ROCKET: robust confidence intervals via Kendall's tau for transelliptical graphical models

DOI10.1214/17-AOS1663zbMath1410.62059arXiv1502.07641OpenAlexW2963611525MaRDI QIDQ1990586

Rina Foygel Barber, Mladen Kolar

Publication date: 25 October 2018

Published in: The Annals of Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1502.07641

zbMATH Keywords

graphical model selectioncovariance selectionpost-model selection inferencerank-based estimationtranselliptical graphical modelsuniformly valid inference

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Nonparametric hypothesis testing (62G10) Asymptotic properties of nonparametric inference (62G20) Nonparametric robustness (62G35)

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High-dimensional proportionality test of two covariance matrices and its application to gene expression data, A convex optimization approach to high-dimensional sparse quadratic discriminant analysis, A unified theory of confidence regions and testing for high-dimensional estimating equations, High-Dimensional Inference for Cluster-Based Graphical Models, Unnamed Item, Inference for Nonparanormal Partial Correlation via Regularized Rank-Based Nodewise Regression, Minimax estimation of large precision matrices with bandable Cholesky factor, Dependence in elliptical partial correlation graphs, ROCKET: robust confidence intervals via Kendall's tau for transelliptical graphical models, Unnamed Item, Robust feature screening for elliptical copula regression model, Rejoinder of ``Estimating structured high-dimensional covariance and precision matrices: optimal rates and adaptive estimation, Robust estimator of the correlation matrix with sparse Kronecker structure for a high-dimensional matrix-variate, ROCKET, Inference for high-dimensional varying-coefficient quantile regression, Multiple Testing with the Structure-Adaptive Benjamini–Hochberg Algorithm

Uses Software

• glasso
• covTest

Cites Work

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