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An Introduction to Bayesian Inference, Methods and Computation
Hardcover
ApplicationsDatabasesProbability & Statistics
ISBN13: 9783030828073
Publisher: Springer
Published: Oct 18 2021
Pages: 169
Weight: 0.96
Height: 0.50 Width: 6.14 Depth: 9.21
Language: English
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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