R version 2.9.0 (2009-04-17)
Copyright (C) 2009 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(286602,0,283042,0,276687,0,277915,0,277128,0,277103,0,275037,0,270150,0,267140,0,264993,0,287259,0,291186,0,292300,0,288186,0,281477,0,282656,0,280190,0,280408,0,276836,0,275216,0,274352,0,271311,0,289802,0,290726,0,292300,0,278506,0,269826,0,265861,0,269034,0,264176,0,255198,0,253353,0,246057,0,235372,0,258556,0,260993,0,254663,0,250643,0,243422,0,247105,0,248541,0,245039,0,237080,0,237085,0,225554,0,226839,0,247934,0,248333,1,246969,1,245098,1,246263,1,255765,1,264319,1,268347,1,273046,1,273963,1,267430,1,271993,1,292710,1,295881,1),dim=c(2,60),dimnames=list(c('nwwmb','dummy_variable'),1:60))
> y <- array(NA,dim=c(2,60),dimnames=list(c('nwwmb','dummy_variable'),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 = 'Linear Trend'
> par2 = 'Include Monthly 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
nwwmb dummy_variable M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 286602 0 1 0 0 0 0 0 0 0 0 0 0 1
2 283042 0 0 1 0 0 0 0 0 0 0 0 0 2
3 276687 0 0 0 1 0 0 0 0 0 0 0 0 3
4 277915 0 0 0 0 1 0 0 0 0 0 0 0 4
5 277128 0 0 0 0 0 1 0 0 0 0 0 0 5
6 277103 0 0 0 0 0 0 1 0 0 0 0 0 6
7 275037 0 0 0 0 0 0 0 1 0 0 0 0 7
8 270150 0 0 0 0 0 0 0 0 1 0 0 0 8
9 267140 0 0 0 0 0 0 0 0 0 1 0 0 9
10 264993 0 0 0 0 0 0 0 0 0 0 1 0 10
11 287259 0 0 0 0 0 0 0 0 0 0 0 1 11
12 291186 0 0 0 0 0 0 0 0 0 0 0 0 12
13 292300 0 1 0 0 0 0 0 0 0 0 0 0 13
14 288186 0 0 1 0 0 0 0 0 0 0 0 0 14
15 281477 0 0 0 1 0 0 0 0 0 0 0 0 15
16 282656 0 0 0 0 1 0 0 0 0 0 0 0 16
17 280190 0 0 0 0 0 1 0 0 0 0 0 0 17
18 280408 0 0 0 0 0 0 1 0 0 0 0 0 18
19 276836 0 0 0 0 0 0 0 1 0 0 0 0 19
20 275216 0 0 0 0 0 0 0 0 1 0 0 0 20
21 274352 0 0 0 0 0 0 0 0 0 1 0 0 21
22 271311 0 0 0 0 0 0 0 0 0 0 1 0 22
23 289802 0 0 0 0 0 0 0 0 0 0 0 1 23
24 290726 0 0 0 0 0 0 0 0 0 0 0 0 24
25 292300 0 1 0 0 0 0 0 0 0 0 0 0 25
26 278506 0 0 1 0 0 0 0 0 0 0 0 0 26
27 269826 0 0 0 1 0 0 0 0 0 0 0 0 27
28 265861 0 0 0 0 1 0 0 0 0 0 0 0 28
29 269034 0 0 0 0 0 1 0 0 0 0 0 0 29
30 264176 0 0 0 0 0 0 1 0 0 0 0 0 30
31 255198 0 0 0 0 0 0 0 1 0 0 0 0 31
32 253353 0 0 0 0 0 0 0 0 1 0 0 0 32
33 246057 0 0 0 0 0 0 0 0 0 1 0 0 33
34 235372 0 0 0 0 0 0 0 0 0 0 1 0 34
35 258556 0 0 0 0 0 0 0 0 0 0 0 1 35
36 260993 0 0 0 0 0 0 0 0 0 0 0 0 36
37 254663 0 1 0 0 0 0 0 0 0 0 0 0 37
38 250643 0 0 1 0 0 0 0 0 0 0 0 0 38
39 243422 0 0 0 1 0 0 0 0 0 0 0 0 39
40 247105 0 0 0 0 1 0 0 0 0 0 0 0 40
41 248541 0 0 0 0 0 1 0 0 0 0 0 0 41
42 245039 0 0 0 0 0 0 1 0 0 0 0 0 42
43 237080 0 0 0 0 0 0 0 1 0 0 0 0 43
44 237085 0 0 0 0 0 0 0 0 1 0 0 0 44
45 225554 0 0 0 0 0 0 0 0 0 1 0 0 45
46 226839 0 0 0 0 0 0 0 0 0 0 1 0 46
47 247934 0 0 0 0 0 0 0 0 0 0 0 1 47
48 248333 1 0 0 0 0 0 0 0 0 0 0 0 48
