R help - Jun 2011 - lme convergence failure within a loop

Hi R-users,

I'm attempting to fit a number of mixed models, all with the same 
structure, across a spatial grid with data points collected at various 
time points within each grid cell. I'm trying to use a 'for' loop to
try
the model fit on each grid cell. In some cells lme does not converge, 
giving me the error:

Error message: In lme.formula(logarea ~ year + summ_d, data = grid2, 
random = ~year +  :
   nlminb problem, convergence error code = 1
   message = iteration limit reached without convergence (9)

When I get the error, the program aborts, and my loop stops.

I'm not too worried about the error, as a generic mixed model structure 
may not be the best fit for every cell. I expect the optimization to 
fail in some places. I want to be able to detect when the algorithm has 
failed to converge automatically, so that I can continue my loop and 
record the places where the model does fit. I've used the lmeControl 
method with returnObject=TRUE options to allow me to continue looping, 
however I want to be able to flag the places where the convergence 
failed so that I can reject these gridcells and not mistakenly claim 
that the model fits at these points. Is there a way to do this?

My example code shows the relevant lines of code-- what I'm hoping for 
is a way to determine that the convergence failed and record this as a 
boolean value, or something similar.

Thanks,

Sam Nicol


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I am not an expert in this. But try try()   :)

hth,
Daniel


Sam Nicol wrote:
> 
> Hi R-users,
> 
> I'm attempting to fit a number of mixed models, all with the same 
> structure, across a spatial grid with data points collected at various 
> time points within each grid cell. I'm trying to use a 'for'
loop to try
> the model fit on each grid cell. In some cells lme does not converge, 
> giving me the error:
> 
> Error message: In lme.formula(logarea ~ year + summ_d, data = grid2, 
> random = ~year +  :
>    nlminb problem, convergence error code = 1
>    message = iteration limit reached without convergence (9)
> 
> When I get the error, the program aborts, and my loop stops.
> 
> I'm not too worried about the error, as a generic mixed model structure
> may not be the best fit for every cell. I expect the optimization to 
> fail in some places. I want to be able to detect when the algorithm has 
> failed to converge automatically, so that I can continue my loop and 
> record the places where the model does fit. I've used the lmeControl 
> method with returnObject=TRUE options to allow me to continue looping, 
> however I want to be able to flag the places where the convergence 
> failed so that I can reject these gridcells and not mistakenly claim 
> that the model fits at these points. Is there a way to do this?
> 
> My example code shows the relevant lines of code-- what I'm hoping for 
> is a way to determine that the convergence failed and record this as a 
> boolean value, or something similar.
> 
> Thanks,
> 
> Sam Nicol
> 
> 
> 
> ______________________________________________
> 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.
> 
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