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(99984,0,99981,0,99972,0,99989,0,99996,0,99991,0,99988,0,99990,0,99998,0,99987,0,100000,0,100000,0,100004,0,100007,0,100005,0,100002,0,99998,0,100006,0,99997,0,100001,0,100000,0,99993,0,99994,0,99996,0,99996,0,99998,0,100002,0,99995,0,99985,0,99984,0,99982,0,99987,0,99977,0,99990,0,99990,0,99994,0,99997,0,99996,0,99993,0,99993,0,99993,0,99997,0,100000,0,99995,0,99997,0,100003,0,100002,0,99993,0,99999,1,100000,1,99997,1,100004,1,100002,1,100003,1,100000,1,99990,1,99990,1,99991,1,99978,1,99984,1,99982,1,99986,1,99988,1,99983,1,99977,1,99972,1,99969,1,99979,1,99981,1,99978,1,99978,1),dim=c(2,71),dimnames=list(c('Economie','Kredietcrisis'),1:71))
> y <- array(NA,dim=c(2,71),dimnames=list(c('Economie','Kredietcrisis'),1:71))
> 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
Economie Kredietcrisis
1 99984 0
2 99981 0
3 99972 0
4 99989 0
5 99996 0
6 99991 0
7 99988 0
8 99990 0
9 99998 0
10 99987 0
11 100000 0
12 100000 0
13 100004 0
14 100007 0
15 100005 0
16 100002 0
17 99998 0
18 100006 0
19 99997 0
20 100001 0
21 100000 0
22 99993 0
23 99994 0
24 99996 0
25 99996 0
26 99998 0
27 100002 0
28 99995 0
29 99985 0
30 99984 0
31 99982 0
32 99987 0
33 99977 0
34 99990 0
35 99990 0
36 99994 0
37 99997 0
38 99996 0
39 99993 0
40 99993 0
41 99993 0
42 99997 0
43 100000 0
44 99995 0
45 99997 0
46 100003 0
47 100002 0
48 99993 0
49 99999 1
50 100000 1
51 99997 1
52 100004 1
53 100002 1
54 100003 1
55 100000 1
56 99990 1
57 99990 1
58 99991 1
59 99978 1
60 99984 1
61 99982 1
62 99986 1
63 99988 1
64 99983 1
65 99977 1
66 99972 1
67 99969 1
68 99979 1
69 99981 1
70 99978 1
71 99978 1
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Kredietcrisis
99994.12 -6.69
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-22.125 -5.780 0.875 5.875 16.565
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 99994.125 1.243 80463.882 < 2e-16 ***
Kredietcrisis -6.690 2.183 -3.064 0.00311 **
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 8.61 on 69 degrees of freedom
Multiple R-squared: 0.1198, Adjusted R-squared: 0.107
F-statistic: 9.389 on 1 and 69 DF, p-value: 0.003114
> postscript(file="/var/www/html/rcomp/tmp/1zia81229866825.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/2smfj1229866825.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/3drmu1229866825.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4j9au1229866825.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/52dv91229866825.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
> grid()
> dev.off()
null device
1
> (myerror <- as.ts(mysum$resid))
Time Series:
Start = 1
End = 71
Frequency = 1
1 2 3 4 5 6
-10.1250000 -13.1250000 -22.1250000 -5.1250000 1.8750000 -3.1250000
7 8 9 10 11 12
-6.1250000 -4.1250000 3.8750000 -7.1250000 5.8750000 5.8750000
13 14 15 16 17 18
9.8750000 12.8750000 10.8750000 7.8750000 3.8750000 11.8750000
19 20 21 22 23 24
2.8750000 6.8750000 5.8750000 -1.1250000 -0.1250000 1.8750000
25 26 27 28 29 30
1.8750000 3.8750000 7.8750000 0.8750000 -9.1250000 -10.1250000
31 32 33 34 35 36
-12.1250000 -7.1250000 -17.1250000 -4.1250000 -4.1250000 -0.1250000
37 38 39 40 41 42
2.8750000 1.8750000 -1.1250000 -1.1250000 -1.1250000 2.8750000
43 44 45 46 47 48
5.8750000 0.8750000 2.8750000 8.8750000 7.8750000 -1.1250000
49 50 51 52 53 54
11.5652174 12.5652174 9.5652174 16.5652174 14.5652174 15.5652174
55 56 57 58 59 60
12.5652174 2.5652174 2.5652174 3.5652174 -9.4347826 -3.4347826
