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(97.3,0,101,0,113.2,0,101,0,105.7,0,113.9,0,86.4,0,96.5,0,103.3,0,114.9,0,105.8,0,94.2,0,98.4,0,99.4,0,108.8,0,112.6,0,104.4,0,112.2,0,81.1,0,97.1,0,112.6,0,113.8,0,107.8,0,103.2,0,103.3,0,101.2,0,107.7,0,110.4,0,101.9,0,115.9,0,89.9,0,88.6,0,117.2,0,123.9,0,100,0,103.6,0,94.1,0,98.7,0,119.5,0,112.7,0,104.4,0,124.7,0,89.1,0,97,0,121.6,1,118.8,1,114,1,111.5,1,97.2,1,102.5,1,113.4,1,109.8,1,104.9,1,126.1,1,80,1,96.8,1,117.2,1,112.3,1,117.3,1,111.1,1,102.2,1,104.3,1,122.9,1,107.6,1,121.3,1,131.5,1,89,1,104.4,1,128.9,1,135.9,1,133.3,1,121.3,1),dim=c(2,72),dimnames=list(c('y','x'),1:72))
> y <- array(NA,dim=c(2,72),dimnames=list(c('y','x'),1:72))
> 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
y x
1 97.3 0
2 101.0 0
3 113.2 0
4 101.0 0
5 105.7 0
6 113.9 0
7 86.4 0
8 96.5 0
9 103.3 0
10 114.9 0
11 105.8 0
12 94.2 0
13 98.4 0
14 99.4 0
15 108.8 0
16 112.6 0
17 104.4 0
18 112.2 0
19 81.1 0
20 97.1 0
21 112.6 0
22 113.8 0
23 107.8 0
24 103.2 0
25 103.3 0
26 101.2 0
27 107.7 0
28 110.4 0
29 101.9 0
30 115.9 0
31 89.9 0
32 88.6 0
33 117.2 0
34 123.9 0
35 100.0 0
36 103.6 0
37 94.1 0
38 98.7 0
39 119.5 0
40 112.7 0
41 104.4 0
42 124.7 0
43 89.1 0
44 97.0 0
45 121.6 1
46 118.8 1
47 114.0 1
48 111.5 1
49 97.2 1
50 102.5 1
51 113.4 1
52 109.8 1
53 104.9 1
54 126.1 1
55 80.0 1
56 96.8 1
57 117.2 1
58 112.3 1
59 117.3 1
60 111.1 1
61 102.2 1
62 104.3 1
63 122.9 1
64 107.6 1
65 121.3 1
66 131.5 1
67 89.0 1
68 104.4 1
69 128.9 1
70 135.9 1
71 133.3 1
72 121.3 1
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) x
104.282 8.472
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-32.7536 -7.2068 -0.5677 8.4502 23.1464
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 104.282 1.702 61.265 < 2e-16 ***
x 8.472 2.730 3.104 0.00276 **
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 11.29 on 70 degrees of freedom
Multiple R-squared: 0.121, Adjusted R-squared: 0.1084
F-statistic: 9.633 on 1 and 70 DF, p-value: 0.002756
> postscript(file="/var/www/html/freestat/rcomp/tmp/1usc91227560575.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/2kpgc1227560575.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/3y53t1227560575.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/40x8q1227560575.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/5w9ke1227560575.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
> grid()
> dev.off()
null device
1
> (myerror <- as.ts(mysum$resid))
Time Series:
Start = 1
End = 72
Frequency = 1
1 2 3 4 5 6
-6.9818182 -3.2818182 8.9181818 -3.2818182 1.4181818 9.6181818
7 8 9 10 11 12
-17.8818182 -7.7818182 -0.9818182 10.6181818 1.5181818 -10.0818182
13 14 15 16 17 18
-5.8818182 -4.8818182 4.5181818 8.3181818 0.1181818 7.9181818
19 20 21 22 23 24
-23.1818182 -7.1818182 8.3181818 9.5181818 3.5181818 -1.0818182
25 26 27 28 29 30
-0.9818182 -3.0818182 3.4181818 6.1181818 -2.3818182 11.6181818
31 32 33 34 35 36
-14.3818182 -15.6818182 12.9181818 19.6181818 -4.2818182 -0.6818182
37 38 39 40 41 42
-10.1818182 -5.5818182 15.2181818 8.4181818 0.1181818 20.4181818
43 44 45 46 47 48
-15.1818182 -7.2818182 8.8464286 6.0464286 1.2464286 -1.2535714
49 50 51 52 53 54
-15.5535714 -10.2535714 0.6464286 -2.9535714 -7.8535714 13.3464286
55 56 57 58 59 60
-32.7535714 -15.9535714 4.4464286 -0.4535714 4.5464286 -1.6535714
61 62 63 64 65 66
-10.5535714 -8.4535714 10.1464286 -5.1535714 8.5464286 18.7464286
67 68 69 70 71 72
-23.7535714 -8.3535714 16.1464286 23.1464286 20.5464286 8.5464286
