README.md

In Veliatrimarliana/saeHB.panel: Small Area Estimation using Hierarchical Bayesian Method for Rao Yu Model

saeHB.panel

We designed this package to provide several functions for area level of small area estimation using hierarchical Bayesian (HB) method. This package provides model using Rao-Yu Model for variable interest.This package also provides a dataset produced by a data generation. The “rjags” package is employed to obtain parameter estimates. Model-based estimators involves the HB estimators which include the mean and the variation of mean. For the reference, see Rao and Molina (2015) and Torabi and Shokoohi (2012).

Author

Velia Tri Marliana, Azka Ubaidillah

Maintaner

Velia Tri Marliana [e-mail]

Function

• RaoYuAr1() This function gives estimation of y using Hierarchical Bayesian under Rao Yu Model
• Panel() This function gives estimation of y using Hierarchical Bayesian under Rao Yu Model when rho = 0

Installation

You can install the development version of saeHB.panel from GitHub with:

# install.packages("devtools")
devtools::install_github("Veliatrimarliana/saeHB.panel")

Example

This is a basic example which shows you how to solve a common problem:

library(saeHB.panel)
data(dataAr1)
formula = ydi ~ xdi1 + xdi2
area = max(dataAr1[, "area"])
period = max(dataAr1[,"period"])
vardir = dataAr1[,4]
result <- Raoyu.Ar1(formula, area, period,  vardir = vardir, data = dataAr1)

Extract area mean estimation

result$Est

Extract coefficient estimation

result$coefficient

Extract area random effect variance

result$refVar

References * Rao, J.N.K & Molina. (2015). Small Area Estimation 2nd

Edition. New York: John Wiley and Sons, Inc. * Torabi, M., & Shokoohi, F. (2012). Likelihood inference in small area estimation by combining time-series and cross-sectional data. Journal of Multivariate Analysis, 111, 213–221. https://doi.org/10.1016/j.jmva.2012.05.016

Veliatrimarliana/saeHB.panel documentation built on April 4, 2022, 11:50 a.m.