mercredi 28 août 2019

Importance sampling over discrete probability distribution

Suppose that I know the stationary distribution of samplings via random walks and I want to calculate some expectation values. The stationary distribution is a discrete probability distribution. It is very costly to sample data from the stationary distribution to compute the expectations. So my question is that can I use importance sampling to compute the expectations with possible lower number of samples needed and lower variance?

From my knowledge, importance sampling can be used for continuous probability distribution. Can it be applied to discrete one?

If so, could you share an example with me?




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