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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 |
DOI: | 10.32614/CRAN.package.NSAE |
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 |
Reference manual: | NSAE.pdf |
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, r-oldrel (x86_64): NSAE_0.4.0.tgz |
Old sources: | NSAE archive |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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