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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>).

Versions across snapshots

VersionRepositoryFileSize
0.1.0 rolling linux/jammy R-4.5 rDecode_0.1.0.tar.gz 611.0 KiB
0.1.0 rolling linux/noble R-4.5 rDecode_0.1.0.tar.gz 610.8 KiB
0.1.0 rolling source/ R- rDecode_0.1.0.tar.gz 418.1 KiB
0.1.0 latest linux/jammy R-4.5 rDecode_0.1.0.tar.gz 611.0 KiB
0.1.0 latest linux/noble R-4.5 rDecode_0.1.0.tar.gz 610.8 KiB
0.1.0 latest source/ R- rDecode_0.1.0.tar.gz 418.1 KiB
0.1.0 2026-04-26 source/ R- rDecode_0.1.0.tar.gz 418.1 KiB
0.1.0 2026-04-23 source/ R- rDecode_0.1.0.tar.gz 418.1 KiB
0.1.0 2026-04-09 windows/windows R-4.5 rDecode_0.1.0.zip 613.8 KiB
0.1.0 2025-04-20 source/ R- rDecode_0.1.0.tar.gz 418.1 KiB

Dependencies (latest)

Imports