IDRE ECR Group is excited to announce the following workshop on Hierarchical Bayesian modeling with applications for spatial environmental data science:

Title: Hierarchical Bayesian modeling with applications for spatial environmental data science

Date and Time: Friday, May 6, 2022, @9 AM (PST)

Recording is available here: https://youtu.be/Ubsns37DD_U

Abstract: Effectively addressing pressing environmental problems in the modern era requires flexible analytical approaches capable of leveraging the diverse stream of data resources now available to make a reliable statistical inference. Hierarchical Bayesian methods serve as a powerful resource in this regard, allowing researchers to model complex dynamics while explicitly quantifying uncertainty in model output.

This two-part workshop will focus on the application of hierarchical Bayesian models for environmental data science. Part I (morning session) will serve as an introduction to Bayesian modeling using Stan. Part II (afternoon session) will focus on taking a hierarchical Bayesian approach to spatial data science, covering exploratory spatial data analysis (e.g., variogram fitting) and the basics of geostatistical modeling approaches (e.g., Gaussian Processes). The material will be directed towards those with a basic understanding of linear regression and familiarity with R, but no or limited prior experience with Bayesian modeling. Participants will practice fitting models during the workshop and, upon completion, understand the basics of a principled approach to spatial environmental data science using a hierarchical Bayesian approach.

Tentative agenda*: Friday, May 6, 2022, at 9 AM (PST)

*Software needed for hands-on exercises is listed here: https://github.com/caseyyoungflesh/IDRE-Hierarchicial-Bayesian-Modeling.