Package: saeHB.spatial 0.1.1
saeHB.spatial: Small Area Estimation Hierarchical Bayes For Spatial Model
Provides several functions and datasets for area level of Small Area Estimation under Spatial Model using Hierarchical Bayesian (HB) Method. Model-based estimators include the HB estimators based on a Spatial Fay-Herriot model with univariate normal distribution for variable of interest.The 'rjags' package is employed to obtain parameter estimates. For the reference, see Rao and Molina (2015) <doi:10.1002/9781118735855>.
Authors:
saeHB.spatial_0.1.1.tar.gz
saeHB.spatial_0.1.1.zip(r-4.5)saeHB.spatial_0.1.1.zip(r-4.4)saeHB.spatial_0.1.1.zip(r-4.3)
saeHB.spatial_0.1.1.tgz(r-4.4-any)saeHB.spatial_0.1.1.tgz(r-4.3-any)
saeHB.spatial_0.1.1.tar.gz(r-4.5-noble)saeHB.spatial_0.1.1.tar.gz(r-4.4-noble)
saeHB.spatial_0.1.1.tgz(r-4.4-emscripten)saeHB.spatial_0.1.1.tgz(r-4.3-emscripten)
saeHB.spatial.pdf |saeHB.spatial.html✨
saeHB.spatial/json (API)
| # Install 'saeHB.spatial' in R: |
| install.packages('saeHB.spatial', repos = c('https://arinams.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/arinams/saehb.spatial/issues
- prox.mat - Proximity Matrix for Small Area Estimation under Spatial Simultaneous Autoregressive (SAR) Model
- sp.norm - Synthetic Data for Small Area Estimation under Spatial Simultaneous Autoregressive (SAR) Model and Normal Distribution
- sp.normNs - Synthetic Data for Small Area Estimation under Spatial Simultaneous Autoregressive (SAR) Model and Normal Distribution with non-sampled area
Last updated 1 days agofrom:f72fbe3d79. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 23 2024 |
| R-4.5-win | OK | Nov 23 2024 |
| R-4.5-linux | OK | Nov 23 2024 |
| R-4.4-win | OK | Nov 23 2024 |
| R-4.4-mac | OK | Nov 23 2024 |
| R-4.3-win | OK | Nov 23 2024 |
| R-4.3-mac | OK | Nov 23 2024 |
Exports:sar.normal
Dependencies:clicodagluelatticelifecyclemagrittrrjagsrlangstringistringrvctrs
