saens: Small Area Estimation with Cluster Information for Estimation of Non-Sampled Areas

Implementation of small area estimation (Fay-Herriot model) with EBLUP (Empirical Best Linear Unbiased Prediction) Approach for non-sampled area estimation by adding cluster information and assuming that there are similarities among particular areas. See also Rao & Molina (2015, ISBN:978-1-118-73578-7) and Anisa et al. (2013) <doi:10.9790/5728-10121519>.

Version:	0.1.1
Depends:	R (≥ 4.00)
Imports:	cli, dplyr, ggplot2, methods, rlang, stats, tidyr
Published:	2024-10-24
DOI:	10.32614/CRAN.package.saens
Author:	Ridson Al Farizal P [aut, cre, cph], Azka Ubaidillah [aut]
Maintainer:	Ridson Al Farizal P <alfrzlp at gmail.com>
BugReports:	https://github.com/Alfrzlp/sae-ns/issues
License:	MIT + file LICENSE
URL:	https://github.com/Alfrzlp/sae-ns
NeedsCompilation:	no
Materials:	README
CRAN checks:	saens results

Documentation:

Reference manual:

saens.pdf

Downloads:

Package source:	saens_0.1.1.tar.gz
Windows binaries:	r-devel: saens_0.1.1.zip, r-release: saens_0.1.1.zip, r-oldrel: saens_0.1.1.zip
macOS binaries:	r-release (arm64): saens_0.1.1.tgz, r-oldrel (arm64): saens_0.1.1.tgz, r-release (x86_64): saens_0.1.1.tgz, r-oldrel (x86_64): saens_0.1.1.tgz
Old sources:	saens archive

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