Taking a Closer Look at Plant Dynamics Using the Univariate and Bivariate Centered Autologistic Models

• Activity Number: 21
• Type: Topic Contributed
• Date/Time: Sunday, July 31, 2011 : 2:00 PM to 3:50 PM
• Sponsor: ENAR
• Author(s): Petrutza Caragea*+
• Companies: Iowa State University
• Keywords: autologistic models ; bivariate ; plant distribution ; spatial models

Abstract

An issue that often arises in environmental monitoring situations is that of detecting and modeling changes in the structure of the underlying scientific processes that govern the observable phenomena of interest. Ideally, a statistical model used in this type of situation contains parameter values, for which we can assess, for example, changes over time, that correspond to components of the underlying scientific process in an interpretable manner. A traditional approach is to consider the overall level of a process, possibly adjusted by the influence of covariates, to be appropriately modeled as what is called the large-scale model component. When the response variable is binary, a typical approach is to use the logistic automodel. We explore the Pre-Euro-American Data from a Public Land Survey in the Driftless Area in the Midwest using the univariate and bivariate centered autologistic model, in an effort to inform ecosystem restoration work.