Message-ID: <4A21367B.4070800@statistik.tu-dortmund.de>
Date: 2009-05-30T13:36:59Z
From: Uwe Ligges
Subject: Looping until a solution is found
In-Reply-To: <4A212FD2.7000905@zoo.ufl.edu>
John Poulsen wrote:
> Hello,
>
> I am using maximum likelihood to find the best parameters for a model.
> This involves sometimes tweaking the starting values to find a solution
> that converges.
>
> I would like to automate the process so that when the optimizer runs
> into an error it tweaks one of the parameters slightly, tries the fit
> again, and then continues this until a solution if found.
>
> I have been using try() to test if a fit will work (see below), but how
> do I run a loop that says continue until class(m1) is not "try error"?
>
> m1<-mlefun(startvals, data=data)
>
> if(class(m1)=="try-error"){startvals<-list(alpha=10,beta=1,loggamma=log(5),logk=log(exp(unlist(startvals[4]))+0.2))
>
> mlefun(starvals, data)}
>
m1 <- mlefun(starvals, data=data)
while(class(m1) == "try-error"){
startvals <- list(alpha=10, beta=1, loggamma=log(5),
logk=log(exp(unlist(startvals[4]))+0.2))
m1 <- mlefun(starvals, data=data)
}
Uwe Ligges
> This seems like it should be easy... but I am stymied. Thanks for your
> help
>
> John
>
> ______________________________________________
> R-help at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.