saens: Small Area Estimation with Cluster Information for Estimation ofNon-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: | 0.1.2 |
| Depends: | R (≥ 4.00) |
| Imports: | cli,dplyr,ggplot2, methods,rlang, stats,tidyr |
| Published: | 2024-11-18 |
| 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 + fileLICENSE |
| URL: | https://github.com/Alfrzlp/sae-ns |
| NeedsCompilation: | no |
| Materials: | README,NEWS |
| CRAN checks: | saens results |
Documentation:
Downloads:
Linking:
Please use the canonical formhttps://CRAN.R-project.org/package=saensto link to this page.