README.md

In JasonQxZ/SMLE: Joint Feature Screening via Sparse MLE

SMLE R Package

Joint Feature Screening via Sparse MLE Explore the docs »

Table of Contents

1. Getting Started
   • Prerequisites
   • Installation
2. Usage
3. License
4. Contact

Getting Started

Prerequisites

R softeware and R package glmnet

Installation

# Install package from CRAN:
install.packages("SMLE")

Usage

set.seed(1)
Data_sim <- Gen_Data(n = 200, p = 1000, correlation = "AR", rho = 0.9, sigma = 1,
                     family = "gaussian", pos_truecoef = c(1,3,5,7,9),
                     effect_truecoef = (0.8)*c(2,-3,-3,2,-4))
fit_path <- SMLE(Y = Data_sim$Y, X = Data_sim$X , k = 10 , coef_initial = rep(0,1000))
plot(fit_path)

For more examples, please refer to the Vignette

License

Distributed under the GPL-3 License.

Contact

Qianxiang Zang - [e-mail]

JasonQxZ/SMLE documentation built on Feb. 13, 2023, 11:22 a.m.