Results 51 to 60 of about 38,389 (265)
MCMC methods for entropy optimization and nonlinear network coding [PDF]
Although determining the space of entropic vectors for n random variables, denoted by Γ* n , is crucial for solving a large class of network information theory problems, there has been scant progress in explicitly characterizing Γ* n for n ≥ 4. In this paper, we present a certain characterization of quasi-uniform distributions that allows one to ...
Shadbakht, Sormeh, Hassibi, Babak
openaire +2 more sources
Evolutionary morphology of the haplorhine hamate
Abstract Primates adopt a variety of hand postures during an impressive diversity of locomotor and manipulative behaviors. Morphological research has found that elements of the hand skeleton, such as the hamate, hold key information for inferring hand use and locomotor kinematics in extinct species.
Laura E. Hunter +4 more
wiley +1 more source
Aim The number of pregnancies among women with cystic fibrosis (wwCF) has steadily increased over the past decade. However, the pharmacokinetics (PK) of elexacaftor–tezacaftor–ivacaftor (ETI) during gestation remains uncharacterized, despite its widespread use in this population.
Paulette Magnas +16 more
wiley +1 more source
Application of Markov chain Monte carlo method in Bayesian statistics
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
Breaking point: Identifying the factors that predict suspension from school
Abstract School suspensions are associated with adverse educational and psychosocial outcomes, yet little is known about how structural disadvantage, relational factors, health behaviours, well‐being indicators and school‐level factors jointly predict suspension risk in England.
Stephanie Cahill +5 more
wiley +1 more source
Advanced MCMC methods for sampling on diffusion pathspace
The need to calibrate increasingly complex statistical models requires a persistent effort for further advances on available, computationally intensive Monte Carlo methods. We study here an advanced version of familiar Markov Chain Monte Carlo (MCMC) algorithms that sample from target distributions defined as change of measures from Gaussian laws on ...
Alexandros Beskos +2 more
openaire +4 more sources
Climate Risk and Real Estate Markets in the EU: Institutional Control Through Regulation
ABSTRACT Climate change is increasingly reshaping the economic foundations of asset markets, yet its implications for the estate sector remain unevenly understood, particularly when institutional and financial mechanisms mediate risk transmission. While a growing body of evidence links climate vulnerability to property valuation and market behaviour ...
Qiulin Yang +4 more
wiley +1 more source
Quantum annealing enhanced Markov-Chain Monte Carlo
In this study, we propose quantum annealing-enhanced Markov Chain Monte Carlo (QAEMCMC), where QA is integrated into the MCMC subroutine. QA efficiently explores low-energy configurations and overcomes local minima, enabling the generation of proposal ...
Shunta Arai, Tadashi Kadowaki
doaj +1 more source
A full-waveform inversion (FWI) of ground-penetrating radar (GPR) data can be used to effectively obtain the parameters of a shallow subsurface. Introducing the Markov chain Monte Carlo (MCMC) algorithm into the FWI can reduce the dependence on the ...
Shengchao Wang, Xiangbo Gong, Liguo Han
doaj +1 more source
Legacy effects of redlining on the distribution of greenspaces in US cities
We investigated how a discriminatory housing policy—redlining—has shaped the spatial patterns and configurations of greenspaces throughout 177 cities in the contiguous US. Housing segregation has been a long‐term development practice that has sequestered communities of color to areas with elevated environmental and public health risks.
Travis Gallo +4 more
wiley +1 more source

