A note on testing the covariance matrix for large dimension

By Melanie Birke, Holger Dette. 2005

72 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/76f76d0266c13a201b990185e51ca16ed9cf9f71

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Citations in the corpus

Estimating structured high-dimensional covariance and precision matrices: Optimal rates and adaptive estimation (2016, background): “Birke and Dette (2005) further investigated and modified their test statistic in the extreme cases where p/n → c ∈ {0,∞}.”
Independence test for high dimensional data based on regularized canonical correlation coefficients (2015, background): “There have been a substantial body of research work dealing with high dimensional data, for example, [2, 4, 7, 9, 10, 12], etc.”
Substitution principle for CLT of linear spectral statistics of high-dimensional sample covariance matrices with applications to hypothesis testing (2014, methodology): “[2, 3, 9, 14, 20, 21], so that LSS of the sample covariance matrices are approximated using either the CLT (1.”
Global Testing and Large-Scale Multiple Testing for High-Dimensional Covariance Structures (2017, background): “The results have been extended by Birke and Dette (2005); Srivastava (2005).”
Approximation of Rectangular Beta-Laguerre Ensembles and Large Deviations (2013, unknown): “Birke and Dette [11] further”
On the sphericity test with large-dimensional observations (2013, background): “It is worth noticing that [7] has extended the LW test to such a scheme (p ≫ n) for multivariate normal distribution.”
Optimal hypothesis testing for high dimensional covariance matrices (2012, background): “Birke and Dette [3] derived the asymptotic null distribution of the Ledoit–Wolf test under the current asymptotic regime.”
Asymptotic power of sphericity tests for high-dimensional data (2013, methodology): “In the context of sphericity tests, such asymptotic regimes have been recently studied in Birke and Dette (2005). Third, a thorough analysis of the finite sample properties of the proposed LR tests would clarify the related practical implementation issues.”