R version 2.6.1 (2007-11-26)
Copyright (C) 2007 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(115.4
+ ,126.6
+ ,117
+ ,106.9
+ ,93.9
+ ,103.8
+ ,107.1
+ ,89.8
+ ,100.8
+ ,99.3
+ ,93.4
+ ,110.6
+ ,99.2
+ ,101.5
+ ,104
+ ,108.3
+ ,110.4
+ ,112.6
+ ,105.6
+ ,105.9
+ ,107.3
+ ,99.5
+ ,108.4
+ ,98.9
+ ,107.4
+ ,113.9
+ ,109.8
+ ,93.1
+ ,86.1
+ ,104.9
+ ,88.1
+ ,69.4
+ ,102.2
+ ,110.7
+ ,101.2
+ ,123.9
+ ,113.1
+ ,100.5
+ ,124.9
+ ,99.6
+ ,98
+ ,112.7
+ ,93.6
+ ,106.6
+ ,121.9
+ ,98.6
+ ,90.1
+ ,100.6
+ ,99.6
+ ,96.9
+ ,104.3
+ ,114.3
+ ,125.9
+ ,120.4
+ ,107.8
+ ,112
+ ,107.5
+ ,101.2
+ ,100
+ ,102.9
+ ,112.5
+ ,123.9
+ ,125.6
+ ,100.5
+ ,79.8
+ ,107.5
+ ,93.9
+ ,83.4
+ ,108.8
+ ,116.2
+ ,113.6
+ ,128.4
+ ,112
+ ,112.9
+ ,121.1
+ ,106.4
+ ,104
+ ,119.5
+ ,95.7
+ ,109.9
+ ,128.7
+ ,96
+ ,99
+ ,108.7
+ ,95.8
+ ,106.3
+ ,105.5
+ ,103
+ ,128.9
+ ,119.8
+ ,102.2
+ ,111.1
+ ,111.3
+ ,98.4
+ ,102.9
+ ,110.6
+ ,111.4
+ ,130
+ ,120.1
+ ,86.6
+ ,87
+ ,97.5
+ ,91.3
+ ,87.5
+ ,107.7
+ ,107.9
+ ,117.6
+ ,127.3
+ ,101.8
+ ,103.4
+ ,117.2
+ ,104.4
+ ,110.8
+ ,119.8
+ ,93.4
+ ,112.6
+ ,116.2
+ ,100.1
+ ,102.5
+ ,111
+ ,98.5
+ ,112.4
+ ,112.4
+ ,112.9
+ ,135.6
+ ,130.6
+ ,101.4
+ ,105.1
+ ,109.1
+ ,107.1
+ ,127.7
+ ,118.8
+ ,110.8
+ ,137
+ ,123.9
+ ,90.3
+ ,91
+ ,101.6
+ ,95.5
+ ,90.5
+ ,112.8
+ ,111.4
+ ,122.4
+ ,128
+ ,113
+ ,123.3
+ ,129.6
+ ,107.5
+ ,124.3
+ ,125.8
+ ,95.9
+ ,120
+ ,119.5
+ ,106.3
+ ,118.1
+ ,115.7
+ ,105.2
+ ,119
+ ,113.6
+ ,117.2
+ ,142.7
+ ,129.7
+ ,106.9
+ ,123.6
+ ,112
+ ,108.2
+ ,129.6
+ ,116.8
+ ,113
+ ,151.6
+ ,127
+ ,96.1
+ ,108.7
+ ,112.9
+ ,100.2
+ ,99.3
+ ,113.3
+ ,108.1
+ ,126.4
+ ,121.7)
+ ,dim=c(3
+ ,60)
+ ,dimnames=list(c('Inter.'
+ ,'Inv.'
+ ,'Cons.')
+ ,1:60))
> y <- array(NA,dim=c(3,60),dimnames=list(c('Inter.','Inv.','Cons.'),1:60))
> 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 = '3'
> #'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
Cons. Inter. Inv.
