Results 61 to 70 of about 758,750 (320)

Bayesian hierarchical models for misaligned data: a simulation study

Statistica, 2015
In this paper, the problem of combining information from different data sources is considered. We focus our attention on spatially misaligned data, where available information (typically counts or rates from administrative sources) refers to spatial ...
Giulia Roli, Meri Raggi
doaj   +1 more source

Mapping Brucellosis Increases Relative to Elk Density Using Hierarchical Bayesian Models

PLoS ONE, 2010
The relationship between host density and parasite transmission is central to the effectiveness of many disease management strategies. Few studies, however, have empirically estimated this relationship particularly in large mammals.
P. Cross, D. Heisey, B. Scurlock, W. Edwards, M. Ebinger, Angela Brennan   +5 more
semanticscholar   +1 more source

An introduction to Bayesian inference in gravitational-wave astronomy: Parameter estimation, model selection, and hierarchical models [PDF]

Publications Astronomical Society of Australia, 2018
This is an introduction to Bayesian inference with a focus on hierarchical models and hyper-parameters. We write primarily for an audience of Bayesian novices, but we hope to provide useful insights for seasoned veterans as well.
E. Thrane, C. Talbot
semanticscholar   +1 more source

Development of a Personalized Visualization and Analysis Tool to Improve Clinical Care in Complex Multisystem Diseases With Application to Scleroderma

Arthritis Care &Research, EarlyView.
Objective In complex diseases, it is challenging to assess a patient's disease state, trajectory, treatment exposures, and risk of multiple outcomes simultaneously, efficiently, and at the point of care. Methods We developed an interactive patient‐level data visualization and analysis tool (VAT) that automates illustration of the trajectory of a ...
Ji Soo Kim, John Scott, Lauren Fisher, Lauren N. Smith, Willie Stewart, Adrianne Woods, Rob Smithwright, Diane Koher, Parastoo Aslanbeik, Aalok B. Shah, Brad Tibbils, Samantha I. Pitts, Ayse P. Gurses, Yushi Yang, Ana‐Maria Orbai, Antony Rosen, Laura K. Hummers, Scott L. Zeger, Ami A. Shah   +18 more
wiley   +1 more source

Hierarchical Bayesian Models of Subtask Learning

Journal of Experimental Psychology: Learning, Memory, and Cognition, 2015
The current study used Bayesian hierarchical methods to challenge and extend previous work on subtask learning consistency. A general model of individual-level subtask learning was proposed focusing on power and exponential functions with constraints to test for inconsistency. To study subtask learning, we developed a novel computer-based booking task,
Jeromy, Anglim, Sarah K A, Wynton
openaire   +3 more sources

Modelling unexpected failures with a hierarchical Bayesian model [PDF]

2017 2nd International Conference on System Reliability and Safety (ICSRS), 2017
Systems, especially those in the design and development phase, frequently suffer from unexpected failures, which are caused by insufficient knowledge of the system failure processes. In this paper, we develop a hierarchical Bayesian reliability model that account for unexpected failures.
Zeng, Zhiguo, Zio, Enrico
openaire   +3 more sources

Global and Regional Temporal Changes in Cross‐Country Inequalities of Site‐Specific Osteoarthritis Burden, 1990 to 2021

Arthritis Care &Research, EarlyView.
Objective This study examined the global and regional temporal changes in cross‐country inequalities of site‐specific osteoarthritis (OA) burden from 1990 to 2021. Methods Age‐standardized years lived with disability rates (ASYRs) for site‐specific OA across 204 countries and territories were obtained from the Global Burden of Diseases, Injuries, and ...
Haowei Chen, Lei Si, David J. Hunter, Lei Zhang, Zhe‐Sheng Chen, Xiaomeng Wang, Vicky Duong, Zhounan Zhou, Peihua Cao, Han Cen, Su'an Tang, Tianyu Chen, Houjun Xue, Zhaohua Zhu, Changhai Ding   +14 more
wiley   +1 more source

Rejoinder: Bayesian Checking of the Second Levels of Hierarchical Models

, 2007
Rejoinder: Bayesian Checking of the Second Levels of Hierarchical Models [arXiv:0802.0743]Comment: Published in at http://dx.doi.org/10.1214/07-STS235REJ the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics
Bayarri, M. J., Castellanos, M. E.
core   +2 more sources

Universal Electronic‐Structure Relationship Governing Intrinsic Magnetic Properties in Permanent Magnets

Advanced Functional Materials, EarlyView.
Permanent magnets derive their extraordinary strength from deep, universal electronic‐structure principles that control magnetization, anisotropy, and intrinsic performance. This work uncovers those governing rules, examines modern modeling and AI‐driven discovery methods, identifies critical bottlenecks, and reveals electronic fingerprints shared ...
Prashant Singh
wiley   +1 more source

Income, education, and other poverty-related variables: A journey through Bayesian hierarchical models

Heliyon
One-shirt-size policy cannot handle poverty issues well since each area has its unique challenges, while having a custom-made policy for each area separately is unrealistic due to limitation of resources as well as having issues of ignoring dependencies ...
Irving Gómez-Méndez, Chainarong Amornbunchornvej   +1 more
doaj   +1 more source