msaeRB

Implements multivariate ratio benchmarking small area estimation. This package provides ratio benchmarking estimation for univariate and multivariate small area estimation and its MSE. In fact, MSE estimators for ratio benchmark are not readily available, so resampling method that called parametric bootstrap is applied. The ratio benchmark model and parametric bootstrap in this package are based on the model proposed in small area estimation (J.N.K Rao and Isabel Molina, 2015).

Installation

You can install the released version of msaeRB from CRAN with:

install.packages("msaeRB")

Atuhors

Zenda Oka Briantiko, Azka Ubaidillah

Maintainer

Zenda Oka Briantiko 221710087@stis.ac.id

Functions

• est_saeRB : Produces EBLUPs Ratio Benchmarking based on a Univariate Fay-Herriot (Model 1)
• mse_saeRB : Parametric Bootstrap Mean Squared Error Estimators of Ratio Benchmarking for Univariate Small Area Estimation
• est_msaeRB : Produces EBLUPs Ratio Benchmarking based on a Multivariate Fay-Herriot (Model 1)
• mse_msaeRB : Parametric Bootstrap Mean Squared Error Estimators of Ratio Benchmarking for Multivariate Small Area Estimation

References

• Rao, J.N.K & Molina. (2015). Small Area Estimation 2nd Edition. New York: John Wiley and Sons, Inc.
• 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.
• 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.
• Wang, J., Fuller, W.A., and Qu, Y. (2008). Small Area Estimation Under Restriction. Survey Methodology. 34. 29–36.
• Krzciuk, M. K. (2018). On the Simulation Study of Jackknife and Bootstrap MSE Estimators of a Domain Mean Predictor for Fay‑Herriot Model. Acta Universitatis Lodziensis. Folia Oeconomica, 5(331), 169-183.