Huber-type principal expectile component analysis

DOI10.1016/J.CSDA.2020.106992OpenAlexW3028037798MaRDI QIDQ830604

Mong-Na Lo Huang, Liang-Ching Lin, Ray-Bing Chen, Mei-Hui Guo

Publication date: 7 May 2021

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2020.106992

zbMATH Keywords

asymmetric normparticle swarm optimizationexpectileprincipal componentHuber's criterion

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (1)

Particle swarm stepwise (PaSS) algorithm for information criteria-based variable selections

Uses Software

• car
• carData

Cites Work

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• Asymmetric Least Squares Estimation and Testing
• Recent trends indicate rapid growth of nature-inspired optimization in academia and industry
• Survival of the flexible: explaining the recent popularity of nature-inspired optimization within a rapidly evolving world
• On convergence analysis of particle swarm optimization algorithm
• Robust regression: Asymptotics, conjectures and Monte Carlo
• Weak convergence and empirical processes. With applications to statistics
• Principal component analysis in an asymmetric norm
• Robust regression using iteratively reweighted least-squares
• Probabilistic Principal Component Analysis
• Robust Statistics

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