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(20.7246301,0,21.44580352,0,22.09413114,0,21.53321848,0,23.3470789,0,23.5656163,0,26.42117166,0,25.21193138,0,26.43574082,0,29.33500366,0,29.40056488,0,33.05013946,0,28.38072368,0,26.0059506,0,29.31314992,0,30.36212944,0,35.74543406,0,36.15337054,0,34.20838768,0,37.90895432,0,38.70297354,0,42.11944156,0,42.16314904,0,39.79566054,0,37.36261082,0,38.3533137,0,42.60022384,0,41.24529196,0,42.15586446,0,46.94183352,0,47.42990038,0,47.0583868,0,50.18347162,0,50.12519498,0,43.22669772,0,40.04333626,0,40.37114236,0,42.2141411,0,36.99838182,0,39.74466848,0,42.68035422,0,46.2935059,0,46.97097184,0,48.72655562,0,52.36884562,0,50.05234918,0,54.03701444,0,57.78128856,0,64.71620872,0,63.4122689,0,64.3592643,0,66.02743312,0,72.13919574,0,76.60464328,0,86.97060062,0,93.48301514,0,95.58825876,0,81.88596378,1,70.5511573,1,50.38015528,1,36.24807008,1),dim=c(2,61),dimnames=list(c('Olie','Dumivariabele'),1:61))
> y <- array(NA,dim=c(2,61),dimnames=list(c('Olie','Dumivariabele'),1:61))
> 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
Olie Dumivariabele M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 20.72463 0 1 0 0 0 0 0 0 0 0 0 0 1
2 21.44580 0 0 1 0 0 0 0 0 0 0 0 0 2
3 22.09413 0 0 0 1 0 0 0 0 0 0 0 0 3
4 21.53322 0 0 0 0 1 0 0 0 0 0 0 0 4
5 23.34708 0 0 0 0 0 1 0 0 0 0 0 0 5
6 23.56562 0 0 0 0 0 0 1 0 0 0 0 0 6
7 26.42117 0 0 0 0 0 0 0 1 0 0 0 0 7
8 25.21193 0 0 0 0 0 0 0 0 1 0 0 0 8
9 26.43574 0 0 0 0 0 0 0 0 0 1 0 0 9
10 29.33500 0 0 0 0 0 0 0 0 0 0 1 0 10
11 29.40056 0 0 0 0 0 0 0 0 0 0 0 1 11
12 33.05014 0 0 0 0 0 0 0 0 0 0 0 0 12
13 28.38072 0 1 0 0 0 0 0 0 0 0 0 0 13
14 26.00595 0 0 1 0 0 0 0 0 0 0 0 0 14
15 29.31315 0 0 0 1 0 0 0 0 0 0 0 0 15
16 30.36213 0 0 0 0 1 0 0 0 0 0 0 0 16
17 35.74543 0 0 0 0 0 1 0 0 0 0 0 0 17
18 36.15337 0 0 0 0 0 0 1 0 0 0 0 0 18
19 34.20839 0 0 0 0 0 0 0 1 0 0 0 0 19
20 37.90895 0 0 0 0 0 0 0 0 1 0 0 0 20
21 38.70297 0 0 0 0 0 0 0 0 0 1 0 0 21
22 42.11944 0 0 0 0 0 0 0 0 0 0 1 0 22
23 42.16315 0 0 0 0 0 0 0 0 0 0 0 1 23
24 39.79566 0 0 0 0 0 0 0 0 0 0 0 0 24
25 37.36261 0 1 0 0 0 0 0 0 0 0 0 0 25
26 38.35331 0 0 1 0 0 0 0 0 0 0 0 0 26
27 42.60022 0 0 0 1 0 0 0 0 0 0 0 0 27
28 41.24529 0 0 0 0 1 0 0 0 0 0 0 0 28
29 42.15586 0 0 0 0 0 1 0 0 0 0 0 0 29
30 46.94183 0 0 0 0 0 0 1 0 0 0 0 0 30
31 47.42990 0 0 0 0 0 0 0 1 0 0 0 0 31
32 47.05839 0 0 0 0 0 0 0 0 1 0 0 0 32
33 50.18347 0 0 0 0 0 0 0 0 0 1 0 0 33
34 50.12519 0 0 0 0 0 0 0 0 0 0 1 0 34
35 43.22670 0 0 0 0 0 0 0 0 0 0 0 1 35
36 40.04334 0 0 0 0 0 0 0 0 0 0 0 0 36
37 40.37114 0 1 0 0 0 0 0 0 0 0 0 0 37
38 42.21414 0 0 1 0 0 0 0 0 0 0 0 0 38
39 36.99838 0 0 0 1 0 0 0 0 0 0 0 0 39
40 39.74467 0 0 0 0 1 0 0 0 0 0 0 0 40
41 42.68035 0 0 0 0 0 1 0 0 0 0 0 0 41
42 46.29351 0 0 0 0 0 0 1 0 0 0 0 0 42
43 46.97097 0 0 0 0 0 0 0 1 0 0 0 0 43
44 48.72656 0 0 0 0 0 0 0 0 1 0 0 0 44
45 52.36885 0 0 0 0 0 0 0 0 0 1 0 0 45
46 50.05235 0 0 0 0 0 0 0 0 0 0 1 0 46
47 54.03701 0 0 0 0 0 0 0 0 0 0 0 1 47
48 57.78129 0 0 0 0 0 0 0 0 0 0 0 0 48
49 64.71621 0 1 0 0 0 0 0 0 0 0 0 0 49
50 63.41227 0 0 1 0 0 0 0 0 0 0 0 0 50
51 64.35926 0 0 0 1 0 0 0 0 0 0 0 0 51
