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Activity Number:
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310
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Type:
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Contributed
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Date/Time:
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Tuesday, August 5, 2008 : 2:00 PM to 3:50 PM
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Sponsor:
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Business and Economics Statistics Section
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| Abstract - #302028 |
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Title:
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Models for Continuous Dynamical Processes with Bounded Support
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Author(s):
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Amanda R. Cangelosi*+ and Mevin B. Hooten+
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Companies:
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Utah State University and Utah State University
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Address:
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3900 Old Main Hill, Logan, UT, 84322, , Logan, UT, 84322,
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Keywords:
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Bias-Correction ; Differential Equations ; Numerical Approximations ; Population Dynamics ; Truncated Normal ; Hierarchical Models
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Abstract:
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Models for natural nonlinear processes, such as population dynamics, have been given much attention in applied mathematics. For example, species competition has been extensively modeled by differential equations. It is of both scientific and mathematical interest to implement such models in a statistical framework to quantify uncertainty in the presence of observations. This study offers an alternative to common ecological modeling practices by using a bias-corrected truncated normal distribution to model the observations and latent process, both having bounded support. Parameters of an underlying continuous process are characterized in a Bayesian hierarchical context, utilizing a fourth-order Runge-Kutta approximation.
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- The address information is for the authors that have a + after their name.
- Authors who are presenting talks have a * after their name.
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