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Ecological Niches and Geographic Distributions (MPB-49)$
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A. Townsend Peterson, Jorge Soberón, Richard G. Pearson, Robert P. Anderson, Enrique Martínez-Meyer, Miguel Nakamura, and Miguel B. Araújo

Print publication date: 2011

Print ISBN-13: 9780691136868

Published to Princeton Scholarship Online: October 2017

DOI: 10.23943/princeton/9780691136868.001.0001

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PRINTED FROM PRINCETON SCHOLARSHIP ONLINE (www.princeton.universitypressscholarship.com). (c) Copyright Princeton University Press, 2022. All Rights Reserved. An individual user may print out a PDF of a single chapter of a monograph in PRSO for personal use.date: 06 July 2022

Evaluating Model Performance and Significance

Evaluating Model Performance and Significance

(p.150) Chapter Nine Evaluating Model Performance and Significance
Ecological Niches and Geographic Distributions (MPB-49)

A. Townsend Peterson

Jorge Soberón

Richard G. Pearson

Robert P. Anderson

Enrique Martínez-Meyer

Miguel Nakamura

Miguel Bastos Araújo

Princeton University Press

This chapter describes a framework for selecting appropriate strategies for evaluating model performance and significance. It begins with a review of key concepts, focusing on how primary occurrence data can be presence-only, presence/background, presence/pseudoabsence, or presence/absence as well as factors that may contribute to apparent commission error. It then considers the availability of two pools of occurrence data: one for model calibration and another for evaluation of model predictions. It also discusses strategies for detecting overfitting or sensitivity to bias in model calibration, with particular emphasis on quantification of performance and tests of significance. Finally, it suggests directions for future research as regards model evaluation, highlighting areas in need of theoretical and/or methodological advances.

Keywords:   model performance, primary occurrence data, commission error, model calibration, model prediction, overfitting, sensitivity, model significance, model evaluation

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