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: Ian Fiske, Richard Chandler
Title: unmarked: An R Package for Fitting Hierarchical Models of Wildlife Occurrence and Abundance
Abstract: Ecological research uses data collection techniques that are prone to substantial and unique types of measurement error to address scientific questions about species abundance and distribution. These data collection schemes include a number of survey methods in which unmarked individuals are counted, or determined to be present, at spatially- referenced sites. Examples include site occupancy sampling, repeated counts, distance sampling, removal sampling, and double observer sampling. To appropriately analyze these data, hierarchical models have been developed to separately model explanatory variables of both a latent abundance or occurrence process and a conditional detection process. Because these models have a straightforward interpretation paralleling mechanisms under which the data arose, they have recently gained immense popularity. The common hierarchical structure of these models is well-suited for a unified modeling interface. The R package unmarked provides such a unified modeling framework, including tools for data exploration, model fitting, model criticism, post-hoc analysis, and model comparison.

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Paper: unmarked: An R Package for Fitting Hierarchical Models of Wildlife Occurrence and Abundance     Download PDF (Downloads: 17245)
unmarked_0.9-2.tar.gz: unmarked_0.9-0.tar.gz: R source package Download (Downloads: 857; 700KB)
v43i10.R: R example code from the paper Download (Downloads: 1013; 4KB)

DOI: 10.18637/jss.v043.i10

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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.