A Bayesian benchmarking of the Scott–Smith model for small areas

DOI10.1080/00949655.2010.496726zbMath1431.62039OpenAlexW2058183844MaRDI QIDQ5300756

Balgobin Nandram, Jai Won Choi, Ma. Criselda S. Toto

Publication date: 28 June 2013

Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00949655.2010.496726

zbMATH Keywords

random samplesposterior proprietyfinite population meanmultivariate normal densitymultiplication rule of probability

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Bayesian inference (62F15) Sampling theory, sample surveys (62D05)

Related Items (4)

Benchmarking techniques for reconciling Bayesian small area models at distinct geographic levels ⋮ Bayesian predictive inference under a Dirichlet process with sensitivity to the normal baseline ⋮ A Bayesian predictive inference for small area means incorporating covariates and sampling weights ⋮ A nonparametric Bayesian prediction interval for a finite population mean

Cites Work

• Small area estimation using unmatched sampling and linking models
• Bench-Marking Time Series with Reliable Bench-Marks
• Benchmarking of Economic Time Series
• Estimation in Covariance Components Models
• Bayesian Predictive Inference for Longitudinal Sample Surveys
• The Estimation of the Mean Squared Error of Small-Area Estimators
• Forecasting Cause-Age Specific Mortality Using Two Random Processes

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