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Concept
Gibbs Sampling
Gibbs Sampling
is a
Markov Chain Monte Carlo
algorithm used to generate samples from a
multivariate
probability distribution
when direct sampling is difficult. It iteratively samples each variable from its
conditional distribution
, given the current values of the other variables, allowing for
efficient approximation
of
complex distributions
.
Relevant Fields:
Probability and Statistics 70%
Computational Mathematics 30%
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