Published by the Foundation for Open Access Statistics Editors-in-chief: Bettina Grün, Torsten Hothorn, Edzer Pebesma, Achim Zeileis    ISSN 1548-7660; CODEN JSSOBK
Authors: Lester L. Yuan
Title: Maximum Likelihood Method for Predicting Environmental Conditions from Assemblage Composition: The R Package bio.infer
Abstract: This paper provides a brief introduction to the R package bio.infer, a set of scripts that facilitates the use of maximum likelihood (ML) methods for predicting environmental conditions from assemblage composition. Environmental conditions can often be inferred from only biological data, and these inferences are useful when other sources of data are unavailable. ML prediction methods are statistically rigorous and applicable to a broader set of problems than more commonly used weighted averaging techniques. However, ML methods require a substantially greater investment of time to program algorithms and to perform computations. This package is designed to reduce the effort required to apply ML prediction methods.

Page views:: 6325. Submitted: 2007-01-10. Published: 2007-09-30.
Paper: Maximum Likelihood Method for Predicting Environmental Conditions from Assemblage Composition: The R Package bio.infer     Download PDF (Downloads: 6327)
Supplements:
bio.infer_1.0-4.tar.gz: R source package Download (Downloads: 2557; 1MB)
v22i03.R.zip: v22i03.R: R example code from the paper Download (Downloads: 2214; 1KB)

DOI: 10.18637/jss.v022.i03

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Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license.