Optimum nonparametric estimation of population density based on ordered distances

Biometrics
By: , and 

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Abstract

The asymptotic mean and error mean square are determined for the nonparametric estimator of plant density by distance sampling proposed by Patil, Burnham and Kovner (1979, Biometrics 35, 597-604. On the basis of these formulae, a bias-reduced version of this estimator is given, and its specific form is determined which gives minimum mean square error under varying assumptions about the true probability density function of the sampled data. Extension is given to line-transect sampling.
Publication type Article
Publication Subtype Journal Article
Title Optimum nonparametric estimation of population density based on ordered distances
Series title Biometrics
DOI 10.2307/2530307
Volume 38
Issue 1
Year Published 1982
Language English
Publisher International Biometric Society
Publisher location Washington, D.C.
Description 6 p.
Larger Work Type Article
Larger Work Subtype Journal Article
Larger Work Title Biometrics
First page 243
Last page 248
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