[R] AlgDesign--exact and approximate design

[sun]

Thanks, Steve. I have read that document a bit, seems I need read it more.

I have 6 variables, all factors. 3^2 and 4^4
the following is the code

################
require(AlgDesign)
set.seed(1)
levels = c(v1=2,v2=2, v3=4,v4=4,v5=4,v6=4)

dat<-gen.factorial(levels,center=FALSE,varNames=names(levels),factors= 
c(1,2,3,4,5,6))

model = ~.+v3:v4+v5:v6

optDgn<-optFederov(model,dat,nRepeat=5,nTrials = 32,criterion = "D", 
approximate = F)

----------------------------
this lead to a error msg " nTrials must be greater than or equal to the 
number of columns in expanded X" . I thought I do not have that many 
columns. if I change approximate to T, this error has gone. And I get

$D
[1] 0.06249726

$A
[1] 47.78238

$Ge
[1] 0.997

$Dea
[1] 0.997


can this be intepreted as 99.7% efficiency in D-effi?  If set nTrials = 64 
and approximate = F, i got

$D
[1] 0.05602027

$A
[1] 62.87131

$Ge
[1] 0.701

$Dea
[1] 0.653

which is more plausible to me. Is this efficiency good enough for practical 
use of this design?

thanks,
Sun


----- Original Message ----- 
From: "S Ellison" <S.Ellison at lgc.co.uk>
To: <flyhyena at yahoo.com.cn>
Sent: Tuesday, October 09, 2007 5:00 PM
Subject: Re: [R] AlgDesign--exact and approximate design


Have you looked at the file "AlgDesign.pdf" which you can find by browsing 
the directory for AlgDesign? (Try using start.help() to get a browser 
window, look at packages and follow the link at the top of the AlgDesign 
page) (this is pretty much like saying 'try reading the help pages', 
because I found it just by looking at the AlgDesign help. But it is not 
always that easy to find stuff there.

Your formula will work. I prefer to be more explicit, because my data frames 
usualy hold more information than the bare factors and response, so I would 
probably take the time to say

~v1+v2+v3+v4+v1:v2 +v3:v4

or, more simply,
~v1*v2+v3*v4

Steve E


>>> "sun" <flyhyena at yahoo.com.cn> 09/10/2007 13:30:55 >>>