R version 2.7.0 (2008-04-22)
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(119.5,0,125,0,145,0,105.3,0,116.9,0,120.1,0,88.9,0,78.4,0,114.6,0,113.3,0,117,0,99.6,0,99.4,0,101.9,0,115.2,0,108.5,0,113.8,0,121,0,92.2,0,90.2,0,101.5,0,126.6,0,93.9,0,89.8,0,93.4,0,101.5,0,110.4,0,105.9,0,108.4,0,113.9,0,86.1,0,69.4,0,101.2,0,100.5,0,98,0,106.6,0,90.1,0,96.9,0,109.9,0,99,0,106.3,0,128.9,0,111.1,0,102.9,0,130,0,87,0,87.5,0,117.6,0,103.4,0,110.8,0,112.6,0,102.5,1,112.4,1,135.6,1,105.1,1,127.7,1,137,1,91,1,90.5,1,122.4,1,123.3,1,124.3,1,120,1,118.1,1,119,1,142.7,1,123.6,1,129.6,1,151.6,1,110.4,1,99.2,1,130.5,1,136.2,1,129.7,1,128,1,121.6,1),dim=c(2,76),dimnames=list(c('y','x'),1:76))
> y <- array(NA,dim=c(2,76),dimnames=list(c('y','x'),1:76))
> 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
1 119.5 0
2 125.0 0
3 145.0 0
4 105.3 0
5 116.9 0
6 120.1 0
7 88.9 0
8 78.4 0
9 114.6 0
10 113.3 0
11 117.0 0
12 99.6 0
13 99.4 0
14 101.9 0
15 115.2 0
16 108.5 0
17 113.8 0
18 121.0 0
19 92.2 0
20 90.2 0
21 101.5 0
22 126.6 0
23 93.9 0
24 89.8 0
25 93.4 0
26 101.5 0
27 110.4 0
28 105.9 0
29 108.4 0
30 113.9 0
31 86.1 0
32 69.4 0
33 101.2 0
34 100.5 0
35 98.0 0
36 106.6 0
37 90.1 0
38 96.9 0
39 109.9 0
40 99.0 0
41 106.3 0
42 128.9 0
43 111.1 0
44 102.9 0
45 130.0 0
46 87.0 0
47 87.5 0
48 117.6 0
49 103.4 0
50 110.8 0
51 112.6 0
52 102.5 1
53 112.4 1
54 135.6 1
55 105.1 1
56 127.7 1
57 137.0 1
58 91.0 1
59 90.5 1
60 122.4 1
61 123.3 1
62 124.3 1
63 120.0 1
64 118.1 1
65 119.0 1
66 142.7 1
67 123.6 1
68 129.6 1
69 151.6 1
70 110.4 1
71 99.2 1
72 130.5 1
73 136.2 1
74 129.7 1
75 128.0 1
76 121.6 1
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) x
105.63 15.65
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-36.2255 -8.7641 0.8245 8.5586 39.3745
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 105.625 2.032 51.984 < 2e-16 ***
x 15.655 3.543 4.419 3.34e-05 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 14.51 on 74 degrees of freedom
Multiple R-squared: 0.2088, Adjusted R-squared: 0.1981
F-statistic: 19.53 on 1 and 74 DF, p-value: 3.339e-05
> postscript(file="/var/www/html/rcomp/tmp/1tn2s1227455077.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/2ex5m1227455077.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/3vwkq1227455077.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4s2km1227455077.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5s88k1227455077.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
> grid()
> dev.off()
null device
1
> (myerror <- as.ts(mysum$resid))
Time Series:
Start = 1
End = 76
Frequency = 1
1 2 3 4 5 6
13.8745098 19.3745098 39.3745098 -0.3254902 11.2745098 14.4745098
7 8 9 10 11 12
-16.7254902 -27.2254902 8.9745098 7.6745098 11.3745098 -6.0254902
