Results 31 to 40 of about 50,503 (261)

Performance of criteria for selecting evolutionary models in phylogenetics: a comprehensive study based on simulated datasets

BMC Evolutionary Biology, 2010
Background Explicit evolutionary models are required in maximum-likelihood and Bayesian inference, the two methods that are overwhelmingly used in phylogenetic studies of DNA sequence data.
Luo Arong, Qiao Huijie, Zhang Yanzhou, Shi Weifeng, Ho Simon YW, Xu Weijun, Zhang Aibing, Zhu Chaodong   +7 more
doaj   +1 more source

Grand Canonical Ensembles of Sparse Networks and Bayesian Inference

Entropy, 2022
Maximum entropy network ensembles have been very successful in modelling sparse network topologies and in solving challenging inference problems. However the sparse maximum entropy network models proposed so far have fixed number of nodes and are ...
Ginestra Bianconi
doaj   +1 more source

Hierarchical modeling of risk factors with and without prior information—the process of regression model evaluation for an example of respiratory diseases in piglet production from daily practice data

Frontiers in Veterinary Science
In veterinary epidemiology, regression models are commonly used to describe animal health and related risk factors. However, model selection and evaluation present ongoing challenges—especially when many potential predictors, complex interactions, and ...
Timur Tug, Fiona Mers, Franziska Schäkel, Doris Höltig, Lothar Kreienbrock, Katja Ickstadt   +5 more
doaj   +1 more source

Probabilistic inference: Task dependency and individual differences of probability weighting revealed by hierarchical Bayesian modelling

Frontiers in Psychology, 2016
Cognitive determinants of probabilistic inference were examined using hierarchical Bayesian modelling techniques. A classic urn-ball paradigm served as experimental strategy, involving a factorial two (prior probabilities) by two (likelihoods) design ...
Moritz eBoos, Caroline eSeer, Florian eLange, Bruno eKopp   +3 more
doaj   +1 more source

A Hierarchical Bayesian Implementation of the Experience-Weighted Attraction Model

Computational Psychiatry, 2020
Social and decision-making deficits are often the first symptoms of neuropsychiatric disorders. In recent years, economic games, together with computational models of strategic learning, have been increasingly applied to the characterization of ...
Zhihao Zhang, Saksham Chandra, Andrew Kayser, Ming Hsu, Joshua L. Warren   +4 more
doaj   +1 more source

Evaluating the Benefits of Bayesian Hierarchical Methods for Analyzing Heterogeneous Environmental Datasets: A Case Study of Marine Organic Carbon Fluxes

Frontiers in Environmental Science, 2021
Large compilations of heterogeneous environmental observations are increasingly available as public databases, allowing researchers to test hypotheses across datasets.
Gregory L. Britten, Gregory L. Britten, Yara Mohajerani, Louis Primeau, Louis Primeau, Murat Aydin, Catherine Garcia, Wei-Lei Wang, Benoît Pasquier, Benoît Pasquier, B. B. Cael, B. B. Cael, B. B. Cael, François W. Primeau   +13 more
doaj   +1 more source

Bayesian hierarchical modeling of size spectra

Methods in Ecology and Evolution, 2023
Abstract A fundamental pattern in ecology is that smaller organisms are more abundant than larger organisms. This pattern is known as the individual size distribution (ISD), which is the frequency of all individual body sizes in an ecosystem.
Jeff S. Wesner, Justin P. F. Pomeranz, James R. Junker, Vojsava Gjoni   +3 more
openaire   +3 more sources

Bayesian Hierarchical Model-Based Information Fusion for Degradation Analysis Considering Non-Competing Relationship

IEEE Access, 2019
Degradation analysis methods are increasingly used in reliability assessment of long-life products. The small sample size problem is worthy of attention in the degradation analysis.
Junyu Guo, Hualin Zheng, Binglin Li, Guo-Zhong Fu   +3 more
doaj   +1 more source

Bayesian hierarchical models for linear networks [PDF]

Journal of Applied Statistics, 2020
The purpose of this study is to highlight dangerous motorways via estimating the intensity of accidents and study its pattern across the UK motorway network. Two methods have been developed to achieve this aim. First, the motorway-specific intensity is estimated by using a homogeneous Poisson process.
Zainab, Al-Kaabawi, Yinghui, Wei, Rana, Moyeed   +2 more
openaire   +2 more sources

Bayesian Hierarchical Models for Counterfactual Estimation

CoRR, 2023
Counterfactual explanations utilize feature perturbations to analyze the outcome of an original decision and recommend an actionable recourse. We argue that it is beneficial to provide several alternative explanations rather than a single point solution and propose a probabilistic paradigm to estimate a diverse set of counterfactuals.
Natraj Raman, Daniele Magazzeni, Sameena Shah   +2 more
openaire   +3 more sources