On Accuracy Estimation Using Parametric Bootstrap in small Area Prediction Problems-Reference-Cited by-同舟云学术

On Accuracy Estimation Using Parametric Bootstrap in small Area Prediction Problems

Published:2020-06-01 Issue:2 Volume:36 Page:435-458
ISSN:2001-7367
Container-title:Journal of Official Statistics
language:en
Short-container-title:

Author:

Żądło Tomasz¹

Affiliation:

1. University of Economics in Katowice , Department of Statistics, Econometrics and Mathematics , 50, 1 Maja Street, 40-287 Katowice , Poland .

Abstract

Abstract We consider longitudinal data and the problem of prediction of subpopulation (domain) characteristics that can be written as a linear combination of the variable of interest, including cases of small or zero sample sizes in the domain and time period of interest. We consider the empirical version of the predictor proposed by Royall (1976) showing that it is a generalization of the empirical version of the predictor presented by Henderson (1950). We propose a parametric bootstrap MSE estimator of the predictor. We prove its asymptotic unbiasedness and derive the order of its bias. Considerations are supported by Monte Carlo simulation analyses to compare its accuracy (not only the bias) with other MSE estimators, including jackknife and weighted jackknife MSE estimators that we adapt for the considered predictor.

Publisher

Walter de Gruyter GmbH

Link

https://www.sciendo.com/pdf/10.2478/jos-2020-0022

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