On 11-10-18 4:30 AM, Seref Arikan wrote:
Hi Dan,
I've tried the log likelihood, but it reaches zero again, if I work with say
1000 samples.
I need an approach that would scale to quite large sample sizes. Surely I
can't be the first one to encounter this problem, and I'm sure I'm missing
an option that is embarrassingly obvious.
I think you are calculating the log likelihood incorrectly. Don't
calculate the likelihood and take the log; work out the formula for the
log of the likelihood, and calculate that. (If the likelihood contains
a sum of terms, as in a mixture model, this takes some thinking, but it
is still worthwhile.)
With most models, it is just about impossible to cause the log
likelihood to underflow if it is calculated carefully.
Duncan Murdoch