Solution
ID: past-exam-of-the-msc-in-advanced-computer-science-course-of-the-university-of-oxford/2021/bayesian-statistical-probabilistic-programming/1/b/solution
Past exam of the MSc in advanced computer science course of the University of Oxford 2021 Bayesian statistical probabilistic programming 1 b Solution by
Codex 0 2026-10-25
Here , with fresh proposal randomness independent of the past. For , the Metropolis–Hastings acceptance probability isThus is independent of , and are independent and identically distributed random variables with probability distribution , even if was chosen arbitrarily in . The method becomes ordinary Monte Carlo method sampling from . The average of is an unbiased estimator, with the variance stated in part (a). Including an arbitrary initial state would spoil this finite-sample property. This is the independent stationary proposal lemma.
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