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.
Natural language support but running in an English locale
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(9,911,8,915,9,452,9,112,8,472,8,230,8,384,8,625,8,221,8,649,8,625,10,443,10,357,8,586,8,892,8,329,8,101,7,922,8,120,7,838,7,735,8,406,8,209,9,451,10,041,9,411,10,405,8,467,8,464,8,102,7,627,7,513,7,510,8,291,8,064,9,383,9,706,8,579,9,474,8,318,8,213,8,059,9,111,7,708,7,680,8,014,8,007,8,718,9,486,9,113,9,025,8,476,7,952,7,759,7,835,7,600,7,651,8,319,8,812,8,630),dim=c(2,60),dimnames=list(c('y',''),1:60))
> y <- array(NA,dim=c(2,60),dimnames=list(c('y',''),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
y M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 9 911 1 0 0 0 0 0 0 0 0 0 0 1
2 8 915 0 1 0 0 0 0 0 0 0 0 0 2
3 9 452 0 0 1 0 0 0 0 0 0 0 0 3
4 9 112 0 0 0 1 0 0 0 0 0 0 0 4
5 8 472 0 0 0 0 1 0 0 0 0 0 0 5
6 8 230 0 0 0 0 0 1 0 0 0 0 0 6
7 8 384 0 0 0 0 0 0 1 0 0 0 0 7
8 8 625 0 0 0 0 0 0 0 1 0 0 0 8
9 8 221 0 0 0 0 0 0 0 0 1 0 0 9
10 8 649 0 0 0 0 0 0 0 0 0 1 0 10
11 8 625 0 0 0 0 0 0 0 0 0 0 1 11
12 10 443 0 0 0 0 0 0 0 0 0 0 0 12
13 10 357 1 0 0 0 0 0 0 0 0 0 0 13
14 8 586 0 1 0 0 0 0 0 0 0 0 0 14
15 8 892 0 0 1 0 0 0 0 0 0 0 0 15
16 8 329 0 0 0 1 0 0 0 0 0 0 0 16
17 8 101 0 0 0 0 1 0 0 0 0 0 0 17
18 7 922 0 0 0 0 0 1 0 0 0 0 0 18
19 8 120 0 0 0 0 0 0 1 0 0 0 0 19
20 7 838 0 0 0 0 0 0 0 1 0 0 0 20
21 7 735 0 0 0 0 0 0 0 0 1 0 0 21
22 8 406 0 0 0 0 0 0 0 0 0 1 0 22
23 8 209 0 0 0 0 0 0 0 0 0 0 1 23
24 9 451 0 0 0 0 0 0 0 0 0 0 0 24
25 10 41 1 0 0 0 0 0 0 0 0 0 0 25
26 9 411 0 1 0 0 0 0 0 0 0 0 0 26
27 10 405 0 0 1 0 0 0 0 0 0 0 0 27
28 8 467 0 0 0 1 0 0 0 0 0 0 0 28
29 8 464 0 0 0 0 1 0 0 0 0 0 0 29
30 8 102 0 0 0 0 0 1 0 0 0 0 0 30
31 7 627 0 0 0 0 0 0 1 0 0 0 0 31
32 7 513 0 0 0 0 0 0 0 1 0 0 0 32
33 7 510 0 0 0 0 0 0 0 0 1 0 0 33
34 8 291 0 0 0 0 0 0 0 0 0 1 0 34
35 8 64 0 0 0 0 0 0 0 0 0 0 1 35
36 9 383 0 0 0 0 0 0 0 0 0 0 0 36
37 9 706 1 0 0 0 0 0 0 0 0 0 0 37
38 8 579 0 1 0 0 0 0 0 0 0 0 0 38
39 9 474 0 0 1 0 0 0 0 0 0 0 0 39
40 8 318 0 0 0 1 0 0 0 0 0 0 0 40
41 8 213 0 0 0 0 1 0 0 0 0 0 0 41
42 8 59 0 0 0 0 0 1 0 0 0 0 0 42
43 9 111 0 0 0 0 0 0 1 0 0 0 0 43
44 7 708 0 0 0 0 0 0 0 1 0 0 0 44
45 7 680 0 0 0 0 0 0 0 0 1 0 0 45
46 8 14 0 0 0 0 0 0 0 0 0 1 0 46
47 8 7 0 0 0 0 0 0 0 0 0 0 1 47
48 8 718 0 0 0 0 0 0 0 0 0 0 0 48
49 9 486 1 0 0 0 0 0 0 0 0 0 0 49
50 9 113 0 1 0 0 0 0 0 0 0 0 0 50
51 9 25 0 0 1 0 0 0 0 0 0 0 0 51
52 8 476 0 0 0 1 0 0 0 0 0 0 0 52
53 7 952 0 0 0 0 1 0 0 0 0 0 0 53
54 7 759 0 0 0 0 0 1 0 0 0 0 0 54
55 7 835 0 0 0 0 0 0 1 0 0 0 0 55
56 7 600 0 0 0 0 0 0 0 1 0 0 0 56
57 7 651 0 0 0 0 0 0 0 0 1 0 0 57
58 8 319 0 0 0 0 0 0 0 0 0 1 0 58
59 8 812 0 0 0 0 0 0 0 0 0 0 1 59
60 8 630 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) V2 M1 M2 M3 M4
9.815647 -0.001308 0.467048 -0.496870 0.019139 -0.914555
M5 M6 M7 M8 M9 M10
-1.174619 -1.399489 -1.189043 -1.464159 -1.582419 -1.065745
M11 t
-1.046667 -0.009138
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-0.53100 -0.22828 -0.02762 0.13973 0.94166
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 9.8156467 0.2236632 43.886 < 2e-16 ***
V2 -0.0013080 0.0001955 -6.690 2.66e-08 ***
M1 0.4670475 0.2414309 1.934 0.059216 .
