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(274412,0,272433,0,268361,0,268586,0,264768,0,269974,0,304744,0,309365,0,308347,0,298427,0,289231,0,291975,0,294912,0,293488,0,290555,0,284736,0,281818,0,287854,0,316263,0,325412,0,326011,0,328282,0,317480,0,317539,0,313737,0,312276,0,309391,0,302950,0,300316,0,304035,0,333476,0,337698,0,335932,0,323931,0,313927,0,314485,0,313218,0,309664,0,302963,0,298989,0,298423,0,301631,0,329765,0,335083,0,327616,0,309119,0,295916,0,291413,0,291542,1,284678,1,276475,1,272566,1,264981,1,263290,1,296806,1,303598,1,286994,1,276427,1,266424,1,267153,1,268381,1,262522,1,255542,1,253158,1,243803,1,250741,1,280445,1,285257,1,270976,1,261076,1,255603,1),dim=c(2,71),dimnames=list(c('WerklozenVrouwen','Kredietcrisis'),1:71))
> y <- array(NA,dim=c(2,71),dimnames=list(c('WerklozenVrouwen','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
WerklozenVrouwen Kredietcrisis
1 274412 0
2 272433 0
3 268361 0
4 268586 0
5 264768 0
6 269974 0
7 304744 0
8 309365 0
9 308347 0
10 298427 0
11 289231 0
12 291975 0
13 294912 0
14 293488 0
15 290555 0
16 284736 0
17 281818 0
18 287854 0
19 316263 0
20 325412 0
21 326011 0
22 328282 0
23 317480 0
24 317539 0
25 313737 0
26 312276 0
27 309391 0
28 302950 0
29 300316 0
30 304035 0
31 333476 0
32 337698 0
33 335932 0
34 323931 0
35 313927 0
36 314485 0
37 313218 0
38 309664 0
39 302963 0
40 298989 0
41 298423 0
42 301631 0
43 329765 0
44 335083 0
45 327616 0
46 309119 0
47 295916 0
48 291413 0
49 291542 1
50 284678 1
51 276475 1
52 272566 1
53 264981 1
54 263290 1
55 296806 1
56 303598 1
57 286994 1
58 276427 1
59 266424 1
60 267153 1
61 268381 1
62 262522 1
63 255542 1
64 253158 1
65 243803 1
66 250741 1
67 280445 1
68 285257 1
69 270976 1
70 261076 1
71 255603 1
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Kredietcrisis
304186 -32950
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-39418.0 -11454.5 -260.4 12685.5 33512.0
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 304186 2620 116.106 < 2e-16 ***
Kredietcrisis -32950 4603 -7.158 6.87e-10 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 18150 on 69 degrees of freedom
Multiple R-squared: 0.4261, Adjusted R-squared: 0.4178
F-statistic: 51.24 on 1 and 69 DF, p-value: 6.871e-10
> postscript(file="/var/www/html/rcomp/tmp/1qxr51229866289.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/2oyto1229866289.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/3m5xg1229866289.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4wee11229866289.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5v0701229866289.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$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
-29773.9792 -31752.9792 -35824.9792 -35599.9792 -39417.9792 -34211.9792
7 8 9 10 11 12
558.0208 5179.0208 4161.0208 -5758.9792 -14954.9792 -12210.9792
13 14 15 16 17 18
-9273.9792 -10697.9792 -13630.9792 -19449.9792 -22367.9792 -16331.9792
19 20 21 22 23 24
12077.0208 21226.0208 21825.0208 24096.0208 13294.0208 13353.0208
25 26 27 28 29 30
9551.0208 8090.0208 5205.0208 -1235.9792 -3869.9792 -150.9792
31 32 33 34 35 36
29290.0208 33512.0208 31746.0208 19745.0208 9741.0208 10299.0208
37 38 39 40 41 42
9032.0208 5478.0208 -1222.9792 -5196.9792 -5762.9792 -2554.9792
43 44 45 46 47 48
25579.0208 30897.0208 23430.0208 4933.0208 -8269.9792 -12772.9792
49 50 51 52 53 54
20305.5652 13441.5652 5238.5652 1329.5652 -6255.4348 -7946.4348
55 56 57 58 59 60
25569.5652 32361.5652 15757.5652 5190.5652 -4812.4348 -4083.4348
