Description: Implements Benchmarking Method for Multivariate Small Area Estimation under Fay Herriot Model. Multivariate Small Area Estimation (MSAE) is a development of Univariate Small Area Estimation that considering the correlation among response variables and borrowing the strength from related areas and auxiliary variables to increase the effectiveness of sample size, the multivariate model in this package is based on multivariate model 1 proposed by Roberto Benavent and Domingo Morales (2016) <doi:10.1016/j.csda.2015.07.013>. Benchmarking in Small Area Estimation is a modification of Small Area Estimation model to guarantee that the aggregate weighted mean of the county predictors equals the corresponding weighted mean of survey estimates. Difference Benchmarking is the simplest benchmarking method but widely used by multiplying empirical best linear unbiased prediction (EBLUP) estimator by the common adjustment factors (J.N.K Rao and Isabel Molina, 2015).

Title: Multivariate Small Area Estimation using Hierarchical Bayesian
Author: Azka Ubaidillah [aut], Novia Permatasari [aut, cre]
Description: Implements area level of multivariate small area estimation using Hierarchical Bayesian method under Normal and T distribution. The 'rjags' package is employed to obtain parameter estimates. For the reference, see Rao and Molina (2015) <doi:10.1002/9781118735855>.

Title: Optimum Benchmarking for Multivariate Small Area Estimation
Author: Muhammad Yasqi Imanda [aut, cre], Zenda Oka Briantiko [aut], Azka Ubaidillah [aut]
Maintainer: Muhammad Yasqi Imanda <221810403@stis.ac.id>
Description: Implements multivariate optimum benchmarking small area estimation. This package provides optimum benchmarking estimation for univariate and multivariate small area estimation and its MSE. In fact, MSE estimators for optimum benchmark are not readily available, so resampling method that called parametric bootstrap is applied. The optimum benchmark model and parametric bootstrap in this package are based on the model proposed in small area estimation. J.N.K Rao and Isabel Molina (2015, ISBN: 978-1-118-73578-7).
Imports: magic, abind, Matrix, MASS, stats