Package: primePCA 1.2
Ziwei Zhu
primePCA: Projected Refinement for Imputation of Missing Entries in PCA
Implements the primePCA algorithm, developed and analysed in Zhu, Z., Wang, T. and Samworth, R. J. (2019) High-dimensional principal component analysis with heterogeneous missingness. <arxiv:1906.12125>.
Authors:
primePCA_1.2.tar.gz
primePCA_1.2.tar.gz(r-4.5-noble)primePCA_1.2.tar.gz(r-4.4-noble)
primePCA_1.2.tgz(r-4.4-emscripten)primePCA_1.2.tgz(r-4.3-emscripten)
primePCA.pdf |primePCA.html✨
primePCA/json (API)
| # Install 'primePCA' in R: |
| install.packages('primePCA', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 3 years agofrom:5986afa764. Checks:OK: 2. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Dec 10 2024 |
| R-4.5-linux | OK | Dec 10 2024 |
Exports:col_scaleinverse_prob_methodprimePCAsin_theta_distance
Dependencies:latticeMASSMatrixsoftImpute
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Center and/or normalize each column of a matrix | col_scale |
| Inverse probability weighted method for estimating the top K eigenspaces | inverse_prob_method |
| primePCA algorithm | primePCA |
| Frobenius norm sin theta distance between two column spaces | sin_theta_distance |