N-mixture models with auxiliary populations and for large population abundances

Simple item page
dc.contributor.authorParker, Matthew R. P.
dc.contributor.supervisorCowen, Laura Louise Elizabeth
dc.date.accessioned2020-04-30T04:20:20Z
dc.date.available2020-04-30T04:20:20Z
dc.date.copyright2020en_US
dc.date.issued2020-04-29
dc.degree.departmentDepartment of Mathematics and Statistics
dc.degree.levelMaster of Science M.Sc.en_US
dc.description.abstractThe key results of this thesis are (1) an extension of N-mixture models to incorporate the additional layer of obfuscation brought by observing counts from a related auxiliary population (rather than the target population), (2) an extension of N-mixture models to allow for grouped counts, the purpose being two-fold: to extend the applicability of N-mixtures to larger population sizes, and to allow for the use of coarse counts in fitting N-mixture models, (3) a new R package allowing the easy application of the new N-mixture models, (4) a new R package allowing for optimization of multi-parameter functions using arbitrary precision arithmetic, which was a necessary tool for optimization of the likelihood in large population abundance N-mixture models, as well as (5) simulation studies validating the new grouped count models and comparing them to the classic N-mixtures models.en_US
dc.description.scholarlevelGraduateen_US
dc.identifier.urihttp://hdl.handle.net/1828/11702
dc.languageEnglisheng
dc.language.isoenen_US
dc.rightsAvailable to the World Wide Weben_US
dc.subjectN-mixturesen_US
dc.subjectgrouped countsen_US
dc.subjectcoarse countsen_US
dc.subjectmaximum likelihooden_US
dc.titleN-mixture models with auxiliary populations and for large population abundancesen_US
dc.typeThesisen_US

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Parker_Matthew_MSc_2020.pdf
Size:
3.3 MB
Format:
Adobe Portable Document Format
Description:
Main article
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections

Electronic Theses and Dissertations (ETD)
 
University of Victoria Libraries

We acknowledge and respect the Lək̓ʷəŋən (Songhees and Esquimalt) Peoples on whose territory the university stands, and the Lək̓ʷəŋən and W̱SÁNEĆ Peoples whose historical relationships with the land continue to this day.