Adaptive independent sticky MCMC algorithms

Adaptive independent sticky MCMC algorithms

Abstract Monte Carlo methods have become essential tools to solve complex Bayesian inference problems in different fields, such as computational statistics, machine learning, and statistical signal processing. In this work, we introduce a novel class of adaptive Monte Carlo methods, called adaptive...

Full description

Bibliographic Details
Main Authors: Luca Martino, Roberto Casarin, Fabrizio Leisen, David Luengo
Format: Article
Language:English
Published: SpringerOpen 2018-01-01
Series:EURASIP Journal on Advances in Signal Processing
Subjects:
Bayesian inference
Monte Carlo methods
Adaptive Markov chain Monte Carlo (MCMC)
Adaptive rejection Metropolis sampling (ARMS)
Gibbs sampling
Metropolis-within-Gibbs
Online Access:http://link.springer.com/article/10.1186/s13634-017-0524-6

Internet

http://link.springer.com/article/10.1186/s13634-017-0524-6

Similar Items