61 62 63 64 65 66
-2855.4348 -8714.4348 -15694.4348 -18078.4348 -27433.4348 -20495.4348
67 68 69 70 71
9208.5652 14020.5652 -260.4348 -10160.4348 -15633.4348
> postscript(file="/var/www/html/rcomp/tmp/67vgo1229866289.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 -29773.9792 NA
1 -31752.9792 -29773.9792
2 -35824.9792 -31752.9792
3 -35599.9792 -35824.9792
4 -39417.9792 -35599.9792
5 -34211.9792 -39417.9792
6 558.0208 -34211.9792
7 5179.0208 558.0208
8 4161.0208 5179.0208
9 -5758.9792 4161.0208
10 -14954.9792 -5758.9792
11 -12210.9792 -14954.9792
12 -9273.9792 -12210.9792
13 -10697.9792 -9273.9792
14 -13630.9792 -10697.9792
15 -19449.9792 -13630.9792
16 -22367.9792 -19449.9792
17 -16331.9792 -22367.9792
18 12077.0208 -16331.9792
19 21226.0208 12077.0208
20 21825.0208 21226.0208
21 24096.0208 21825.0208
22 13294.0208 24096.0208
23 13353.0208 13294.0208
24 9551.0208 13353.0208
25 8090.0208 9551.0208
26 5205.0208 8090.0208
27 -1235.9792 5205.0208
28 -3869.9792 -1235.9792
29 -150.9792 -3869.9792
30 29290.0208 -150.9792
31 33512.0208 29290.0208
32 31746.0208 33512.0208
33 19745.0208 31746.0208
34 9741.0208 19745.0208
35 10299.0208 9741.0208
36 9032.0208 10299.0208
37 5478.0208 9032.0208
38 -1222.9792 5478.0208
39 -5196.9792 -1222.9792
40 -5762.9792 -5196.9792
41 -2554.9792 -5762.9792
42 25579.0208 -2554.9792
43 30897.0208 25579.0208
44 23430.0208 30897.0208
45 4933.0208 23430.0208
46 -8269.9792 4933.0208
47 -12772.9792 -8269.9792
48 20305.5652 -12772.9792
49 13441.5652 20305.5652
50 5238.5652 13441.5652
51 1329.5652 5238.5652
52 -6255.4348 1329.5652
53 -7946.4348 -6255.4348
54 25569.5652 -7946.4348
55 32361.5652 25569.5652
56 15757.5652 32361.5652
57 5190.5652 15757.5652
58 -4812.4348 5190.5652
59 -4083.4348 -4812.4348
60 -2855.4348 -4083.4348
61 -8714.4348 -2855.4348
62 -15694.4348 -8714.4348
63 -18078.4348 -15694.4348
64 -27433.4348 -18078.4348
65 -20495.4348 -27433.4348
66 9208.5652 -20495.4348
67 14020.5652 9208.5652
68 -260.4348 14020.5652
69 -10160.4348 -260.4348
70 -15633.4348 -10160.4348
71 NA -15633.4348
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -31752.9792 -29773.9792
[2,] -35824.9792 -31752.9792
[3,] -35599.9792 -35824.9792
[4,] -39417.9792 -35599.9792
[5,] -34211.9792 -39417.9792
[6,] 558.0208 -34211.9792
[7,] 5179.0208 558.0208
[8,] 4161.0208 5179.0208
[9,] -5758.9792 4161.0208
[10,] -14954.9792 -5758.9792
[11,] -12210.9792 -14954.9792
[12,] -9273.9792 -12210.9792
[13,] -10697.9792 -9273.9792
[14,] -13630.9792 -10697.9792
[15,] -19449.9792 -13630.9792
[16,] -22367.9792 -19449.9792
[17,] -16331.9792 -22367.9792
[18,] 12077.0208 -16331.9792
[19,] 21226.0208 12077.0208
[20,] 21825.0208 21226.0208
[21,] 24096.0208 21825.0208
[22,] 13294.0208 24096.0208
[23,] 13353.0208 13294.0208
[24,] 9551.0208 13353.0208
[25,] 8090.0208 9551.0208
[26,] 5205.0208 8090.0208
[27,] -1235.9792 5205.0208
[28,] -3869.9792 -1235.9792
[29,] -150.9792 -3869.9792
[30,] 29290.0208 -150.9792
[31,] 33512.0208 29290.0208
[32,] 31746.0208 33512.0208
[33,] 19745.0208 31746.0208
[34,] 9741.0208 19745.0208
[35,] 10299.0208 9741.0208
[36,] 9032.0208 10299.0208
[37,] 5478.0208 9032.0208
[38,] -1222.9792 5478.0208
[39,] -5196.9792 -1222.9792
[40,] -5762.9792 -5196.9792
[41,] -2554.9792 -5762.9792
[42,] 25579.0208 -2554.9792
[43,] 30897.0208 25579.0208
[44,] 23430.0208 30897.0208
[45,] 4933.0208 23430.0208
[46,] -8269.9792 4933.0208
[47,] -12772.9792 -8269.9792
[48,] 20305.5652 -12772.9792
[49,] 13441.5652 20305.5652
[50,] 5238.5652 13441.5652
