An Introduction to Bayesian Inference, Methods and Computation by Nick Heard

An Introduction to Bayesian Inference, Methods and Computation by Nick Heard

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.

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.

SKU	Non disponible
ISBN 13	9783030828103
ISBN 10	3030828107
Titre	An Introduction to Bayesian Inference, Methods and Computation
Auteur	Nick Heard
État	Non disponible
Type de reliure	Paperback
Éditeur	Springer Nature Switzerland AG
Année de publication	2022-10-19
Nombre de pages	169
Note de couverture	La photo du livre est présentée à titre d'illustration uniquement. La reliure, la couverture ou l'édition réelle peuvent varier.
Note	Non disponible