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Bias-Corrected Diagonal Discriminant Rules for High-Dimensional Classification

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  • Song Huang
  • Tiejun Tong
  • Hongyu Zhao

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  • Song Huang & Tiejun Tong & Hongyu Zhao, 2010. "Bias-Corrected Diagonal Discriminant Rules for High-Dimensional Classification," Biometrics, The International Biometric Society, vol. 66(4), pages 1096-1106, December.
    • Handle: RePEc:bla:biomet:v:66:y:2010:i:4:p:1096-1106
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    File URL: http://hdl.handle.net/10.1111/j.1541-0420.2010.01395.x
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    References listed on IDEAS

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    1. Tong, Tiejun & Wang, Yuedong, 2007. "Optimal Shrinkage Estimation of Variances With Applications to Microarray Data Analysis," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 113-122, March.
    2. Herbert Pang & Tiejun Tong & Hongyu Zhao, 2009. "Shrinkage-based Diagonal Discriminant Analysis and Its Applications in High-Dimensional Data," Biometrics, The International Biometric Society, vol. 65(4), pages 1021-1029, December.
    3. Lee, Jae Won & Lee, Jung Bok & Park, Mira & Song, Seuck Heun, 2005. "An extensive comparison of recent classification tools applied to microarray data," Computational Statistics & Data Analysis, Elsevier, vol. 48(4), pages 869-885, April.
    4. Xingye Qiao & Yufeng Liu, 2009. "Adaptive Weighted Learning for Unbalanced Multicategory Classification," Biometrics, The International Biometric Society, vol. 65(1), pages 159-168, March.
    5. Debashis Ghosh, 2003. "Penalized Discriminant Methods for the Classification of Tumors from Gene Expression Data," Biometrics, The International Biometric Society, vol. 59(4), pages 992-1000, December.
    6. Dai Jian J & Lieu Linh & Rocke David, 2006. "Dimension Reduction for Classification with Gene Expression Microarray Data," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 5(1), pages 1-21, February.
    7. Mette Langaas & Bo Henry Lindqvist & Egil Ferkingstad, 2005. "Estimating the proportion of true null hypotheses, with application to DNA microarray data," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 67(4), pages 555-572, September.
    8. Lee, Yoonkyung & Lin, Yi & Wahba, Grace, 2004. "Multicategory Support Vector Machines: Theory and Application to the Classification of Microarray Data and Satellite Radiance Data," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 67-81, January.
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    Cited by:

    1. Makoto Aoshima & Kazuyoshi Yata, 2019. "High-Dimensional Quadratic Classifiers in Non-sparse Settings," Methodology and Computing in Applied Probability, Springer, vol. 21(3), pages 663-682, September.
    2. Rauf Ahmad, M. & Pavlenko, Tatjana, 2018. "A U-classifier for high-dimensional data under non-normality," Journal of Multivariate Analysis, Elsevier, vol. 167(C), pages 269-283.
    3. Makoto Aoshima & Kazuyoshi Yata, 2014. "A distance-based, misclassification rate adjusted classifier for multiclass, high-dimensional data," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 66(5), pages 983-1010, October.

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