M2 -0.4968704 0.2410199 -2.062 0.044929 *
M3 0.0191391 0.2411512 0.079 0.937086
M4 -0.9145548 0.2431122 -3.762 0.000476 ***
M5 -1.1746190 0.2407167 -4.880 1.31e-05 ***
M6 -1.3994888 0.2408968 -5.809 5.58e-07 ***
M7 -1.1890431 0.2406886 -4.940 1.07e-05 ***
M8 -1.4641588 0.2409448 -6.077 2.22e-07 ***
M9 -1.5824185 0.2395419 -6.606 3.56e-08 ***
M10 -1.0657454 0.2422089 -4.400 6.37e-05 ***
M11 -1.0466670 0.2419324 -4.326 8.08e-05 ***
t -0.0091377 0.0028783 -3.175 0.002676 **
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 0.3784 on 46 degrees of freedom
Multiple R-squared: 0.8361, Adjusted R-squared: 0.7898
F-statistic: 18.05 on 13 and 46 DF, p-value: 7.375e-14
> postscript(file="/var/www/html/freestat/rcomp/tmp/1jf2c1291072399.ps",horizontal=F,onefile=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/2jf2c1291072399.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/3tojf1291072399.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/4tojf1291072399.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/5tojf1291072399.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$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
-0.0819858412 -0.1036983254 -0.2161652740 0.2819527155 0.0220277707
6 7 8 9 10
-0.0604961213 -0.0603750311 0.5391017765 0.1380748076 0.1903552151
11 12 13 14 15
0.1490230161 0.8734411312 0.3030449093 -0.4243718542 -0.5310014280
16 17 18 19 20
-0.3245631973 -0.3535809592 -0.0457210680 -0.2960297961 -0.0726460603
21 22 23 24 25
-0.0799707538 -0.0178319493 -0.2854448581 -0.0064428068 -0.0006248667
26 27 28 29 30
0.4563836882 0.9416640482 -0.0344096078 0.2308683512 -0.0086132586
31 32 33 34 35
-0.5232312243 -0.3880876651 -0.2646142605 -0.0585975480 -0.3654498862
36 37 38 39 40
0.0142667006 -0.0211652999 -0.2142232927 0.1415669501 -0.1196465598
41 42 43 44 45
0.0122173390 0.0447957734 0.9115028034 -0.0233791596 0.0673947205
46 47 48 49 50
-0.3112560657 -0.3303525880 -0.4379074564 -0.1992689016 0.2859097841
51 52 53 54 55
-0.3360642964 0.1966666494 0.0884674984 0.0700346745 -0.0318667519
56 57 58 59 60
-0.0549888914 0.1391154862 0.1973303478 0.8322243162 -0.4433575686
> postscript(file="/var/www/html/freestat/rcomp/tmp/64gii1291072399.ps",horizontal=F,onefile=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 -0.0819858412 NA
1 -0.1036983254 -0.0819858412
2 -0.2161652740 -0.1036983254
3 0.2819527155 -0.2161652740
4 0.0220277707 0.2819527155
5 -0.0604961213 0.0220277707
6 -0.0603750311 -0.0604961213
7 0.5391017765 -0.0603750311
8 0.1380748076 0.5391017765
9 0.1903552151 0.1380748076
10 0.1490230161 0.1903552151
11 0.8734411312 0.1490230161
12 0.3030449093 0.8734411312
13 -0.4243718542 0.3030449093
14 -0.5310014280 -0.4243718542
15 -0.3245631973 -0.5310014280
16 -0.3535809592 -0.3245631973
17 -0.0457210680 -0.3535809592
18 -0.2960297961 -0.0457210680
19 -0.0726460603 -0.2960297961
20 -0.0799707538 -0.0726460603
21 -0.0178319493 -0.0799707538
22 -0.2854448581 -0.0178319493
23 -0.0064428068 -0.2854448581
24 -0.0006248667 -0.0064428068
25 0.4563836882 -0.0006248667
26 0.9416640482 0.4563836882
27 -0.0344096078 0.9416640482
28 0.2308683512 -0.0344096078
29 -0.0086132586 0.2308683512
