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Strong consistency and rates of convergence for a random estimator of a fuzzy set

Listed author(s):
  • Terán, Pedro
  • López-Díaz, Miguel
Registered author(s):

    An approximation scheme for estimating a fixed, unknown fuzzy set from random samples taken from the nested random set defined by its α-level sets is presented. Its strong consistency is studied, giving rates of convergence in four metrics. A simulation study suggests that the behaviour for moderately small samples is coherent with the theoretical rate of convergence valid for large samples.

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    Article provided by Elsevier in its journal Computational Statistics & Data Analysis.

    Volume (Year): 77 (2014)
    Issue (Month): C ()
    Pages: 130-145

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    Handle: RePEc:eee:csdana:v:77:y:2014:i:c:p:130-145
    DOI: 10.1016/j.csda.2014.02.016
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    1. Baíllo, Amparo & Cuesta-Albertos, Juan A. & Cuevas, Antonio, 2001. "Convergence rates in nonparametric estimation of level sets," Statistics & Probability Letters, Elsevier, vol. 53(1), pages 27-35, May.
    2. Hall, Peter & Nussbaum, Michael & Stern, Steven E., 1997. "On the Estimation of a Support Curve of Indeterminate Sharpness," Journal of Multivariate Analysis, Elsevier, vol. 62(2), pages 204-232, August.
    3. Norberg, Tommy, 1987. "Semicontinuous processes in multi-dimensional extreme value theory," Stochastic Processes and their Applications, Elsevier, vol. 25, pages 27-55.
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