49 246969 1 1 0 0 0 0 0 0 0 0 0 0 49
50 245098 1 0 1 0 0 0 0 0 0 0 0 0 50
51 246263 1 0 0 1 0 0 0 0 0 0 0 0 51
52 255765 1 0 0 0 1 0 0 0 0 0 0 0 52
53 264319 1 0 0 0 0 1 0 0 0 0 0 0 53
54 268347 1 0 0 0 0 0 1 0 0 0 0 0 54
55 273046 1 0 0 0 0 0 0 1 0 0 0 0 55
56 273963 1 0 0 0 0 0 0 0 1 0 0 0 56
57 267430 1 0 0 0 0 0 0 0 0 1 0 0 57
58 271993 1 0 0 0 0 0 0 0 0 0 1 0 58
59 292710 1 0 0 0 0 0 0 0 0 0 0 1 59
60 295881 1 0 0 0 0 0 0 0 0 0 0 0 60
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) dummy_variable M1 M2 M3
301925.2 27102.1 -8235.6 -12725.7 -17303.9
M4 M5 M6 M7 M8
-13996.8 -11033.1 -10879.2 -13472.6 -13976.9
M9 M10 M11 t
-18842.0 -19865.2 2267.1 -981.7
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-33571 -7354 -2401 10539 25757
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 301925.2 7126.7 42.366 < 2e-16 ***
dummy_variable 27102.1 6092.4 4.448 5.44e-05 ***
M1 -8235.6 8508.3 -0.968 0.3381
M2 -12725.7 8496.9 -1.498 0.1410
M3 -17303.9 8488.0 -2.039 0.0473 *
M4 -13996.8 8481.7 -1.650 0.1057
M5 -11033.1 8477.9 -1.301 0.1996
M6 -10879.2 8476.6 -1.283 0.2058
M7 -13472.6 8477.9 -1.589 0.1189
M8 -13976.9 8481.7 -1.648 0.1062
M9 -18842.0 8488.0 -2.220 0.0314 *
M10 -19865.2 8496.9 -2.338 0.0238 *
M11 2267.1 8508.3 0.266 0.7911
t -981.7 146.6 -6.698 2.58e-08 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 13340 on 46 degrees of freedom
Multiple R-squared: 0.571, Adjusted R-squared: 0.4497
F-statistic: 4.709 on 13 and 46 DF, p-value: 4.254e-05
> postscript(file="/var/www/html/rcomp/tmp/15axx1258641286.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/2b3on1258641286.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/3ks8v1258641286.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4or6n1258641286.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5egj31258641286.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$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 7
-6105.882 -4194.082 -4989.082 -6086.482 -8855.482 -8052.682 -6543.482
8 9 10 11 12 13 14
-9944.482 -7107.682 -7249.682 -6134.282 1041.532 11372.866 12730.666
15 16 17 18 19 20 21
11581.666 10435.266 5987.266 7033.066 7036.266 6902.266 11885.066
22 23 24 25 26 27 28
10849.066 8189.466 12362.280 23153.614 14831.414 11711.414 5421.014
29 30 31 32 33 34 35
6612.014 2581.814 -2820.986 -3179.986 -4629.186 -13309.186 -11275.786
36 37 38 39 40 41 42
-5589.972 -2702.638 -1250.838 -2911.838 -1554.238 -2100.238 -4774.438
43 44 45 46 47 48 49
-9158.238 -7667.238 -13351.438 -10061.438 -10117.038 -33571.294 -25717.960
50 51 52 53 54 55 56
-22117.160 -15392.160 -8215.560 -1643.560 3212.240 11486.440 13889.440
57 58 59 60
13203.240 19771.240 19337.640 25757.454
> postscript(file="/var/www/html/rcomp/tmp/62h8w1258641286.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 -6105.882 NA
