A selection procedure for estimating the number of signal components
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Publication:1611816
DOI10.1016/S0378-3758(01)00268-3zbMath0992.62023OpenAlexW2034677010WikidataQ127846619 ScholiaQ127846619MaRDI QIDQ1611816
Publication date: 28 August 2002
Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/s0378-3758(01)00268-3
least favorable configurationmultivariate normal distributioncorrect selectionmultiplicity of smallest eigenvalues
Multivariate distribution of statistics (62H10) Exact distribution theory in statistics (62E15) Statistical ranking and selection procedures (62F07)
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Cites Work
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- A decision procedure for determining the number of components in principal component analysis
- On the evaluation of some distributions that arise in simultaneous tests for the equality of the latent roots of the covariance matrix
- Asymptotic expansions of the distributions of the latent roots and the latent vector of the Wishart and multivariate F matrices
- Screening among multivariate normal data
- On detection of the number of signals in presence of white noise
- TESTS OF SIGNIFICANCE FOR THE LATENT ROOTS OF COVARIANCE AND CORRELATION MATRICES
- Tables for the extreme roots of the wishart matrix
- The Distribution of the Latent Roots of the Covariance Matrix
- Joint Distribution of the Extreme Roots of a Covariance Matrix
- Distributions of Matrix Variates and Latent Roots Derived from Normal Samples
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