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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