Package: rDecode 0.1.0
rDecode: Descent-Based Calibrated Optimal Direct Estimation
Algorithms for solving a self-calibrated l1-regularized quadratic programming problem without parameter tuning. The algorithm, called DECODE, can handle high-dimensional data without cross-validation. It is found useful in high dimensional portfolio selection (see Pun (2018) <https://ssrn.com/abstract=3179569>) and large precision matrix estimation and sparse linear discriminant analysis (see Pun and Hadimaja (2019) <https://ssrn.com/abstract=3422590>).
Authors:
rDecode_0.1.0.tar.gz
rDecode_0.1.0.zip(r-4.7-any)rDecode_0.1.0.zip(r-4.6-any)rDecode_0.1.0.zip(r-4.5-any)
rDecode_0.1.0.tgz(r-4.6-any)rDecode_0.1.0.tgz(r-4.5-any)
rDecode_0.1.0.tar.gz(r-4.7-any)rDecode_0.1.0.tar.gz(r-4.6-any)
rDecode_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
rDecode/json (API)
| # Install 'rDecode' in R: |
| install.packages('rDecode', repos = c('https://cspun.r-universe.dev', 'https://cloud.r-project.org')) |
- lung.test - Lung cancer test data set from Gordon et al.
- lung.train - Lung cancer training data set from Gordon et al.
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:fd4ff30abc. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 107 | ||
| source / vignettes | OK | 126 | ||
| linux-release-x86_64 | OK | 102 | ||
| macos-release-arm64 | OK | 86 | ||
| macos-oldrel-arm64 | OK | 101 | ||
| windows-devel | OK | 54 | ||
| windows-release | OK | 73 | ||
| windows-oldrel | OK | 56 | ||
| wasm-release | OK | 89 |
Exports:decodedecodeLDAdecodePM
Dependencies:
