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Interval estimation for mark-recapture studies of closed populations
1Department of Mathematical and Computational Sciences, University of St Andrews, Fife, Scotland.
Biometrics
|June 1, 1992
Summary
A new likelihood interval approach offers a better way to estimate population size (N) in mark-recapture studies, moving beyond traditional asymptotic normal distribution methods for more accurate results.
Area of Science:
- Statistics
- Ecology
- Population Dynamics
Background:
- Traditional methods for estimating population size (N) in mark-recapture studies rely on asymptotic normal distributions.
- These textbook recommendations may not always provide the most accurate interval estimates for unknown population sizes.
Purpose of the Study:
- To propose and demonstrate a novel likelihood interval approach for estimating population size (N).
- To offer an alternative to the commonly recommended asymptotic normal distribution method.
Main Methods:
- The study implements a likelihood interval approach.
- This method is applied to various models used in mark-recapture experiments and multiple-record systems.
- It includes models for incomplete contingency tables with main effects and interactions.
Main Results:
- The likelihood interval approach provides a robust method for estimating population size (N).
- Demonstrated implementation across diverse mark-recapture and multiple-record system models.
Conclusions:
- The proposed likelihood interval approach is a valuable alternative for population size estimation.
- This method enhances the accuracy of interval estimates in ecological and statistical studies.