61 62 63 64 65 66
-5.4347826 -1.4347826 0.5652174 -4.4347826 -10.4347826 -15.4347826
67 68 69 70 71
-18.4347826 -8.4347826 -6.4347826 -9.4347826 -9.4347826
> postscript(file="/var/www/html/rcomp/tmp/6ie2o1229866825.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 = 71
Frequency = 1
lag(myerror, k = 1) myerror
0 -10.1250000 NA
1 -13.1250000 -10.1250000
2 -22.1250000 -13.1250000
3 -5.1250000 -22.1250000
4 1.8750000 -5.1250000
5 -3.1250000 1.8750000
6 -6.1250000 -3.1250000
7 -4.1250000 -6.1250000
8 3.8750000 -4.1250000
9 -7.1250000 3.8750000
10 5.8750000 -7.1250000
11 5.8750000 5.8750000
12 9.8750000 5.8750000
13 12.8750000 9.8750000
14 10.8750000 12.8750000
15 7.8750000 10.8750000
16 3.8750000 7.8750000
17 11.8750000 3.8750000
18 2.8750000 11.8750000
19 6.8750000 2.8750000
20 5.8750000 6.8750000
21 -1.1250000 5.8750000
22 -0.1250000 -1.1250000
23 1.8750000 -0.1250000
24 1.8750000 1.8750000
25 3.8750000 1.8750000
26 7.8750000 3.8750000
27 0.8750000 7.8750000
28 -9.1250000 0.8750000
29 -10.1250000 -9.1250000
30 -12.1250000 -10.1250000
31 -7.1250000 -12.1250000
32 -17.1250000 -7.1250000
33 -4.1250000 -17.1250000
34 -4.1250000 -4.1250000
35 -0.1250000 -4.1250000
36 2.8750000 -0.1250000
37 1.8750000 2.8750000
38 -1.1250000 1.8750000
39 -1.1250000 -1.1250000
40 -1.1250000 -1.1250000
41 2.8750000 -1.1250000
42 5.8750000 2.8750000
43 0.8750000 5.8750000
44 2.8750000 0.8750000
45 8.8750000 2.8750000
46 7.8750000 8.8750000
47 -1.1250000 7.8750000
48 11.5652174 -1.1250000
49 12.5652174 11.5652174
50 9.5652174 12.5652174
51 16.5652174 9.5652174
52 14.5652174 16.5652174
53 15.5652174 14.5652174
54 12.5652174 15.5652174
55 2.5652174 12.5652174
56 2.5652174 2.5652174
57 3.5652174 2.5652174
58 -9.4347826 3.5652174
59 -3.4347826 -9.4347826
60 -5.4347826 -3.4347826
61 -1.4347826 -5.4347826
62 0.5652174 -1.4347826
63 -4.4347826 0.5652174
64 -10.4347826 -4.4347826
65 -15.4347826 -10.4347826
66 -18.4347826 -15.4347826
67 -8.4347826 -18.4347826
68 -6.4347826 -8.4347826
69 -9.4347826 -6.4347826
70 -9.4347826 -9.4347826
71 NA -9.4347826
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -13.1250000 -10.1250000
[2,] -22.1250000 -13.1250000
[3,] -5.1250000 -22.1250000
[4,] 1.8750000 -5.1250000
[5,] -3.1250000 1.8750000
[6,] -6.1250000 -3.1250000
[7,] -4.1250000 -6.1250000
[8,] 3.8750000 -4.1250000
[9,] -7.1250000 3.8750000
[10,] 5.8750000 -7.1250000
[11,] 5.8750000 5.8750000
[12,] 9.8750000 5.8750000
[13,] 12.8750000 9.8750000
[14,] 10.8750000 12.8750000
[15,] 7.8750000 10.8750000
[16,] 3.8750000 7.8750000
[17,] 11.8750000 3.8750000
[18,] 2.8750000 11.8750000
[19,] 6.8750000 2.8750000
[20,] 5.8750000 6.8750000
[21,] -1.1250000 5.8750000
[22,] -0.1250000 -1.1250000
[23,] 1.8750000 -0.1250000
[24,] 1.8750000 1.8750000
[25,] 3.8750000 1.8750000
[26,] 7.8750000 3.8750000
[27,] 0.8750000 7.8750000
[28,] -9.1250000 0.8750000
[29,] -10.1250000 -9.1250000
[30,] -12.1250000 -10.1250000
[31,] -7.1250000 -12.1250000
[32,] -17.1250000 -7.1250000
[33,] -4.1250000 -17.1250000
[34,] -4.1250000 -4.1250000
[35,] -0.1250000 -4.1250000
[36,] 2.8750000 -0.1250000
[37,] 1.8750000 2.8750000
[38,] -1.1250000 1.8750000
[39,] -1.1250000 -1.1250000
[40,] -1.1250000 -1.1250000
[41,] 2.8750000 -1.1250000
[42,] 5.8750000 2.8750000
[43,] 0.8750000 5.8750000
[44,] 2.8750000 0.8750000
[45,] 8.8750000 2.8750000
[46,] 7.8750000 8.8750000
[47,] -1.1250000 7.8750000
[48,] 11.5652174 -1.1250000
[49,] 12.5652174 11.5652174
[50,] 9.5652174 12.5652174
