Tuning-Free Heterogeneity Pursuit in Massive Networks

DOI10.48550/arXiv.1606.03803zbMath1428.62098arXiv1606.03803OpenAlexW2905419188MaRDI QIDQ148592

Jinchi Lv, Zhao Ren, Yongjian Kang, Yingying Fan, Zhao Ren, Yingying Fan, Yongjian Kang, Jinchi Lv

Publication date: 13 June 2016

Published in: Journal of the American Statistical Association (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1606.03803

zbMATH Keywords

efficiencyscalabilityhigh dimensionalitysparsitylarge-scale inferencemultiple networksheterogeneous learningheterogeneous group square-root Lasso

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Asymptotic distribution theory in statistics (62E20) Point estimation (62F10)

Related Items

Hypothesis testing for high-dimensional multivariate regression with false discovery rate control, Inference on Multi-level Partial Correlations Based on Multi-subject Time Series Data, RANK: Large-Scale Inference With Graphical Nonlinear Knockoffs, HGSL

Uses Software

• glasso
• LogConcDEAD
• camel
• SOFAR

Cites Work

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