1 117.0 115.4 126.6
2 103.8 106.9 93.9
3 100.8 107.1 89.8
4 110.6 99.3 93.4
5 104.0 99.2 101.5
6 112.6 108.3 110.4
7 107.3 105.6 105.9
8 98.9 99.5 108.4
9 109.8 107.4 113.9
10 104.9 93.1 86.1
11 102.2 88.1 69.4
12 123.9 110.7 101.2
13 124.9 113.1 100.5
14 112.7 99.6 98.0
15 121.9 93.6 106.6
16 100.6 98.6 90.1
17 104.3 99.6 96.9
18 120.4 114.3 125.9
19 107.5 107.8 112.0
20 102.9 101.2 100.0
21 125.6 112.5 123.9
22 107.5 100.5 79.8
23 108.8 93.9 83.4
24 128.4 116.2 113.6
25 121.1 112.0 112.9
26 119.5 106.4 104.0
27 128.7 95.7 109.9
28 108.7 96.0 99.0
29 105.5 95.8 106.3
30 119.8 103.0 128.9
31 111.3 102.2 111.1
32 110.6 98.4 102.9
33 120.1 111.4 130.0
34 97.5 86.6 87.0
35 107.7 91.3 87.5
36 127.3 107.9 117.6
37 117.2 101.8 103.4
38 119.8 104.4 110.8
39 116.2 93.4 112.6
40 111.0 100.1 102.5
41 112.4 98.5 112.4
42 130.6 112.9 135.6
43 109.1 101.4 105.1
44 118.8 107.1 127.7
45 123.9 110.8 137.0
46 101.6 90.3 91.0
47 112.8 95.5 90.5
48 128.0 111.4 122.4
49 129.6 113.0 123.3
50 125.8 107.5 124.3
51 119.5 95.9 120.0
52 115.7 106.3 118.1
53 113.6 105.2 119.0
54 129.7 117.2 142.7
55 112.0 106.9 123.6
56 116.8 108.2 129.6
57 127.0 113.0 151.6
58 112.9 96.1 108.7
59 113.3 100.2 99.3
60 121.7 108.1 126.4
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Inter. Inv.
48.8917 0.3389 0.2806
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-14.1272 -4.5309 -0.3345 4.4381 16.5396
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 48.89174 11.51750 4.245 8.14e-05 ***
Inter. 0.33889 0.14952 2.267 0.027232 *
Inv. 0.28059 0.06899 4.067 0.000148 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 6.171 on 57 degrees of freedom
Multiple R-Squared: 0.5453, Adjusted R-squared: 0.5293
F-statistic: 34.17 on 2 and 57 DF, p-value: 1.762e-10
> postscript(file="/var/www/html/rcomp/tmp/1pk7r1198175475.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/2nwa61198175475.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/31ndh1198175475.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/43olr1198175475.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/51e7j1198175475.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
> grid()
> dev.off()
null device
1
> (myerror <- as.ts(mysum$resid))
Time Series:
Start = 1
End = 60
Frequency = 1
1 2 3 4 5 6
-6.5223336 -7.6664578 -9.5838133 1.8493943 -6.9895023 -3.9706506
7 8 9 10 11 12
-7.0929916 -14.1272455 -7.4477182 0.2988191 3.9791305 9.0974511
13 14 15 16 17 18
9.4805310 2.5570099 11.3772632 -6.9874338 -5.5343402 -2.5531421
19 20 21 22 23 24
-9.3501513 -8.3463942 3.8180398 2.1587623 4.6853030 8.2542356
25 26 27 28 29 30
2.5739830 5.3690197 16.5396466 -0.5035804 -5.6841154 -0.1654685
31 32 33 34 35 36
-3.3998410 -0.5112182 -3.0207862 -5.1509340 3.3159922 8.8446513
37 38 39 40 41 42
4.7962637 4.4387803 4.0614962 -0.5750932 -1.4107197 5.3995718
43 44 45 46 47 48
-3.6451850 -2.2182045 -0.9815883 -3.4271866 6.1508859 7.0117039
49 50 51 52 53 54
7.8169497 5.6002486 4.4379018 -2.3534216 -4.3331754 1.0501543
55 56 57 58 59 60
