An Introduction to Bayesian Inference, Methods and Computation
Author | : Nick Heard |
Publisher | : Springer Nature |
Total Pages | : 177 |
Release | : 2021-10-17 |
ISBN-10 | : 9783030828080 |
ISBN-13 | : 3030828085 |
Rating | : 4/5 (80 Downloads) |
Download or read book An Introduction to Bayesian Inference, Methods and Computation written by Nick Heard and published by Springer Nature. This book was released on 2021-10-17 with total page 177 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.