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USGS · 5220997

Mathematical models for non-parametric inferences from line transect data

K.P. Burnham·David R. Anderson
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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).

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BibTeXRIS

K.P. Burnham, David R. Anderson. 1976. Mathematical models for non-parametric inferences from line transect data. https://doi.org/10.2307/2529501

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