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Activity Number: 577 - Statistical Models in Ecology
Type: Contributed
Date/Time: Wednesday, July 31, 2019 : 2:00 PM to 3:50 PM
Sponsor: Section on Statistics and the Environment
Abstract #306637 Presentation
Title: Identifying and Characterizing Extrapolation in Multivariate Response Data
Author(s): Meridith Bartley* and Ephraim Hanks and Tyler Wagner and Erin Schliep and Patricia Soranno
Companies: Penn State University and Pennsylvania State University and Penn State University and University of Missouri and Michigan State University
Keywords: extrapolation; multivariate response; classification and regression trees; prediction ; predictive variance ; joint model

Extrapolation is making predictions beyond the range of the data used to estimate a statistical model. In ecological studies, it is not always obvious when and where extrapolation occurs. Previous work on identifying extrapolation has focused on univariate response data, but these methods are not directly applicable to multivariate response data, which are more and more common in ecological investigations. In this paper, we extend previous work for identifying extrapolation by examining predictive variance within a univariate setting and applying novel methods to the multivariate case. We illustrate our approach through an analysis of jointly modeled lake nutrients, productivity, and clarity variables in over 7000 inland lakes from across the northeast and Midwest US. In addition, we illustrate novel exploratory approaches for identifying regions of parameter space where extrapolation are more likely to occur using classification and regression trees.

Authors who are presenting talks have a * after their name.

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