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Point and interval estimates of abundance using multiple covariate distance sampling: an example using great bustards.

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dc.contributor.authorRexstad, Eric
dc.coverage.spatial14 p.en
dc.date.accessioned2009-01-12T17:23:39Z
dc.date.available2009-01-12T17:23:39Z
dc.date.issued2007
dc.identifier.citationCREEM technical report ; 2007-02en
dc.identifier.urihttps://hdl.handle.net/10023/629
dc.descriptionPreviously in the University eprints HAIRST pilot service at http://eprints.st-andrews.ac.uk/archive/00000447/en
dc.descriptionThe pdf file contains the tech report, the ASCII (.R) file contains the accompanying R code.en
dc.description.abstractDescription of computations to produce sex-specific estimates of density from a multiple-covariate distance sampling analysis. Program Distance 5.0 has limited capacity to bootstrap certain types of analytical situations (e.g., cluster size as a covariate). Herein I describe steps and code to perform an analysis of this sort. Possible ways to adapt this code for similar analyses are described.en
dc.format.extent22458 bytes
dc.format.extent220717 bytes
dc.format.mimetypeapplication/octet-stream
dc.format.mimetypeapplication/pdf
dc.language.isoenen
dc.publisherCREEM, University of St Andrewsen
dc.subjectmultiple covariate distance samplingen
dc.subjectbootstrapen
dc.subjectprogram Distanceen
dc.subjectestimation of population sizeen
dc.subjectdensityen
dc.subject.lccQAen
dc.subject.lccQHen
dc.subject.lccQLen
dc.titlePoint and interval estimates of abundance using multiple covariate distance sampling: an example using great bustards.en
dc.typeReporten
dc.description.versionhttps://doi.org/Postprinten
dc.publicationstatusNot publisheden
dc.statusNon peer revieweden


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