Using capture-recapture data and hybrid Monte Carlo sampling to estimate an animal population affected by an environmental catastrophe

DOI10.1016/j.csda.2010.06.009zbMath1247.62291OpenAlexW2063279792MaRDI QIDQ452656

Richard M. Huggins, Ning Li, Guoqi Qian

Publication date: 15 September 2012

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2010.06.009

zbMATH Keywords

Gibbs samplerpopulation sizesequential importance samplingacceptance-rejection sampling

Mathematics Subject Classification ID

Applications of statistics to environmental and related topics (62P12) Sampling theory, sample surveys (62D05) Monte Carlo methods (65C05) Numerical analysis or methods applied to Markov chains (65C40)

Uses Software

• BayesDA

Cites Work

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• Embedding population dynamics models in inference
• Bayesian forecasting and dynamic models.
• Inference from iterative simulation using multiple sequences
• On the use of linear models in the estimation of the size of a population using capture-recapture data
• Sequential Monte Carlo Methods in Practice
• ESTIMATION IN RICKER'S TWO-RELEASE METHOD: A BAYESIAN APPROACH
• Dynamic Generalized Linear Models and Bayesian Forecasting
• Posterior Mode Estimation by Extended Kalman Filtering for Multivariate Dynamic Generalized Linear Models
• Monte Carlo maximum likelihood estimation for non-Gaussian state space models
• Sequential Monte Carlo Methods for Dynamic Systems
• Applied Bayesian Modeling and Causal Inference from Incomplete‐Data Perspectives
• Modeling Association among Demographic Parameters in Analysis of Open Population Capture–Recapture Data
• Monte Carlo strategies in scientific computing

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