The Metropolis-Hastings Algorithm: Breaking the Symmetry

 Posted on January 29, 2026  |  3439 words  • Other languages: CH

The original Metropolis is limited by symmetric proposals, often ‘hitting walls’ at boundaries or getting lost in high dimensions. The MH algorithm introduces the ‘Hastings Correction’, allowing asymmetric proposals (like Langevin dynamics) while maintaining detailed balance, significantly improving efficiency. [Read More]
MCMC  MH Algorithm  Hastings Correction  Detailed Balance  Python  Bayesian Statistics 

Metropolis Algorithm Explained: Implementation & Intuition

 Posted on January 24, 2026  |  2757 words  • Other languages: CH

The Metropolis algorithm is the cornerstone of MCMC. We delve into its strategy for handling unnormalized densities, from the random walk mechanism to sampling 2D correlated Gaussians, complete with Python implementation and visual diagnostics. [Read More]
MCMC  Metropolis Algorithm  Monte Carlo Simulation  Bayesian Statistics  Python Implementation  Random Walk