Evaluations of small area composite estimators based on the iterative proportional fitting algorithm
Moretti, Angelo and Whitworth, Adam (2020) Evaluations of small area composite estimators based on the iterative proportional fitting algorithm. Communications in Statistics - Simulation and Computation, 49 (12). p. 3093. ISSN 0361-0918 (https://doi.org/10.1080/03610918.2018.1535067)
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Abstract
This article deals with the use of sample size dependent composite estimators in spatial microsimulation approaches for small area estimation. This approach has been applied to regression-based small area estimation approaches but never to our knowledge to spatial microsimulation approaches. In this paper, we extend the iterative proportional fitting (IPF) spatial microsimulation technique to small area composite estimators. Using a simulation study, we show both the impact of sample size and the gains from composite estimation to the mean squared error of IPF-based composite estimators. The target variable used is a binary variable reporting good health or bad health.
ORCID iDs
Moretti, Angelo and Whitworth, Adam ORCID: https://orcid.org/0000-0001-6119-9373;-
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Item type: Article ID code: 78235 Dates: DateEvent2020Published21 January 2019Published Online8 October 2018AcceptedSubjects: Science > Mathematics > Probabilities. Mathematical statistics
Geography. Anthropology. RecreationDepartment: Strathclyde Business School > Work, Organisation and Employment Depositing user: Pure Administrator Date deposited: 21 Oct 2021 10:30 Last modified: 11 Nov 2024 13:16 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/78235