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.
Natural language support but running in an English locale
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(1.39,1.08,1.34,1.12,1.33,1.12,1.3,1.16,1.28,1.16,1.29,1.16,1.29,1.16,1.28,1.15,1.27,1.17,1.26,1.16,1.29,1.19,1.36,1.13,1.33,1.14,1.35,1.13,1.31,1.16,1.3,1.17,1.32,1.14,1.33,1.14,1.36,1.11,1.35,1.12,1.4,1.08,1.41,1.07,1.4,1.09,1.4,1.08,1.4,1.08,1.41,1.08,1.4,1.09,1.39,1.08,1.41,1.07,1.42,1.07,1.43,1.07,1.42,1.08,1.42,1.07,1.43,1.06,1.43,1.06,1.43,1.06,1.46,1.04,1.47,1.03,1.47,1.03,1.46,1.04,1.47,1.03,1.49,1.02,1.5,1.01,1.47,1.03,1.48,1.02,1.49,1.01,1.49,1.02,1.5,1.01,1.48,1.02,1.46,1.03,1.43,1.04,1.44,1.04,1.43,1.03),dim=c(2,53),dimnames=list(c('eu/us','us/ch'),1:53))
> y <- array(NA,dim=c(2,53),dimnames=list(c('eu/us','us/ch'),1:53))
> 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 = 'Include Monthly Dummies'
> par1 = '2'
> #'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
us/ch eu/us M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11
1 1.08 1.39 1 0 0 0 0 0 0 0 0 0 0
2 1.12 1.34 0 1 0 0 0 0 0 0 0 0 0
3 1.12 1.33 0 0 1 0 0 0 0 0 0 0 0
4 1.16 1.30 0 0 0 1 0 0 0 0 0 0 0
5 1.16 1.28 0 0 0 0 1 0 0 0 0 0 0
6 1.16 1.29 0 0 0 0 0 1 0 0 0 0 0
7 1.16 1.29 0 0 0 0 0 0 1 0 0 0 0
8 1.15 1.28 0 0 0 0 0 0 0 1 0 0 0
9 1.17 1.27 0 0 0 0 0 0 0 0 1 0 0
10 1.16 1.26 0 0 0 0 0 0 0 0 0 1 0
11 1.19 1.29 0 0 0 0 0 0 0 0 0 0 1
12 1.13 1.36 0 0 0 0 0 0 0 0 0 0 0
13 1.14 1.33 1 0 0 0 0 0 0 0 0 0 0
14 1.13 1.35 0 1 0 0 0 0 0 0 0 0 0
15 1.16 1.31 0 0 1 0 0 0 0 0 0 0 0
16 1.17 1.30 0 0 0 1 0 0 0 0 0 0 0
17 1.14 1.32 0 0 0 0 1 0 0 0 0 0 0
18 1.14 1.33 0 0 0 0 0 1 0 0 0 0 0
19 1.11 1.36 0 0 0 0 0 0 1 0 0 0 0
20 1.12 1.35 0 0 0 0 0 0 0 1 0 0 0
21 1.08 1.40 0 0 0 0 0 0 0 0 1 0 0
22 1.07 1.41 0 0 0 0 0 0 0 0 0 1 0
23 1.09 1.40 0 0 0 0 0 0 0 0 0 0 1
24 1.08 1.40 0 0 0 0 0 0 0 0 0 0 0
25 1.08 1.40 1 0 0 0 0 0 0 0 0 0 0
26 1.08 1.41 0 1 0 0 0 0 0 0 0 0 0
27 1.09 1.40 0 0 1 0 0 0 0 0 0 0 0
28 1.08 1.39 0 0 0 1 0 0 0 0 0 0 0
29 1.07 1.41 0 0 0 0 1 0 0 0 0 0 0
30 1.07 1.42 0 0 0 0 0 1 0 0 0 0 0
31 1.07 1.43 0 0 0 0 0 0 1 0 0 0 0
32 1.08 1.42 0 0 0 0 0 0 0 1 0 0 0
33 1.07 1.42 0 0 0 0 0 0 0 0 1 0 0
34 1.06 1.43 0 0 0 0 0 0 0 0 0 1 0
35 1.06 1.43 0 0 0 0 0 0 0 0 0 0 1
36 1.06 1.43 0 0 0 0 0 0 0 0 0 0 0
37 1.04 1.46 1 0 0 0 0 0 0 0 0 0 0
38 1.03 1.47 0 1 0 0 0 0 0 0 0 0 0
39 1.03 1.47 0 0 1 0 0 0 0 0 0 0 0
40 1.04 1.46 0 0 0 1 0 0 0 0 0 0 0
41 1.03 1.47 0 0 0 0 1 0 0 0 0 0 0
42 1.02 1.49 0 0 0 0 0 1 0 0 0 0 0
43 1.01 1.50 0 0 0 0 0 0 1 0 0 0 0
44 1.03 1.47 0 0 0 0 0 0 0 1 0 0 0
45 1.02 1.48 0 0 0 0 0 0 0 0 1 0 0
46 1.01 1.49 0 0 0 0 0 0 0 0 0 1 0
47 1.02 1.49 0 0 0 0 0 0 0 0 0 0 1
48 1.01 1.50 0 0 0 0 0 0 0 0 0 0 0
49 1.02 1.48 1 0 0 0 0 0 0 0 0 0 0
50 1.03 1.46 0 1 0 0 0 0 0 0 0 0 0
51 1.04 1.43 0 0 1 0 0 0 0 0 0 0 0
52 1.04 1.44 0 0 0 1 0 0 0 0 0 0 0
53 1.03 1.43 0 0 0 0 1 0 0 0 0 0 0
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) `eu/us` M1 M2 M3 M4
2.122236 -0.739709 -0.005767 -0.004205 -0.007520 -0.004917
