An introduction to Bayesian inference, methods and computation

An introduction to Bayesian inference, methods and computation / 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 advance...

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Bibliographic Details
Main Author: Heard, Nicholas (Author)
Format: eBook
Language:English
Published: Cham, Switzerland : Springer, 2021.
Subjects:
Bayesian statistical decision theory.
Estadística bayesiana
Bayesian statistical decision theory
Online Access:Click for online access
Table of Contents:
  • Uncertainty and Decisions
  • Prior and Likelihood Representation
  • Graphical Modeling
  • Parametric Models
  • Computational Inference
  • Bayesian Software Packages
  • Model choice
  • Linear Models
  • Nonparametric Models
  • Nonparametric Regression
  • Clustering and Latent Factor Models
  • Conjugate Parametric Models.

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