# [R] how to generate and evaluate a design using Algdesign

sun flyhyena at yahoo.com.cn
Mon Oct 15 13:01:28 CEST 2007

```Thanks Steve,

Now it is a bit clear to me, thanks very much.

----- Original Message -----
From: "S Ellison" <S.Ellison at lgc.co.uk>
To: <r-help at stat.math.ethz.ch>; "sun" <flyhyena at yahoo.com.cn>
Sent: Friday, October 12, 2007 12:59 PM
Subject: Re: [R] how to generate and evaluate a design using Algdesign

> 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.
>
> Steve E
>>>> "sun" <flyhyena at yahoo.com.cn> 10/10/2007 14:59:59 >>>
> Hi,
>
>  I have some problems when using AlgDesign->optFederov() generating
> designs.
>
> I have 6 variables, all factors. 3^2 and 4^4, I want to have a design
> that
> can take care of  main effects and two interactions within 2 pair of
> variables v3-v4 and v5-v6, the following is the code
>
> ################
> require(AlgDesign)
> set.seed(1)
> levels = c(v1=3,v2=3, 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.
>
> 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
> is
> able to handle which effects(main effects/which intercations)? I got
> some
> other designs generated by other packages, so I 'd like to check their
>
> characteristics.
>