52 66.02743 0 0 0 0 1 0 0 0 0 0 0 0 52
53 72.13920 0 0 0 0 0 1 0 0 0 0 0 0 53
54 76.60464 0 0 0 0 0 0 1 0 0 0 0 0 54
55 86.97060 0 0 0 0 0 0 0 1 0 0 0 0 55
56 93.48302 0 0 0 0 0 0 0 0 1 0 0 0 56
57 95.58826 0 0 0 0 0 0 0 0 0 1 0 0 57
58 81.88596 1 0 0 0 0 0 0 0 0 0 1 0 58
59 70.55116 1 0 0 0 0 0 0 0 0 0 0 1 59
60 50.38016 1 0 0 0 0 0 0 0 0 0 0 0 60
61 36.24807 1 1 0 0 0 0 0 0 0 0 0 0 61
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Dumivariabele M1 M2 M3
13.6377 -10.6175 -2.0557 1.0349 0.9134
M4 M5 M6 M7 M8
0.7147 3.2375 5.0275 6.6077 7.7770
M9 M10 M11 t
9.0469 8.3099 4.5738 0.9082
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-20.118 -4.423 0.191 3.548 21.208
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 13.63768 4.81914 2.830 0.00683 **
Dumivariabele -10.61746 5.67324 -1.871 0.06751 .
M1 -2.05570 5.62034 -0.366 0.71619
M2 1.03489 5.95570 0.174 0.86280
M3 0.91341 5.95266 0.153 0.87870
M4 0.71470 5.95058 0.120 0.90491
M5 3.23752 5.94944 0.544 0.58890
M6 5.02751 5.94926 0.845 0.40236
M7 6.60770 5.95003 1.111 0.27242
M8 7.77704 5.95175 1.307 0.19768
M9 9.04691 5.95443 1.519 0.13537
M10 8.30992 5.86123 1.418 0.16285
M11 4.57382 5.85978 0.781 0.43898
t 0.90822 0.07529 12.063 5.37e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 9.264 on 47 degrees of freedom
Multiple R-squared: 0.7892, Adjusted R-squared: 0.7309
F-statistic: 13.53 on 13 and 47 DF, p-value: 9.118e-12
> postscript(file="/var/www/html/freestat/rcomp/tmp/1ppc61229870508.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/2bntb1229870508.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/3vmmq1229870508.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/42wss1229870508.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/51qfk1229870508.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
> grid()
> dev.off()
null device
1
> (myerror <- as.ts(mysum$resid))
Time Series:
Start = 1
End = 61
Frequency = 1
1 2 3 4 5 6
8.23443210 4.95679532 4.81838830 3.54795755 1.93078079 -0.54889025
7 8 9 10 11 12
-0.18174741 -3.46854991 -4.42282989 -1.69479110 1.19864407 8.51381931
13 14 15 16 17 18
4.99188200 -1.38170128 1.13876340 1.47822482 3.43049226 1.14022031
19 20 21 22 23 24
-3.29317508 -1.67017065 -3.05424085 0.19100312 3.06258455 4.36069671
25 26 27 28 29 30
3.07512546 0.06701814 3.52719364 1.46274366 -1.05772102 1.03003961
31 32 33 34 35 36
-0.97030606 -3.41938185 -2.47238645 -2.70188714 -6.77251045 -6.29027125
37 38 39 40 41 42
-4.81498668 -6.97079814 -12.97329206 -10.93652350 -11.43187494 -10.51693169
43 44 45 46 47 48
-12.32787828 -12.64985671 -11.18565613 -13.67337663 -6.86083741 0.54903737
49 50 51 52 53 54
8.63143599 3.32868597 3.48894673 4.44759746 7.12832290 8.89556201
55 56 57 58 59 60
16.77310682 21.20795913 21.13511333 17.87905176 9.37211923 -7.13328213
61
-20.11788886
> postscript(file="/var/www/html/freestat/rcomp/tmp/6q38a1229870508.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 = 61
Frequency = 1
lag(myerror, k = 1) myerror
0 8.23443210 NA
1 4.95679532 8.23443210
2 4.81838830 4.95679532
3 3.54795755 4.81838830
4 1.93078079 3.54795755
