Zobrazeno 1 - 10
of 258 867
pro vyhledávání: '"Markov chain [Monte Carlo]"'
Autor:
Suwa, Hidemaro1 (AUTHOR) suwamaro@phys.s.u-tokyo.ac.jp, Todo, Synge1,2,3 (AUTHOR) wistaria@phys.s.u-tokyo.ac.jp
Publikováno v:
Journal of Chemical Physics. 11/7/2024, Vol. 161 Issue 17, p1-10. 10p.
Autor:
Hauzenberger, Niko1,2 (AUTHOR) niko.hauzenberger@strath.ac.uk, Huber, Florian2 (AUTHOR), Koop, Gary1 (AUTHOR)
Publikováno v:
Studies in Nonlinear Dynamics & Econometrics. Apr2024, Vol. 28 Issue 2, p201-225. 25p.
Autor:
Chun, Young H.1 (AUTHOR) chun@lsu.edu, Watson, Edward F.1 (AUTHOR)
Publikováno v:
INFOR. 2023, Vol. 61 Issue 4, p509-529. 21p.
Autor:
Bumbaca, Federico (Rico)1 (AUTHOR) federico.bumbaca@colorado.edu, Misra, Sanjog2 (AUTHOR) sanjog.misra@chicagobooth.edu, Rossi, Peter E.3 (AUTHOR) perossichi@gmail.com
Publikováno v:
Journal of Marketing Research (JMR). Dec2020, Vol. 57 Issue 6, p999-1018. 20p. 6 Charts, 6 Graphs.
Autor:
Zhang, Xiao1 (AUTHOR) xzhang35@mtu.edu
Publikováno v:
Communications in Statistics: Theory & Methods. Nov2024, p1-16. 16p. 7 Illustrations.
Autor:
Brown, Austin, Rosenthal, Jeffrey S.
We investigate lower bounds on the subgeometric convergence of adaptive Markov chain Monte Carlo under any adaptation strategy. In particular, we prove general lower bounds in total variation and on the weak convergence rate under general adaptation
Externí odkaz:
http://arxiv.org/abs/2411.17084
Autor:
Todo, Synge
Markov chain Monte Carlo (MCMC) is a powerful tool for sampling from complex probability distributions. Despite its versatility, MCMC often suffers from strong autocorrelation and the negative sign problem, leading to slowing down the convergence of
Externí odkaz:
http://arxiv.org/abs/2412.02974
Today, cheap numerical hardware offers huge amounts of parallel computing power, much of which is used for the task of fitting neural networks to data. Adoption of this hardware to accelerate statistical Markov chain Monte Carlo (MCMC) applications h
Externí odkaz:
http://arxiv.org/abs/2411.04260