Mathematical models for nonparametric inferences from line transect data
A general mathematical theory of line transects is develoepd 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(O) = 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/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(O/r).
Citation Information
| Publication Year | 1976 |
|---|---|
| Title | Mathematical models for nonparametric inferences from line transect data |
| DOI | 10.2307/2529501 |
| Authors | K.P. Burnham, David R. Anderson |
| Publication Type | Article |
| Publication Subtype | Journal Article |
| Series Title | Biometrics |
| Index ID | 70119552 |
| Record Source | USGS Publications Warehouse |