JSM 2005 Online Program

Abstract #303878

This is the preliminary program for the 2005 Joint Statistical Meetings in Minneapolis, Minnesota. Currently included in this program is the "technical" program, schedule of invited, topic contributed, regular contributed and poster sessions; Continuing Education courses (August 7-10, 2005); and Committee and Business Meetings. This on-line program will be updated frequently to reflect the most current revisions.

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Activity Number:	136
Type:	Contributed
Date/Time:	Monday, August 8, 2005 : 10:30 AM to 12:20 PM
Sponsor:	Section on Bayesian Statistical Science
Abstract - #303878
Title:	Assessing the Stability of Likelihood-based Models Incorporating Dynamic Biological Components
Author(s):	Michael Brimacombe*+
Companies:	New Jersey Medical School
Address:	185 S Orange Ave MSB F647, Newark, NJ, 07101-1709, United States
Keywords:	likelihood ; nonlinearity ; chaos ; ecology ; dynamics ; sensitivity
Abstract:	Many biological and growth-related processes are expressed in terms of nonlinear dynamic functions. Often, these reflect population dynamics or specific properties of components evolving through time. In settings where such mathematical biology components are integrated into statistical models, they can yield likelihood functions that are highly unstable locally, often with the likelihood inheriting chaotic properties. Bayesian methods, which average likelihood properties, can smooth some of this nonlinearity, but not in all situations. The use of measures such as box-counting along directional profiles of the likelihood or posterior function is discussed as diagnostic measure of likelihood function instability. This approach also can be extended to examine the local effects of reparameterization. Examples are drawn from population dynamics and ecology.

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