Case Studies in Applied Bayesian Data Science: CIRM Jean-Morlet Chair, Fall 2018: 2259 (Lecture Notes in Mathematics) - Tapa blanda

 
9783030425524: Case Studies in Applied Bayesian Data Science: CIRM Jean-Morlet Chair, Fall 2018: 2259 (Lecture Notes in Mathematics)
Tapa blanda
ISBN 10: 3030425525 ISBN 13: 9783030425524
Editorial: Springer, 2020

Sinopsis

Presenting a range of substantive applied problems within Bayesian Statistics along with their Bayesian solutions, this book arises from a research program at CIRM in France in the second semester of 2018, which supported Kerrie Mengersen as a visiting Jean-Morlet Chair and Pierre Pudlo as the local Research Professor.

The field of Bayesian statistics has exploded over the past thirty years and is now an established field of research in mathematical statistics and computer science, a key component of data science, and an underpinning methodology in many domains of science, business and social science. Moreover, while remaining naturally entwined, the three arms of Bayesian statistics, namely modelling, computation and inference, have grown into independent research fields. While the research arms of Bayesian statistics continue to grow in many directions, they are harnessed when attention turns to solving substantive applied problems. Each such problem set has its own challenges and hence draws from the suite of research a bespoke solution.

The book will be useful for both theoretical and applied statisticians, as well as practitioners, to inspect these solutions in the context of the problems, in order to draw further understanding, awareness and inspiration. 

"Sinopsis" puede pertenecer a otra edición de este libro.

De la contraportada

Presenting a range of substantive applied problems within Bayesian Statistics along with their Bayesian solutions, this book arises from a research program at CIRM in France in the second semester of 2018, which supported Kerrie Mengersen as a visiting Jean-Morlet Chair and Pierre Pudlo as the local Research Professor.

The field of Bayesian statistics has exploded over the past thirty years and is now an established field of research in mathematical statistics and computer science, a key component of data science, and an underpinning methodology in many domains of science, business and social science. Moreover, while remaining naturally entwined, the three arms of Bayesian statistics, namely modelling, computation and inference, have grown into independent research fields.While the research arms of Bayesian statistics continue to grow in many directions, they are harnessed when attention turns to solving substantive applied problems. Each such problem set has its own challenges and hence draws from the suite of research a bespoke solution.

The book will be useful for both theoretical and applied statisticians, as well as practitioners, to inspect these solutions in the context of the problems, in order to draw further understanding, awareness and inspiration. 

"Sobre este título" puede pertenecer a otra edición de este libro.

Editorial
Springer
Año de publicación
2020
Idioma
Inglés
ISBN 10 
3030425525
ISBN 13 
9783030425524
Encuadernación
Tapa blanda
Número de páginas
428
Editor
Mengersen Kerrie L., Pudlo Pierre, Robert Christian P.
Contacto del fabricante
Springer Nature Customer Service Center GmbH
ProductSafety@springernature.com

Europaplatz 3,69115 Heidelberg, Germany
Heidelberg
69115
Alemania

Otras ediciones populares con el mismo título

9783030425548: Case Studies in Applied Bayesian Data Science: CIRM Jean-Morlet Chair, Fall 2018

Edición Destacada

ISBN 10:  3030425541 ISBN 13:  9783030425548
Editorial: Springer, 2020
Tapa blanda