-7.8000044 -5.1241050 -2.7237698 0.9408000 2.5889084 0.7076745
> postscript(file="/var/www/html/rcomp/tmp/6dspy1198175475.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 = 60
Frequency = 1
lag(myerror, k = 1) myerror
0 -6.5223336 NA
1 -7.6664578 -6.5223336
2 -9.5838133 -7.6664578
3 1.8493943 -9.5838133
4 -6.9895023 1.8493943
5 -3.9706506 -6.9895023
6 -7.0929916 -3.9706506
7 -14.1272455 -7.0929916
8 -7.4477182 -14.1272455
9 0.2988191 -7.4477182
10 3.9791305 0.2988191
11 9.0974511 3.9791305
12 9.4805310 9.0974511
13 2.5570099 9.4805310
14 11.3772632 2.5570099
15 -6.9874338 11.3772632
16 -5.5343402 -6.9874338
17 -2.5531421 -5.5343402
18 -9.3501513 -2.5531421
19 -8.3463942 -9.3501513
20 3.8180398 -8.3463942
21 2.1587623 3.8180398
22 4.6853030 2.1587623
23 8.2542356 4.6853030
24 2.5739830 8.2542356
25 5.3690197 2.5739830
26 16.5396466 5.3690197
27 -0.5035804 16.5396466
28 -5.6841154 -0.5035804
29 -0.1654685 -5.6841154
30 -3.3998410 -0.1654685
31 -0.5112182 -3.3998410
32 -3.0207862 -0.5112182
33 -5.1509340 -3.0207862
34 3.3159922 -5.1509340
35 8.8446513 3.3159922
36 4.7962637 8.8446513
37 4.4387803 4.7962637
38 4.0614962 4.4387803
39 -0.5750932 4.0614962
40 -1.4107197 -0.5750932
41 5.3995718 -1.4107197
42 -3.6451850 5.3995718
43 -2.2182045 -3.6451850
44 -0.9815883 -2.2182045
45 -3.4271866 -0.9815883
46 6.1508859 -3.4271866
47 7.0117039 6.1508859
48 7.8169497 7.0117039
49 5.6002486 7.8169497
50 4.4379018 5.6002486
51 -2.3534216 4.4379018
52 -4.3331754 -2.3534216
53 1.0501543 -4.3331754
54 -7.8000044 1.0501543
55 -5.1241050 -7.8000044
56 -2.7237698 -5.1241050
57 0.9408000 -2.7237698
58 2.5889084 0.9408000
59 0.7076745 2.5889084
60 NA 0.7076745
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -7.6664578 -6.5223336
[2,] -9.5838133 -7.6664578
[3,] 1.8493943 -9.5838133
[4,] -6.9895023 1.8493943
[5,] -3.9706506 -6.9895023
[6,] -7.0929916 -3.9706506
[7,] -14.1272455 -7.0929916
[8,] -7.4477182 -14.1272455
[9,] 0.2988191 -7.4477182
[10,] 3.9791305 0.2988191
[11,] 9.0974511 3.9791305
[12,] 9.4805310 9.0974511
[13,] 2.5570099 9.4805310
[14,] 11.3772632 2.5570099
[15,] -6.9874338 11.3772632
[16,] -5.5343402 -6.9874338
[17,] -2.5531421 -5.5343402
[18,] -9.3501513 -2.5531421
[19,] -8.3463942 -9.3501513
[20,] 3.8180398 -8.3463942
[21,] 2.1587623 3.8180398
[22,] 4.6853030 2.1587623
[23,] 8.2542356 4.6853030
[24,] 2.5739830 8.2542356
[25,] 5.3690197 2.5739830
[26,] 16.5396466 5.3690197
[27,] -0.5035804 16.5396466
[28,] -5.6841154 -0.5035804
[29,] -0.1654685 -5.6841154
[30,] -3.3998410 -0.1654685
[31,] -0.5112182 -3.3998410
[32,] -3.0207862 -0.5112182
[33,] -5.1509340 -3.0207862
[34,] 3.3159922 -5.1509340
[35,] 8.8446513 3.3159922
[36,] 4.7962637 8.8446513
[37,] 4.4387803 4.7962637
[38,] 4.0614962 4.4387803
[39,] -0.5750932 4.0614962
[40,] -1.4107197 -0.5750932
[41,] 5.3995718 -1.4107197
[42,] -3.6451850 5.3995718
[43,] -2.2182045 -3.6451850
[44,] -0.9815883 -2.2182045
[45,] -3.4271866 -0.9815883
[46,] 6.1508859 -3.4271866
[47,] 7.0117039 6.1508859
[48,] 7.8169497 7.0117039