[51,] 1329.5652 5238.5652
[52,] -6255.4348 1329.5652
[53,] -7946.4348 -6255.4348
[54,] 25569.5652 -7946.4348
[55,] 32361.5652 25569.5652
[56,] 15757.5652 32361.5652
[57,] 5190.5652 15757.5652
[58,] -4812.4348 5190.5652
[59,] -4083.4348 -4812.4348
[60,] -2855.4348 -4083.4348
[61,] -8714.4348 -2855.4348
[62,] -15694.4348 -8714.4348
[63,] -18078.4348 -15694.4348
[64,] -27433.4348 -18078.4348
[65,] -20495.4348 -27433.4348
[66,] 9208.5652 -20495.4348
[67,] 14020.5652 9208.5652
[68,] -260.4348 14020.5652
[69,] -10160.4348 -260.4348
[70,] -15633.4348 -10160.4348
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -31752.9792 -29773.9792
2 -35824.9792 -31752.9792
3 -35599.9792 -35824.9792
4 -39417.9792 -35599.9792
5 -34211.9792 -39417.9792
6 558.0208 -34211.9792
7 5179.0208 558.0208
8 4161.0208 5179.0208
9 -5758.9792 4161.0208
10 -14954.9792 -5758.9792
11 -12210.9792 -14954.9792
12 -9273.9792 -12210.9792
13 -10697.9792 -9273.9792
14 -13630.9792 -10697.9792
15 -19449.9792 -13630.9792
16 -22367.9792 -19449.9792
17 -16331.9792 -22367.9792
18 12077.0208 -16331.9792
19 21226.0208 12077.0208
20 21825.0208 21226.0208
21 24096.0208 21825.0208
22 13294.0208 24096.0208
23 13353.0208 13294.0208
24 9551.0208 13353.0208
25 8090.0208 9551.0208
26 5205.0208 8090.0208
27 -1235.9792 5205.0208
28 -3869.9792 -1235.9792
29 -150.9792 -3869.9792
30 29290.0208 -150.9792
31 33512.0208 29290.0208
32 31746.0208 33512.0208
33 19745.0208 31746.0208
34 9741.0208 19745.0208
35 10299.0208 9741.0208
36 9032.0208 10299.0208
37 5478.0208 9032.0208
38 -1222.9792 5478.0208
39 -5196.9792 -1222.9792
40 -5762.9792 -5196.9792
41 -2554.9792 -5762.9792
42 25579.0208 -2554.9792
43 30897.0208 25579.0208
44 23430.0208 30897.0208
45 4933.0208 23430.0208
46 -8269.9792 4933.0208
47 -12772.9792 -8269.9792
48 20305.5652 -12772.9792
49 13441.5652 20305.5652
50 5238.5652 13441.5652
51 1329.5652 5238.5652
52 -6255.4348 1329.5652
53 -7946.4348 -6255.4348
54 25569.5652 -7946.4348
55 32361.5652 25569.5652
56 15757.5652 32361.5652
57 5190.5652 15757.5652
58 -4812.4348 5190.5652
59 -4083.4348 -4812.4348
60 -2855.4348 -4083.4348
61 -8714.4348 -2855.4348
62 -15694.4348 -8714.4348
63 -18078.4348 -15694.4348
64 -27433.4348 -18078.4348
65 -20495.4348 -27433.4348
66 9208.5652 -20495.4348
67 14020.5652 9208.5652
68 -260.4348 14020.5652
69 -10160.4348 -260.4348
70 -15633.4348 -10160.4348
> 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/7fdx11229866289.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8xfg71229866289.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9ia2f1229866289.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/10iule1229866289.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/11bz0u1229866289.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/12nu2j1229866289.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/13mtn41229866289.tab")
>
> system("convert tmp/1qxr51229866289.ps tmp/1qxr51229866289.png")
> system("convert tmp/2oyto1229866289.ps tmp/2oyto1229866289.png")
> system("convert tmp/3m5xg1229866289.ps tmp/3m5xg1229866289.png")
> system("convert tmp/4wee11229866289.ps tmp/4wee11229866289.png")
> system("convert tmp/5v0701229866289.ps tmp/5v0701229866289.png")
> system("convert tmp/67vgo1229866289.ps tmp/67vgo1229866289.png")
> system("convert tmp/7fdx11229866289.ps tmp/7fdx11229866289.png")
> system("convert tmp/8xfg71229866289.ps tmp/8xfg71229866289.png")
> system("convert tmp/9ia2f1229866289.ps tmp/9ia2f1229866289.png")
>
>
> proc.time()
user system elapsed
1.935 1.430 2.357