ADMM for Penalized Quantile Regression in Big Data

DOI10.1111/insr.12221OpenAlexW2749191054MaRDI QIDQ6064701

Nan Lin, Unnamed Author

Publication date: 10 November 2023

Published in: International Statistical Review (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1111/insr.12221

zbMATH Keywords

ADMMMapReducelarge-scaledivide-and-conquerpenalized quantile regressionHadoop

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (11)

Penalized and constrained LAD estimation in fixed and high dimension ⋮ Penalized Quantile Regression for Distributed Big Data Using the Slack Variable Representation ⋮ Weighted expectile regression with covariates missing at random ⋮ Distributed smoothed rank regression with heterogeneous errors for massive data ⋮ Communication-efficient surrogate quantile regression for non-randomly distributed system ⋮ Quantile regression for compositional covariates ⋮ Distributed adaptive lasso penalized generalized linear models for big data ⋮ Nonparametric Quantile Regression for Homogeneity Pursuit in Panel Data Models ⋮ Tensor quantile regression with application to association between neuroimages and human intelligence ⋮ Advanced algorithms for penalized quantile and composite quantile regression ⋮ Generalized \(\ell_1\)-penalized quantile regression with linear constraints

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