[R] Beyond double-precision?

[spencerg]

Dear Jamie: 

      The harmonic mean is exp(mean(logs)).  Therefore, log(harmonic 
mean) = mean(logs). 

      Does this make sense?
      Best Wishes,
      Spencer     

joaks1 wrote:
> Yes, all of the numbers are positive.  I actually have a Bayesian posterior
> sample of log likelihoods [i.e. thousands of ln(likelihood) scores].  I want
> to calculate the harmonic mean of these likelihoods, which means I need to
> convert them back into likelihoods [i.e. e^ln(likelihood)], calculate the
> harmonic mean, and then take the log of the mean.  I have done this before
> in Mathematica, but I have a simulation pipeline written almost entirely in
> R, so it would be nice if I could do these calculations in R.
>
> If R cannot handle such small values, then perhaps there's a way to
> calculate the harmonic mean from the log likelihood scores without
> converting back to likelihoods?  I am a biologist, not a mathematician, so
> any recommendations are welcome!  Thanks! -Jamie
>
>
> spencerg wrote:
>   
>>       Are all your numbers positive?  If yes, have you considered using 
>> logarithms? 
>>
>>       I would guess it is quite rare for people to compute likelihoods.  
>> Instead I think most people use log(likelihoods).  Most of the 
>> probability functions in R have an option of returning the logarithms. 
>>
>>       Hope this helps. 
>>       Spencer
>>
>> joaks1 wrote:
>>     
>>> I need to perform some calculations with some extremely small numbers
>>> (i.e.
>>> likelihood values on the order of 1.0E-16,000).  Even when using the
>>> double() function, R is rounding these values to zero.  Is there any way
>>> to
>>> get R to deal with such small numbers?
>>>
>>> For example, I would like to be able to calculate e^-10000 (i.e.
>>> exp(-10000)) without the result being rounded to zero.
>>>
>>> I know I can do it in Mathematica, but I would prefer to use R if I can. 
>>> Any help would be appreciated!
>>>
>>> Many Thanks in Advance!
>>>
>>>       
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>>     
>
>