I have a numerical problem while doing likelihood ratio tests in python. I'll not go into too much detail about what the statistics mean, my problems comes down to calculating this:
LR = LR_H0 / LR_h1
where LR is the number of interest and LR_H0 and LR_H1 are numbers that can be VERY close to zero. This leads to a few numerical issues; if LR_H1 is too small then python will recognise this as a division by zero.
ZeroDivisionError: float division by zero
Also, although this is not the main issue, if LR_H1 is small enough to allow the division then the fraction LR_H0 / LR_h1 might become too big (I'm assuming that python also has an upper limit value of what a float can be).
Any tips on what the best way is to circumvent this problem? I'm considering doing something like:
def small_enough( num ):
if num == 0.0:
return *other small number*
else:
return num
But this is not ideal because it would approximate the LR value and I would like to guarantee some precision.