Estimation of the population size by using the one-inflated positive Poisson model
Estimation of the population size by using the one-inflated positive Poisson model
In population size estimation, many capture–recapture-type data exhibit a preponderance of ‘1’-counts. This excess of 1s can arise as subjects gain information from the initial capture that provides a desire and ability to avoid subsequent captures. Existing population size estimators that purport to deal with heterogeneity can be much too large in the presence of 1-inflation, which is a specific form of heterogeneity. To deal with the phenomena of excess 1s, we propose the one-inflated positive Poisson model for use as the truncated count distribution in Horvitz–Thompson estimation of the population size.
425-448
Godwin, Ryan T.
32582d16-e4b0-46ff-9eeb-33804261af05
Böhning, Dankmar
1df635d4-e3dc-44d0-b61d-5fd11f6434e1
February 2017
Godwin, Ryan T.
32582d16-e4b0-46ff-9eeb-33804261af05
Böhning, Dankmar
1df635d4-e3dc-44d0-b61d-5fd11f6434e1
Godwin, Ryan T. and Böhning, Dankmar
(2017)
Estimation of the population size by using the one-inflated positive Poisson model.
Journal of the Royal Statistical Society, Series C (Applied Statistics), 66 (2), .
(doi:10.1111/rssc.12192).
Abstract
In population size estimation, many capture–recapture-type data exhibit a preponderance of ‘1’-counts. This excess of 1s can arise as subjects gain information from the initial capture that provides a desire and ability to avoid subsequent captures. Existing population size estimators that purport to deal with heterogeneity can be much too large in the presence of 1-inflation, which is a specific form of heterogeneity. To deal with the phenomena of excess 1s, we propose the one-inflated positive Poisson model for use as the truncated count distribution in Horvitz–Thompson estimation of the population size.
Text
JRSSC2017.pdf
- Accepted Manuscript
More information
Accepted/In Press date: 30 August 2016
e-pub ahead of print date: 2 November 2016
Published date: February 2017
Organisations:
Statistics, Statistical Sciences Research Institute
Identifiers
Local EPrints ID: 404678
URI: http://eprints.soton.ac.uk/id/eprint/404678
ISSN: 0035-9254
PURE UUID: 344fb2ff-72cb-4784-8b47-95a2111f414c
Catalogue record
Date deposited: 19 Jan 2017 16:07
Last modified: 16 Mar 2024 04:07
Export record
Altmetrics
Contributors
Author:
Ryan T. Godwin
Download statistics
Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.
View more statistics