5 -0.54889025 1.93078079
6 -0.18174741 -0.54889025
7 -3.46854991 -0.18174741
8 -4.42282989 -3.46854991
9 -1.69479110 -4.42282989
10 1.19864407 -1.69479110
11 8.51381931 1.19864407
12 4.99188200 8.51381931
13 -1.38170128 4.99188200
14 1.13876340 -1.38170128
15 1.47822482 1.13876340
16 3.43049226 1.47822482
17 1.14022031 3.43049226
18 -3.29317508 1.14022031
19 -1.67017065 -3.29317508
20 -3.05424085 -1.67017065
21 0.19100312 -3.05424085
22 3.06258455 0.19100312
23 4.36069671 3.06258455
24 3.07512546 4.36069671
25 0.06701814 3.07512546
26 3.52719364 0.06701814
27 1.46274366 3.52719364
28 -1.05772102 1.46274366
29 1.03003961 -1.05772102
30 -0.97030606 1.03003961
31 -3.41938185 -0.97030606
32 -2.47238645 -3.41938185
33 -2.70188714 -2.47238645
34 -6.77251045 -2.70188714
35 -6.29027125 -6.77251045
36 -4.81498668 -6.29027125
37 -6.97079814 -4.81498668
38 -12.97329206 -6.97079814
39 -10.93652350 -12.97329206
40 -11.43187494 -10.93652350
41 -10.51693169 -11.43187494
42 -12.32787828 -10.51693169
43 -12.64985671 -12.32787828
44 -11.18565613 -12.64985671
45 -13.67337663 -11.18565613
46 -6.86083741 -13.67337663
47 0.54903737 -6.86083741
48 8.63143599 0.54903737
49 3.32868597 8.63143599
50 3.48894673 3.32868597
51 4.44759746 3.48894673
52 7.12832290 4.44759746
53 8.89556201 7.12832290
54 16.77310682 8.89556201
55 21.20795913 16.77310682
56 21.13511333 21.20795913
57 17.87905176 21.13511333
58 9.37211923 17.87905176
59 -7.13328213 9.37211923
60 -20.11788886 -7.13328213
61 NA -20.11788886
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 4.95679532 8.23443210
[2,] 4.81838830 4.95679532
[3,] 3.54795755 4.81838830
[4,] 1.93078079 3.54795755
[5,] -0.54889025 1.93078079
[6,] -0.18174741 -0.54889025
[7,] -3.46854991 -0.18174741
[8,] -4.42282989 -3.46854991
[9,] -1.69479110 -4.42282989
[10,] 1.19864407 -1.69479110
[11,] 8.51381931 1.19864407
[12,] 4.99188200 8.51381931
[13,] -1.38170128 4.99188200
[14,] 1.13876340 -1.38170128
[15,] 1.47822482 1.13876340
[16,] 3.43049226 1.47822482
[17,] 1.14022031 3.43049226
[18,] -3.29317508 1.14022031
[19,] -1.67017065 -3.29317508
[20,] -3.05424085 -1.67017065
[21,] 0.19100312 -3.05424085
[22,] 3.06258455 0.19100312
[23,] 4.36069671 3.06258455
[24,] 3.07512546 4.36069671
[25,] 0.06701814 3.07512546
[26,] 3.52719364 0.06701814
[27,] 1.46274366 3.52719364
[28,] -1.05772102 1.46274366
[29,] 1.03003961 -1.05772102
[30,] -0.97030606 1.03003961
[31,] -3.41938185 -0.97030606
[32,] -2.47238645 -3.41938185
[33,] -2.70188714 -2.47238645
[34,] -6.77251045 -2.70188714
[35,] -6.29027125 -6.77251045
[36,] -4.81498668 -6.29027125
[37,] -6.97079814 -4.81498668
[38,] -12.97329206 -6.97079814
[39,] -10.93652350 -12.97329206
[40,] -11.43187494 -10.93652350
[41,] -10.51693169 -11.43187494
[42,] -12.32787828 -10.51693169
[43,] -12.64985671 -12.32787828
[44,] -11.18565613 -12.64985671
[45,] -13.67337663 -11.18565613
[46,] -6.86083741 -13.67337663
[47,] 0.54903737 -6.86083741
[48,] 8.63143599 0.54903737
[49,] 3.32868597 8.63143599
[50,] 3.48894673 3.32868597
[51,] 4.44759746 3.48894673
[52,] 7.12832290 4.44759746
[53,] 8.89556201 7.12832290
[54,] 16.77310682 8.89556201
