Package: NSAE 0.4.0

Saurav Guha

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.

Authors:Hukum Chandra [aut], Nicola Salvati [aut], Ray Chambers [aut], Saurav Guha [aut, cre]

NSAE_0.4.0.tar.gz
NSAE_0.4.0.tar.gz(r-4.5-noble)NSAE_0.4.0.tar.gz(r-4.4-noble)
NSAE_0.4.0.tgz(r-4.4-emscripten)NSAE_0.4.0.tgz(r-4.3-emscripten)
NSAE.pdf |NSAE.html
NSAE/json (API)

# Install 'NSAE' in R:
install.packages('NSAE', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

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This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.30 score 2 stars 186 downloads 10 exports 15 dependencies

Last updated 2 years agofrom:0526288fea. Checks:OK: 1 NOTE: 1. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 20 2024
R-4.5-linuxNOTENov 20 2024

Exports:eblupFH1eblupFH2eblupNSFH1eblupNSFH2ebpebpNPebpNSebpSPNS.testNSglm.test

Dependencies:clusterdata.tablejsonlitelatticeMASSMatrixnlmenumDerivrlistSemiParspspDataspgwrXMLyaml