Prediction Error of Small Area Predictors Shrinking Both Means and Variances Academic Article uri icon

abstract

  • The article considers a new approach for small area estimation based on a joint modelling of mean and variances. Model parameters are estimated via expectation-maximization algorithm. The conditional mean squared error is used to evaluate the prediction error. Analytical expressions are obtained for the conditional mean squared error and its estimator. Our approximations are second-order correct, an unwritten standardization in the small area literature. Simulation studies indicate that the proposed method outperforms the existing methods in terms of prediction errors and their estimated values. 2014 Board of the Foundation of the Scandinavian Journal of Statistics.

published proceedings

  • SCANDINAVIAN JOURNAL OF STATISTICS

altmetric score

  • 1

author list (cited authors)

  • Maiti, T., Ren, H., & Sinha, S.

citation count

  • 29

complete list of authors

  • Maiti, Tapabrata||Ren, Hao||Sinha, Samiran

publication date

  • September 2014

publisher