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Smallest nonparametric tolerance regions

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  • Di Bucchianico, A.
  • Einmahl, J.H.J.

    (Tilburg University, School of Economics and Management)

  • Mushkudiani, N.A.

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Suggested Citation

  • Di Bucchianico, A. & Einmahl, J.H.J. & Mushkudiani, N.A., 2001. "Smallest nonparametric tolerance regions," Other publications TiSEM 436f9be2-d0ad-49af-b6df-9, Tilburg University, School of Economics and Management.
  • Handle: RePEc:tiu:tiutis:436f9be2-d0ad-49af-b6df-99889634d2d0
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    File URL: https://pure.uvt.nl/ws/portalfiles/portal/434252/Smallest.pdf
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    References listed on IDEAS

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    1. J. Beirlant & J. H. J. Einmahl, 1995. "Asymptotic confidence intervals for the length of the shortt under random censoring," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 49(1), pages 1-8, March.
    2. Einmahl, J. H.J. & Mason, D.M., 1992. "Generalized quantile processes," Other publications TiSEM b2a76bac-045d-457f-869f-d, Tilburg University, School of Economics and Management.
    3. Polonik, Wolfgang, 1997. "Minimum volume sets and generalized quantile processes," Stochastic Processes and their Applications, Elsevier, vol. 69(1), pages 1-24, July.
    4. P.J. Rousseeuw & A.M. Leroy, 1988. "A robust scale estimator based on the shortest half," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 42(2), pages 103-116, June.
    5. Nolan, D., 1991. "The excess-mass ellipsoid," Journal of Multivariate Analysis, Elsevier, vol. 39(2), pages 348-371, November.
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    Cited by:

    1. Kedai Cheng & Derek S. Young, 2023. "An Approach for Specifying Trimming and Winsorization Cutoffs," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 28(2), pages 299-323, June.
    2. Amparo Baíllo & Antonio Cuevas, 2006. "Parametric versus nonparametric tolerance regions in detection problems," Computational Statistics, Springer, vol. 21(3), pages 523-536, December.
    3. Florens, Jean-Pierre & Simar, Léopold & Van Keilegom, Ingrid, 2014. "Frontier estimation in nonparametric location-scale models," Journal of Econometrics, Elsevier, vol. 178(P3), pages 456-470.
    4. Serfling, Robert, 2002. "Generalized Quantile Processes Based on Multivariate Depth Functions, with Applications in Nonparametric Multivariate Analysis," Journal of Multivariate Analysis, Elsevier, vol. 83(1), pages 232-247, October.
    5. Ilaria Lucrezia Amerise, 2023. "A direct method for constructing distribution-free tolerance regions," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(5), pages 3941-3954, October.
    6. Frey, Jesse, 2014. "Shorter nonparametric prediction intervals for an order statistic from a future sample," Statistics & Probability Letters, Elsevier, vol. 91(C), pages 69-75.
    7. C. Tsao & Yu-Ling Tseng, 2006. "Confidence estimation for tolerance intervals," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 58(3), pages 441-456, September.
    8. Algo Carè & Simone Garatti & Marco C. Campi, 2017. "A coverage theory for least squares," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 79(5), pages 1367-1389, November.
    9. Olive, David J., 2007. "Prediction intervals for regression models," Computational Statistics & Data Analysis, Elsevier, vol. 51(6), pages 3115-3122, March.
    10. David J. Olive, 2018. "Applications of hyperellipsoidal prediction regions," Statistical Papers, Springer, vol. 59(3), pages 913-931, September.
    11. Jesse Frey, 2010. "Data-driven nonparametric tolerance sets," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 22(2), pages 169-180.

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