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>).

Getting started

Package details

AuthorChi Seng Pun, Matthew Zakharia Hadimaja
MaintainerChi Seng Pun <cspun@ntu.edu.sg>
Package repositoryView on CRAN
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rDecode documentation built on Dec. 18, 2019, 5:08 p.m.