BYU

Abstract by Joshua Fullwood

Personal Infomation


Presenter's Name

Joshua Fullwood

Co-Presenters

Hunter Klein

Degree Level

Undergraduate

Abstract Infomation


Department

Mathematics

Faculty Advisor

Jared Whitehead

Title

Statistical Approximation of Uncertain Data for Random Walk Bayesian Monte Carlo

Abstract

Solving inverse problems for 19th century seismic events requires abstraction of data that was not observed directly. Additionally, many types of data necessary for modern geophysical modeling requires measurements that are uncertain by nature. We discuss the use of kernel density estimators (KDE) in the construction of a prior distribution from modern USGS data. We also discuss different kinds of sensitivity analyses to benchmark the effect of different approximations on the results of our model.