Asymptotic power of sphericity tests for high-dimensional data
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[1] J. Mauchly. Significance Test for Sphericity of a Normal $n$-Variate Distribution , 1940 .
[2] Le Cam,et al. Locally asymptotically normal families of distributions : certain approximations to families of distributions & thier use in the theory of estimation & testing hypotheses , 1960 .
[3] A. James. Distributions of Matrix Variates and Latent Roots Derived from Normal Samples , 1964 .
[4] W. Rudin. Real and complex analysis , 1968 .
[5] S. John. Some optimal multivariate tests , 1971 .
[6] N. Sugiura. Locally Best Invariant Test for Sphericity and the Limiting Distributions , 1972 .
[7] S. John. The distribution of a statistic used for testing sphericity of normal distributions , 1972 .
[8] F. Olver. Asymptotics and Special Functions , 1974 .
[9] S. Geman. A Limit Theorem for the Norm of Random Matrices , 1980 .
[10] J. Dickey. Multiple Hypergeometric Functions: Probabilistic Interpretations and Statistical Uses , 1983 .
[11] P. W. Karlsson,et al. Multiple Gaussian hypergeometric series , 1985 .
[12] W. Rudin. Real and complex analysis, 3rd ed. , 1987 .
[13] Z. Bai,et al. Convergence Rate of Expected Spectral Distributions of Large Random Matrices. Part II. Sample Covariance Matrices , 1993 .
[14] Z. Bai,et al. Convergence rate of expected spectral distributions of large random matrices , 2008 .
[15] Z. Bai,et al. Convergence Rate of Expected Spectral Distributions of Large Random Matrices. Part I. Wigner Matrices , 1993 .
[16] H. Uhlig. On singular Wishart and singular multivariate beta distributions , 1994 .
[17] J. W. Silverstein,et al. On the empirical distribution of eigenvalues of a class of large dimensional random matrices , 1995 .
[18] A. V. D. Vaart,et al. Asymptotic Statistics: U -Statistics , 1998 .
[19] I. Johnstone. On the distribution of the largest eigenvalue in principal components analysis , 2001 .
[20] G. Hillier. THE DENSITY OF A QUADRATIC FORM IN A VECTOR UNIFORMLY DISTRIBUTED ON THE n-SPHERE , 2001, Econometric Theory.
[21] Olivier Ledoit,et al. Some hypothesis tests for the covariance matrix when the dimension is large compared to the sample size , 2002 .
[22] J. Azaïs,et al. The Distribution of the Maximum of a Gaussian Process: Rice Method Revisited. , 2002 .
[23] Andrew T. A. Wood,et al. Laplace approximations for hypergeometric functions with matrix argument , 2002 .
[24] Holger Dette,et al. A note on testing the covariance matrix for large dimension , 2005 .
[25] S. Péché,et al. Phase transition of the largest eigenvalue for nonnull complex sample covariance matrices , 2004, math/0403022.
[26] J. W. Silverstein,et al. Eigenvalues of large sample covariance matrices of spiked population models , 2004, math/0408165.
[27] Means of a Dirichlet process and multiple hypergeometric functions , 2004, math/0410151.
[28] T. Ratnarajah,et al. Complex singular wishart matrices and applications , 2005 .
[29] M. Srivastava. Some Tests Concerning the Covariance Matrix in High Dimensional Data , 2005 .
[30] A. Guionnet,et al. A Fourier view on the R-transform and related asymptotics of spherical integrals , 2005 .
[31] D. Reich,et al. Population Structure and Eigenanalysis , 2006, PLoS genetics.
[32] D. Paindaveine,et al. SEMIPARAMETRICALLY EFFICIENT RANK-BASED INFERENCE FOR SHAPE I. OPTIMAL RANK-BASED TESTS FOR SPHERICITY , 2006, 0707.4621.
[33] James R. Schott,et al. A high-dimensional test for the equality of the smallest eigenvalues of a covariance matrix , 2006 .