30 -0.5232312243 -0.0086132586
31 -0.3880876651 -0.5232312243
32 -0.2646142605 -0.3880876651
33 -0.0585975480 -0.2646142605
34 -0.3654498862 -0.0585975480
35 0.0142667006 -0.3654498862
36 -0.0211652999 0.0142667006
37 -0.2142232927 -0.0211652999
38 0.1415669501 -0.2142232927
39 -0.1196465598 0.1415669501
40 0.0122173390 -0.1196465598
41 0.0447957734 0.0122173390
42 0.9115028034 0.0447957734
43 -0.0233791596 0.9115028034
44 0.0673947205 -0.0233791596
45 -0.3112560657 0.0673947205
46 -0.3303525880 -0.3112560657
47 -0.4379074564 -0.3303525880
48 -0.1992689016 -0.4379074564
49 0.2859097841 -0.1992689016
50 -0.3360642964 0.2859097841
51 0.1966666494 -0.3360642964
52 0.0884674984 0.1966666494
53 0.0700346745 0.0884674984
54 -0.0318667519 0.0700346745
55 -0.0549888914 -0.0318667519
56 0.1391154862 -0.0549888914
57 0.1973303478 0.1391154862
58 0.8322243162 0.1973303478
59 -0.4433575686 0.8322243162
60 NA -0.4433575686
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -0.1036983254 -0.0819858412
[2,] -0.2161652740 -0.1036983254
[3,] 0.2819527155 -0.2161652740
[4,] 0.0220277707 0.2819527155
[5,] -0.0604961213 0.0220277707
[6,] -0.0603750311 -0.0604961213
[7,] 0.5391017765 -0.0603750311
[8,] 0.1380748076 0.5391017765
[9,] 0.1903552151 0.1380748076
[10,] 0.1490230161 0.1903552151
[11,] 0.8734411312 0.1490230161
[12,] 0.3030449093 0.8734411312
[13,] -0.4243718542 0.3030449093
[14,] -0.5310014280 -0.4243718542
[15,] -0.3245631973 -0.5310014280
[16,] -0.3535809592 -0.3245631973
[17,] -0.0457210680 -0.3535809592
[18,] -0.2960297961 -0.0457210680
[19,] -0.0726460603 -0.2960297961
[20,] -0.0799707538 -0.0726460603
[21,] -0.0178319493 -0.0799707538
[22,] -0.2854448581 -0.0178319493
[23,] -0.0064428068 -0.2854448581
[24,] -0.0006248667 -0.0064428068
[25,] 0.4563836882 -0.0006248667
[26,] 0.9416640482 0.4563836882
[27,] -0.0344096078 0.9416640482
[28,] 0.2308683512 -0.0344096078
[29,] -0.0086132586 0.2308683512
[30,] -0.5232312243 -0.0086132586
[31,] -0.3880876651 -0.5232312243
[32,] -0.2646142605 -0.3880876651
[33,] -0.0585975480 -0.2646142605
[34,] -0.3654498862 -0.0585975480
[35,] 0.0142667006 -0.3654498862
[36,] -0.0211652999 0.0142667006
[37,] -0.2142232927 -0.0211652999
[38,] 0.1415669501 -0.2142232927
[39,] -0.1196465598 0.1415669501
[40,] 0.0122173390 -0.1196465598
[41,] 0.0447957734 0.0122173390
[42,] 0.9115028034 0.0447957734
[43,] -0.0233791596 0.9115028034
[44,] 0.0673947205 -0.0233791596
[45,] -0.3112560657 0.0673947205
[46,] -0.3303525880 -0.3112560657
[47,] -0.4379074564 -0.3303525880
[48,] -0.1992689016 -0.4379074564
[49,] 0.2859097841 -0.1992689016
[50,] -0.3360642964 0.2859097841
[51,] 0.1966666494 -0.3360642964
[52,] 0.0884674984 0.1966666494
[53,] 0.0700346745 0.0884674984
[54,] -0.0318667519 0.0700346745
[55,] -0.0549888914 -0.0318667519
[56,] 0.1391154862 -0.0549888914
[57,] 0.1973303478 0.1391154862
[58,] 0.8322243162 0.1973303478
[59,] -0.4433575686 0.8322243162
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -0.1036983254 -0.0819858412
2 -0.2161652740 -0.1036983254
3 0.2819527155 -0.2161652740
4 0.0220277707 0.2819527155
5 -0.0604961213 0.0220277707
6 -0.0603750311 -0.0604961213
