Package: nlfh 0.1.0
Paul Parker
nlfh: Nonlinear Fay-Herriot Models for Small Area Estimation
Fits nonlinear Bayesian extensions of the Fay-Herriot model for small area estimation using area-level direct estimates and corresponding sampling variances. The package provides model fitting, prediction, uncertainty summaries, and diagnostic tools for nonlinear small area estimation workflows.
Authors:
nlfh_0.1.0.tar.gz
nlfh_0.1.0.tar.gz(r-4.7-any)nlfh_0.1.0.tar.gz(r-4.6-any)
nlfh_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
nlfh/json (API)
NEWS
| # Install 'nlfh' in R: |
| install.packages('nlfh', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/paparker/nlfh/issues
Datasets:
- acs_dat - Example ACS Small Area Data
Last updated from:dcb5fa9ba5. Checks:4 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 104 | ||
| source / vignettes | OK | 217 | ||
| linux-release-x86_64 | OK | 120 | ||
| wasm-release | OK | 107 |
Exports:fit_fhfit_fh_bartfit_fh_linearfit_fh_rnnposterior_draws
Dependencies:dbarts
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Example ACS Small Area Data | acs_dat |
| Fit a Fay-Herriot Model | fit_fh |
| Fit a BART Fay-Herriot Model | fit_fh_bart |
| Fit a Linear Fay-Herriot Model | fit_fh_linear |
| Fit a Random-Weight Neural Network Fay-Herriot Model | fit_fh_rnn |
| Extract Fitted Values from a Nonlinear Fay-Herriot Model | fitted.nlfh_fit |
| Extract Posterior Draws from a Fay-Herriot Model | posterior_draws posterior_draws.nlfh_fit |
| Print a Fitted Nonlinear Fay-Herriot Model | print.nlfh_fit |
| Print a Summary of a Fitted Nonlinear Fay-Herriot Model | print.summary.nlfh_fit |
| Summarize a Fitted Nonlinear Fay-Herriot Model | summary.nlfh_fit |