[55,] 21.20795913 16.77310682
[56,] 21.13511333 21.20795913
[57,] 17.87905176 21.13511333
[58,] 9.37211923 17.87905176
[59,] -7.13328213 9.37211923
[60,] -20.11788886 -7.13328213
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 4.95679532 8.23443210
2 4.81838830 4.95679532
3 3.54795755 4.81838830
4 1.93078079 3.54795755
5 -0.54889025 1.93078079
6 -0.18174741 -0.54889025
7 -3.46854991 -0.18174741
8 -4.42282989 -3.46854991
9 -1.69479110 -4.42282989
10 1.19864407 -1.69479110
11 8.51381931 1.19864407
12 4.99188200 8.51381931
13 -1.38170128 4.99188200
14 1.13876340 -1.38170128
15 1.47822482 1.13876340
16 3.43049226 1.47822482
17 1.14022031 3.43049226
18 -3.29317508 1.14022031
19 -1.67017065 -3.29317508
20 -3.05424085 -1.67017065
21 0.19100312 -3.05424085
22 3.06258455 0.19100312
23 4.36069671 3.06258455
24 3.07512546 4.36069671
25 0.06701814 3.07512546
26 3.52719364 0.06701814
27 1.46274366 3.52719364
28 -1.05772102 1.46274366
29 1.03003961 -1.05772102
30 -0.97030606 1.03003961
31 -3.41938185 -0.97030606
32 -2.47238645 -3.41938185
33 -2.70188714 -2.47238645
34 -6.77251045 -2.70188714
35 -6.29027125 -6.77251045
36 -4.81498668 -6.29027125
37 -6.97079814 -4.81498668
38 -12.97329206 -6.97079814
39 -10.93652350 -12.97329206
40 -11.43187494 -10.93652350
41 -10.51693169 -11.43187494
42 -12.32787828 -10.51693169
43 -12.64985671 -12.32787828
44 -11.18565613 -12.64985671
45 -13.67337663 -11.18565613
46 -6.86083741 -13.67337663
47 0.54903737 -6.86083741
48 8.63143599 0.54903737
49 3.32868597 8.63143599
50 3.48894673 3.32868597
51 4.44759746 3.48894673
52 7.12832290 4.44759746
53 8.89556201 7.12832290
54 16.77310682 8.89556201
55 21.20795913 16.77310682
56 21.13511333 21.20795913
57 17.87905176 21.13511333
58 9.37211923 17.87905176
59 -7.13328213 9.37211923
60 -20.11788886 -7.13328213
> 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/7j8nt1229870508.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/8damy1229870508.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/958s71229870508.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
>
> #Note: the /var/www/html/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/freestat/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/10pm4z1229870508.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/11wgj21229870508.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/123b0n1229870508.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/13526f1229870508.tab")
>
> system("convert tmp/1ppc61229870508.ps tmp/1ppc61229870508.png")
> system("convert tmp/2bntb1229870508.ps tmp/2bntb1229870508.png")
> system("convert tmp/3vmmq1229870508.ps tmp/3vmmq1229870508.png")
> system("convert tmp/42wss1229870508.ps tmp/42wss1229870508.png")
> system("convert tmp/51qfk1229870508.ps tmp/51qfk1229870508.png")
> system("convert tmp/6q38a1229870508.ps tmp/6q38a1229870508.png")
> system("convert tmp/7j8nt1229870508.ps tmp/7j8nt1229870508.png")
> system("convert tmp/8damy1229870508.ps tmp/8damy1229870508.png")
> system("convert tmp/958s71229870508.ps tmp/958s71229870508.png")
>
>
> proc.time()
user system elapsed
3.070 2.304 5.493