Analyzing large datasets with bootstrap penalization

DOI10.1002/bimj.201600052zbMath1367.62216OpenAlexW2549203804WikidataQ39168493 ScholiaQ39168493MaRDI QIDQ2980232

Kuangnan Fang, Shuangge Ma

Publication date: 28 April 2017

Published in: Biometrical Journal (Search for Journal in Brave)

Full work available at URL: http://europepmc.org/articles/pmc5577005

zbMATH Keywords

bootstrappenalizationlarge datasetscomputational feasibility

Mathematics Subject Classification ID

Ridge regression; shrinkage estimators (Lasso) (62J07) Applications of statistics to biology and medical sciences; meta analysis (62P10) Bootstrap, jackknife and other resampling methods (62F40)

Related Items (1)

bootpenal

Uses Software

• R

Cites Work

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• Sure independence screening in generalized linear models with NP-dimensionality
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• Random lasso
• Least angle regression. (With discussion)
• Pitfalls of hypothesis tests and model selection on bootstrap samples: Causes and consequences in biometrical applications
• Well-Separated Clusters and Optimal Fuzzy Partitions
• Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
• Model-Free Variable Selection
• Regularization and Variable Selection Via the Elastic Net
• Random forests

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