An Introduction to Bayesian Inference, Met...

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Beschreibung

These lecture notes provide a rapid, accessible introduction to Bayesian statistical methods. The course covers the fundamental philosophy and principles of Bayesian inference, including the reasoning behind the prior/likelihood model construction synonymous with Bayesian methods, through to advanced topics such as nonparametrics, Gaussian processes and latent factor models. These advanced modelling techniques can easily be applied using computer code samples written in Python and Stan which are integrated into the main text. Importantly, the reader will learn methods for assessing model fit, and to choose between rival modelling approaches.

Über den Autor

Professor Nick Heard received his PhD degree from the Department of Mathematics at Imperial College London in 2001 and currently holds the position of Chair in Statistics at Imperial. His research interests include developing statistical models for cyber-security applications, finding community structure in large dynamic networks, clustering and changepoint analysis, in each case using computational Bayesian methods.

Zusammenfassung

Quickly progresses from fundamental concepts to advanced modelling techniques

Provides Stan and Python codes for illustrating concepts

Presents exercises with solutions integrated into each chapter

Inhaltsverzeichnis

Uncertainty and Decisions.- Prior and Likelihood Representation.- Graphical Modeling.- Parametric Models.- Computational Inference.- Bayesian Software Packages.- Model choice.- Linear Models.- Nonparametric Models.- Nonparametric Regression.- Clustering and Latent Factor Models.- Conjugate Parametric Models.

Details

Erscheinungsjahr:	2021
Fachbereich:	Wahrscheinlichkeitstheorie
Genre:	Mathematik , Medizin , Naturwissenschaften , Technik
Rubrik:	Naturwissenschaften & Technik
Medium:	Buch
Inhalt:	xii 169 S. 12 s/w Illustr. 70 farbige Illustr. 169 p. 82 illus. 70 illus. in color.
ISBN-13:	9783030828073
ISBN-10:	3030828077
Sprache:	Englisch
Einband:	Gebunden
Autor:	Heard, Nick
Auflage:	1st edition 2021
Hersteller:	Springer International Publishing
Verantwortliche Person für die EU:	Springer Verlag GmbH, Tiergartenstr. 17, D-69121 Heidelberg, juergen.hartmann@springer.com
Maße:	241 x 160 x 16 mm
Von/Mit:	Nick Heard
Erscheinungsdatum:	18.10.2021
Gewicht:	0,448 kg

Artikel-ID: 120302675