Small Area Estimation: Time-series Models
Time series models for small area estimation based on area-level models.

Small Area Estimation: Time-Series Models

Selecting Auxiliary Variables in Small Area Estimation (SAE)
Model
Azka Ubaidillah [aut], Sheerin Dahwan Aziz [aut, cre]
Select best combination of auxiliary variables with certain criterion.

Small Area Estimation using Hierarchical Bayesian Method
Azka Ubaidillah [aut], Ika Yuni Wulansari [aut], Zaza Yuda Perwira [aut, cre]
Provides several functions for area level of small area estimation using hierarchical Bayesian (HB) method with Univariate Normal distribution and Univariate Beta distribution for variables of interest. Some dataset produced by a data generation are also provided. 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) <doi:10.1002/9781118735855>.
stringr, coda, rjags, stats, grDevices, graphics

Provides several functions for area level of small area estimation using hierarchical Bayesian (HB) method with several univariate distributions for variable of interest. The dataset that used in every function is generated accordingly in the Example. 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) <doi:10.1002/9781118735855>.
stringr, coda, rjags, stats, grDevices, graphics, nimble,
CARBayesdata, MASS

stringr, coda, rjags, stats, nimble, CARBayesdata, MASS,
grDevices, graphics

Small Area Estimation with Measurement Error using Hierarchical
Bayesian Method
c(person("Azka Ubaidillah", role = "aut", email = "azka@stis.ac.id"),
person("Muhammad Rifqi Mubarak", role = c("aut","cre"), email = "rifqi.mubarak@bps.go.id"))
Implementation of small area estimation using Hierarchical Bayesian (HB) Method when auxiliary variable measured with error. The 'rjags' package is employed to obtain parameter estimates. For the references, see Rao and Molina (2015) <doi:10.1002/9781118735855>, Ybarra and Lohr (2008) <doi:10.1093/biomet/asn048>, and Ntzoufras (2009, ISBN-10: 1118210352).
Azka Ubaidillah [aut],
Muhammad Rifqi Mubarak [aut, cre]