7 0.5391017765 -0.0603750311
8 0.1380748076 0.5391017765
9 0.1903552151 0.1380748076
10 0.1490230161 0.1903552151
11 0.8734411312 0.1490230161
12 0.3030449093 0.8734411312
13 -0.4243718542 0.3030449093
14 -0.5310014280 -0.4243718542
15 -0.3245631973 -0.5310014280
16 -0.3535809592 -0.3245631973
17 -0.0457210680 -0.3535809592
18 -0.2960297961 -0.0457210680
19 -0.0726460603 -0.2960297961
20 -0.0799707538 -0.0726460603
21 -0.0178319493 -0.0799707538
22 -0.2854448581 -0.0178319493
23 -0.0064428068 -0.2854448581
24 -0.0006248667 -0.0064428068
25 0.4563836882 -0.0006248667
26 0.9416640482 0.4563836882
27 -0.0344096078 0.9416640482
28 0.2308683512 -0.0344096078
29 -0.0086132586 0.2308683512
30 -0.5232312243 -0.0086132586
31 -0.3880876651 -0.5232312243
32 -0.2646142605 -0.3880876651
33 -0.0585975480 -0.2646142605
34 -0.3654498862 -0.0585975480
35 0.0142667006 -0.3654498862
36 -0.0211652999 0.0142667006
37 -0.2142232927 -0.0211652999
38 0.1415669501 -0.2142232927
39 -0.1196465598 0.1415669501
40 0.0122173390 -0.1196465598
41 0.0447957734 0.0122173390
42 0.9115028034 0.0447957734
43 -0.0233791596 0.9115028034
44 0.0673947205 -0.0233791596
45 -0.3112560657 0.0673947205
46 -0.3303525880 -0.3112560657
47 -0.4379074564 -0.3303525880
48 -0.1992689016 -0.4379074564
49 0.2859097841 -0.1992689016
50 -0.3360642964 0.2859097841
51 0.1966666494 -0.3360642964
52 0.0884674984 0.1966666494
53 0.0700346745 0.0884674984
54 -0.0318667519 0.0700346745
55 -0.0549888914 -0.0318667519
56 0.1391154862 -0.0549888914
57 0.1973303478 0.1391154862
58 0.8322243162 0.1973303478
59 -0.4433575686 0.8322243162
> 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/7f70l1291072399.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/8f70l1291072399.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/97gz61291072399.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
>
> #Note: the /var/www/html/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/freestat/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/10thxt1291072399.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/11ezez1291072399.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/1231el1291072400.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/1362v91291072400.tab")
>
> try(system("convert tmp/1jf2c1291072399.ps tmp/1jf2c1291072399.png",intern=TRUE))
character(0)
> try(system("convert tmp/2jf2c1291072399.ps tmp/2jf2c1291072399.png",intern=TRUE))
character(0)
> try(system("convert tmp/3tojf1291072399.ps tmp/3tojf1291072399.png",intern=TRUE))
character(0)
> try(system("convert tmp/4tojf1291072399.ps tmp/4tojf1291072399.png",intern=TRUE))
character(0)
> try(system("convert tmp/5tojf1291072399.ps tmp/5tojf1291072399.png",intern=TRUE))
character(0)
> try(system("convert tmp/64gii1291072399.ps tmp/64gii1291072399.png",intern=TRUE))
character(0)
> try(system("convert tmp/7f70l1291072399.ps tmp/7f70l1291072399.png",intern=TRUE))
character(0)
> try(system("convert tmp/8f70l1291072399.ps tmp/8f70l1291072399.png",intern=TRUE))
character(0)
> try(system("convert tmp/97gz61291072399.ps tmp/97gz61291072399.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
3.072 2.203 3.907