3811111111 -4.1851111111
20 -5.5671111111 -4.3811111111
21 -3.9057222222 -5.5671111111
22 -4.6457222222 -3.9057222222
23 -2.0997222222 -4.6457222222
24 -6.9680000000 -2.0997222222
25 -7.0100000000 -6.9680000000
26 -5.3200000000 -7.0100000000
27 -4.2453888889 -5.3200000000
28 2.2606111111 -4.2453888889
29 0.0006111111 2.2606111111
30 -5.1493888889 0.0006111111
31 -2.4453888889 -5.1493888889
32 -1.8313888889 -2.4453888889
33 5.2100000000 -1.8313888889
34 3.8300000000 5.2100000000
35 0.9760000000 3.8300000000
36 1.1977222222 0.9760000000
37 1.4557222222 1.1977222222
38 5.2057222222 1.4557222222
39 4.9903333333 5.2057222222
40 0.6763333333 4.9903333333
41 -0.0836666667 0.6763333333
42 0.4563333333 -0.0836666667
43 5.2503333333 0.4563333333
44 2.4343333333 5.2503333333
45 3.2457222222 2.4343333333
46 7.1557222222 3.2457222222
47 9.6117222222 7.1557222222
48 4.0534444444 9.6117222222
49 6.4614444444 4.0534444444
50 3.9814444444 6.4614444444
51 3.5230000000 3.9814444444
52 -0.3810000000 3.5230000000
53 1.2990000000 -0.3810000000
54 3.5990000000 1.2990000000
55 -5.1670000000 3.5990000000
56 -2.8730000000 -5.1670000000
57 -9.4385555556 -2.8730000000
58 -4.9685555556 -9.4385555556
59 -6.3325555556 -4.9685555556
60 NA -6.3325555556
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 4.0185555556 5.3505555556
[2,] 2.1185555556 4.0185555556
[3,] 4.3731666667 2.1185555556
[4,] 3.6491666667 4.3731666667
[5,] 3.0391666667 3.6491666667
[6,] 5.2791666667 3.0391666667
[7,] 6.7431666667 5.2791666667
[8,] 7.8371666667 6.7431666667
[9,] 4.8885555556 7.8371666667
[10,] -1.3714444444 4.8885555556
[11,] -2.1554444444 -1.3714444444
[12,] -3.6337222222 -2.1554444444
[13,] -4.9257222222 -3.6337222222
[14,] -5.9857222222 -4.9257222222
[15,] -8.6411111111 -5.9857222222
[16,] -6.2051111111 -8.6411111111
[17,] -4.2551111111 -6.2051111111
[18,] -4.1851111111 -4.2551111111
[19,] -4.3811111111 -4.1851111111
[20,] -5.5671111111 -4.3811111111
[21,] -3.9057222222 -5.5671111111
[22,] -4.6457222222 -3.9057222222
[23,] -2.0997222222 -4.6457222222
[24,] -6.9680000000 -2.0997222222
[25,] -7.0100000000 -6.9680000000
[26,] -5.3200000000 -7.0100000000
[27,] -4.2453888889 -5.3200000000
[28,] 2.2606111111 -4.2453888889
[29,] 0.0006111111 2.2606111111
[30,] -5.1493888889 0.0006111111
[31,] -2.4453888889 -5.1493888889
[32,] -1.8313888889 -2.4453888889
[33,] 5.2100000000 -1.8313888889
[34,] 3.8300000000 5.2100000000
[35,] 0.9760000000 3.8300000000
[36,] 1.1977222222 0.9760000000
[37,] 1.4557222222 1.1977222222
[38,] 5.2057222222 1.4557222222
[39,] 4.9903333333 5.2057222222
[40,] 0.6763333333 4.9903333333
[41,] -0.0836666667 0.6763333333
[42,] 0.4563333333 -0.0836666667
[43,] 5.2503333333 0.4563333333
[44,] 2.4343333333 5.2503333333
[45,] 3.2457222222 2.4343333333
[46,] 7.1557222222 3.2457222222
[47,] 9.6117222222 7.1557222222
[48,] 4.0534444444 9.6117222222
[49,] 6.4614444444 4.0534444444
[50,] 3.9814444444 6.4614444444
[51,] 3.5230000000 3.9814444444
[52,] -0.3810000000 3.5230000000
[53,] 1.2990000000 -0.3810000000
[54,] 3.5990000000 1.2990000000
[55,] -5.1670000000 3.5990000000
[56,] -2.8730000000 -5.1670000000
[57,] -9.4385555556 -2.8730000000
