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rpgbs

R package implementing rpgbs method

https://github.com/rsarkar2/rpgbs

Science Score: 44.0%

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    CITATION.cff file
    Found CITATION.cff file
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    Scientific vocabulary similarity
    Low similarity (2.2%) to scientific vocabulary
Last synced: 6 months ago · JSON representation ·

Repository

R package implementing rpgbs method

Basic Info
  • Host: GitHub
  • Owner: rsarkar2
  • Default Branch: main
  • Size: 12.7 KB
Statistics
  • Stars: 0
  • Watchers: 1
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Created over 2 years ago · Last pushed about 1 year ago
Metadata Files
Readme Citation

README.md

rPGBS: repeatedly randomized Pseudo Group Bi-level Selection

R package implementing rPGBS method, a two-stage procedure to address the issue of stable variable selection in various strong correlation settings. This approach involves repeatedly running a two-stage hierarchical approach consisting of a random pseudo-group clustering and bi-level variable selection.

Authors: Reetika Sarkar, Sithija Manage, and Xiaoli Gao.

Owner

  • Name: Reetika Sarkar
  • Login: rsarkar2
  • Kind: user

Citation (citation.cff) 

cff-version: 1.2.0
title: >-
  rPGBS: repeatedly randomized Pseudo Group Bi-level
  Selection
message: >-
  If you use this software, please cite it using the
  metadata from this file.
type: R Package
authors:
  - given-names: Reetika
    family-names: Sarkar
    email: rsarkar@uncg.edu
    name-particle: Reetika
    affiliation: >-
      Department of Mathematics and Statistics, University
      of North Carolina at Greensboro
  - given-names: Sithija
    family-names: Manage
    affiliation: 'Department of Mathematics, Texas A&M University'
  - given-names: Xiaoli
    family-names: Gao
    affiliation: Meta Platforms
identifiers:
  - type: url
    value: >-
      https://link-springer-com.libproxy.uncg.edu/article/10.1007/s40745-023-00481-5
    description: >-
      Stable Variable Selection for High-Dimensional Genomic
      Data with Strong Correlations
repository-code: 'https://github.com/rsarkar2/rpgbs'
abstract: >-
  R package implementing rPGBS method, a two-stage procedure
  to address the issue of stable variable selection in
  various strong correlation settings. This approach
  involves repeatedly running a two-stage hierarchical
  approach consisting of a random pseudo-group clustering
  and bi-level variable selection.
keywords:
  - feature selection
  - penalty-based regression

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