Package: pcpr 1.0.0
Lawrence G. Chillrud
pcpr: Principal Component Pursuit for Environmental Epidemiology
Implementation of the pattern recognition technique Principal Component Pursuit tailored to environmental health data, as described in Gibson et al (2022) <doi:10.1289/EHP10479>.
Authors:
pcpr_1.0.0.tar.gz
pcpr_1.0.0.tar.gz(r-4.5-noble)pcpr_1.0.0.tar.gz(r-4.4-noble)
pcpr_1.0.0.tgz(r-4.4-emscripten)pcpr_1.0.0.tgz(r-4.3-emscripten)
pcpr.pdf |pcpr.html✨
pcpr/json (API)
NEWS
| # Install 'pcpr' in R: |
| install.packages('pcpr', repos = 'https://cloud.r-project.org') |
Bug tracker:https://github.com/columbia-prime/pcpr/issues
Pkgdown site:https://columbia-prime.github.io
- queens - Daily chemical concentrations of 26 PM2.5 species from Queens, NYC
Last updated 3 hours agofrom:c848c72042. Checks:3 OK. Indexed: yes.
| Target | Result | Latest binary |
|---|---|---|
| Doc / Vignettes | OK | Mar 27 2025 |
| R-4.5-linux | OK | Mar 27 2025 |
| R-4.4-linux | OK | Mar 27 2025 |
Exports:get_pcp_defaultsgrid_search_cvhard_thresholdimpute_matrixmatrix_rankproj_rank_rroot_pcprrmcsim_datasim_lodsim_nasingsparsity
Dependencies:backportscheckmateclicodetoolsdigestdplyrfansiforeachfurrrfuturegenericsglobalsglueiteratorslifecyclelistenvmagrittrparallellypillarpkgconfigprogressrpurrrR6rlangtibbletidyselectutf8vctrswithr
Air pollution source apportionment with PCP
Rendered frompcp-applied.Rmdusingknitr::rmarkdownon Mar 27 2025.Last update: 2025-03-27
Started: 2025-03-27
Quickstart: applying PCP to a simulated environmental mixture
Rendered frompcp-quickstart.Rmdusingknitr::rmarkdownon Mar 27 2025.Last update: 2025-03-27
Started: 2025-03-27
Theory crash course
Rendered fromtheory-crash-course.Rmdusingknitr::rmarkdownon Mar 27 2025.Last update: 2025-03-27
Started: 2025-03-27
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Retrieve default PCP parameter settings for given matrix | get_pcp_defaults |
| Cross-validated grid search for PCP models | grid_search_cv |
| Hard-thresholding operator | hard_threshold |
| Impute missing values in given matrix | impute_matrix |
| Estimate rank of a given matrix | matrix_rank |
| Project matrix to rank r | proj_rank_r |
| Daily chemical concentrations of 26 PM2.5 species from Queens, NYC (2001-2021) | queens |
| Square root principal component pursuit (convex PCP) | root_pcp |
| Rank-based robust matrix completion (non-convex PCP) | rrmc |
| Simulate simple mixtures data | sim_data |
| Simulate limit of detection data | sim_lod |
| Simulate random missingness in a given matrix | sim_na |
| Compute singular values of given matrix | sing |
| Estimate sparsity of given matrix | sparsity |
