Variable selection methods in high-dimensional regression: a simulation study

A challenging problem in the analysis of high-dimensional data is variable selection. In this study, we describe a bootstrap based technique for selecting predictors in partial least-squares regression (PLSR) and principle component regression (PCR) in high-dimensional data. Using a bootstrap-based...

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Bibliographic Details
Main Author: Shahriari, Shirin (author)
Other Authors: Faria, Susana (author), Gonçalves, A. Manuela (author)
Format: article
Language:eng
Published: 2015
Subjects:
High-dimensional data
Partial least-squares regression
Principle component regression
Variable selection
Bootstrap
Ciências Naturais::Outras Ciências Naturais
Ciências Naturais::Matemáticas
Science & Technology
Online Access:http://hdl.handle.net/1822/43688
Country:Portugal
Oai:oai:repositorium.sdum.uminho.pt:1822/43688

Internet

http://hdl.handle.net/1822/43688

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