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For discrete distributions you indeed cannot, but for continuous distributions all you need is sufficiently small variance. Try for example a Gaussian with vari
by blackbear_ 3y ago
For discrete distributions you indeed cannot, but for continuous distributions all you need is sufficiently small variance. Try for example a Gaussian with variance 1e-12
- KeplerBoy 3y agoThe value of a continuous probability density distribution at a specific point is pretty meaningless though; You have to talk about the integral between two values and that won't go above one.
- blackbear_ 3y agoIn context of maximum likelihood the value of the density at the maximizer is actually quite useful, for example for model comparison.