Metropolis-Hastings algorithm

Efficiency, “burn-in”, and convergence
• Efficiency also decreases if proposal distribution is too broad:
– If too broad, proposed positions are far away, away from main
mass of distribution.
– Probability bilit of accepting a move will be small.
– Random walk rejects too many proposals before accepting one.
• Simulation for 1–64 dimensional target distribution:
ciency
% Effic
Stdev of proposal distribution