13 14 15 16 17 18
-6.2254902 -3.7254902 9.5745098 2.8745098 8.1745098 15.3745098
19 20 21 22 23 24
-13.4254902 -15.4254902 -4.1254902 20.9745098 -11.7254902 -15.8254902
25 26 27 28 29 30
-12.2254902 -4.1254902 4.7745098 0.2745098 2.7745098 8.2745098
31 32 33 34 35 36
-19.5254902 -36.2254902 -4.4254902 -5.1254902 -7.6254902 0.9745098
37 38 39 40 41 42
-15.5254902 -8.7254902 4.2745098 -6.6254902 0.6745098 23.2745098
43 44 45 46 47 48
5.4745098 -2.7254902 24.3745098 -18.6254902 -18.1254902 11.9745098
49 50 51 52 53 54
-2.2254902 5.1745098 6.9745098 -18.7800000 -8.8800000 14.3200000
55 56 57 58 59 60
-16.1800000 6.4200000 15.7200000 -30.2800000 -30.7800000 1.1200000
61 62 63 64 65 66
2.0200000 3.0200000 -1.2800000 -3.1800000 -2.2800000 21.4200000
67 68 69 70 71 72
2.3200000 8.3200000 30.3200000 -10.8800000 -22.0800000 9.2200000
73 74 75 76
14.9200000 8.4200000 6.7200000 0.3200000
> postscript(file="/var/www/html/rcomp/tmp/6o65k1227455077.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 = 76
Frequency = 1
lag(myerror, k = 1) myerror
0 13.8745098 NA
1 19.3745098 13.8745098
2 39.3745098 19.3745098
3 -0.3254902 39.3745098
4 11.2745098 -0.3254902
5 14.4745098 11.2745098
6 -16.7254902 14.4745098
7 -27.2254902 -16.7254902
8 8.9745098 -27.2254902
9 7.6745098 8.9745098
10 11.3745098 7.6745098
11 -6.0254902 11.3745098
12 -6.2254902 -6.0254902
13 -3.7254902 -6.2254902
14 9.5745098 -3.7254902
15 2.8745098 9.5745098
16 8.1745098 2.8745098
17 15.3745098 8.1745098
18 -13.4254902 15.3745098
19 -15.4254902 -13.4254902
20 -4.1254902 -15.4254902
21 20.9745098 -4.1254902
22 -11.7254902 20.9745098
23 -15.8254902 -11.7254902
24 -12.2254902 -15.8254902
25 -4.1254902 -12.2254902
26 4.7745098 -4.1254902
27 0.2745098 4.7745098
28 2.7745098 0.2745098
29 8.2745098 2.7745098
30 -19.5254902 8.2745098
31 -36.2254902 -19.5254902
32 -4.4254902 -36.2254902
33 -5.1254902 -4.4254902
34 -7.6254902 -5.1254902
35 0.9745098 -7.6254902
36 -15.5254902 0.9745098
37 -8.7254902 -15.5254902
38 4.2745098 -8.7254902
39 -6.6254902 4.2745098
40 0.6745098 -6.6254902
41 23.2745098 0.6745098
42 5.4745098 23.2745098
43 -2.7254902 5.4745098
44 24.3745098 -2.7254902
45 -18.6254902 24.3745098
46 -18.1254902 -18.6254902
47 11.9745098 -18.1254902
48 -2.2254902 11.9745098
49 5.1745098 -2.2254902
50 6.9745098 5.1745098
51 -18.7800000 6.9745098
52 -8.8800000 -18.7800000
53 14.3200000 -8.8800000
54 -16.1800000 14.3200000
55 6.4200000 -16.1800000
56 15.7200000 6.4200000
57 -30.2800000 15.7200000
58 -30.7800000 -30.2800000
59 1.1200000 -30.7800000
60 2.0200000 1.1200000
61 3.0200000 2.0200000
62 -1.2800000 3.0200000
63 -3.1800000 -1.2800000
64 -2.2800000 -3.1800000
65 21.4200000 -2.2800000
66 2.3200000 21.4200000
