Designing sampling plans to capture rare objects

DOI10.1002/CJS.10030zbMath1177.62014OpenAlexW2125837536MaRDI QIDQ3645631

Hongmei Zhang

Publication date: 18 November 2009

Published in: Canadian Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1002/cjs.10030

zbMATH Keywords

Markov chain Monte CarlosimulationsMCMCBayesian hierarchical modelspecies problemhypergeometric binomial modelrare categories

Mathematics Subject Classification ID

Point estimation (62F10) Bayesian inference (62F15) Sampling theory, sample surveys (62D05) Monte Carlo methods (65C05)

Related Items (1)

Sampling designs via a multivariate hypergeometric-Dirichlet process model for a multi-species assemblage with unknown heterogeneity

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Inference from iterative simulation using multiple sequences
• Adaptive Cluster Sampling
• Inverse Adaptive Cluster Sampling
• Bayesian Shrinkage Estimation of the Relative Abundance of mRNA Transcripts Using SAGE
• A multinomial Bayesian approach to the estimation of population and vocabulary size
• Methodology for Estimating the Abundance of Rare Animals: Seabird Nesting on North East Herald Cay
• Investigation of a generalized multinomial model for species data
• A Bayesian Formulation of Exploratory Data Analysis and Goodness‐of‐fit Testing*
• Sample size calculation for finding unseen species

This page was built for publication: Designing sampling plans to capture rare objects