JSM 2004 - Toronto

Abstract #302167

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Activity Number: 233
Type: Contributed
Date/Time: Tuesday, August 10, 2004 : 12:00 PM to 1:50 PM
Sponsor: Section on Physical and Engineering Sciences
Abstract - #302167
Title: Using Markov Chain Monte Carlo to Model Survival
Author(s): Andrew Ostarello*+
Companies: California State University, Hayward
Address: 25013 Whitman St #18S, Hayward, CA, 94544,
Keywords: Markov chain Monte Carlo ; survival analysis
Abstract:

New developments in physical and engineering sciences have increased the need for effective simulation before costly development projects are undertaken. There are several techniques that are currently being employed to help researchers more fully understand the behavior and characteristics of fluids, protiens, and particles on a microscopic and molecular level. Some of the major techniques employed to enable these simulations are Markov chain Monte Carlo techniques, Molecular Dynamics Techniques, and most recently gemoetric cluster algorithms. Our research focuses on furthering comparisons between gemetric cluster algorithms and Markov chain Monte Carlo methods. In particular, we focus on the applicablility of these methods to modeling the survival time and reliability of these molecular structures over time. We employed R as our chief simulation tool, and used both discrete-time and continuous-time approaches to compare the two methods.

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