Likelihood ratio tests for covariance matrices of high-dimensional normal distributions
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Publication:433736
DOI10.1016/j.jspi.2012.02.057zbMath1244.62082OpenAlexW2145234455MaRDI QIDQ433736
Tiefeng Jiang, Dandan Jiang, Fan Yang
Publication date: 6 July 2012
Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.jspi.2012.02.057
Asymptotic distribution theory in statistics (62E20) Hypothesis testing in multivariate analysis (62H15) Gamma, beta and polygamma functions (33B15) Hypergeometric integrals and functions defined by them ((E), (G), (H) and (I) functions) (33C60)
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Cites Work
- Corrections to LRT on large-dimensional covariance matrix by RMT
- CLT for linear spectral statistics of large-dimensional sample covariance matrices.
- Book review of: Daniel S. Alexander, A history of complex dynamics. From Schröder to Fatou and Julia.
- The importance of the Selberg integral
- Matrix models for beta ensembles
- A High Dimensional Two Sample Significance Test
- Some Non-Central Distribution Problems in Multivariate Analysis
- Complex analysis. Transl. from the German by Dan Fulea
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