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rDecode  

Descent-Based Calibrated Optimal Direct Estimation
View on CRAN: Click here


Download and install rDecode package within the R console
Install from CRAN:
install.packages("rDecode")

Install from Github:
library("remotes")
install_github("cran/rDecode")

Install by package version:
library("remotes")
install_version("rDecode", "0.1.0")



Attach the package and use:
library("rDecode")
Maintained by
Chi Seng Pun
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2019-12-18
Latest Update: 2019-12-18
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) ).
How to cite:
Chi Seng Pun (2019). rDecode: Descent-Based Calibrated Optimal Direct Estimation. R package version 0.1.0, https://cran.r-project.org/web/packages/rDecode. Accessed 06 Nov. 2024.
Previous versions and publish date:
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Complete documentation for rDecode
Functions, R codes and Examples using the rDecode R package
Some associated functions: decode . decodeLDA . decodePM . lung.test . lung.train . 
Some associated R codes: apg.R . data.R . decode.R . decodeLDA.R . decodePM.R . homotopy.R .  Full rDecode package functions and examples
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