From: Thomas BRUNEL <Thomas.Brunel_at_ifremer.fr>

Date: Tue 16 Jan 2007 - 13:48:19 GMT

Date: Tue 16 Jan 2007 - 13:48:19 GMT

Dear R-user,

I am trying to use the R "nlme" function to fit a non linear mixed
effects model. The model I wand to fit is an individual somatic growth
model 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).

The data are simulated with the same growth model as in the nlme, with
know parameters, and covariance matrix.

I tried to fit the model with several simulated data sets, but most of
the time, R returns an error message.

there are three main types of errors :

- there is a singular matrix - a factor is reduced bellow the PNLS level. - max number of iteration is reached but there is no convergence.

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?

Furthermore, do you know if it is possible to fix the values of the fixed effects so that the model only has to estimate the random effects?

Thank you for your help and answers.

Regards,

Thomas Brunel

pds.fit<-nlme(pds~(exp (lna)/(exp (lnb) + 1/(1 + exp(1000 * (exp

(lntmat) - t + 0.5))) * exp (lnc)))^4 * (1 - (1 - ( 0.051 * (1 - 1/(1 +

exp(1000 * (exp (lntmat) - t + 0.5)))) + (exp (lna)/exp (lnb))^4 * (1 -

*(1 - (0.051)^0.25 * (exp (lnb)/exp (lna))) * exp( - ((exp (lnb) * exp
**(lntmat))/4)))^4 * 1/(1 + exp(1000 * (exp (lntmat) - t + 0.5))))^0.25 *
**((exp (lnb) + 1/(1 + exp(1000 * (exp (lntmat) - t + 0.5))) * exp
**(lnc))/exp (lna))) * exp( - (((exp (lnb) + 1/(1 + exp(1000 * (exp
**(lntmat) - t + 0.5))) * exp (lnc)) *(t - (1/(1 + exp(1000 * (exp
*

(lntmat) - t + 0.5))) * exp

(lntmat))))/4)))^4,data=pdsdata,fixed=lna+lnb+lnc+lntmat~1,random=

lna+lnb+lnc+lntmat~1|indi ,start=c(lna=log(a2),lnb=log(b2) ,lnc =
log(c2), lntmat=log(1200)))

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