e-space
Manchester Metropolitan University's Research Repository

    Evaluations of small area composite estimators based on the iterative proportional fitting algorithm

    Moretti, A ORCID logoORCID: https://orcid.org/0000-0001-6543-9418 and Whitworth, A (2020) Evaluations of small area composite estimators based on the iterative proportional fitting algorithm. Communications in Statistics: Simulation and Computation, 49 (12). pp. 3093-3110. ISSN 0361-0918

    [img]
    Preview
    Accepted Version
    Download (1MB) | Preview

    Abstract

    © 2019, © 2019 Taylor & Francis Group, LLC. 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.

    Impact and Reach

    Statistics

    Activity Overview
    6 month trend
    303Downloads
    6 month trend
    137Hits

    Additional statistics for this dataset are available via IRStats2.

    Altmetric

    Repository staff only

    Edit record Edit record