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rDecode (version 0.1.0)

Descent-Based Calibrated Optimal Direct Estimation

Description

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) ) and large precision matrix estimation and sparse linear discriminant analysis (see Pun and Hadimaja (2019) ).

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Version

Install

install.packages('rDecode')

Monthly Downloads

162

Version

0.1.0

License

GPL-2

Maintainer

Chi Pun

Last Published

December 18th, 2019

Functions in rDecode (0.1.0)

lung.train

Lung cancer training data set from Gordon et al. (2002)
decodeLDA

Implement DECODE for simple LDA
decode

Descent-based Calibrated Optimal Direct Estimation
lung.test

Lung cancer test data set from Gordon et al. (2002)
decodePM

Implement DECODE for simple precision matrix estimation