Read me
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
Installation
The package is currently not available on R CRAN. You can download it via:
devtools::install_github(yxwang99/alphanorm) library(alphanorm)
Available at: https://github.com/yxwang99/alphanorm