67 8.3200000 2.3200000
68 30.3200000 8.3200000
69 -10.8800000 30.3200000
70 -22.0800000 -10.8800000
71 9.2200000 -22.0800000
72 14.9200000 9.2200000
73 8.4200000 14.9200000
74 6.7200000 8.4200000
75 0.3200000 6.7200000
76 NA 0.3200000
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 19.3745098 13.8745098
[2,] 39.3745098 19.3745098
[3,] -0.3254902 39.3745098
[4,] 11.2745098 -0.3254902
[5,] 14.4745098 11.2745098
[6,] -16.7254902 14.4745098
[7,] -27.2254902 -16.7254902
[8,] 8.9745098 -27.2254902
[9,] 7.6745098 8.9745098
[10,] 11.3745098 7.6745098
[11,] -6.0254902 11.3745098
[12,] -6.2254902 -6.0254902
[13,] -3.7254902 -6.2254902
[14,] 9.5745098 -3.7254902
[15,] 2.8745098 9.5745098
[16,] 8.1745098 2.8745098
[17,] 15.3745098 8.1745098
[18,] -13.4254902 15.3745098
[19,] -15.4254902 -13.4254902
[20,] -4.1254902 -15.4254902
[21,] 20.9745098 -4.1254902
[22,] -11.7254902 20.9745098
[23,] -15.8254902 -11.7254902
[24,] -12.2254902 -15.8254902
[25,] -4.1254902 -12.2254902
[26,] 4.7745098 -4.1254902
[27,] 0.2745098 4.7745098
[28,] 2.7745098 0.2745098
[29,] 8.2745098 2.7745098
[30,] -19.5254902 8.2745098
[31,] -36.2254902 -19.5254902
[32,] -4.4254902 -36.2254902
[33,] -5.1254902 -4.4254902
[34,] -7.6254902 -5.1254902
[35,] 0.9745098 -7.6254902
[36,] -15.5254902 0.9745098
[37,] -8.7254902 -15.5254902
[38,] 4.2745098 -8.7254902
[39,] -6.6254902 4.2745098
[40,] 0.6745098 -6.6254902
[41,] 23.2745098 0.6745098
[42,] 5.4745098 23.2745098
[43,] -2.7254902 5.4745098
[44,] 24.3745098 -2.7254902
[45,] -18.6254902 24.3745098
[46,] -18.1254902 -18.6254902
[47,] 11.9745098 -18.1254902
[48,] -2.2254902 11.9745098
[49,] 5.1745098 -2.2254902
[50,] 6.9745098 5.1745098
[51,] -18.7800000 6.9745098
[52,] -8.8800000 -18.7800000
[53,] 14.3200000 -8.8800000
[54,] -16.1800000 14.3200000
[55,] 6.4200000 -16.1800000
[56,] 15.7200000 6.4200000
[57,] -30.2800000 15.7200000
[58,] -30.7800000 -30.2800000
[59,] 1.1200000 -30.7800000
[60,] 2.0200000 1.1200000
[61,] 3.0200000 2.0200000
[62,] -1.2800000 3.0200000
[63,] -3.1800000 -1.2800000
[64,] -2.2800000 -3.1800000
[65,] 21.4200000 -2.2800000
[66,] 2.3200000 21.4200000
[67,] 8.3200000 2.3200000
[68,] 30.3200000 8.3200000
[69,] -10.8800000 30.3200000
[70,] -22.0800000 -10.8800000
[71,] 9.2200000 -22.0800000
[72,] 14.9200000 9.2200000
[73,] 8.4200000 14.9200000
[74,] 6.7200000 8.4200000
[75,] 0.3200000 6.7200000
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 19.3745098 13.8745098
2 39.3745098 19.3745098
3 -0.3254902 39.3745098
4 11.2745098 -0.3254902
5 14.4745098 11.2745098
6 -16.7254902 14.4745098
7 -27.2254902 -16.7254902
8 8.9745098 -27.2254902
9 7.6745098 8.9745098
10 11.3745098 7.6745098
11 -6.0254902 11.3745098
12 -6.2254902 -6.0254902
