[R] how to generate and evaluate a design using Algdesign
S.Ellison at lgc.co.uk
Fri Oct 12 12:59:46 CEST 2007
If you do something like length(coef(lm(y~.+v3:v4 + v5:v6, data=dat)))
to get a quick empirical estimate of required number of coefficients,
you will find that you have 35 coefficients, so 32 observations cannot
provide a solution at all. And indeed, nTrials=35 is the first size at
which optFederov even tries to find a design.
After that,many possible trial designs will be singular because (I
think) most subsets of the data will miss out support points for the
design. You need a lot of repeats to find a design at all with so few
points, or optfederov won't find a viable design at all.
If you're prepared to wait a while, run with at least nTrials=45 with
plenty of repeats and you have a chance of something useful, though the
efficiency (judged by Ge) looked pretty poor.
>>> "sun" <flyhyena at yahoo.com.cn> 10/10/2007 14:59:59 >>>
I have some problems when using AlgDesign->optFederov() generating
I have 6 variables, all factors. 3^2 and 4^4, I want to have a design
can take care of main effects and two interactions within 2 pair of
variables v3-v4 and v5-v6, the following is the code
levels = c(v1=3,v2=3, v3=4,v4=4,v5=4,v6=4)
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
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.
if I remove nTrials argument in function call:
> optDgn<-optFederov(~.+v3:v4+v5:v6,dat,nRepeat=5,criterion =
> "D",approximate = F)
I got a error : "Singular design."
what would be the cause and what is the sullotion?
another question is, how do I measure or evaluate a design to see if it
able to handle which effects(main effects/which intercations)? I got
other designs generated by other packages, so I 'd like to check their
Thanks in advance,
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