Results 41 to 50 of about 198,078 (301)
Multilevel Markov Chain Monte Carlo [PDF]
SIAM Review, 2019 In this paper we address the problem of the prohibitively large computational cost of existing Markov chain Monte Carlo methods for large-scale applications with high-dimensional parameter spaces, ...
Dodwell, T. J. +3 more
openaire +2 more sources
Statistical Inference for Partially Observed Markov Processes via the R Package pomp
Journal of Statistical Software, 2016 Partially observed Markov process (POMP) models, also known as hidden Markov models or state space models, are ubiquitous tools for time series analysis.
Aaron A. King +2 more
doaj +1 more source
An efficient interpolation technique for jump proposals in reversible-jump Markov chain Monte Carlo calculations [PDF]
Royal Society Open Science, 2015 Selection among alternative theoretical models given an observed dataset is an important challenge in many areas of physics and astronomy. Reversible-jump Markov chain Monte Carlo (RJMCMC) is an extremely powerful technique for performing Bayesian model ...
W. M. Farr, I. Mandel, D. Stevens
doaj +1 more source
A Short Review of Ergodicity and Convergence of Markov chain Monte Carlo Estimators [PDF]
arXiv, 2021 This short note reviews the basic theory for quantifying both the asymptotic and preasymptotic convergence of Markov chain Monte Carlo estimators.
arxiv
Hematological Oncology, Volume 40, Issue 5, Page 987-998, December 2022., 2022 Abstract The treatment scenario for newly‐diagnosed transplant‐ineligible multiple myeloma patients (NEMM) is quickly evolving. Currently, combinations of proteasome inhibitors and/or immunomodulatory drugs +/− the monoclonal antibody Daratumumab are used for first‐line treatment, even if head‐to‐head comparisons are lacking.
Cirino Botta +17 more
wiley +1 more source
Integrated Environmental Assessment and Management, Volume 19, Issue 1, Page 213-223, January 2023., 2023 Abstract Developing population models for assessing risks to terrestrial plant species listed as threatened or endangered under the Endangered Species Act (ESA) is challenging given a paucity of data on their life histories. The purpose of this study was to develop a novel approach for identifying relatively data‐rich nonlisted species that could serve
Pamela Rueda‐Cediel +5 more
wiley +1 more source
Discrepancy estimates for variance bounding Markov chain quasi-Monte Carlo [PDF]
Electron. J. Probab. 19 (2014), no. 105, 1-24, 2013 Markov chain Monte Carlo (MCMC) simulations are modeled as driven by true random numbers. We consider variance bounding Markov chains driven by a deterministic sequence of numbers. The star-discrepancy provides a measure of efficiency of such Markov chain quasi-Monte Carlo methods.
arxiv +1 more source
Application of Markov chain Monte carlo method in Bayesian statistics
MATEC Web of Conferences, 2016 In statistical inference methods, bayesian method is a method of great influence. This paper introduces the basic idea of the bayesian method. However, the widespread popularity of MCMC samplers is largely due to their impact on solving statistical ...
Zhao Qi
doaj +1 more source
Markov Chain Monte Carlo Solution of Poisson’s Equation in Axisymmetric Regions
Advanced Electromagnetics, 2019 The advent of the Monte Carlo methods to the field of EM have seen floating random walk, fixed random walk and Exodus methods deployed to solve Poisson’s equation in rectangular coordinate and axisymmetric solution regions.
A. E. Shadare +2 more
doaj +1 more source
Coupling Control Variates for Markov Chain Monte Carlo [PDF]
, 2008 We show that Markov couplings can be used to improve the accuracy of Markov chain Monte Carlo calculations in some situations where the steady-state probability distribution is not explicitly known. The technique generalizes the notion of control variates from classical Monte Carlo integration.
arxiv +1 more source