Variable Selection for Sparse Data with Applications to Vaginal Microbiome and Gene Expression Data

Variable Selection for Sparse Data with Applications to Vaginal Microbiome and Gene Expression Data

Sparse data with a high portion of zeros arise in various disciplines. Modeling sparse high-dimensional data is a challenging and growing research area. In this paper, we provide statistical methods and tools for analyzing sparse data in a fairly general and complex context. We utilize two real scie...

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Bibliographic Details
Main Authors: Niloufar Dousti Mousavi, Jie Yang, Hani Aldirawi
Format: Article
Language:English
Published: MDPI AG 2023-02-01
Series:Genes
Subjects:
zero-inflated model
hurdle model
longitudinal data
model selection
vaginal microbiome
gene expression
Online Access:https://www.mdpi.com/2073-4425/14/2/403

Internet

https://www.mdpi.com/2073-4425/14/2/403

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