Illustrating advantages and challenges of Bayesian statistical modelling: An empirical perspective

Article type: Research Article

Authors: Sosa, Juan | Buitrago, Lina

Affiliations: Universidad Nacional de Colombia, Bogotá, Colombia

Correspondence: [*] Corresponding author: Juan Sosa, Universidad Nacional de Colombia, Bogotá, Colombia. E-mail: [email protected].

Abstract: We provide four case studies that use Bayesian machinery to making inductive reasoning. Our main motivation relies in offering several instances where the Bayesian approach to data analysis is exploited at its best to perform complex tasks, such as description, testing, estimation, and prediction. This work is not meant to be either a reference text or a survey in Bayesian statistical inference. Our goal is simply to provide several examples that use Bayesian methodology to solve data-driven problems. The topics we cover here include analysis of times series and analysis of spatial data.

Keywords: Bayesian models, Gibbs sampler, hierarchical models, Markov chain Monte Carlo, statistical inference

DOI: 10.3233/MAS-221342

Journal: Model Assisted Statistics and Applications, vol. 17, no. 3, pp. 175-187, 2022