Spatial Statistical Models – Bayesian Approach Overview

Spatial Statistical Models – Bayesian Approach Overview

  • Posted by MGUG Admin
  • On February 7, 2022

Spatial documentation is exponentially increasing given the availability of Big IoT Data, enabled by the devices miniaturization and data storage capacity. Bayesian spatial statistics is a useful statistical tool to determine the dependence structure and hidden patterns over space through prior knowledge and data likelihood. Nevertheless, this modeling class is not well explored.

This systematic review aims to unravel the main models presented in the literature in the past 20 years, identify gaps, and research opportunities. Elements such as random fields, spatial domains, prior specification, covariance function, and numerical approximations are discussed.

Paper (free PDF download) available at:

https://arxiv.org/abs/2009.14371