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CLUES: A non-parametric clustering method based on local shrinking

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  • Wang, Xiaogang
  • Qiu, Weiliang
  • Zamar, Ruben H.

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  • Wang, Xiaogang & Qiu, Weiliang & Zamar, Ruben H., 2007. "CLUES: A non-parametric clustering method based on local shrinking," Computational Statistics & Data Analysis, Elsevier, vol. 52(1), pages 286-298, September.
    • Handle: RePEc:eee:csdana:v:52:y:2007:i:1:p:286-298
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    References listed on IDEAS

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    1. Lawrence Hubert & Phipps Arabie, 1985. "Comparing partitions," Journal of Classification, Springer;The Classification Society, vol. 2(1), pages 193-218, December.
    2. Glenn Milligan & Martha Cooper, 1985. "An examination of procedures for determining the number of clusters in a data set," Psychometrika, Springer;The Psychometric Society, vol. 50(2), pages 159-179, June.
    3. Mack, Y. P. & Rosenblatt, M., 1979. "Multivariate k-nearest neighbor density estimates," Journal of Multivariate Analysis, Elsevier, vol. 9(1), pages 1-15, March.
    4. M.‐Y. Cheng & P. Hall, 1998. "Calibrating the excess mass and dip tests of modality," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 60(3), pages 579-589.
    5. Fraley C. & Raftery A.E., 2002. "Model-Based Clustering, Discriminant Analysis, and Density Estimation," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 611-631, June.
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    Cited by:

    1. Chang, Fang & Qiu, Weiliang & Zamar, Ruben H. & Lazarus, Ross & Wang, Xiaogang, 2010. "clues: An R Package for Nonparametric Clustering Based on Local Shrinking," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 33(i04).
    2. Qiu Weiliang & He Wenqing & Wang Xiaogang & Lazarus Ross, 2008. "A Marginal Mixture Model for Selecting Differentially Expressed Genes across Two Types of Tissue Samples," The International Journal of Biostatistics, De Gruyter, vol. 4(1), pages 1-30, October.
    3. Jing Qi & Yang Zhou & Zicen Zhao & Shuilin Jin, 2021. "SDImpute: A statistical block imputation method based on cell-level and gene-level information for dropouts in single-cell RNA-seq data," PLOS Computational Biology, Public Library of Science, vol. 17(6), pages 1-20, June.
    4. repec:jss:jstsof:33:i04 is not listed on IDEAS
    5. Fraiman, Ricardo & Justel, Ana & Svarc, Marcela, 2010. "Pattern recognition via projection-based kNN rules," Computational Statistics & Data Analysis, Elsevier, vol. 54(5), pages 1390-1403, May.
    6. Bécue-Bertaut, Monica & Pagès, Jérome, 2008. "Multiple factor analysis and clustering of a mixture of quantitative, categorical and frequency data," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 3255-3268, February.

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