> postscript(file="/var/www/html/freestat/rcomp/tmp/6forb1227560575.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 = 72
Frequency = 1
lag(myerror, k = 1) myerror
0 -6.9818182 NA
1 -3.2818182 -6.9818182
2 8.9181818 -3.2818182
3 -3.2818182 8.9181818
4 1.4181818 -3.2818182
5 9.6181818 1.4181818
6 -17.8818182 9.6181818
7 -7.7818182 -17.8818182
8 -0.9818182 -7.7818182
9 10.6181818 -0.9818182
10 1.5181818 10.6181818
11 -10.0818182 1.5181818
12 -5.8818182 -10.0818182
13 -4.8818182 -5.8818182
14 4.5181818 -4.8818182
15 8.3181818 4.5181818
16 0.1181818 8.3181818
17 7.9181818 0.1181818
18 -23.1818182 7.9181818
19 -7.1818182 -23.1818182
20 8.3181818 -7.1818182
21 9.5181818 8.3181818
22 3.5181818 9.5181818
23 -1.0818182 3.5181818
24 -0.9818182 -1.0818182
25 -3.0818182 -0.9818182
26 3.4181818 -3.0818182
27 6.1181818 3.4181818
28 -2.3818182 6.1181818
29 11.6181818 -2.3818182
30 -14.3818182 11.6181818
31 -15.6818182 -14.3818182
32 12.9181818 -15.6818182
33 19.6181818 12.9181818
34 -4.2818182 19.6181818
35 -0.6818182 -4.2818182
36 -10.1818182 -0.6818182
37 -5.5818182 -10.1818182
38 15.2181818 -5.5818182
39 8.4181818 15.2181818
40 0.1181818 8.4181818
41 20.4181818 0.1181818
42 -15.1818182 20.4181818
43 -7.2818182 -15.1818182
44 8.8464286 -7.2818182
45 6.0464286 8.8464286
46 1.2464286 6.0464286
47 -1.2535714 1.2464286
48 -15.5535714 -1.2535714
49 -10.2535714 -15.5535714
50 0.6464286 -10.2535714
51 -2.9535714 0.6464286
52 -7.8535714 -2.9535714
53 13.3464286 -7.8535714
54 -32.7535714 13.3464286
55 -15.9535714 -32.7535714
56 4.4464286 -15.9535714
57 -0.4535714 4.4464286
58 4.5464286 -0.4535714
59 -1.6535714 4.5464286
60 -10.5535714 -1.6535714
61 -8.4535714 -10.5535714
62 10.1464286 -8.4535714
63 -5.1535714 10.1464286
64 8.5464286 -5.1535714
65 18.7464286 8.5464286
66 -23.7535714 18.7464286
67 -8.3535714 -23.7535714
68 16.1464286 -8.3535714
69 23.1464286 16.1464286
70 20.5464286 23.1464286
71 8.5464286 20.5464286
72 NA 8.5464286
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -3.2818182 -6.9818182
[2,] 8.9181818 -3.2818182
[3,] -3.2818182 8.9181818
[4,] 1.4181818 -3.2818182
[5,] 9.6181818 1.4181818
[6,] -17.8818182 9.6181818
[7,] -7.7818182 -17.8818182
[8,] -0.9818182 -7.7818182
[9,] 10.6181818 -0.9818182
[10,] 1.5181818 10.6181818
[11,] -10.0818182 1.5181818
[12,] -5.8818182 -10.0818182
[13,] -4.8818182 -5.8818182
[14,] 4.5181818 -4.8818182
[15,] 8.3181818 4.5181818
[16,] 0.1181818 8.3181818
[17,] 7.9181818 0.1181818
[18,] -23.1818182 7.9181818
[19,] -7.1818182 -23.1818182
[20,] 8.3181818 -7.1818182
[21,] 9.5181818 8.3181818
[22,] 3.5181818 9.5181818
[23,] -1.0818182 3.5181818
[24,] -0.9818182 -1.0818182
[25,] -3.0818182 -0.9818182
[26,] 3.4181818 -3.0818182
[27,] 6.1181818 3.4181818
[28,] -2.3818182 6.1181818
[29,] 11.6181818 -2.3818182
[30,] -14.3818182 11.6181818
[31,] -15.6818182 -14.3818182
[32,] 12.9181818 -15.6818182
[33,] 19.6181818 12.9181818
[34,] -4.2818182 19.6181818
[35,] -0.6818182 -4.2818182
[36,] -10.1818182 -0.6818182
[37,] -5.5818182 -10.1818182
[38,] 15.2181818 -5.5818182
[39,] 8.4181818 15.2181818
[40,] 0.1181818 8.4181818
[41,] 20.4181818 0.1181818
[42,] -15.1818182 20.4181818
[43,] -7.2818182 -15.1818182
[44,] 8.8464286 -7.2818182
[45,] 6.0464286 8.8464286
[46,] 1.2464286 6.0464286
[47,] -1.2535714 1.2464286
[48,] -15.5535714 -1.2535714
[49,] -10.2535714 -15.5535714
[50,] 0.6464286 -10.2535714
[51,] -2.9535714 0.6464286
[52,] -7.8535714 -2.9535714
[53,] 13.3464286 -7.8535714
[54,] -32.7535714 13.3464286
[55,] -15.9535714 -32.7535714
[56,] 4.4464286 -15.9535714
