R help - Sep 2016 - NaN Log-lik value in EM algorithm (fitting Gamma mixture model)

Hi,

I am trying to fit Gamma mixture model to my data (residual values obtained
after fitting Generalized linear Model) using gammamixEM. It is part of the
script which does it for multiple datasets in loop. The code is running
fine for some datasets but it terminates for some giving following error:

" iteration = 1  log-lik diff = NaN  log-lik = NaN
Error in while (diff > epsilon && iter < maxit) { :
  missing value where TRUE/FALSE needed"

Seems like EM is not able to calculate log-lik value (NaN) at the first
iteration itself. any idea why that can happen?
It works fine for the other genes in the loop. Tried looking for difference
in the inputs, but could not come up with anything striking.

Regards
Anchal



-- 
Anchal Sharma, PhD
Postdoctoral Fellow
195, Little Albany street,
Cancer Institute of New Jersey
Rutgers University
NJ-08901

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On 14/09/2016 4:46 PM, Aanchal Sharma wrote:
> Hi,
>
> I am trying to fit Gamma mixture model to my data (residual values obtained
> after fitting Generalized linear Model) using gammamixEM. It is part of the
> script which does it for multiple datasets in loop. The code is running
> fine for some datasets but it terminates for some giving following error:
>
> " iteration = 1  log-lik diff = NaN  log-lik = NaN
> Error in while (diff > epsilon && iter < maxit) { :
>   missing value where TRUE/FALSE needed"
>
> Seems like EM is not able to calculate log-lik value (NaN) at the first
> iteration itself. any idea why that can happen?
> It works fine for the other genes in the loop. Tried looking for difference
> in the inputs, but could not come up with anything striking.
>
THere are lots of ways to get NaN in numerical calculations.   A common 
one if you are using log() to calculate log likelihoods is that rounding 
error gives you a negative likelihood, and then log(lik) comes out to NaN.

You just need to look really closely at each step of your calculations. 
Avoid using log(); use the functions that build it in (e.g. instead of 
log(dnorm(x)), use dnorm(x, log = TRUE)).

Duncan Murdoch

I am using a function gammamixEM where it does it by default. I do not have
the option to change it.
Conceptually, what can make the algorithm not able to calculate likelihood
value at all (and hence log-lik=Nan)? Is there sth wrong with the data?
Under what conditions does it happen?

On Wed, Sep 14, 2016 at 8:04 PM, Duncan Murdoch <murdoch.duncan at
gmail.com>
wrote:
> On 14/09/2016 4:46 PM, Aanchal Sharma wrote:
>
>> Hi,
>>
>> I am trying to fit Gamma mixture model to my data (residual values
>> obtained
>> after fitting Generalized linear Model) using gammamixEM. It is part of
>> the
>> script which does it for multiple datasets in loop. The code is running
>> fine for some datasets but it terminates for some giving following
error:
>>
>> " iteration = 1  log-lik diff = NaN  log-lik = NaN
>> Error in while (diff > epsilon && iter < maxit) { :
>>   missing value where TRUE/FALSE needed"
>>
>> Seems like EM is not able to calculate log-lik value (NaN) at the first
>> iteration itself. any idea why that can happen?
>> It works fine for the other genes in the loop. Tried looking for
>> difference
>> in the inputs, but could not come up with anything striking.
>>
>>
> THere are lots of ways to get NaN in numerical calculations.   A common
> one if you are using log() to calculate log likelihoods is that rounding
> error gives you a negative likelihood, and then log(lik) comes out to NaN.
>
> You just need to look really closely at each step of your calculations.
> Avoid using log(); use the functions that build it in (e.g. instead of
> log(dnorm(x)), use dnorm(x, log = TRUE)).
>
> Duncan Murdoch
>
>

-- 
Anchal Sharma, PhD
Postdoctoral Fellow
195, Little Albany street,
Cancer Institute of New Jersey
Rutgers University
NJ-08901

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