1 -4194.082 -6105.882
2 -4989.082 -4194.082
3 -6086.482 -4989.082
4 -8855.482 -6086.482
5 -8052.682 -8855.482
6 -6543.482 -8052.682
7 -9944.482 -6543.482
8 -7107.682 -9944.482
9 -7249.682 -7107.682
10 -6134.282 -7249.682
11 1041.532 -6134.282
12 11372.866 1041.532
13 12730.666 11372.866
14 11581.666 12730.666
15 10435.266 11581.666
16 5987.266 10435.266
17 7033.066 5987.266
18 7036.266 7033.066
19 6902.266 7036.266
20 11885.066 6902.266
21 10849.066 11885.066
22 8189.466 10849.066
23 12362.280 8189.466
24 23153.614 12362.280
25 14831.414 23153.614
26 11711.414 14831.414
27 5421.014 11711.414
28 6612.014 5421.014
29 2581.814 6612.014
30 -2820.986 2581.814
31 -3179.986 -2820.986
32 -4629.186 -3179.986
33 -13309.186 -4629.186
34 -11275.786 -13309.186
35 -5589.972 -11275.786
36 -2702.638 -5589.972
37 -1250.838 -2702.638
38 -2911.838 -1250.838
39 -1554.238 -2911.838
40 -2100.238 -1554.238
41 -4774.438 -2100.238
42 -9158.238 -4774.438
43 -7667.238 -9158.238
44 -13351.438 -7667.238
45 -10061.438 -13351.438
46 -10117.038 -10061.438
47 -33571.294 -10117.038
48 -25717.960 -33571.294
49 -22117.160 -25717.960
50 -15392.160 -22117.160
51 -8215.560 -15392.160
52 -1643.560 -8215.560
53 3212.240 -1643.560
54 11486.440 3212.240
55 13889.440 11486.440
56 13203.240 13889.440
57 19771.240 13203.240
58 19337.640 19771.240
59 25757.454 19337.640
60 NA 25757.454
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -4194.082 -6105.882
[2,] -4989.082 -4194.082
[3,] -6086.482 -4989.082
[4,] -8855.482 -6086.482
[5,] -8052.682 -8855.482
[6,] -6543.482 -8052.682
[7,] -9944.482 -6543.482
[8,] -7107.682 -9944.482
[9,] -7249.682 -7107.682
[10,] -6134.282 -7249.682
[11,] 1041.532 -6134.282
[12,] 11372.866 1041.532
[13,] 12730.666 11372.866
[14,] 11581.666 12730.666
[15,] 10435.266 11581.666
[16,] 5987.266 10435.266
[17,] 7033.066 5987.266
[18,] 7036.266 7033.066
[19,] 6902.266 7036.266
[20,] 11885.066 6902.266
[21,] 10849.066 11885.066
[22,] 8189.466 10849.066
[23,] 12362.280 8189.466
[24,] 23153.614 12362.280
[25,] 14831.414 23153.614
[26,] 11711.414 14831.414
[27,] 5421.014 11711.414
[28,] 6612.014 5421.014
[29,] 2581.814 6612.014
[30,] -2820.986 2581.814
[31,] -3179.986 -2820.986
[32,] -4629.186 -3179.986
[33,] -13309.186 -4629.186
[34,] -11275.786 -13309.186
[35,] -5589.972 -11275.786
[36,] -2702.638 -5589.972
[37,] -1250.838 -2702.638
[38,] -2911.838 -1250.838
[39,] -1554.238 -2911.838
[40,] -2100.238 -1554.238
[41,] -4774.438 -2100.238
[42,] -9158.238 -4774.438
[43,] -7667.238 -9158.238
[44,] -13351.438 -7667.238
[45,] -10061.438 -13351.438
[46,] -10117.038 -10061.438
[47,] -33571.294 -10117.038
[48,] -25717.960 -33571.294
[49,] -22117.160 -25717.960
[50,] -15392.160 -22117.160
[51,] -8215.560 -15392.160
