In arinams/spatial: Small Area Estimation under Spatial SAR Model using Hierarchical Bayesian Method

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saeHB.spatial

Provides several functions and datasets for area level of Small Area Estimation under Spatial SAR Model using Hierarchical Bayesian (HB) Method. For the reference, see Rao and Molina (2015) .

Author

Arina Mana Sikana, Azka Ubaidillah

Maintaner

Arina Mana Sikana [e-mail]

Function

• spatial.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 (-∞ < y < ∞)

Installation

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

# install.packages("devtools")
devtools::install_github("arinams/saeHB.spatial")

Example

This is a basic example of using spatial.normal() function to make an estimate based on synthetic data in this package

library(saeHB.twofold)

## For data without any non-sampled area
data(sp.norm)       # Load dataset
data(prox.mat)      # Load proximity Matrix

## For data with non-sampled area use sp.normNs

## Fitting model
result <- spatial.normal(y ~ x1 + x2, "vardir", prox.mat, data = sp.norm)

Small Area mean Estimates

result$Est

Estimated model coefficient

result$coefficient

Estimated random effect variances

result$refVar

References

Rao, J.N.K & Molina. (2015). Small Area Estimation 2nd Edition. New York: John Wiley and Sons, Inc. .

arinams/spatial documentation built on Feb. 14, 2022, 12:44 a.m.