alj1983/MaxentVariableSelection: Selecting the Best Set of Relevant Environmental Variables along with the Optimal Regularization Multiplier for Maxent Niche Modeling

Complex niche models show low performance in identifying the most important range-limiting environmental variables and in transferring habitat suitability to novel environmental conditions (Warren and Seifert, 2011 <DOI:10.1890/10-1171.1>; Warren et al., 2014 <DOI:10.1111/ddi.12160>). This package helps to identify the most important set of uncorrelated variables and to fine-tune Maxent's regularization multiplier. In combination, this allows to constrain complexity and increase performance of Maxent niche models (assessed by information criteria, such as AICc (Akaike, 1974 <DOI:10.1109/TAC.1974.1100705>), and by the area under the receiver operating characteristic (AUC) (Fielding and Bell, 1997 <DOI:10.1017/S0376892997000088>). Users of this package should be familiar with Maxent niche modelling.

Getting started

Package details

AuthorAlexander Jueterbock
Maintainer"Alexander Jueterbock" <Alexander-Jueterbock@web.de>
LicenseGPL (>= 2)
Version1.0-3
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("remotes")
remotes::install_github("alj1983/MaxentVariableSelection")
alj1983/MaxentVariableSelection documentation built on May 10, 2019, 9:17 a.m.