Resampling methods for evaluating classification accuracy of wildlife habitat models
Abstract
Predictive models of wildlife-habitat relationships often have been developed without being tested The apparent classification accuracy of such models can be optimistically biased and misleading. Data resampling methods exist that yield a more realistic estimate of model classification accuracy These methods are simple and require no new sample data. We illustrate these methods (cross-validation, jackknife resampling, and bootstrap resampling) with computer simulation to demonstrate the increase in precision of the estimate. The bootstrap method is then applied to field data as a technique for model comparison We recommend that biologists use some resampling procedure to evaluate wildlife habitat models prior to field evaluation.
- Publication:
-
Environmental Management
- Pub Date:
- November 1989
- DOI:
- 10.1007/BF01868317
- Bibcode:
- 1989EnMan..13..783V
- Keywords:
-
- Bootstrap;
- Cross-validation;
- Discriminant analysis;
- Habitat modeling;
- Resampling methods