Package: hierSDR 0.1
hierSDR: Hierarchical Sufficient Dimension Reduction
Provides semiparametric sufficient dimension reduction for central mean subspaces for heterogeneous data defined by combinations of binary factors (such as chronic conditions). Subspaces are estimated to be hierarchically nested to respect the structure of subpopulations with overlapping characteristics. This package is an implementation of the proposed methodology of Huling and Yu (2021) <doi:10.1111/biom.13546>.
Authors:
hierSDR_0.1.tar.gz
hierSDR_0.1.zip(r-4.5)hierSDR_0.1.zip(r-4.4)hierSDR_0.1.zip(r-4.3)
hierSDR_0.1.tgz(r-4.4-any)hierSDR_0.1.tgz(r-4.3-any)
hierSDR_0.1.tar.gz(r-4.5-noble)hierSDR_0.1.tar.gz(r-4.4-noble)
hierSDR_0.1.tgz(r-4.4-emscripten)hierSDR_0.1.tgz(r-4.3-emscripten)
hierSDR.pdf |hierSDR.html✨
hierSDR/json (API)
| # Install 'hierSDR' in R: |
| install.packages('hierSDR', repos = c('https://jaredhuling.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/jaredhuling/hiersdr/issues
Last updated 3 years agofrom:f5fe8e2720. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Sep 09 2024 |
| R-4.5-win | OK | Sep 09 2024 |
| R-4.5-linux | OK | Sep 09 2024 |
| R-4.4-win | OK | Sep 09 2024 |
| R-4.4-mac | OK | Sep 09 2024 |
| R-4.3-win | OK | Sep 09 2024 |
| R-4.3-mac | OK | Sep 09 2024 |
Exports:anglehier.phd.nthier.sphdphdprojnormsemi.phdsimulate_data
Dependencies:latticelbfgslocfitMASSMatrixnloptrnumDerivoptimxpracmaRcpp
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Angle between two subspaces | angle |
| Main hierarchical SDR fitting function | hier.phd.nt |
| Main hierarchical sufficient dimension reduction fitting function | hier.sphd |
| PHD SDR fitting function | phd |
| Plotting hierarchical SDR models | plot.hier_sdr_fit |
| Norm of difference of projections | projnorm |
| Semiparametric PHD SDR fitting function | semi.phd |
| Simulate data with hierarchical subspaces | simulate_data |
