A. Nishimura

activity

20172025

most citedDiscontinuous Hamiltonian Monte Carlo for discrete parameters and discontinuous likelihoods

56 citations · 56 across the 3 of their papers we have counts for

collaborators

Showing 2024Show all

2 papers · 1 filter

stat.CO2024

MCMC using $bouncy$ Hamiltonian dynamics: A unifying framework for Hamiltonian Monte Carlo and piecewise deterministic Markov process samplers

Andrew Chin, Akihiko Nishimura

Piecewise-deterministic Markov process (PDMP) samplers constitute a state-of-the-art Markov chain Monte Carlo paradigm in Bayesian computation, with examples including the zig-zag…

stat.ME2024

Constructing Genetic Risk Scores: Robust Bayesian Approach through Projected Summary Statistics and Flexible Shrinkage

Yuzheng Dun, Nilanjan Chatterjee, Jin Jin +1

Polygenic risk scores (PRS) developed from genome-wide association studies (GWAS) can be used for risk stratification by quantifying the genetic contribution to disease, and many c…

MCMC using bouncy Hamiltonian dynamics: A unifying framework for Hamiltonian Monte Carlo and piecewise deterministic Markov process samplers

Constructing Genetic Risk Scores: Robust Bayesian Approach through Projected Summary Statistics and Flexible Shrinkage

MCMC using $bouncy$ Hamiltonian dynamics: A unifying framework for Hamiltonian Monte Carlo and piecewise deterministic Markov process samplers