saeHB.spatial: saeHB.spatial : Small Area Estimation Hierarchical Bayes For...

In saeHB.spatial: Small Area Estimation Hierarchical Bayes For Spatial Model

saeHB.spatial : Small Area Estimation Hierarchical Bayes For Spatial Model

Description

Provides several functions and datasets for area level of Small Area Estimation under Spatial Model using Hierarchical Bayesian (HB) Method. Model-based estimators include the HB estimators based on a Spatial Fay-Herriot model with univariate normal distribution for variable of interest.The 'rjags' package is employed to obtain parameter estimates. For the reference, see Rao and Molina (2015) <doi:10.1002/9781118735855>.

Author(s)

Arina Mana Sikana, Azka Ubaidillah

Maintaner: Arina Mana Sikana [e-mail]

Functions

sar.normal

This function gives small area estimator under Spatial SAR Model and is implemented to variable of interest (y) that assumed to be a Normal Distribution. The range of data is (-\infty < y < \infty)

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Reference

• Rao, J.N.K & Molina. (2015). Small Area Estimation 2nd Edition. New Jersey: John Wiley and Sons, Inc. <doi:10.1002/9781118735855>.

• J. Kubacki and A. Jedrzejczak. (2016). Small Area Estimation of Income Under Spatial SAR Model. Statistics in Transition New Series, Vol. 17, No. 3, pp. 365–390. <doi: 10.21307/stattrans-2016-028>.

• H. C. Chung and G. S. Datta. (2020). Bayesian Hierarchical Spatial Models for Small Area Estimation. Research Report Series. Washington, D.C.: U.S. Census Bureau.

saeHB.spatial documentation built on April 3, 2025, 10:31 p.m.