Package: orthoDr 2.0.0
orthoDr: Semi-Parametric Dimension Reduction Models Using Orthogonality Constrained Optimization
Utilize an orthogonality constrained optimization algorithm of Wen & Yin (2013) <doi:10.1007/s10107-012-0584-1> to solve a variety of dimension reduction problems in the semiparametric framework, such as Ma & Zhu (2012) <doi:10.1080/01621459.2011.646925>, Ma & Zhu (2013) <doi:10.1214/12-AOS1072>, Sun, Zhu, Wang & Zeng (2017) <doi:10.48550/arXiv.1704.05046> and Zhou & Zhu (2018+) <doi:10.48550/arXiv.1802.06156>. It also serves as a general purpose optimization solver for problems with orthogonality constraints. Parallel computing for approximating the gradient is enabled through `OpenMP'.
Authors:
orthoDr_2.0.0.tar.gz
orthoDr_2.0.0.zip(r-4.7)orthoDr_2.0.0.zip(r-4.6)orthoDr_2.0.0.zip(r-4.5)
orthoDr_2.0.0.tgz(r-4.6-x86_64)orthoDr_2.0.0.tgz(r-4.6-arm64)orthoDr_2.0.0.tgz(r-4.5-x86_64)orthoDr_2.0.0.tgz(r-4.5-arm64)
orthoDr_2.0.0.tar.gz(r-4.7-arm64)orthoDr_2.0.0.tar.gz(r-4.7-x86_64)orthoDr_2.0.0.tar.gz(r-4.6-arm64)orthoDr_2.0.0.tar.gz(r-4.6-x86_64)
orthoDr_2.0.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
orthoDr/json (API)
| # Install 'orthoDr' in R: |
| install.packages('orthoDr', repos = c('https://teazrq.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/rqzhu-aide/orthodr/issues
- skcm.clinical - Skcm.clinical
- skcm.melgene - Skcm.melgene
Last updated from:16fc0f1101. Checks:13 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | OK | 337 | ||
| linux-devel-x86_64 | OK | 329 | ||
| source / vignettes | OK | 361 | ||
| linux-release-arm64 | OK | 339 | ||
| linux-release-x86_64 | OK | 311 | ||
| macos-release-arm64 | OK | 238 | ||
| macos-release-x86_64 | OK | 430 | ||
| macos-oldrel-arm64 | OK | 318 | ||
| macos-oldrel-x86_64 | OK | 603 | ||
| windows-devel | OK | 307 | ||
| windows-release | OK | 275 | ||
| windows-oldrel | OK | 238 | ||
| wasm-release | OK | 240 |
Exports:CP_SIRdist_crossdistancehMavekernel_weightortho_optimorthoDr_pdoseorthoDr_regorthoDr_survpSAVEsilvermanview_dr_surv
Dependencies:base64encbslibcachemclidigestdrevaluatefastmapfontawesomefshighrhtmltoolshtmlwidgetsjquerylibjsonliteknitrlatticelifecyclemagrittrMASSMatrixmemoisemimemisc3dplot3DpracmaR6rappdirsRcppRcppArmadillorglrlangrmarkdownsasssurvivaltinytexxfunyaml
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Counting-Process Based Sliced Inverse Regression | CP_SIR |
| dist_cross | dist_cross |
| Distance Between Two Linear Subspaces | distance |
| Hazard MAVE for Censored Survival Data | hMave |
| kernel_weight | kernel_weight |
| Orthogonality Constrained Optimization | ortho_optim |
| Personalized Dose Estimation via Dimension Reduction | orthoDr_pdose |
| Semiparametric Dimension Reduction for Regression | orthoDr_reg |
| Semiparametric Dimension Reduction for Censored Survival Outcomes | orthoDr_surv |
| predict.orthoDr | predict.orthoDr |
| Partial Sliced Averaged Variance Estimation | pSAVE |
| A simple Silverman bandwidth formula | silverman |
| skcm.clinical | skcm.clinical |
| skcm.melgene | skcm.melgene |
| 2D or 3D view of survival data on reduced dimension | view_dr_surv |
