Estimation of the Size of an Open Population from Capture‐Recapture Data Using Weighted Martingale Methods
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Publication:4666575
DOI10.1111/j.0006-341X.1999.00387.xzbMath1059.62660OpenAlexW1995751609WikidataQ30650122 ScholiaQ30650122MaRDI QIDQ4666575
Paul S. F. Yip, Richard M. Huggins
Publication date: 13 April 2005
Published in: Biometrics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1111/j.0006-341x.1999.00387.x
Asymptotic properties of nonparametric inference (62G20) Applications of statistics to biology and medical sciences; meta analysis (62P10) Sampling theory, sample surveys (62D05)
Related Items (11)
Population size estimation using local sample coverage for open populations. ⋮ Capture-Recapture Experiments with Time Heterogeneous Capture Probabilities in Continuous Time: A Counting Process Approach ⋮ Estimating the size of an open population with massive datasets based on a generalized varying-coefficient model ⋮ Semivarying coefficient models for capture-recapture data: colony size estimation for the little penguin \(Eudyptula minor\) ⋮ Some properties of a nonparametric estimator of the size of an open population ⋮ Estimating population size of heterogeneous populations with large data sets and a large number of parameters ⋮ NONPARAMETRIC METHOD FOR ESTIMATING THE SIZE OF AN OPEN POPULATION USING MARGINAL DATA FROM REPEATED MULTIPLE LISTS ⋮ Estimation of the Size of an Open Population Using Local Estimating Equations II: A Partially Parametric Approach ⋮ Semiparametric inference for open populations using the Jolly–Seber model: a penalized spline approach ⋮ Estimating the size of an open population using sparse capture-recapture data ⋮ Semiparametric Estimation of Animal Abundance Using Capture-Recapture Data from Open Populations
Cites Work
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- The Kernel Estimate of a Regression Function in Likelihood-Based Models
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