Advanced Bayesian Methods: Introduction

Katz, Gabriel (2021) Advanced Bayesian Methods: Introduction. [Video]

Full text not available from this repository.

Abstract

In this video, Dr Gabriel Katz introduces this online resource which will explore fundamental aspects of modern Bayesian computation. He explains that he will focus on two Bayesian algorithms, the Gibbs Sampler and the Metropolis-Hastings, he will then review some criteria to address model convergence and he will finally present methods to speed up conversion or execution time.

Item Type: Video
Subjects: 5. Quantitative Data Handling and Data Analysis > 5.2 Statistical Theory and Methods of Inference
5. Quantitative Data Handling and Data Analysis > 5.2 Statistical Theory and Methods of Inference > 5.2.5 Bayesian methods
7. ICT and Software > 7.2 Quantitative Software
7. ICT and Software > 7.2 Quantitative Software > 7.2.6 R
Depositing User: NCRM users
Date Deposited: 09 Jan 2022 20:12
Last Modified: 09 Jan 2022 20:12
URI: https://eprints.ncrm.ac.uk/id/eprint/4510

Actions (login required)

View Item
View Item