Suggestion for Model convergence problem:non-positive-definite Hessian matrix.

[cc'ing r-sig-mixed-models at r-project.org]

 Without a repeatable example this is hard.  The only general advice I
can give is:

 - try centering and scaling any continuous predictors
 - you can probably extract some information about the fit (via
VarCorr(), fixef(), etc.) even though the model may not have converged
properly, but it will be hard to trust it
 - visualize your data (look for outlier individual observations or groups)
 - do you have combinations of predictor variables (especially
combinations of fixed effects) that lead to all-zero values?
 - if necessary, try simplifying the model

Hi Dr. Bolker,


My data set contains large amount of zeros and total number of
observations is 52172. I am trying to run zero inflated negative
binomial random parameter model by glmmTMB. But I am getting the
following error: 

/Model convergence problem; non-positive-definite Hessian matrix./

/
/

Can you please give suggestions  how can I solve this problem? 

Thanks,

Zohora