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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