13 -3.7254902 -6.2254902
14 9.5745098 -3.7254902
15 2.8745098 9.5745098
16 8.1745098 2.8745098
17 15.3745098 8.1745098
18 -13.4254902 15.3745098
19 -15.4254902 -13.4254902
20 -4.1254902 -15.4254902
21 20.9745098 -4.1254902
22 -11.7254902 20.9745098
23 -15.8254902 -11.7254902
24 -12.2254902 -15.8254902
25 -4.1254902 -12.2254902
26 4.7745098 -4.1254902
27 0.2745098 4.7745098
28 2.7745098 0.2745098
29 8.2745098 2.7745098
30 -19.5254902 8.2745098
31 -36.2254902 -19.5254902
32 -4.4254902 -36.2254902
33 -5.1254902 -4.4254902
34 -7.6254902 -5.1254902
35 0.9745098 -7.6254902
36 -15.5254902 0.9745098
37 -8.7254902 -15.5254902
38 4.2745098 -8.7254902
39 -6.6254902 4.2745098
40 0.6745098 -6.6254902
41 23.2745098 0.6745098
42 5.4745098 23.2745098
43 -2.7254902 5.4745098
44 24.3745098 -2.7254902
45 -18.6254902 24.3745098
46 -18.1254902 -18.6254902
47 11.9745098 -18.1254902
48 -2.2254902 11.9745098
49 5.1745098 -2.2254902
50 6.9745098 5.1745098
51 -18.7800000 6.9745098
52 -8.8800000 -18.7800000
53 14.3200000 -8.8800000
54 -16.1800000 14.3200000
55 6.4200000 -16.1800000
56 15.7200000 6.4200000
57 -30.2800000 15.7200000
58 -30.7800000 -30.2800000
59 1.1200000 -30.7800000
60 2.0200000 1.1200000
61 3.0200000 2.0200000
62 -1.2800000 3.0200000
63 -3.1800000 -1.2800000
64 -2.2800000 -3.1800000
65 21.4200000 -2.2800000
66 2.3200000 21.4200000
67 8.3200000 2.3200000
68 30.3200000 8.3200000
69 -10.8800000 30.3200000
70 -22.0800000 -10.8800000
71 9.2200000 -22.0800000
72 14.9200000 9.2200000
73 8.4200000 14.9200000
74 6.7200000 8.4200000
75 0.3200000 6.7200000
> 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/7zivx1227455077.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8cm341227455077.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9zv1w1227455077.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/10fccj1227455077.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/11ql0x1227455077.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/12c3v11227455078.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/13lzo11227455078.tab")
>
> system("convert tmp/1tn2s1227455077.ps tmp/1tn2s1227455077.png")
> system("convert tmp/2ex5m1227455077.ps tmp/2ex5m1227455077.png")
> system("convert tmp/3vwkq1227455077.ps tmp/3vwkq1227455077.png")
> system("convert tmp/4s2km1227455077.ps tmp/4s2km1227455077.png")
> system("convert tmp/5s88k1227455077.ps tmp/5s88k1227455077.png")
> system("convert tmp/6o65k1227455077.ps tmp/6o65k1227455077.png")
> system("convert tmp/7zivx1227455077.ps tmp/7zivx1227455077.png")
> system("convert tmp/8cm341227455077.ps tmp/8cm341227455077.png")
> system("convert tmp/9zv1w1227455077.ps tmp/9zv1w1227455077.png")
>
>
> proc.time()
user system elapsed
6.349 3.692 6.944