Results 151 to 160 of about 29,218,928 (220)

Bayesian Clustering Factor Models. [PDF]

Stat Med
Shin H, Ferreira MAR, Tegge AN.
europepmc   +1 more source

Some of the next articles are maybe not open access.

Related searches:

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, S. Li
semanticscholar   +2 more sources

A MCMC method for resolving two person mixtures.

Science & Justice, 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
J. Curran
semanticscholar   +3 more sources

A Nested MCMC Method Incorporated With Atmospheric Process Decomposition for Photovoltaic Power Simulation

IEEE Transactions on Sustainable Energy, 2020
Large-scale photovoltaic (PV) generation's uncertainties significantly affect power system planning and operations. Thus, a stochastic PV power simulation method, which can accurately capture such uncertainties, is urgently needed to provide a foundation
Chenxi Zhu, Yan Zhang, Zheng Yan, Jinzhou Zhu   +3 more
semanticscholar   +1 more source

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.
M. Davy, C. Doncarli, J.-Y. Tourneret
openaire   +1 more source

Scaling Analysis of Delayed Rejection MCMC Methods

Methodology and Computing in Applied Probability, 2013
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Bédard, Mylène, Douc, Randal, Moulines, Eric   +2 more
openaire   +1 more source

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.
Lesage, Stéphane, Tourneret, Jean-Yves, Djurić, Petar M.   +2 more
openaire   +1 more source

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.
Zhang, Lihao, Ye, Zeyang, Deng, Yuefan
openaire   +2 more sources