arXiv · 1710.09759
Directional Metropolis-Hastings
Abstract
We propose a new kernel for Metropolis Hastings called Directional Metropolis Hastings (DMH) with multivariate update where the proposal kernel has state dependent covariance matrix. We use the derivative of the target distribution at the current state to change the orientation of the proposal distribution, therefore producing a more plausible proposal. We study the conditions for geometric ergodicity of our algorithm and provide necessary and sufficient conditions for convergence. We also suggest a scheme for adaptively update the variance parameter and study the conditions of ergodicity of the adaptive algorithm. We demonstrate the performance of our algorithm in a Bayesian generalized linear model problem.
Explore related subjects
Keep this discovery
Abhirup Mallik, Galin L. Jones. 2017-10-26. Directional Metropolis-Hastings. https://arxiv.org/abs/1710.09759
Cite the original work for its findings. Save a collection to share your selection of sources.