Prior-Preconditioned Conjugate Gradient Method for Accelerated Gibbs Sampling in “Large <i>n</i> , Large <i>p</i> ” Bayesian Sparse Regression
Akihiko Nishimura, Marc A. Suchard
Abstract
= 22,175 clinical covariates, designed to assess the relative risk of adverse events from two alternative blood anti-coagulants. Our algorithm demonstrates an order of magnitude speed-up in posterior inference, in our case cutting the computation time from two weeks to less than a day. Supplementary materials for this article are available online.
Topics & Concepts
Gibbs samplingMathematicsConjugate gradient methodBayesian probabilityStatisticsSampling (signal processing)Applied mathematicsComputer scienceAlgorithmComputer visionFilter (signal processing)Sparse and Compressive Sensing TechniquesStatistical Methods and InferenceMarkov Chains and Monte Carlo Methods