README.md

In yxwang99/alphanorm: alpha-norm regularization

README

This package is related to the work in "Sparse Regularization in Marketing and Economics" by Guanhao Feng, Nicholas Polson, Yuexi Wang and Jianeng Xu. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3022856

Functions

The package contains five functions and their usage is similar to those in glmnet package.

• alphanorm: build the alpha-norm model with input data. The coefficients are solved via a proximal algorithm and coordinate descent.

• coef.alphanorm: take an alphanorm object as input and output the coefficients in the object

• cv.alphanorm: use cross-validation to find the best tuning parameter $\alpha$ and $\lambda$

• plot.alphanorm: plot the coefficient profile with respect to either $log(\lambda)$, or $l_\alpha$ norm of the coefficients

• predict.alphanorm: get predicted value from a new input and a fitted alphanorm model

Detailed usage of functions can be found in alphanorm.pdf

Installation of Package

The package is currently not available on R CRAN. You can use it via:

devtools::install_github(yxwang99/alphanorm)
library(alphanorm)

If you encounter any problem using this package, please email to [e-mail]

yxwang99/alphanorm documentation built on May 23, 2019, 11:34 p.m.