An Introduction to Bayesian Inference Methods and Computation

This book PDF is perfect for those who love Mathematics genre, written by Nick Heard and published by Springer Nature which was released on 17 October 2021 with total hardcover pages 177. You could read this book directly on your devices with pdf, epub and kindle format, check detail and related An Introduction to Bayesian Inference Methods and Computation books below.

An Introduction to Bayesian Inference  Methods and Computation
Author : Nick Heard
File Size : 46,6 Mb
Publisher : Springer Nature
Language : English
Release Date : 17 October 2021
ISBN : 9783030828080
Pages : 177 pages
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An Introduction to Bayesian Inference Methods and Computation by Nick Heard Book PDF Summary

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.

An Introduction to Bayesian Inference  Methods and Computation

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

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