An Introduction to Bayesian Inference, Methods and Computation - Tapa blanda

Heard, Nick

 
9783030828103: An Introduction to Bayesian Inference, Methods and Computation
Tapa blanda
ISBN 10: 3030828107 ISBN 13: 9783030828103
Editorial: Springer, 2022

Sinopsis

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.

 


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Acerca del 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.

De la contraportada

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.

 


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Editorial
Springer
Año de publicación
2022
Idioma
Inglés
ISBN 10 
3030828107
ISBN 13 
9783030828103
Encuadernación
Tapa blanda
Número de edición
1
Número de páginas
184
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Heidelberg
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Alemania

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