Bayesian hierarchical models for disease mapping applied to contagious pathologies. [PDF]
PLoS One, 2021 Coly S, Garrido M, Abrial D, Yao AF.
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Hierarchical Generalized Linear Models: The R Package HGLMMM [PDF]
The R package HGLMMM has been developed to fit generalized linear models with random effects using the h-likelihood approach. The response variable is allowed to follow a binomial, Poisson, Gaussian or gamma distribution.
Marek Molas, Emmanuel Lesaffre
core
Design of a Multistable Finger Prosthesis with Programmable Metamaterials
Advanced Engineering Materials, EarlyView.This research article shows the development of a multistable programmble metamaterial for the use as a finger prosthesis. The material was designed on different hierarchical levels where the influence of geometrical parameters and combination of mechanical elements was explored.
Franziska Wenz +5 more
wiley +1 more source
Obtaining population-based estimates for survey data using Bayesian hierarchical models with poststratification. [PDF]
Am J EpidemiolZhang Y +5 more
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Empirical Bayesian Analysis Through the Lens of a Particular Class of Constrained Bayesian Hierarchical Models. [PDF]
Stat, 2021 Bradley JR, Zong Q.
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MODELING A HIERARCHICAL DATABASE WITH XML
, 2009 Electronic Warfare Integrated Reprogramming DataBase (EWIRDB) is the largest data source in the area of electronic warfare. The information in this data source is stored and managed as plain files. The structure of this data source has the following characteristics; dynamic data expandability, ability to store over 2400 parameters, ability to ...
Yurekten, Ozguer, Bilge, Hasan Sakir
openaire +3 more sources
Computational and robotic models of the hierarchical organization of behavior: an overview
, 2013 The hierarchical organisation of behaviour is a fundamental means through which robots and organisms can acquire and produce a sophisticated and exible behaviour that allows them to solve multiple tasks in multiple conditions.
Marco, Baldassarre, Mirolli, Gianluca
core
Advanced Engineering Materials, EarlyView.This article explores the transformative potential of symbolic artificial intelligence (AI) in the field of materials science, particularly in leveraging experimental data. The article presents several symbolic AI models and discusses their applications in materials science.
Ahmed Amrani +7 more
wiley +1 more source
Bayesian hierarchical models for multivariate mixed responses with repeated measures: A case study in arterial occlusive disease. [PDF]
PLoS OneEbrahim EA, Cengiz MA.
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Bayesian hierarchical models for the prediction of volleyball results. [PDF]
J Appl Stat, 2021 Gabrio A.
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