A split-and-conquer variable selection approach for high-dimensional general semiparametric models with massive data
Author:
Funder
Scientific Research Foundation of Hunan Provincial Education Department
Publisher
Elsevier BV
Subject
Statistics, Probability and Uncertainty,Numerical Analysis,Statistics and Probability
Reference26 articles.
1. A scalable bootstrap for massive data;Ariel;J. R. Stat. Soc. Ser. B Stat. Methodol.,2014
2. A split-and-conquer approach for analysis of extraordinarily large data;Chen;Statist. Sinica,2014
3. Semiparametric estimates of the relation between weather and electricity sales;Engle;J. Amer. Statist. Assoc.,1986
4. Variable selection via nonconcave penalized likelihood and its oracle properties;Fan;J. Amer. Statist. Assoc.,2001
5. Nonconcave penalized likelihood with a diverging number of parameters;Fan;Ann. Statist.,2004
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