[58,] -4.9685555556 -9.4385555556
[59,] -6.3325555556 -4.9685555556
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 4.0185555556 5.3505555556
2 2.1185555556 4.0185555556
3 4.3731666667 2.1185555556
4 3.6491666667 4.3731666667
5 3.0391666667 3.6491666667
6 5.2791666667 3.0391666667
7 6.7431666667 5.2791666667
8 7.8371666667 6.7431666667
9 4.8885555556 7.8371666667
10 -1.3714444444 4.8885555556
11 -2.1554444444 -1.3714444444
12 -3.6337222222 -2.1554444444
13 -4.9257222222 -3.6337222222
14 -5.9857222222 -4.9257222222
15 -8.6411111111 -5.9857222222
16 -6.2051111111 -8.6411111111
17 -4.2551111111 -6.2051111111
18 -4.1851111111 -4.2551111111
19 -4.3811111111 -4.1851111111
20 -5.5671111111 -4.3811111111
21 -3.9057222222 -5.5671111111
22 -4.6457222222 -3.9057222222
23 -2.0997222222 -4.6457222222
24 -6.9680000000 -2.0997222222
25 -7.0100000000 -6.9680000000
26 -5.3200000000 -7.0100000000
27 -4.2453888889 -5.3200000000
28 2.2606111111 -4.2453888889
29 0.0006111111 2.2606111111
30 -5.1493888889 0.0006111111
31 -2.4453888889 -5.1493888889
32 -1.8313888889 -2.4453888889
33 5.2100000000 -1.8313888889
34 3.8300000000 5.2100000000
35 0.9760000000 3.8300000000
36 1.1977222222 0.9760000000
37 1.4557222222 1.1977222222
38 5.2057222222 1.4557222222
39 4.9903333333 5.2057222222
40 0.6763333333 4.9903333333
41 -0.0836666667 0.6763333333
42 0.4563333333 -0.0836666667
43 5.2503333333 0.4563333333
44 2.4343333333 5.2503333333
45 3.2457222222 2.4343333333
46 7.1557222222 3.2457222222
47 9.6117222222 7.1557222222
48 4.0534444444 9.6117222222
49 6.4614444444 4.0534444444
50 3.9814444444 6.4614444444
51 3.5230000000 3.9814444444
52 -0.3810000000 3.5230000000
53 1.2990000000 -0.3810000000
54 3.5990000000 1.2990000000
55 -5.1670000000 3.5990000000
56 -2.8730000000 -5.1670000000
57 -9.4385555556 -2.8730000000
58 -4.9685555556 -9.4385555556
59 -6.3325555556 -4.9685555556
> 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/7iy1e1227481052.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/8w5yg1227481052.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/9djg21227481052.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
>
> #Note: the /var/www/html/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/freestat/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/10s2q21227481052.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/11tzln1227481052.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/12w6kn1227481053.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/13wvj21227481053.tab")
>
> system("convert tmp/1wup71227481052.ps tmp/1wup71227481052.png")
> system("convert tmp/28pv51227481052.ps tmp/28pv51227481052.png")
> system("convert tmp/331qv1227481052.ps tmp/331qv1227481052.png")
> system("convert tmp/41n461227481052.ps tmp/41n461227481052.png")
> system("convert tmp/5snoi1227481052.ps tmp/5snoi1227481052.png")
> system("convert tmp/61y9h1227481052.ps tmp/61y9h1227481052.png")
> system("convert tmp/7iy1e1227481052.ps tmp/7iy1e1227481052.png")
> system("convert tmp/8w5yg1227481052.ps tmp/8w5yg1227481052.png")
> system("convert tmp/9djg21227481052.ps tmp/9djg21227481052.png")
>
>
> proc.time()
user system elapsed
2.986 2.241 3.420