saeHB.Spatial.Beta-package: saeHB.Spatial.Beta : Small Area Estimation Hierarchical Bayes...
In saeHB.Spatial.Beta: Small Area Estimation Hierarchical Bayes for Spatial Beta Model
saeHB.Spatial.Beta-package R Documentation
saeHB.Spatial.Beta : Small Area Estimation Hierarchical Bayes for Spatial Beta Model
Description
Provides several functions and datasets for area-level Small Area Estimation using the Hierarchical Bayesian (HB) method.
Model-based estimators are designed for variables of interest that follow a Beta distribution (proportions bounded between 0 and 1).
The package supports spatial structures under the Simultaneous Autoregressive (SAR) model and the Leroux Conditional Autoregressive (CAR) model.
It also accommodates survey design effect (DEFF) adjustments to handle complex survey data. The rjags package is employed to obtain parameter estimates via Markov Chain Monte Carlo (MCMC).
Author(s)
Boby Iwan, Cucu Sumarni
Maintainer: Boby Iwan bobyiwanboby2122@gmail.com
Functions
betadeff_sarEstimates small area means using Spatial SAR Model with Beta distribution and Design Effect (DEFF) adjustments.
beta_sarEstimates small area means using Spatial SAR Model with Beta distribution without DEFF adjustments (estimates a global precision parameter).
betadeff_lerouxcarEstimates small area means using Spatial Leroux CAR Model with Beta distribution and Design Effect (DEFF) adjustments.
beta_lerouxcarEstimates small area means using Spatial Leroux CAR Model with Beta distribution without DEFF adjustments.
betadeff_nonspatialEstimates small area means using a Non-Spatial Beta Model with Independent and Identically Distributed (IID) random effects and DEFF adjustments.
beta_nonspatialEstimates small area means using a Non-Spatial Beta Model without DEFF adjustments.
build_wA utility function to construct spatial weights matrices (contiguity, distance, or kernel) required for spatial modeling.
moran_testA diagnostic function to perform Moran's I test for spatial autocorrelation.
Reference
Rao, J. N. K., & Molina, I. (2015). Small Area Estimation (2nd Edition). New Jersey: John Wiley and Sons, Inc. <doi:10.1002/9781118735855>.
Kubacki, J., & Jedrzejczak, A. (2016). Small Area Estimation of Income Under Spatial SAR Model. Statistics in Transition New Series, Vol. 17, No. 3, pp. 365–390. <doi:10.59170/stattrans-2016-022>.
Leroux, B. G., Lei, X., & Breslow, N. (2000). Estimation of Disease Rates in Small Areas: A New Mixed Model for Spatial Dependence. In M. E. Halloran & D. Berry (Eds.), Statistical Models in Epidemiology, the Environment, and Clinical Trials (Vol. 116, pp. 179–191). New York: Springer. <doi:10.1007/978-1-4612-1284-3_4>.
Chung, H. C., & Datta, G. S. (2020). Bayesian Hierarchical Spatial Models for Small Area Estimation. Research Report Series. Washington, D.C.: U.S. Census Bureau.
Author(s)
Maintainer: Boby Iwan bobyiwanboby2122@gmail.com
Authors:
Boby Iwan bobyiwanboby2122@gmail.com
Cucu Sumarni
See Also
Useful links:
saeHB.Spatial.Beta documentation built on July 1, 2026, 5:07 p.m.
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| saeHB.Spatial.Beta-package | R Documentation |
saeHB.Spatial.Beta : Small Area Estimation Hierarchical Bayes for Spatial Beta Model
Description
Provides several functions and datasets for area-level Small Area Estimation using the Hierarchical Bayesian (HB) method.
Model-based estimators are designed for variables of interest that follow a Beta distribution (proportions bounded between 0 and 1).
The package supports spatial structures under the Simultaneous Autoregressive (SAR) model and the Leroux Conditional Autoregressive (CAR) model.
It also accommodates survey design effect (DEFF) adjustments to handle complex survey data. The rjags package is employed to obtain parameter estimates via Markov Chain Monte Carlo (MCMC).
Author(s)
Boby Iwan, Cucu Sumarni
Maintainer: Boby Iwan bobyiwanboby2122@gmail.com
Functions
betadeff_sarEstimates small area means using Spatial SAR Model with Beta distribution and Design Effect (DEFF) adjustments.
beta_sarEstimates small area means using Spatial SAR Model with Beta distribution without DEFF adjustments (estimates a global precision parameter).
betadeff_lerouxcarEstimates small area means using Spatial Leroux CAR Model with Beta distribution and Design Effect (DEFF) adjustments.
beta_lerouxcarEstimates small area means using Spatial Leroux CAR Model with Beta distribution without DEFF adjustments.
betadeff_nonspatialEstimates small area means using a Non-Spatial Beta Model with Independent and Identically Distributed (IID) random effects and DEFF adjustments.
beta_nonspatialEstimates small area means using a Non-Spatial Beta Model without DEFF adjustments.
build_wA utility function to construct spatial weights matrices (contiguity, distance, or kernel) required for spatial modeling.
moran_testA diagnostic function to perform Moran's I test for spatial autocorrelation.
Reference
Rao, J. N. K., & Molina, I. (2015). Small Area Estimation (2nd Edition). New Jersey: John Wiley and Sons, Inc. <doi:10.1002/9781118735855>.
Kubacki, J., & Jedrzejczak, A. (2016). Small Area Estimation of Income Under Spatial SAR Model. Statistics in Transition New Series, Vol. 17, No. 3, pp. 365–390. <doi:10.59170/stattrans-2016-022>.
Leroux, B. G., Lei, X., & Breslow, N. (2000). Estimation of Disease Rates in Small Areas: A New Mixed Model for Spatial Dependence. In M. E. Halloran & D. Berry (Eds.), Statistical Models in Epidemiology, the Environment, and Clinical Trials (Vol. 116, pp. 179–191). New York: Springer. <doi:10.1007/978-1-4612-1284-3_4>.
Chung, H. C., & Datta, G. S. (2020). Bayesian Hierarchical Spatial Models for Small Area Estimation. Research Report Series. Washington, D.C.: U.S. Census Bureau.
Author(s)
Maintainer: Boby Iwan bobyiwanboby2122@gmail.com
Authors:
Boby Iwan bobyiwanboby2122@gmail.com
Cucu Sumarni
See Also
Useful links:
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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