Package: saens 0.1.1
Ridson Al Farizal P
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>.
Authors:
saens_0.1.1.tar.gz
saens_0.1.1.tar.gz(r-4.5-noble)saens_0.1.1.tar.gz(r-4.4-noble)
saens_0.1.1.tgz(r-4.4-emscripten)saens_0.1.1.tgz(r-4.3-emscripten)
saens.pdf |saens.html✨
saens/json (API)
| # Install 'saens' in R: |
| install.packages('saens', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/alfrzlp/sae-ns/issues
Last updated 5 days agofrom:6b97a8093d. Checks:OK: 2. Indexed: no.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Oct 25 2024 |
| R-4.5-linux | OK | Oct 25 2024 |
Exports:autoploteblupfheblupfh_cluster
Dependencies:clicolorspacecpp11dplyrfansifarvergenericsggplot2gluegtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigpurrrR6RColorBrewerrlangscalesstringistringrtibbletidyrtidyselectutf8vctrsviridisLitewithr
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Akaike's An Information Criterion. | AIC.eblupres BIC.eblupres |
| Create a complete ggplot appropriate to a particular data type | autoplot |
| Autoplot EBLUP results. | autoplot.eblupres |
| Extract Model Coefficients. | coef.eblupres |
| EBLUPs based on a Fay-Herriot Model. | eblupfh |
| EBLUPs based on a Fay-Herriot Model with Cluster Information. | eblupfh_cluster |
| Extract Log-Likelihood. | logLik.eblupres |
| milk: Data on fresh milk expenditure. | milk |
| mys: mean years of schooling people with disabilities in Papua Island, Indonesia. | mys |
| Summarizing EBLUP Model Fits. | summary.eblupres |