Contiguity under high-dimensional Gaussianity with applications to covariance testing
Author:
Affiliation:
1. Department of Statistics, Rutgers University
2. School of Statistics, University of Minnesota
3. Department of Statistics, University of Chicago
Publisher
Institute of Mathematical Statistics
Subject
Statistics, Probability and Uncertainty,Statistics and Probability
Reference32 articles.
1. Cai, T. T. and Ma, Z. (2013). Optimal hypothesis testing for high dimensional covariance matrices. Bernoulli 19 2359–2388.
2. Chatterjee, S. (2009). Fluctuations of eigenvalues and second order Poincaré inequalities. Probab. Theory Related Fields 143 1–40.
3. CHATTERJEE, S. (2014). Superconcentration and Related Topics. Springer Monographs in Mathematics. Springer, Cham.
4. LE CAM, L. (1960). Locally asymptotically normal families of distributions. Certain approximations to families of distributions and their use in the theory of estimation and testing hypotheses. Univ. California Publ. Statist. 3 37–98.
5. BAI, Z., JIANG, D., YAO, J.-F. and ZHENG, S. (2009). Corrections to LRT on large-dimensional covariance matrix by RMT. Ann. Statist. 37 3822–3840.
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