NSAE: Nonstationary Small Area Estimation

Executes nonstationary Fay-Herriot model and nonstationary generalized linear mixed model for small area estimation.The empirical best linear unbiased predictor (EBLUP) under stationary and nonstationary Fay-Herriot models and empirical best predictor (EBP) under nonstationary generalized linear mixed model along with the mean squared error estimation are included. EBLUP for prediction of non-sample area is also included under both stationary and nonstationary Fay-Herriot models. This extension to the Fay-Herriot model that accounts for the presence of spatial nonstationarity was developed by Hukum Chandra, Nicola Salvati and Ray Chambers (2015) <doi:10.1093/jssam/smu026> and nonstationary generalized linear mixed model was developed by Hukum Chandra, Nicola Salvati and Ray Chambers (2017) <doi:10.1016/j.spasta.2017.01.004>. This package is dedicated to the memory of Dr. Hukum Chandra who passed away while the package creation was in progress.

Version: 0.4.0
Depends: R (≥ 3.5.0)
Imports: rlist, cluster, MASS, lattice, Matrix, numDeriv, nlme, spgwr, SemiPar
Published: 2022-05-27
Author: Hukum Chandra [aut], Nicola Salvati [aut], Ray Chambers [aut], Saurav Guha [aut, cre]
Maintainer: Saurav Guha <saurav.iasri at gmail.com>
License: GPL-3
NeedsCompilation: no
CRAN checks: NSAE results

Documentation:

Reference manual: NSAE.pdf

Downloads:

Package source: NSAE_0.4.0.tar.gz
Windows binaries: r-devel: NSAE_0.4.0.zip, r-release: NSAE_0.4.0.zip, r-oldrel: NSAE_0.4.0.zip
macOS binaries: r-release (arm64): NSAE_0.4.0.tgz, r-oldrel (arm64): NSAE_0.4.0.tgz, r-release (x86_64): NSAE_0.4.0.tgz
Old sources: NSAE archive

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