Mathematical models for non-parametric inferences from line transect data

Biometrics
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Abstract

A general mathematical theory of line transects is developed which supplies a framework for nonparametric density estimation based on either right angle or sighting distances. The probability of observing a point given its right angle distance (y) from the line is generalized to an arbitrary function g(y). Given only that g(0) = 1, it is shown there are nonparametric approaches to density estimation using the observed right angle distances. The model is then generalized to include sighting distances (r). Let f(y I r) be the conditional distribution of right angle distance given sighting distance. It is shown that nonparametric estimation based only on sighting distances requires we know the transformation of r given by f(0 I r).

Additional publication details

Publication type Article
Publication Subtype Journal Article
Title Mathematical models for non-parametric inferences from line transect data
Series title Biometrics
Volume 32
Issue 2
Year Published 1976
Language English
Contributing office(s) Patuxent Wildlife Research Center
Description 325-336
Larger Work Type Article
Larger Work Subtype Journal Article
Larger Work Title Biometrics
First page 325
Last page 336