JSM 2005 - Toronto

Abstract #302486

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Legend: = Applied Session, = Theme Session, = Presenter
Activity Number: 46
Type: Invited
Date/Time: Sunday, August 7, 2005 : 4:00 PM to 5:50 PM
Sponsor: Section on Statistics and the Environment
Abstract - #302486
Title: Bayesian Models for a Multivariate Discrete Response: Comparing Impacted and Nonimpacted Streams
Author(s): Jennifer A. Hoeting*+ and Devin S. Johnson and Megan Dailey
Companies: Colorado State University and University of Alaska Fairbanks and Colorado State University
Address: Department of Statistics, Fort Collins, CO, 80523-1877,
Keywords: compositional data ; graphical models ; logistic normal ; random effects ; Bayesian state space models
Abstract:

Comparing impacted to nonimpacted waterways and land areas is a key component to monitoring for environmental protection agencies around the world. In this paper, we propose a new approach to compare impacted and nonimpacted areas via a Bayesian hierarchical model. This approach has several advantages over the traditional approaches. Using a Gibbs sampling approach, we illustrate application of the model on a dataset of fish species richness in the mid-Atlantic region of the United States.

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Revised March 2005