JSM 2015 Online Program

Online Program Home
My Program

Abstract Details

Activity Number: 372
Type: Contributed
Date/Time: Tuesday, August 11, 2015 : 10:30 AM to 12:20 PM
Sponsor: Biopharmaceutical Section
Abstract #316308
Title: Statistical Analysis on Models Defined by Differential Equations
Author(s): Hongyuan Wang* and David Allen
Companies: and University of Kentucky
Keywords: differential equations ; differential evolution ; derivative free optimization ; compartment models

Differential equations, which describe mathematical relations between some unknown function and its derivatives, are widely used in physics, chemistry and biomedical sciences, etc. The statistical analysis of data having an underlying model defined by non-linear differential equations requires methodology from numerical analysis, numerical solution of differential equations and derivative-free optimization. In this talk we would like to present an outline for statistical inference of models based on differential equations without analytically solving them. Our methods would involve numerical integration algorithms like Runge-Kutta methods, along with optimization algorithms like Gauss-Newton, differential evolutions, etc. Examples like Compartment models, logistic models will be presented to illustrate the proposed methods. The methodology will be evaluated by both simulation study and real data analysis. The efficiency of different derivative free optimization algorithms will also be studied and compared.

Authors who are presenting talks have a * after their name.

Back to the full JSM 2015 program

For program information, contact the JSM Registration Department or phone (888) 231-3473.

For Professional Development information, contact the Education Department.

The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.

2015 JSM Online Program Home