Package: saeHB.panel 0.1.1

Velia Tri Marliana

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

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 panel data 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).

Authors:Velia Tri Marliana [aut, cre], Azka Ubaidillah [aut]

saeHB.panel_0.1.1.tar.gz
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saeHB.panel.pdf |saeHB.panel.html✨
saeHB.panel/json (API)

# Install 'saeHB.panel' in R:
install.packages('saeHB.panel', repos = 'https://cloud.r-project.org')

Bug tracker:https://github.com/veliatrimarliana/saehb.panel/issues0 issues

Uses libs:
  • jags– Just Another Gibbs Sampler for Bayesian MCMC
  • c++– GNU Standard C++ Library v3
Datasets:
  • dataAr1 - Sample Data for Small Area Estimation using Hierarchical Bayesian Method for Rao Yu Model
  • dataAr1Ns - Sample Data for Small Area Estimation using Hierarchical Bayesian Method for Rao Yu Model with Non Sampled Area
  • dataPanel - Sample Data for Small Area Estimation using Hierarchical Bayesian Method for Rao Yu Model when 'rho = 0'
  • dataPanelNs - Sample Data for Small Area Estimation using Hierarchical Bayesian Method for Rao Yu Model when 'rho = 0' with Non Sampled Area

On CRAN:

Conda:

jagscpp

2.70 score 187 downloads 2 exports 11 dependencies

Last updated 3 years agofrom:70a7b90b0f. Checks:3 OK. Indexed: no.

TargetResultLatest binary
Doc / VignettesOKMar 17 2025
R-4.5-linuxOKMar 17 2025
R-4.4-linuxOKMar 17 2025

Exports:PanelRaoYuAr1

Dependencies:clicodagluelatticelifecyclemagrittrrjagsrlangstringistringrvctrs

An Application to HB Rao yu Model On sampel dataset

Rendered fromPanel.Rmdusingknitr::rmarkdownon Mar 17 2025.

Last update: 2022-05-10
Started: 2022-03-03

Citation

To cite package ‘saeHB.panel’ in publications use:

Marliana VT, Ubaidillah A (2022). saeHB.panel: Small Area Estimation using Hierarchical Bayesian Method for Rao Yu Model. R package version 0.1.1, https://CRAN.R-project.org/package=saeHB.panel.

ATTENTION: This citation information has been auto-generated from the package DESCRIPTION file and may need manual editing, see ‘help("citation")’.

Corresponding BibTeX entry: 

  @Manual{,
    title = {saeHB.panel: Small Area Estimation using Hierarchical
      Bayesian Method for Rao Yu Model},
    author = {Velia Tri Marliana and Azka Ubaidillah},
    year = {2022},
    note = {R package version 0.1.1},
    url = {https://CRAN.R-project.org/package=saeHB.panel},
  }

Readme and manuals

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 221810642@stis.ac.id

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