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Optimal Choice Of Nonparametric Estimates Of A Density And Of Its Derivatives

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  • Horová Ivana
  • Vieu Philippe
  • Zelinka Jiří

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  • Horová Ivana & Vieu Philippe & Zelinka Jiří, 2002. "Optimal Choice Of Nonparametric Estimates Of A Density And Of Its Derivatives," Statistics & Risk Modeling, De Gruyter, vol. 20(1-4), pages 355-378, April.
    • Handle: RePEc:bpj:strimo:v:20:y:2002:i:1-4:p:355-378:n:20
    DOI: 10.1524/strm.2002.20.14.355
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    References listed on IDEAS

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    1. Duc Devroye & J. Beirlant & R. Cao & R. Fraiman & P. Hall & M. Jones & Gábor Lugosi & E. Mammen & J. Marron & C. Sánchez-Sellero & J. Uña & F. Udina & L. Devroye, 1997. "Universal smoothing factor selection in density estimation: theory and practice," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 6(2), pages 223-320, December.
    2. Philippe Vieu, 1999. "Multiple Kernel Procedure: an Asymptotic Support," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 26(1), pages 61-72, March.
    3. Wand, M. P. & Devroye, Luc, 1993. "How easy is a given density to estimate?," Computational Statistics & Data Analysis, Elsevier, vol. 16(3), pages 311-323, September.
    4. Vieu, Philippe, 1996. "A note on density mode estimation," Statistics & Probability Letters, Elsevier, vol. 26(4), pages 297-307, March.
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    Cited by:

    1. Hu, Shuowen & Poskitt, D.S. & Zhang, Xibin, 2012. "Bayesian adaptive bandwidth kernel density estimation of irregular multivariate distributions," Computational Statistics & Data Analysis, Elsevier, vol. 56(3), pages 732-740.
    2. Horová, Ivana & Koláček, Jan & Vopatová, Kamila, 2013. "Full bandwidth matrix selectors for gradient kernel density estimate," Computational Statistics & Data Analysis, Elsevier, vol. 57(1), pages 364-376.

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