[49,] 5.6002486 7.8169497
[50,] 4.4379018 5.6002486
[51,] -2.3534216 4.4379018
[52,] -4.3331754 -2.3534216
[53,] 1.0501543 -4.3331754
[54,] -7.8000044 1.0501543
[55,] -5.1241050 -7.8000044
[56,] -2.7237698 -5.1241050
[57,] 0.9408000 -2.7237698
[58,] 2.5889084 0.9408000
[59,] 0.7076745 2.5889084
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -7.6664578 -6.5223336
2 -9.5838133 -7.6664578
3 1.8493943 -9.5838133
4 -6.9895023 1.8493943
5 -3.9706506 -6.9895023
6 -7.0929916 -3.9706506
7 -14.1272455 -7.0929916
8 -7.4477182 -14.1272455
9 0.2988191 -7.4477182
10 3.9791305 0.2988191
11 9.0974511 3.9791305
12 9.4805310 9.0974511
13 2.5570099 9.4805310
14 11.3772632 2.5570099
15 -6.9874338 11.3772632
16 -5.5343402 -6.9874338
17 -2.5531421 -5.5343402
18 -9.3501513 -2.5531421
19 -8.3463942 -9.3501513
20 3.8180398 -8.3463942
21 2.1587623 3.8180398
22 4.6853030 2.1587623
23 8.2542356 4.6853030
24 2.5739830 8.2542356
25 5.3690197 2.5739830
26 16.5396466 5.3690197
27 -0.5035804 16.5396466
28 -5.6841154 -0.5035804
29 -0.1654685 -5.6841154
30 -3.3998410 -0.1654685
31 -0.5112182 -3.3998410
32 -3.0207862 -0.5112182
33 -5.1509340 -3.0207862
34 3.3159922 -5.1509340
35 8.8446513 3.3159922
36 4.7962637 8.8446513
37 4.4387803 4.7962637
38 4.0614962 4.4387803
39 -0.5750932 4.0614962
40 -1.4107197 -0.5750932
41 5.3995718 -1.4107197
42 -3.6451850 5.3995718
43 -2.2182045 -3.6451850
44 -0.9815883 -2.2182045
45 -3.4271866 -0.9815883
46 6.1508859 -3.4271866
47 7.0117039 6.1508859
48 7.8169497 7.0117039
49 5.6002486 7.8169497
50 4.4379018 5.6002486
51 -2.3534216 4.4379018
52 -4.3331754 -2.3534216
53 1.0501543 -4.3331754
54 -7.8000044 1.0501543
55 -5.1241050 -7.8000044
56 -2.7237698 -5.1241050
57 0.9408000 -2.7237698
58 2.5889084 0.9408000
59 0.7076745 2.5889084
> 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/7uqyr1198175475.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/87dd51198175475.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9iika1198175475.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> load(file='/var/www/html/rcomp/createtable')
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/10v5uw1198175475.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/11qxrp1198175475.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/12jq1k1198175476.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/130hl51198175476.tab")
>
> system("convert tmp/1pk7r1198175475.ps tmp/1pk7r1198175475.png")
> system("convert tmp/2nwa61198175475.ps tmp/2nwa61198175475.png")
> system("convert tmp/31ndh1198175475.ps tmp/31ndh1198175475.png")
> system("convert tmp/43olr1198175475.ps tmp/43olr1198175475.png")
> system("convert tmp/51e7j1198175475.ps tmp/51e7j1198175475.png")
> system("convert tmp/6dspy1198175475.ps tmp/6dspy1198175475.png")
> system("convert tmp/7uqyr1198175475.ps tmp/7uqyr1198175475.png")
> system("convert tmp/87dd51198175475.ps tmp/87dd51198175475.png")
> system("convert tmp/9iika1198175475.ps tmp/9iika1198175475.png")
>
>
> proc.time()
user system elapsed
4.004 2.489 4.344