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Distance sampling in R
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dc.contributor.author | Miller, David L. | |
dc.contributor.author | Rexstad, Eric | |
dc.contributor.author | Thomas, Len | |
dc.contributor.author | Marshall, Laura | |
dc.contributor.author | Laake, Jeffrey L. | |
dc.date.accessioned | 2019-06-07T15:30:01Z | |
dc.date.available | 2019-06-07T15:30:01Z | |
dc.date.issued | 2019-05-09 | |
dc.identifier.citation | Miller , D L , Rexstad , E , Thomas , L , Marshall , L & Laake , J L 2019 , ' Distance sampling in R ' , Journal of Statistical Software , vol. 89 , no. 1 . https://doi.org/10.18637/jss.v089.i01 | en |
dc.identifier.issn | 1548-7660 | |
dc.identifier.other | PURE: 250727367 | |
dc.identifier.other | PURE UUID: d2d46816-2304-400d-9ac6-8d06c7982666 | |
dc.identifier.other | WOS: 000468776100001 | |
dc.identifier.other | WOS: 000468776100001 | |
dc.identifier.other | ORCID: /0000-0002-7436-067X/work/58285426 | |
dc.identifier.other | ORCID: /0000-0002-4323-8161/work/58285427 | |
dc.identifier.other | Scopus: 85068356686 | |
dc.identifier.uri | https://hdl.handle.net/10023/17847 | |
dc.description.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. | |
dc.format.extent | 28 | |
dc.language.iso | eng | |
dc.relation.ispartof | Journal of Statistical Software | en |
dc.rights | Copyright 2019 the Authors. This work is licensed under the licenses Paper: Creative Commons Attribution 3.0 Unported License | en |
dc.subject | Distance sampling | en |
dc.subject | Abundance estimation | en |
dc.subject | Line transect | en |
dc.subject | Point transect | en |
dc.subject | Detection function | en |
dc.subject | Horvitz-Thompson | en |
dc.subject | R | en |
dc.subject | Distance | en |
dc.subject | QA75 Electronic computers. Computer science | en |
dc.subject | QH301 Biology | en |
dc.subject | DAS | en |
dc.subject.lcc | QA75 | en |
dc.subject.lcc | QH301 | en |
dc.title | Distance sampling in R | en |
dc.type | Journal article | en |
dc.description.version | Publisher PDF | en |
dc.contributor.institution | University of St Andrews. School of Mathematics and Statistics | en |
dc.contributor.institution | University of St Andrews. Applied Mathematics | en |
dc.contributor.institution | University of St Andrews. Centre for Research into Ecological & Environmental Modelling | en |
dc.contributor.institution | University of St Andrews. Scottish Oceans Institute | en |
dc.contributor.institution | University of St Andrews. Statistics | en |
dc.contributor.institution | University of St Andrews. Marine Alliance for Science & Technology Scotland | en |
dc.identifier.doi | https://doi.org/10.18637/jss.v089.i01 | |
dc.description.status | Peer reviewed | en |
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