Package: rsae 0.3
Tobias Schoch
rsae: Robust Small Area Estimation
Empirical best linear unbiased prediction (EBLUP) and robust prediction of the area-level means under the basic unit-level model. The model can be fitted by maximum likelihood or a (robust) M-estimator. Mean square prediction error is computed by a parametric bootstrap.
Authors:
rsae_0.3.tar.gz
rsae_0.3.tar.gz(r-4.5-noble)rsae_0.3.tar.gz(r-4.4-noble)
rsae_0.3.tgz(r-4.4-emscripten)rsae_0.3.tgz(r-4.3-emscripten)
rsae.pdf |rsae.html✨
rsae/json (API)
NEWS
| # Install 'rsae' in R: |
| install.packages('rsae', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/tobiasschoch/rsae/issues
Datasets:
- landsat - LANDSAT Data: Prediction of County Crop Areas Using Survey and Satellite Data
- landsat_means - Means of the LANDSAT Data for Corn and Soybeans
Last updated 9 months agofrom:7fc67ca722. Checks:OK: 2. Indexed: no.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Sep 20 2024 |
| R-4.5-linux-x86_64 | OK | Sep 20 2024 |
Exports:convergencefitsaemodelfitsaemodel.controlmakedatarobpredictsaemodel
Dependencies:
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Robust Small Area Estimation | rsae-package rsae |
| Fitting SAE Models | coef.fit_model_b convergence fitsaemodel print.fit_model_b print.summary_fit_model_b summary.fit_model_b |
| Tuning Parameters of 'fitsaemodel' | fitsaemodel.control |
| LANDSAT Data: Prediction of County Crop Areas Using Survey and Satellite Data | landsat |
| Means of the LANDSAT Data for Corn and Soybeans | landsat_means |
| Synthetic Data Generation for the Basic Unit-Level SAE Model | makedata |
| Robust Prediction of Random Effects, Fixed Effects, and Area-Specific Means | as.matrix.pred_model_b head.pred_model_b plot.pred_model_b print.pred_model_b residuals.pred_model_b robpredict tail.pred_model_b |
| Setting Up a SAE Model | as.matrix.saemodel print.saemodel saemodel summary.saemodel |
