Comparing discriminant analysis, neural networks and logistic regression for predicting species distributions: a case study with a Himalayan river bird
- 13 August 1999
- journal article
- Published by Elsevier in Ecological Modelling
- Vol. 120 (2-3) , 337-347
- https://doi.org/10.1016/s0304-3800(99)00113-1
Abstract
No abstract availableKeywords
This publication has 20 references indexed in Scilit:
- Logistic regression as a tool for defining habitat requirements of two common gammaridsFreshwater Biology, 1998
- The distribution of dippers,Cinclus cinclus(L.), in the acid‐sensitive region of Wales 1984–95Freshwater Biology, 1998
- Some Methodological Issues in MacroecologyThe American Naturalist, 1998
- Use of a new standardized habitat survey for assessing the habitat preferences and distribution of upland river birdsBird Study, 1997
- A review of methods for the assessment of prediction errors in conservation presence/absence modelsEnvironmental Conservation, 1997
- Stochastic models that predict trout population density or biomass on a mesohabitat scaleHydrobiologia, 1996
- Current approaches to modelling the environmental niche of eucalypts: implication for management of forest biodiversityForest Ecology and Management, 1996
- Investigating microclimatic influences on ozone injury in clover (Trifolium subterraneum) using artificial neural networksNew Phytologist, 1996
- Model Uncertainty, Data Mining and Statistical InferenceJournal of the Royal Statistical Society Series A: Statistics in Society, 1995
- Neural Networks and the Bias/Variance DilemmaNeural Computation, 1992