Results 51 to 60 of about 167,711 (260)

Bayesian estimation of parameters in a SI mathematical model for the transmision dynamics of an infectious disease in Peru

Selecciones Matemáticas, 2023
The objective of the research is to estimate the transmission rate of an infection (β) in the SI epidemical model, using Bayesian statistical methods from observed data in Peru.
Emma Cambillo-Moyano, Ysela Agüero-Palacios, Alicia Riojas-Cañari, Pedro Pesantes-Grados, Roxana López-Cruz   +4 more
doaj   +1 more source

������������������Logistic���������MCMC���������������������������������

, 2021
" Logistic MCMC "
openaire   +1 more source

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

AIChE Journal, EarlyView.
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

Advances in Thermal Modeling and Simulation of Lithium‐Ion Batteries with Machine Learning Approaches

Advanced Intelligent Discovery, EarlyView.
Heat generation in lithium‐ion batteries affects performance, aging, and safety, requiring accurate thermal modeling. Traditional methods face efficiency and adaptability challenges. This article reviews machine learning‐based and hybrid modeling approaches, integrating data and physics to improve parameter estimation and temperature prediction ...
Qi Lin, Kang Fu, Junjie Ding, Kai Sun, Peng Tan   +4 more
wiley   +1 more source

Orthogonal MCMC algorithms [PDF]

2014 IEEE Workshop on Statistical Signal Processing (SSP), 2014
Monte Carlo (MC) methods are widely used in signal processing, machine learning and stochastic optimization. A well-known class of MC methods are Markov Chain Monte Carlo (MCMC) algorithms. In this work, we introduce a novel parallel interacting MCMC scheme, where the parallel chains share information using another MCMC technique working on the entire ...
Martino, Luca, Elvira Arregui, Víctor, Luengo García, David, Artés Rodríguez, Antonio, Corander, Jukka   +4 more
openaire   +3 more sources

Accelerating MCMC with active subspaces

, 2016
The Markov chain Monte Carlo (MCMC) method is the computational workhorse for Bayesian inverse problems. However, MCMC struggles in high-dimensional parameter spaces, since its iterates must sequentially explore the high-dimensional space.
Bui-Thanh, Tan, Constantine, Paul G., Kent, Carson   +2 more
core   +1 more source

Composition‐Aware Cross‐Sectional Integration for Spatial Transcriptomics

Advanced Intelligent Discovery, EarlyView.
Multi‐section spatial transcriptomics demands coherent cell‐type deconvolution, domain detection, and batch correction, yet existing pipelines treat these tasks separately. FUSION unifies them within a composition‐aware latent framework, modeling reads as cell‐type–specific topics and clustering in embedding space.
Qishi Dong, Zijian Huang, Xuanwu Wang, Zhenghui Feng, Wei Liu, Bingding Huang   +5 more
wiley   +1 more source

Comparison of item response theory ability and item parameters according to classical and Bayesian estimation methods

International Journal of Assessment Tools in Education
This research aims to compare the ability and item parameter estimations of Item Response Theory according to Maximum likelihood and Bayesian approaches in different Monte Carlo simulation conditions.
Ergül Demir, Eray Selçuk
doaj   +1 more source

Revisiting a long‐overlooked skull: Implications for the distribution of Dinodontosaurus brevirostris (Kannemeyeriiformes) in the Brazilian Triassic

The Anatomical Record, EarlyView.
Abstract Dicynodonts (Anomodontia: Dicynodontia) were one of the main groups of terrestrial tetrapods in Permian and Triassic faunas. In Brazil, the genus Dinodontosaurus is one of the most common tetrapod taxon in the Triassic Santa Maria Supersequence. This genus has a complex taxonomic history and is represented in the Triassic of both Argentina and
Julia Lara Rodrigues de Souza, João Lucas Da Silva, Voltaire D. P. Neto, Arielli Fabrício Machado, Juan A. Escobar, Felipe L. Pinheiro   +5 more
wiley   +1 more source

Regional Shopping Objectives in British Grocery Retail Transactions Using Segmented Topic Models

Applied Stochastic Models in Business and Industry, EarlyView.
ABSTRACT Understanding the customer behaviours behind transactional data has high commercial value in the grocery retail industry. Customers generate millions of transactions every day, choosing and buying products to satisfy specific shopping needs.
Mariflor Vega Carrasco, Mirco Musolesi, Jason O'Sullivan, Rosie Prior, Ioanna Manolopoulou   +4 more
wiley   +1 more source