[52,] -1643.560 -8215.560
[53,] 3212.240 -1643.560
[54,] 11486.440 3212.240
[55,] 13889.440 11486.440
[56,] 13203.240 13889.440
[57,] 19771.240 13203.240
[58,] 19337.640 19771.240
[59,] 25757.454 19337.640
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -4194.082 -6105.882
2 -4989.082 -4194.082
3 -6086.482 -4989.082
4 -8855.482 -6086.482
5 -8052.682 -8855.482
6 -6543.482 -8052.682
7 -9944.482 -6543.482
8 -7107.682 -9944.482
9 -7249.682 -7107.682
10 -6134.282 -7249.682
11 1041.532 -6134.282
12 11372.866 1041.532
13 12730.666 11372.866
14 11581.666 12730.666
15 10435.266 11581.666
16 5987.266 10435.266
17 7033.066 5987.266
18 7036.266 7033.066
19 6902.266 7036.266
20 11885.066 6902.266
21 10849.066 11885.066
22 8189.466 10849.066
23 12362.280 8189.466
24 23153.614 12362.280
25 14831.414 23153.614
26 11711.414 14831.414
27 5421.014 11711.414
28 6612.014 5421.014
29 2581.814 6612.014
30 -2820.986 2581.814
31 -3179.986 -2820.986
32 -4629.186 -3179.986
33 -13309.186 -4629.186
34 -11275.786 -13309.186
35 -5589.972 -11275.786
36 -2702.638 -5589.972
37 -1250.838 -2702.638
38 -2911.838 -1250.838
39 -1554.238 -2911.838
40 -2100.238 -1554.238
41 -4774.438 -2100.238
42 -9158.238 -4774.438
43 -7667.238 -9158.238
44 -13351.438 -7667.238
45 -10061.438 -13351.438
46 -10117.038 -10061.438
47 -33571.294 -10117.038
48 -25717.960 -33571.294
49 -22117.160 -25717.960
50 -15392.160 -22117.160
51 -8215.560 -15392.160
52 -1643.560 -8215.560
53 3212.240 -1643.560
54 11486.440 3212.240
55 13889.440 11486.440
56 13203.240 13889.440
57 19771.240 13203.240
58 19337.640 19771.240
59 25757.454 19337.640
> 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/75n0c1258641286.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8n0q41258641286.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9uzfw1258641286.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/10h1vl1258641286.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/11ph7e1258641286.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/1220ye1258641286.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/13jox11258641286.tab")
>
> system("convert tmp/15axx1258641286.ps tmp/15axx1258641286.png")
> system("convert tmp/2b3on1258641286.ps tmp/2b3on1258641286.png")
> system("convert tmp/3ks8v1258641286.ps tmp/3ks8v1258641286.png")
> system("convert tmp/4or6n1258641286.ps tmp/4or6n1258641286.png")
> system("convert tmp/5egj31258641286.ps tmp/5egj31258641286.png")
> system("convert tmp/62h8w1258641286.ps tmp/62h8w1258641286.png")
> system("convert tmp/75n0c1258641286.ps tmp/75n0c1258641286.png")
> system("convert tmp/8n0q41258641286.ps tmp/8n0q41258641286.png")
> system("convert tmp/9uzfw1258641286.ps tmp/9uzfw1258641286.png")
>
>
> proc.time()
user system elapsed
1.943 1.421 2.292