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
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rDecode_0.1.0.tgz(r-4.5-any)rDecode_0.1.0.tgz(r-4.4-any)rDecode_0.1.0.tgz(r-4.3-any)
rDecode_0.1.0.tar.gz(r-4.5-noble)rDecode_0.1.0.tar.gz(r-4.4-noble)
rDecode_0.1.0.tgz(r-4.4-emscripten)rDecode_0.1.0.tgz(r-4.3-emscripten)
rDecode.pdf |rDecode.html✨
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 5 years agofrom:fd4ff30abc. Checks:9 OK. Indexed: yes.
| Target | Result | Latest binary |
|---|---|---|
| Doc / Vignettes | OK | Mar 17 2025 |
| R-4.5-win | OK | Mar 17 2025 |
| R-4.5-mac | OK | Mar 17 2025 |
| R-4.5-linux | OK | Mar 17 2025 |
| R-4.4-win | OK | Mar 17 2025 |
| R-4.4-mac | OK | Mar 17 2025 |
| R-4.4-linux | OK | Mar 17 2025 |
| R-4.3-win | OK | Mar 17 2025 |
| R-4.3-mac | OK | Mar 17 2025 |
Exports:decodedecodeLDAdecodePM
Dependencies:
