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msaeDB

Implements Benchmarking Method for Multivariate Small Area Estimation under Fay Herriot Model. Multivariate Small Area Estimation (MSAE) is a development of Univariate Small Area Estimation that considering the correlation among response variables and borrowing the strength from related areas and auxiliary variables to increase the effectiveness of sample size, the multivariate model in this package is based on multivariate model 1 proposed by Roberto Benavent and Domingo Morales (2015). Benchmarking in Small Area Estimation is a modification of Small Area Estimation model to guarantee that the aggregate weighted mean of the county predictors equals the corresponding weighted mean of survey estimates. Difference Benchmarking is the simplest benchmarking method but widely used by multiplying empirical best linear unbiased prediction (EBLUP) estimator by the common adjustment factors (J.N.K Rao and Isabel Molina, 2015).

Authors

Zaza Yuda Perwira, Azka Ubaidillah

Maintainer

Zaza Yuda Perwira 221710086@stis.ac.id

Functions

  • msaedb() Produces EBLUPs, MSE, and Aggregation of Multivariate SAE with Difference Benchmarking
  • saedb() Produces EBLUPs, MSE, and Aggregation of Univariate SAE with Difference Benchmarking
  • msaefh() Produces EBLUPs and MSE of Multivariate SAE
  • saefh() Produces EBLUPs and MSE of Univariate SAE

References

  • Benavent, Roberto & Morales, Domingo. (2015). Multivariate Fay-Herriot models for small area estimation. Computational Statistics and Data Analysis 94 2016 372-390. DOI: 10.1016/j.csda.2015.07.013.
  • Rao, J.N.K & Molina. (2015). Small Area Estimation 2nd Edition. New York: John Wiley and Sons, Inc.
  • Steorts, Rebecca & Ghosh, Malay. (2013). On estimation of mean square Errors of Benchmarked Empirical Bayes Estimators. Article in Statistics Sinica April 2013. DOI: 10.5705/ss.2012.053.
  • Ubaidillah, Azka et al. (2019). Multivariate Fay-Herriot models for small area estimation with application to household consumption per capita expenditure in Indonesia. Journal of Applied Statistics. 46:15. 2845-2861. DOI: 10.1080/02664763.2019.1615420.
  • Permatasari, Novia. (2020). Pembangunan paket R pada model Fay Herriot multivariat untuk pendugaan area kecil (Bachelor Thesis). Jakarta: Polytechnic Statistics of STIS

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Version

Install

install.packages('msaeDB')

Monthly Downloads

38

Version

0.2.1

License

GPL-3

Issues

Pull Requests

Stars

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Maintainer

Zaza Perwira

Last Published

April 8th, 2021

Functions in msaeDB (0.2.1)

saedb

EBLUPs under Univariate Fay Herriot Model with Difference Benchmarking
saefh

EBLUPs under Univariate Fay Herriot Model
msaedb

EBLUPs under Multivariate Fay Herriot Model with Difference Benchmarking
datamsaeDB

Sample Data for Multivariate Small Area Estimation with Difference Benchmarking
msaefh

EBLUPs under Multivariate Fay Herriot Model
saefhns

EBLUPs under Univariate Fay Herriot Model for non-sampled area
saedbns

EBLUPs under Univariate Fay Herriot Model with Difference Benchmarking for non-sampled area
msaedbns

EBLUPs under Multivariate Fay Herriot Model with Difference Benchmarking for non-sampled area
msaefhns

EBLUPs under Multivariate Fay Herriot Model for non-sampled area
datamsaeDBns

Sample Data for Multivariate Small Area Estimation with Difference Benchmarking with clustering