Articles liés à Bayesian Statistical Methods

9781032486321: Bayesian Statistical Methods
Couverture rigide
ISBN 10 : 1032486325 ISBN 13 : 9781032486321
Editeur : Chapman and Hall/CRC, 2026

Synopsis

This book provides data scientists with the foundational and computational tools needed to carry out a Bayesian analysis. Compared to others, it is more focused on Bayesian methods applied routinely in practice including multiple linear regression, mixed effects models and generalized linear models.

Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.

À propos de l'auteur

Brian J Reich, Gertrude M Cox Distinguished Professor of Statistics at North Carolina State University, applies Bayesian statistical methods in a variety of fields including environmental epidemiology, engineering, weather and climate. He is a Fellow of the American Statistical Association, former Editor-in-Chief of the Journal of Agricultural, Biological, and Environmental Statistics and recipient of the LeRoy & Elva Martin Teaching Award at NC State University.

Sujit K Ghosh, Professor of Statistics at North Carolina State University, has advanced research fields such as Bayesian inference, spatial statistics, survival analysis, and shape-constrained inference, addressing complex inferential challenges in biomedical and environmental sciences, econometrics, and engineering. At NC State, he has been honored with the D.D. Mason Faculty Award and the Cavell Brownie Mentoring Award, reflecting his excellence in research, mentoring, and teaching. His leadership includes impactful service as Program Director at NSF's Division of Mathematical Sciences, Deputy Director at SAMSI, and President of the IISA.

À propos de la quatrième de couverture

This book provides data scientists with the foundational and computational tools needed to carry out a Bayesian analysis. Compared to others, it is more focused on Bayesian methods applied routinely in practice including multiple linear regression, mixed effects models and generalized linear models.

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.

Éditeur
Chapman and Hall/CRC
Date d'édition
2026
Langue
anglais
ISBN 10 
1032486325
ISBN 13 
9781032486321
Reliure
Relié
Numéro d'édition
2
Nombre de pages
360
Coordonnées du fabricant
non disponible
Personne responsable
GPSR Kontakt
gpsr@libri.de

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