Results 71 to 80 of about 5,420,390 (236)

Multiple-try Metropolis Hastings for modeling extreme PM10 data [PDF]

, 2013
Awareness of catastrophic events brings the attention to work out the relationship of these events by using statistical analysis of Extreme Value Theory (EVT).
Adam, Mohd Bakri, Ibrahim, Noor Akma, Mohd Amin, Nor Azrita   +2 more
core   +1 more source

Sequential Monte Carlo with likelihood tempering and parallel implementation for uncertainty quantification

AIChE Journal, Volume 72, Issue 6, June 2026.
Abstract Bayesian estimation enables uncertainty quantification, but analytical implementation is often intractable. As an approximate approach, the Markov Chain Monte Carlo (MCMC) method is widely used, though it entails a high computational cost due to frequent evaluations of the likelihood function.
Tatsuki Maruchi, Tomoyuki Yajima, Yoshiaki Kawajiri   +2 more
wiley   +1 more source

The DeepJoint Algorithm: An Innovative Approach for Studying the Longitudinal Evolution of Quantitative Mammographic Density and Its Association With Screen‐Detected Breast Cancer Risk

Biometrical Journal, Volume 68, Issue 3, June 2026.
ABSTRACT High mammographic density is a well‐known risk factor for breast cancer and reduces the sensitivity of mammography‐based screening. While automated machine and deep learning‐based methods provide more consistent and precise measurements compared to subjective Breast Imaging Reporting and Data System (BI‐RADS) assessments, they often fail to ...
Manel Rakez, Julien Guillaumin, Aurelien Chick, Gaelle Coureau, Foucauld Chamming's, Pierre Fillard, Brice Amadeo, Virginie Rondeau   +7 more
wiley   +1 more source

Irreducibility and efficiency of ESIP to sample marker genotypes in large pedigrees with loops

Genetics Selection Evolution, 2002
Markov chain Monte Carlo (MCMC) methods have been proposed to overcome computational problems in linkage and segregation analyses. This approach involves sampling genotypes at the marker and trait loci.
Schelling Matthias, Stricker Christian, Guldbrandtsen Bernt, Fernando Rohan L, Fernández Soledad A, Carriquiry Alicia L   +5 more
doaj   +1 more source

Metropolis-Hastings prefetching algorithms [PDF]

, 2008
Prefetching is a simple and general method for single-chain parallelisation of the Metropolis-Hastings algorithm based on the idea of evaluating the posterior in parallel and ahead of time.
Strid, Ingvar
core  

Bayesian Inference for Joint Estimation Models Using Copulas to Handle Endogenous Regressors

Oxford Bulletin of Economics and Statistics, Volume 88, Issue 3, Page 519-534, June 2026.
ABSTRACT This study proposes a Bayesian approach for finite‐sample inference of the Gaussian copula endogeneity correction. Extant studies use frequentist inference, build on a priori computed estimates of marginal distributions of explanatory variables, and use bootstrapping to obtain standard errors. The proposed Bayesian approach facilitates precise
Rouven E. Haschka
wiley   +1 more source

Levy process simulation by stochastic step functions

, 2011
We study a Monte Carlo algorithm for simulation of probability distributions based on stochastic step functions, and compare to the traditional Metropolis/Hastings method.
Benth, Fred Espen, Sørensen, Torquil Macdonald   +1 more
core   +1 more source

A Tutorial on Bayesian Multi‐Study Factor Analysis With Applications in Nutrition and Genomics

Statistics in Medicine, Volume 45, Issue 10-12, May 2026.
ABSTRACT High‐dimensional data are crucial in biomedical research. Integrating such data from multiple studies is a critical process that relies on the choice of advanced statistical models, enhancing statistical power, reproducibility, and scientific insight compared to analyzing each study separately.
Mavis Liang, Blake Hansen, Alejandra Avalos‐Pacheco, Roberta De Vito   +3 more
wiley   +1 more source

Copula-Based Bayesian Inference Approaches for Uncertainty Quantification for Hydrological Simulation

Hydrology
In this study, an advanced copula-based Bayesian inference framework is proposed to characterize probabilistic features in hydrological simulations. Specifically, a Copula–Metropolis–Hastings (CopMH) algorithm is developed through integrating copula ...
Feng Wang, Ruixin Duan, Jiannan Zhang, Mengyu Zhai, Yanfeng Li, Yurui Fan, Yulei Xie   +6 more
doaj   +1 more source

Metropolis-Hastings prefetching algorithms [PDF]

Prefetching is a simple and general method for single-chain parallelisation of the Metropolis-Hastings algorithm based on the idea of evaluating the posterior in parallel and ahead of time.
Strid, Ingvar
core