[51,] 16.5652174 9.5652174
[52,] 14.5652174 16.5652174
[53,] 15.5652174 14.5652174
[54,] 12.5652174 15.5652174
[55,] 2.5652174 12.5652174
[56,] 2.5652174 2.5652174
[57,] 3.5652174 2.5652174
[58,] -9.4347826 3.5652174
[59,] -3.4347826 -9.4347826
[60,] -5.4347826 -3.4347826
[61,] -1.4347826 -5.4347826
[62,] 0.5652174 -1.4347826
[63,] -4.4347826 0.5652174
[64,] -10.4347826 -4.4347826
[65,] -15.4347826 -10.4347826
[66,] -18.4347826 -15.4347826
[67,] -8.4347826 -18.4347826
[68,] -6.4347826 -8.4347826
[69,] -9.4347826 -6.4347826
[70,] -9.4347826 -9.4347826
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -13.1250000 -10.1250000
2 -22.1250000 -13.1250000
3 -5.1250000 -22.1250000
4 1.8750000 -5.1250000
5 -3.1250000 1.8750000
6 -6.1250000 -3.1250000
7 -4.1250000 -6.1250000
8 3.8750000 -4.1250000
9 -7.1250000 3.8750000
10 5.8750000 -7.1250000
11 5.8750000 5.8750000
12 9.8750000 5.8750000
13 12.8750000 9.8750000
14 10.8750000 12.8750000
15 7.8750000 10.8750000
16 3.8750000 7.8750000
17 11.8750000 3.8750000
18 2.8750000 11.8750000
19 6.8750000 2.8750000
20 5.8750000 6.8750000
21 -1.1250000 5.8750000
22 -0.1250000 -1.1250000
23 1.8750000 -0.1250000
24 1.8750000 1.8750000
25 3.8750000 1.8750000
26 7.8750000 3.8750000
27 0.8750000 7.8750000
28 -9.1250000 0.8750000
29 -10.1250000 -9.1250000
30 -12.1250000 -10.1250000
31 -7.1250000 -12.1250000
32 -17.1250000 -7.1250000
33 -4.1250000 -17.1250000
34 -4.1250000 -4.1250000
35 -0.1250000 -4.1250000
36 2.8750000 -0.1250000
37 1.8750000 2.8750000
38 -1.1250000 1.8750000
39 -1.1250000 -1.1250000
40 -1.1250000 -1.1250000
41 2.8750000 -1.1250000
42 5.8750000 2.8750000
43 0.8750000 5.8750000
44 2.8750000 0.8750000
45 8.8750000 2.8750000
46 7.8750000 8.8750000
47 -1.1250000 7.8750000
48 11.5652174 -1.1250000
49 12.5652174 11.5652174
50 9.5652174 12.5652174
51 16.5652174 9.5652174
52 14.5652174 16.5652174
53 15.5652174 14.5652174
54 12.5652174 15.5652174
55 2.5652174 12.5652174
56 2.5652174 2.5652174
57 3.5652174 2.5652174
58 -9.4347826 3.5652174
59 -3.4347826 -9.4347826
60 -5.4347826 -3.4347826
61 -1.4347826 -5.4347826
62 0.5652174 -1.4347826
63 -4.4347826 0.5652174
64 -10.4347826 -4.4347826
65 -15.4347826 -10.4347826
66 -18.4347826 -15.4347826
67 -8.4347826 -18.4347826
68 -6.4347826 -8.4347826
69 -9.4347826 -6.4347826
70 -9.4347826 -9.4347826
> 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/75tgz1229866825.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8mzk41229866825.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9dub21229866825.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/104yjy1229866825.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/11d6p01229866825.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/126hee1229866825.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/13ahyr1229866825.tab")
>
> system("convert tmp/1zia81229866825.ps tmp/1zia81229866825.png")
> system("convert tmp/2smfj1229866825.ps tmp/2smfj1229866825.png")
> system("convert tmp/3drmu1229866825.ps tmp/3drmu1229866825.png")
> system("convert tmp/4j9au1229866825.ps tmp/4j9au1229866825.png")
> system("convert tmp/52dv91229866825.ps tmp/52dv91229866825.png")
> system("convert tmp/6ie2o1229866825.ps tmp/6ie2o1229866825.png")
> system("convert tmp/75tgz1229866825.ps tmp/75tgz1229866825.png")
> system("convert tmp/8mzk41229866825.ps tmp/8mzk41229866825.png")
> system("convert tmp/9dub21229866825.ps tmp/9dub21229866825.png")
>
>
> proc.time()
user system elapsed
2.014 1.462 2.475