Bayesian Nonparametric Data Analysis

Autor: Peter Muller, Fernando Andres Quintana, Alejandro Jara, Tim Hanson

Jazyk:

Vazba: Brožovaná

Vydavatel: Springer International Publishing AG

Dostupnost: Skladem u dodavatele

Odesíláme za 10-18 dnů

2 275 Kč

This book reviews nonparametric Bayesian methods and models that have proven useful in the context o...

Informace o knize

Autor

Peter Muller, Fernando Andres Quintana, Alejandro Jara, Tim Hanson

Jazyk

Angličtina

Vazba

Kniha - Brožovaná

Vydáno

2016

Stránek

193

EAN

9783319368429

ISBN

3319368427

Enbook ID

15193991

Vydavatel

Springer International Publishing AG

Hmotnost

3226

Rozměry

155 x 235 x 12

Kompletní popis

This book reviews nonparametric Bayesian methods and models that have proven useful in the context of data analysis. Rather than providing an encyclopedic review of probability models, the book's structure follows a data analysis perspective. As such, the chapters are organized by traditional data analysis problems. In selecting specific nonparametric models, simpler and more traditional models are favored over specialized ones. The discussed methods are illustrated with a wealth of examples, including applications ranging from stylized examples to case studies from recent literature. The book also includes an extensive discussion of computational methods and details on their implementation. R code for many examples is included in online software pages.

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Bayesian Nonparametric Data Analysis

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