About this Event
Instructor: , Assistant Professor of Biostatistics, Dornsife School of Public Health
Dates: Monday, June 24 - Friday, June 28
Times: 1:00 p.m. - 4:00 p.m. EST
Format: In-person instruction
This course provides an introduction to spatial statistics. The course will cover various types of spatial data including discrete space and continuous space data and will compare/contrast the challenges encountered when analyzing these types of data. The course will cover standard and state-of-the-art methods from the statistical literature for modeling spatial data and delve into their motivations. Models will be fitted using a combination of code written from scratch and existing/freely-available software tools e.g., R, STAN etc.
Learning objectives:
- Familiarity with different types of spatial data
- Knowledge of spatial and spatiotemporal modeling approaches
- Familiarity with software (BUGS, NIMBLE, CARBayes, INLA, spX etc.).
- Building open-source user friendly software that focuses on spatial data ad applications.
Prerequisite knowledge: None
Technical requirements: R/R-Studio (Posit)
Continuing Education Credits*: 1.5 CEU or 15 CPH
Event Venue & Nearby Stays
Drexel University Dornsife School of Public Health, Nesbitt Hall, Philadelphia, United States
USD 800.00