Integrating MT-DREAMzs and nested sampling algorithms to estimate marginal likelihood and comparison with several other methods-Reference-Cited by-同舟云学术

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Integrating MT-DREAMzs and nested sampling algorithms to estimate marginal likelihood and comparison with several other methods

Published:2018-08 Issue: Volume:563 Page:750-765
ISSN:0022-1694
Container-title:Journal of Hydrology
language:en
Short-container-title:Journal of Hydrology

Author:

Cao Tongtong,Zeng Xiankui^ORCID,Wu Jichun,Wang Dong,Sun Yuanyuan,Zhu Xiaobin,Lin Jin,Long Yuqiao

Funder

The National Key Research and Development Program of China

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

Publisher

Elsevier BV

Subject

Water Science and Technology

Reference44 articles.

1. Theoretical and observational constraints on Tachyon Inflation;Barbosa-Cendejas;J. Cosmol. Astropart. Phys.,2018

2. Bayesian model selection in hydrogeophysics: application to conceptual subsurface models of the South Oyster Bacterial Transport Site, Virginia, USA;Brunetti;Adv. Water Resour.,2017

3. Calibration of channelized subsurface flow models using nested sampling and soft probabilities;Elsheikh;Adv. Water Resour.,2015

4. Efficient Bayesian inference of subsurface flow models using nested sampling and sparse polynomial chaos surrogates;Elsheikh;Comput. Method Appl. M.,2014

5. Nested sampling algorithm for subsurface flow model selection, uncertainty quantification, and nonlinear calibration;Elsheikh;Water Resour. Res.,2013

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