1991BiometricsRequires access

Some Practical Aspects of a Conditional Likelihood Approach to Capture Experiments

Richard Huggins

Open publisher page 504 citations

Abstract

The use of conditional likelihood methods in the analysis of capture data allows the modeling of capture probabilities in terms of observable characteristics of the captured individuals and the trapping occasions. The resulting models may then be used to estimate the size of the population. Here the use of conditional likelihood procedures to construct models for capture probabilities is discussed and illustrated by an example.

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The use of conditional likelihood methods in the analysis of capture data allows the modeling of capture probabilities in terms of observable characteristics of the captured individuals and the trapping occasions. The resulting models may then be used to estimate the size of the population. Here the use of conditional likelihood procedures to construct models for capture probabilities is discussed and illustrated by an example.

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Available abstract

The use of conditional likelihood methods in the analysis of capture data allows the modeling of capture probabilities in terms of observable characteristics of the captured individuals and the trapping occasions. The resulting models may then be used to estimate the size of the population. Here the use of conditional likelihood procedures to construct models for capture probabilities is discussed and illustrated by an example.

Key concepts: Maximum likelihood, Computer science, Conditional probability, Construct (python library), Econometrics, Statistics, Population, Conditional probability distribution

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