[R-sig-ME] [R] lme4 : lmer : convergence problem and other errors

[Doran, Harold]

There is no way to know what is going on given your description below.
You say you're fitting a non-linear model, but your notation is of a
linear model. I see you square a covariate, but this doesn't make it a
non-linear model, it is still linear in the parameters.

We don't know anything about your data, your lmer syntax, all of which
would be useful in helping you out. 

> -----Original Message-----
> From: r-sig-mixed-models-bounces at r-project.org 
> [mailto:r-sig-mixed-models-bounces at r-project.org] On Behalf 
> Of yufeng at nsm.umass.edu
> Sent: Thursday, July 03, 2008 9:30 AM
> To: R-SIG-Mixed-Models at r-project.org
> Subject: [R-sig-ME] [R] lme4 : lmer : convergence problem and 
> other errors
> 
> Dear R-user,
> 
> I am trying to use the R "lmer" function in lme4 package to 
> fit a non linear mixed effects model. The model I wand to fit 
> is at an individual level with 4 parameters. For all 
> parameters both fixed and random effects have to be 
> estimated, as well as their covariance matrix (see the 
> formula bellow).
> y~x1+x1^2+x2+x2^2.
> 
> 
> I tried to fit the model with my data sets, but most of the 
> time, R returns an error message.
> there are three main types of errors :
> 
> - In mer_finalize(ans, verbose) :
>   function evaluation limit reached without convergence (9)
> 
> -  there are false convergence (8)
> 
> -there are singular convergence (7)
> 
> Do you know how to resolve these problems. Is there a way to 
> modify the parameters of the maximization algorithm to avoid 
> these error messages?
> 
> Thank you for your help and answers.
> 
> Regards,
> 
> Yufeng Zhang
> 
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