Sparse sliced inverse regression for high dimensional data analysis

Sparse sliced inverse regression for high dimensional data analysis

Abstract Background Dimension reduction and variable selection play a critical role in the analysis of contemporary high-dimensional data. The semi-parametric multi-index model often serves as a reasonable model for analysis of such high-dimensional data. The sliced inverse regression (SIR) method,...

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Bibliographic Details
Main Authors: Haileab Hilafu, Sandra E. Safo
Format: Article
Language:English
Published: BMC 2022-05-01
Series:BMC Bioinformatics
Subjects:
Semiparametric model
Generalized eigenvalue decomposition
Sliced inverse regression
Linear discriminant analysis
High-dimensional data
Online Access:https://doi.org/10.1186/s12859-022-04700-3

Internet

https://doi.org/10.1186/s12859-022-04700-3

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