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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>).

Version: 0.1.0
Depends: R (≥ 2.10)
Imports: stats
Published: 2019-12-18
DOI: 10.32614/CRAN.package.rDecode
Author: Chi Seng Pun, Matthew Zakharia Hadimaja
Maintainer: Chi Seng Pun <cspun at ntu.edu.sg>
License: GPL-2
NeedsCompilation: no
CRAN checks: rDecode results

Documentation:

Reference manual: rDecode.pdf

Downloads:

Package source: rDecode_0.1.0.tar.gz
Windows binaries: r-devel: rDecode_0.1.0.zip, r-release: rDecode_0.1.0.zip, r-oldrel: rDecode_0.1.0.zip
macOS binaries: r-release (arm64): rDecode_0.1.0.tgz, r-oldrel (arm64): rDecode_0.1.0.tgz, r-release (x86_64): rDecode_0.1.0.tgz, r-oldrel (x86_64): rDecode_0.1.0.tgz

Linking:

Please use the canonical form https://CRAN.R-project.org/package=rDecode to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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