M5 M6 M7 M8 M9 M10
-0.013958 -0.002088 -0.002842 -0.006438 -0.007191 -0.013493
M11
0.005206
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-0.0204940 -0.0056144 0.0002391 0.0049588 0.0167827
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 2.122236 0.029143 72.822 <2e-16 ***
`eu/us` -0.739709 0.020180 -36.655 <2e-16 ***
M1 -0.005767 0.006744 -0.855 0.3976
M2 -0.004205 0.006749 -0.623 0.5367
M3 -0.007520 0.006776 -1.110 0.2737
M4 -0.004917 0.006800 -0.723 0.4738
M5 -0.013958 0.006790 -2.056 0.0464 *
M6 -0.002088 0.007151 -0.292 0.7718
M7 -0.002842 0.007127 -0.399 0.6922
M8 -0.006438 0.007157 -0.900 0.3737
M9 -0.007191 0.007131 -1.008 0.3193
M10 -0.013493 0.007123 -1.894 0.0654 .
M11 0.005206 0.007116 0.732 0.4687
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 0.01005 on 40 degrees of freedom
Multiple R-squared: 0.972, Adjusted R-squared: 0.9636
F-statistic: 115.6 on 12 and 40 DF, p-value: < 2.2e-16
> postscript(file="/var/www/html/freestat/rcomp/tmp/1fiqi1290349509.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/2fiqi1290349509.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/389ql1290349509.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/489ql1290349509.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/589ql1290349509.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
> grid()
> dev.off()
null device
1
> (myerror <- as.ts(mysum$resid))
Time Series:
Start = 1
End = 53
Frequency = 1
1 2 3 4 5
-0.0082736018 -0.0068208055 -0.0109031321 0.0043026844 -0.0014503358
6 7 8 9 10
-0.0059230986 -0.0051694633 -0.0189709175 -0.0056143739 -0.0167100115
11 12 13 14 15
0.0167827179 0.0137681766 0.0073438477 0.0105762862 0.0143026844
16 17 18 19 20
0.0143026844 0.0081380312 0.0036652683 -0.0033898211 0.0028087248
21 22 23 24 25
0.0005478188 0.0042463647 -0.0018492729 -0.0066434564 -0.0008765101
26 27 28 29 30
0.0049588367 0.0108765101 -0.0091234899 0.0047118569 0.0002390940
31 32 33 34 35
0.0083898211 0.0145883670 0.0053420023 0.0090405482 -0.0096579977
36 37 38 39 40
-0.0044521812 0.0035060404 -0.0006586128 0.0026561523 0.0026561523
41 42 43 44 45
0.0090944074 0.0020187363 0.0001694633 0.0015738257 -0.0002754472
46 47 48 49 50
0.0034230986 -0.0052754472 -0.0026725390 -0.0016997761 -0.0080557046
51 52 53
-0.0169322147 -0.0121380312 -0.0204939596
> postscript(file="/var/www/html/freestat/rcomp/tmp/689ql1290349509.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 = 53
Frequency = 1
lag(myerror, k = 1) myerror
0 -0.0082736018 NA
1 -0.0068208055 -0.0082736018
2 -0.0109031321 -0.0068208055
3 0.0043026844 -0.0109031321
4 -0.0014503358 0.0043026844
5 -0.0059230986 -0.0014503358
6 -0.0051694633 -0.0059230986
7 -0.0189709175 -0.0051694633
8 -0.0056143739 -0.0189709175
9 -0.0167100115 -0.0056143739
10 0.0167827179 -0.0167100115
11 0.0137681766 0.0167827179
12 0.0073438477 0.0137681766
13 0.0105762862 0.0073438477
14 0.0143026844 0.0105762862
15 0.0143026844 0.0143026844
16 0.0081380312 0.0143026844
17 0.0036652683 0.0081380312
18 -0.0033898211 0.0036652683
19 0.0028087248 -0.0033898211
20 0.0005478188 0.0028087248
21 0.0042463647 0.0005478188
22 -0.0018492729 0.0042463647
23 -0.0066434564 -0.0018492729
24 -0.0008765101 -0.0066434564
25 0.0049588367 -0.0008765101
26 0.0108765101 0.0049588367
27 -0.0091234899 0.0108765101
28 0.0047118569 -0.0091234899
29 0.0002390940 0.0047118569
30 0.0083898211 0.0002390940
31 0.0145883670 0.0083898211
32 0.0053420023 0.0145883670
33 0.0090405482 0.0053420023
34 -0.0096579977 0.0090405482
35 -0.0044521812 -0.0096579977
36 0.0035060404 -0.0044521812
37 -0.0006586128 0.0035060404
38 0.0026561523 -0.0006586128
39 0.0026561523 0.0026561523
40 0.0090944074 0.0026561523
41 0.0020187363 0.0090944074
42 0.0001694633 0.0020187363
43 0.0015738257 0.0001694633
44 -0.0002754472 0.0015738257
45 0.0034230986 -0.0002754472
46 -0.0052754472 0.0034230986
47 -0.0026725390 -0.0052754472
48 -0.0016997761 -0.0026725390
49 -0.0080557046 -0.0016997761
50 -0.0169322147 -0.0080557046
51 -0.0121380312 -0.0169322147
52 -0.0204939596 -0.0121380312
53 NA -0.0204939596
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -0.0068208055 -0.0082736018
[2,] -0.0109031321 -0.0068208055
[3,] 0.0043026844 -0.0109031321
[4,] -0.0014503358 0.0043026844
[5,] -0.0059230986 -0.0014503358
[6,] -0.0051694633 -0.0059230986
[7,] -0.0189709175 -0.0051694633
[8,] -0.0056143739 -0.0189709175
[9,] -0.0167100115 -0.0056143739
[10,] 0.0167827179 -0.0167100115
[11,] 0.0137681766 0.0167827179
[12,] 0.0073438477 0.0137681766
[13,] 0.0105762862 0.0073438477
[14,] 0.0143026844 0.0105762862
[15,] 0.0143026844 0.0143026844
[16,] 0.0081380312 0.0143026844
[17,] 0.0036652683 0.0081380312
[18,] -0.0033898211 0.0036652683
[19,] 0.0028087248 -0.0033898211
[20,] 0.0005478188 0.0028087248
[21,] 0.0042463647 0.0005478188
[22,] -0.0018492729 0.0042463647
[23,] -0.0066434564 -0.0018492729
[24,] -0.0008765101 -0.0066434564
[25,] 0.0049588367 -0.0008765101
[26,] 0.0108765101 0.0049588367
[27,] -0.0091234899 0.0108765101
[28,] 0.0047118569 -0.0091234899
[29,] 0.0002390940 0.0047118569
[30,] 0.0083898211 0.0002390940
[31,] 0.0145883670 0.0083898211
[32,] 0.0053420023 0.0145883670
[33,] 0.0090405482 0.0053420023
[34,] -0.0096579977 0.0090405482
[35,] -0.0044521812 -0.0096579977
[36,] 0.0035060404 -0.0044521812
[37,] -0.0006586128 0.0035060404
[38,] 0.0026561523 -0.0006586128
[39,] 0.0026561523 0.0026561523
[40,] 0.0090944074 0.0026561523
[41,] 0.0020187363 0.0090944074
[42,] 0.0001694633 0.0020187363
[43,] 0.0015738257 0.0001694633
[44,] -0.0002754472 0.0015738257
[45,] 0.0034230986 -0.0002754472
[46,] -0.0052754472 0.0034230986
[47,] -0.0026725390 -0.0052754472
[48,] -0.0016997761 -0.0026725390
[49,] -0.0080557046 -0.0016997761
[50,] -0.0169322147 -0.0080557046
[51,] -0.0121380312 -0.0169322147
[52,] -0.0204939596 -0.0121380312
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -0.0068208055 -0.0082736018
2 -0.0109031321 -0.0068208055
3 0.0043026844 -0.0109031321
4 -0.0014503358 0.0043026844
5 -0.0059230986 -0.0014503358
6 -0.0051694633 -0.0059230986
7 -0.0189709175 -0.0051694633
8 -0.0056143739 -0.0189709175
9 -0.0167100115 -0.0056143739
10 0.0167827179 -0.0167100115
11 0.0137681766 0.0167827179
12 0.0073438477 0.0137681766
13 0.0105762862 0.0073438477
14 0.0143026844 0.0105762862
15 0.0143026844 0.0143026844
16 0.0081380312 0.0143026844
17 0.0036652683 0.0081380312
18 -0.0033898211 0.0036652683
19 0.0028087248 -0.0033898211
20 0.0005478188 0.0028087248
21 0.0042463647 0.0005478188
22 -0.0018492729 0.0042463647
23 -0.0066434564 -0.0018492729
24 -0.0008765101 -0.0066434564
25 0.0049588367 -0.0008765101
26 0.0108765101 0.0049588367
27 -0.0091234899 0.0108765101
28 0.0047118569 -0.0091234899
29 0.0002390940 0.0047118569
30 0.0083898211 0.0002390940
31 0.0145883670 0.0083898211
32 0.0053420023 0.0145883670
33 0.0090405482 0.0053420023
34 -0.0096579977 0.0090405482
35 -0.0044521812 -0.0096579977
36 0.0035060404 -0.0044521812
37 -0.0006586128 0.0035060404
38 0.0026561523 -0.0006586128
39 0.0026561523 0.0026561523
40 0.0090944074 0.0026561523
41 0.0020187363 0.0090944074
42 0.0001694633 0.0020187363
43 0.0015738257 0.0001694633
44 -0.0002754472 0.0015738257
45 0.0034230986 -0.0002754472
46 -0.0052754472 0.0034230986
47 -0.0026725390 -0.0052754472
48 -0.0016997761 -0.0026725390
49 -0.0080557046 -0.0016997761
50 -0.0169322147 -0.0080557046
51 -0.0121380312 -0.0169322147
52 -0.0204939596 -0.0121380312
> 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/711761290349509.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/8usor1290349509.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/9usor1290349509.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
>
> #Note: the /var/www/html/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/freestat/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/10fb5f1290349509.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/11jb321290349509.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/12x3jb1290349509.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/13ilzz1290349509.tab")
>
> try(system("convert tmp/1fiqi1290349509.ps tmp/1fiqi1290349509.png",intern=TRUE))
character(0)
> try(system("convert tmp/2fiqi1290349509.ps tmp/2fiqi1290349509.png",intern=TRUE))
character(0)
> try(system("convert tmp/389ql1290349509.ps tmp/389ql1290349509.png",intern=TRUE))
character(0)
> try(system("convert tmp/489ql1290349509.ps tmp/489ql1290349509.png",intern=TRUE))
character(0)
> try(system("convert tmp/589ql1290349509.ps tmp/589ql1290349509.png",intern=TRUE))
character(0)
> try(system("convert tmp/689ql1290349509.ps tmp/689ql1290349509.png",intern=TRUE))
character(0)
> try(system("convert tmp/711761290349509.ps tmp/711761290349509.png",intern=TRUE))
character(0)
> try(system("convert tmp/8usor1290349509.ps tmp/8usor1290349509.png",intern=TRUE))
character(0)
> try(system("convert tmp/9usor1290349509.ps tmp/9usor1290349509.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
3.065 2.241 3.692