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msae

Multivariate Fay Herriot Models for Small Area Estimation

Installation

About

Implements multivariate Fay-Herriot models for small area estimation. It uses empirical best linear unbiased prediction (EBLUP) estimator. Multivariate models consider the correlation of several target variables and borrow strength from auxiliary variables to improve the effectiveness of a domain sample size. Models which accommodated by this package are univariate model with several target variables (model 0), multivariate model (model 1), autoregressive multivariate model (model 2), and heteroscedastic autoregressive multivariate model (model 3). Functions provide EBLUP estimators and mean squared error (MSE) estimator for each model. These models were developed by Roberto Benavent and Domingo Morales (2015) doi:10.1016/j.csda.2015.07.013.

Key Metrics

Version 0.1.5
R ≥ 2.10
Published 2022-04-24 743 days ago
Needs compilation? no
License GPL-2
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Maintainer

Maintainer

Novia Permatasari

novia.permatasari@bps.go.id

Authors

Novia Permatasari
Azka Ubaidillah

Material

Reference manual
Package source

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

msae archive

Depends

R ≥ 2.10

Imports

magic