Distance sampling in R

David L. Miller; Eric Rexstad; Len Thomas; Laura Marshall; Jeffrey L. Laake

doi:10.18637/jss.v089.i01

Distance sampling in R

David L. Miller^*, Eric Rexstad, Len Thomas, Laura Marshall, Jeffrey L. Laake

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

Abstract

Estimating the abundance and spatial distribution of animal and plant populations is essential for conservation and management. We introduce the R package Distance that implements distance sampling methods to estimate abundance. We describe how users can obtain estimates of abundance (and density) using the package as well as documenting the links it provides with other more specialized R packages. We also demonstrate how Distance provides a migration pathway from previous software, thereby allowing us to deliver cutting-edge methods to the users more quickly.

Original language	English
Number of pages	28
Journal	Journal of Statistical Software
Volume	89
Issue number	1
DOIs	https://doi.org/10.18637/jss.v089.i01
Publication status	Published - 9 May 2019

Keywords

Distance sampling
Abundance estimation
Line transect
Point transect
Detection function
Horvitz-Thompson
R
Distance

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10.18637/jss.v089.i01Licence: CC BY

Miller-2019-Distance-sampling-R-JSS-CC
Copyright 2019 the Authors. This work is licensed under the licenses Paper: Creative Commons Attribution 3.0 Unported License
Final published version, 571 KBLicence: CC BY

Cite this

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AU - Laake, Jeffrey L.

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KW - Abundance estimation

KW - Line transect

KW - Point transect

KW - Detection function

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KW - Distance

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VL - 89

JO - Journal of Statistical Software

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Distance sampling in R

Abstract

Keywords

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