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Variance estimation using auxiliary information: An almost unbiased multivariate ratio estimator

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Abstract

The goal of this paper is to investigate the repeated substitution method (seeSrivastava, 1967) estimating population variance in finite population sample surveys. We propose an almost unbiased multivariate ratio estimator that has a smaller mean squared error than the conventional biased multivariate ratio estimator (established byIsaki (1983)) and with the same precision as the multivariate regression estimator. Furthermore, it is a computationally much more interesting estimator since to compute it we only need to have knowledge of correlation among available variables, which it is common to have in several practical situations. A comparison of the multivariate ratio estimator proposed and the multivariate regression estimator is given.

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Authors and Affiliations

  1. Departamento de Estadística e Investigación Operativa, Facultad de Ciencias, Campus de Fuentenueva, 18071, Granada, España

    A. Arcos Cebrián & M. Rueda García

Authors
  1. A. Arcos Cebrián
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  2. M. Rueda García
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Cebrián, A.A., García, M.R. Variance estimation using auxiliary information: An almost unbiased multivariate ratio estimator. Metrika 45, 171–178 (1997). https://doi.org/10.1007/BF02717100

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  • DOI: https://doi.org/10.1007/BF02717100

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