Stein’s method in high dimensional classification and applications
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DOI: 10.1016/j.csda.2014.08.009
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- Dudoit S. & Fridlyand J. & Speed T. P, 2002. "Comparison of Discrimination Methods for the Classification of Tumors Using Gene Expression Data," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 77-87, March.
- Park, Junyong, 2009. "Independent rule in classification of multivariate binary data," Journal of Multivariate Analysis, Elsevier, vol. 100(10), pages 2270-2286, November.
- Fan J. & Li R., 2001. "Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 1348-1360, December.
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Keywords
Classification; Sparsity; High dimension; Stein’s estimator; Shrinkage;All these keywords.
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