[34] A. Bejan,et al. LARGEST EIGENVALUES AND SAMPLE COVARIANCE MATRICES. TRACY-WIDOM AND PAINLEVÉ II: COMPUTATIONAL ASPECTS AND REALIZATION IN S-PLUS WITH APPLICATIONS , 2006 .
[35] J. W. Silverstein,et al. Fundamental Limit of Sample Eigenvalue based Detection of Signals in Colored Noise using Relatively Few Samples , 2007, 2007 Conference Record of the Forty-First Asilomar Conference on Signals, Systems and Computers.
[36] Noureddine El Karoui. Tracy–Widom limit for the largest eigenvalue of a large class of complex sample covariance matrices , 2005, math/0503109.
[37] Raymond Kan,et al. COMPUTATIONALLY EFFICIENT RECURSIONS FOR TOP-ORDER INVARIANT POLYNOMIALS WITH APPLICATIONS , 2009, Econometric Theory.
[38] Alan Edelman,et al. Sample Eigenvalue Based Detection of High-Dimensional Signals in White Noise Using Relatively Few Samples , 2007, IEEE Transactions on Signal Processing.
[39] Z. Bai,et al. METHODOLOGIES IN SPECTRAL ANALYSIS OF LARGE DIMENSIONAL RANDOM MATRICES, A REVIEW , 2008 .
[40] B. Nadler,et al. Determining the number of components in a factor model from limited noisy data , 2008 .
[41] David C. Hoyle,et al. Automatic PCA Dimension Selection for High Dimensional Data and Small Sample Sizes , 2008 .
[42] B. Nadler. Finite sample approximation results for principal component analysis: a matrix perturbation approach , 2009, 0901.3245.
[43] A. Onatski. TESTING HYPOTHESES ABOUT THE NUMBER OF FACTORS IN LARGE FACTOR MODELS , 2009 .
[44] Z. Bai,et al. Corrections to LRT on large-dimensional covariance matrix by RMT , 2009, 0902.0552.
[45] S. P'ech'e,et al. The largest eigenvalues of sample covariance matrices for a spiked population: Diagonal case , 2008, 0812.2320.
[46] Boaz Nadler,et al. Non-Parametric Detection of the Number of Signals: Hypothesis Testing and Random Matrix Theory , 2009, IEEE Transactions on Signal Processing.
[47] Raj Rao Nadakuditi,et al. Fundamental Limit of Sample Generalized Eigenvalue Based Detection of Signals in Noise Using Relatively Few Signal-Bearing and Noise-Only Samples , 2009, IEEE Journal of Selected Topics in Signal Processing.
[48] A. Onatski. Determining the Number of Factors from Empirical Distribution of Eigenvalues , 2010, The Review of Economics and Statistics.
[49] Zhidong Bai,et al. CLT for Linear Spectral Statistics , 2010 .
[50] Patrick J. Wolfe,et al. Minimax Rank Estimation for Subspace Tracking , 2009, IEEE Journal of Selected Topics in Signal Processing.
[51] Song-xi Chen,et al. Tests for High-Dimensional Covariance Matrices , 2010, Random Matrices: Theory and Applications.
[52] Xiaoqian Sun,et al. A new test for sphericity of the covariance matrix for high dimensional data , 2010, J. Multivar. Anal..
[53] M. Y. Mo. Rank 1 real Wishart spiked model , 2011, 1101.5144.
[54] Pascal Bianchi,et al. Performance of Statistical Tests for Single-Source Detection Using Random Matrix Theory , 2009, IEEE Transactions on Information Theory.
[55] Alex Bloemendal,et al. Limits of spiked random matrices II , 2011, 1109.3704.
[56] Dong Wang. The Largest Eigenvalue of Real Symmetric, Hermitian and Hermitian Self-dual Random Matrix Models with Rank One External Source, Part I , 2010, 1012.4144.
[57] P. Rigollet,et al. Optimal detection of sparse principal components in high dimension , 2012, 1202.5070.
[58] Alexei Onatski,et al. Asymptotics of the principal components estimator of large factor models with weakly influential factors , 2012 .
[59] Alex Bloemendal,et al. Limits of spiked random matrices I , 2010, Probability Theory and Related Fields.