[R] fitdistr, mle's and gamma distribution

[Ben Bolker]

  Spencer Graves's suggestion of using shape and scale parameters on a log 
scale is a good one.

  To do specifically what you want (check values for which the objective 
function is called and see what happens) you can do the following 
(untested!), which makes a local copy of dgamma that you can mess with:

dgamma.old <- dgamma
dgamma <- function(x,shape,rate,...) {
   d <- dgamma.old(x,shape,rate,...)
   cat(shape,rate,d,"\n")
   return(d)
}


On Tue, 30 Sep 2003, Lourens Olivier Walters wrote:

> Dear R Users, 
> 
> I am trying to obtain a best-fit analytic distribution for a dataset
> with 11535459 entries. The data range in value from 1 to 300000000. I
> use: fitdistr(data, "gamma") to obtain mle's for the parameters.
>  
> I get the following error:
> 
> Error in optim(start, mylogfn, x = x, hessian = TRUE, ...) :
>         non-finite finite-difference value [1]
> 
> And the following warnings:
> 
> NaNs produced in: dgamma(x, shape, scale, log)
> 
> I have the same problem with the exponential distribution, but the
> lognormal and weibull distributions don't have this problem. 
> 
> I suspect the problem has to do with:
> 
> "It means that in computing derivatives by finite differencing, one 
> of the values is NA, +Inf or -Inf. Put some print values in 
> your objective function and find out why it is giving a non-finite
> value." - quote by Prof Ripley from r-help
> 
> as from the warnings it is clear that some of the values obtained during
> maximum likelihood computations are NaN. I cannot however print values
> of the objective function, as in my case it is dgamma which is called by
> fitdistr, over which I don't have control.  
> 
> Can anyone please point me in the right direction?
> 
> Lourens
> 
> 

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