[57,] -0.4535714 4.4464286
[58,] 4.5464286 -0.4535714
[59,] -1.6535714 4.5464286
[60,] -10.5535714 -1.6535714
[61,] -8.4535714 -10.5535714
[62,] 10.1464286 -8.4535714
[63,] -5.1535714 10.1464286
[64,] 8.5464286 -5.1535714
[65,] 18.7464286 8.5464286
[66,] -23.7535714 18.7464286
[67,] -8.3535714 -23.7535714
[68,] 16.1464286 -8.3535714
[69,] 23.1464286 16.1464286
[70,] 20.5464286 23.1464286
[71,] 8.5464286 20.5464286
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -3.2818182 -6.9818182
2 8.9181818 -3.2818182
3 -3.2818182 8.9181818
4 1.4181818 -3.2818182
5 9.6181818 1.4181818
6 -17.8818182 9.6181818
7 -7.7818182 -17.8818182
8 -0.9818182 -7.7818182
9 10.6181818 -0.9818182
10 1.5181818 10.6181818
11 -10.0818182 1.5181818
12 -5.8818182 -10.0818182
13 -4.8818182 -5.8818182
14 4.5181818 -4.8818182
15 8.3181818 4.5181818
16 0.1181818 8.3181818
17 7.9181818 0.1181818
18 -23.1818182 7.9181818
19 -7.1818182 -23.1818182
20 8.3181818 -7.1818182
21 9.5181818 8.3181818
22 3.5181818 9.5181818
23 -1.0818182 3.5181818
24 -0.9818182 -1.0818182
25 -3.0818182 -0.9818182
26 3.4181818 -3.0818182
27 6.1181818 3.4181818
28 -2.3818182 6.1181818
29 11.6181818 -2.3818182
30 -14.3818182 11.6181818
31 -15.6818182 -14.3818182
32 12.9181818 -15.6818182
33 19.6181818 12.9181818
34 -4.2818182 19.6181818
35 -0.6818182 -4.2818182
36 -10.1818182 -0.6818182
37 -5.5818182 -10.1818182
38 15.2181818 -5.5818182
39 8.4181818 15.2181818
40 0.1181818 8.4181818
41 20.4181818 0.1181818
42 -15.1818182 20.4181818
43 -7.2818182 -15.1818182
44 8.8464286 -7.2818182
45 6.0464286 8.8464286
46 1.2464286 6.0464286
47 -1.2535714 1.2464286
48 -15.5535714 -1.2535714
49 -10.2535714 -15.5535714
50 0.6464286 -10.2535714
51 -2.9535714 0.6464286
52 -7.8535714 -2.9535714
53 13.3464286 -7.8535714
54 -32.7535714 13.3464286
55 -15.9535714 -32.7535714
56 4.4464286 -15.9535714
57 -0.4535714 4.4464286
58 4.5464286 -0.4535714
59 -1.6535714 4.5464286
60 -10.5535714 -1.6535714
61 -8.4535714 -10.5535714
62 10.1464286 -8.4535714
63 -5.1535714 10.1464286
64 8.5464286 -5.1535714
65 18.7464286 8.5464286
66 -23.7535714 18.7464286
67 -8.3535714 -23.7535714
68 16.1464286 -8.3535714
69 23.1464286 16.1464286
70 20.5464286 23.1464286
71 8.5464286 20.5464286
> 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/756cq1227560575.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/8ansn1227560575.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/9bt0p1227560575.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
>
> #Note: the /var/www/html/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/freestat/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/102gw01227560575.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/11tupm1227560575.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/12sqjr1227560575.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/13r9r41227560575.tab")
>
> system("convert tmp/1usc91227560575.ps tmp/1usc91227560575.png")
> system("convert tmp/2kpgc1227560575.ps tmp/2kpgc1227560575.png")
> system("convert tmp/3y53t1227560575.ps tmp/3y53t1227560575.png")
> system("convert tmp/40x8q1227560575.ps tmp/40x8q1227560575.png")
> system("convert tmp/5w9ke1227560575.ps tmp/5w9ke1227560575.png")
> system("convert tmp/6forb1227560575.ps tmp/6forb1227560575.png")
> system("convert tmp/756cq1227560575.ps tmp/756cq1227560575.png")
> system("convert tmp/8ansn1227560575.ps tmp/8ansn1227560575.png")
> system("convert tmp/9bt0p1227560575.ps tmp/9bt0p1227560575.png")
>
>
> proc.time()
user system elapsed
3.052 2.304 3.401