Parametric Bootstrap for Estimating Mean Square Error of Proportion in Small Area Estimation

Authors

  • Anggun Permatasari  Department of Statistics, Bogor Agricultural University, Bogor, Indonesia
  • Khairil Anwar Notodiputro  Department of Statistics, Bogor Agricultural University, Bogor, Indonesia
  • Erfiani  Department of Statistics, Bogor Agricultural University, Bogor, Indonesia

DOI:

https://doi.org/10.32628/IJSRSET19613

Keywords:

bootstrap, mean square error, parametric, small area estimation

Abstract

Small area estimation (SAE) is an important alternative method to obtain information in a small area when the sample size is small. In this paper, we proposed a parametric bootstrap method to estimate mean square error (MSE) of proportion based on area unit levels. The purpose of this research has been focused on applying the parametric bootstrap method to estimate MSE in SAE for zero inflated binomial models (SAE ZIB). The results showed that the bootstrap method produced a smaller MSE than the direct estimation, implying that the SAE ZIB performs better when compared to the direct estimation

References

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International Journal of Scientific Research in Science, Engineering and Technology

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Published

2019-01-30

Issue

Volume 6, Issue 2, March-April-2019

Section

Research Articles

License

Copyright (c) IJSRSET

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Anggun Permatasari, Khairil Anwar Notodiputro, Erfiani "Parametric Bootstrap for Estimating Mean Square Error of Proportion in Small Area Estimation" International Journal of Scientific Research in Science, Engineering and Technology (IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 6, Issue 2, pp.311-315, March-April-2019. Available at doi : https://doi.org/10.32628/IJSRSET19613