Results 211 to 220 of about 38,389 (265)

Simulation-based assessment of a Bayesian M-spline survival model with flexible baseline hazard and time-dependent effects. [PDF]

BMC Med Res Methodol
Timmins IR, Torabi F, Jackson CH, Lambert PC, Sweeting MJ.   +4 more
europepmc   +1 more source

Genome-wide fine-mapping improves identification of causal variants. [PDF]

Nat Genet
Wu Y, Zheng Z, Thibaut L, Lin T, Feng Q, Cheng H, Yengo L, Goddard ME, Wray NR, Visscher PM, Zeng J.   +10 more
europepmc   +1 more source

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MRF parameter estimation by MCMC method

Pattern Recognition, 2000
Abstract Markov random field (MRF) modeling is a popular pattern analysis method and MRF parameter estimation plays an important role in MRF modeling. In this paper, a method based on Markov Chain Monte Carlo (MCMC) is proposed to estimate MRF parameters. Pseudo-likelihood is used to represent likelihood function and it gives a good estimation result.
Lei Wang, Jun Liu 0020, Stan Z. Li
exaly   +2 more sources

A MCMC method for resolving two person mixtures

Science and Justice - Journal of the Forensic Science Society, 2008
In this paper a Monte Carlo Markov Chain (MCMC) method for resolving DNA mixtures containing at most four peaks per locus into a major and a minor contributor is presented. Unlike previous methods, this method can provide posterior probability assessments of the most probable genotype and a likely range for the mixing proportion. The proposed method is
James Curran
exaly   +3 more sources

The ADT evaluation method based on MCMC

2011 IEEE MTT-S International Microwave Workshop Series on Innovative Wireless Power Transmission: Technologies, Systems, and Applications, 2011
This paper proposes an accelerated degradation testing (ADT) evaluation method based on Markov Chain Monte Carlo (MCMC) method. Firstly the degradation model, reliability model and accelerated model of ADT are introduced; secondly, with the information above, the ADT evaluation method based on MCMC is proposed; Thirdly, the evaluation results of this ...
Lizhi Wang 0004, Xiaoyang Li 0001, Tongmin Jiang, Xiaotian Zhuang   +3 more
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Parallel MCMC methods for global optimization

Monte Carlo Methods and Applications, 2019
Abstract We introduce a parallel scheme for simulated annealing, a widely used Markov chain Monte Carlo (MCMC) method for optimization. Our method is constructed and analyzed under the classical framework of MCMC. The benchmark function for optimization is used for validation and verification of the parallel scheme.
Lihao Zhang, Zeyang Ye, Yuefan Deng
openaire   +2 more sources

Supervised classification using MCMC methods

2000 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.00CH37100), 2002
This paper addresses the problem of supervised classification using general Bayesian learning. General Bayesian learning consists of estimating the unknown class-conditional densities from a set of labelled samples. However, the estimation requires to evaluate intractable multidimensional integrals.
Manuel Davy, Christian Doncarli, Jean-Yves Tourneret   +2 more
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Classification of Digital Modulations Using MCMC Methods

Monte Carlo Methods and Applications, 2001
This paper presents a simulation study of the Markov chain Monte Carlo (MCMC) technique applied to classification of digital modulations. The latter problem consists of determining the underlying symbol constellation of transmitted signals from observed noisy measurements.
Stéphane Lesage, Jean-Yves Tourneret, Petar M. Djuric   +2 more
openaire   +1 more source