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SMLE  

Joint Feature Screening via Sparse MLE
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("SMLE", "2.2-2")



Attach the package and use:
library("SMLE")
Maintained by
Qianxiang Zang
[Scholar Profile | Author Map]
First Published: 2020-05-18
Latest Update: 2024-02-12
Description:
Feature screening is a powerful tool in processing ultrahigh dimensional data. It attempts to screen out most irrelevant features in preparation for a more elaborate analysis. Xu and Chen (2014)<doi:10.1080/01621459.2013.879531> proposed an effective screening method SMLE, which naturally incorporates the joint effects among features in the screening process. This package provides an efficient implementation of SMLE-screening for high-dimensional linear, logistic, and Poisson models. The package also provides a function for conducting accurate post-screening feature selection based on an iterative hard-thresholding procedure and a user-specified selection criterion.
How to cite:
Qianxiang Zang (2020). SMLE: Joint Feature Screening via Sparse MLE. R package version 2.2-2, https://cran.r-project.org/web/packages/SMLE. Accessed 31 Mar. 2025.
Previous versions and publish date:
0.3.1 (2020-05-18 17:40), 0.4.0 (2020-06-08 06:20), 0.4.1 (2020-06-24 16:30), 1.1.1 (2021-05-09 06:20), 1.2.3 (2021-09-03 07:10), 1.2.4 (2021-09-09 09:00), 2.0-0 (2021-09-24 21:30), 2.0-1 (2021-10-01 15:00), 2.0-2 (2021-12-09 19:20), 2.1-0 (2023-01-21 14:30), 2.1-1 (2024-02-12 22:50)
Other packages that cited SMLE R package
View SMLE citation profile
Other R packages that SMLE depends, imports, suggests or enhances
Complete documentation for SMLE
Functions, R codes and Examples using the SMLE R package
Some associated functions: Gen_Data . SMLE-package . SMLE . coef . logLik . plot.selection . plot.smle . predict . print . pvals . smle_select . summary . synSNP . vote_update . 
Some associated R codes: Gen_data.R . ICselect.R . SMLE.R . SMLE_fit.R . coef.R . dummy.R . logLik.R . plot.selection.R . plot.smle.R . predict.R . print.R . pvals.R . smle_select.R . summary.R . synSNP.R . ult.R . vote.R .  Full SMLE package functions and examples
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