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Bootstrap bandwidth selection in kernel density estimation from a contaminated sample

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  • A. Delaigle
  • I. Gijbels
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    Abstract

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    File URL: http://hdl.handle.net/10.1007/BF02530523
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    Bibliographic Info

    Article provided by Springer in its journal Annals of the Institute of Statistical Mathematics.

    Volume (Year): 56 (2004)
    Issue (Month): 1 (March)
    Pages: 19-47

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    Handle: RePEc:spr:aistmt:v:56:y:2004:i:1:p:19-47

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    Web page: http://www.springerlink.com/link.asp?id=102845

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    Related research

    Keywords: Bandwidth selection; bootstrap; consistency; deconvolution; errors-in-variables; kernel density estimation;

    References

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    1. Hall, Peter, 1990. "Using the bootstrap to estimate mean squared error and select smoothing parameter in nonparametric problems," Journal of Multivariate Analysis, Elsevier, vol. 32(2), pages 177-203, February.
    2. Rachdi, Mustapha & Sabre, Rachid, 2000. "Consistent estimates of the mode of the probability density function in nonparametric deconvolution problems," Statistics & Probability Letters, Elsevier, vol. 47(2), pages 105-114, April.
    3. Stefanski, Leonard A., 1990. "Rates of convergence of some estimators in a class of deconvolution problems," Statistics & Probability Letters, Elsevier, vol. 9(3), pages 229-235, March.
    4. Delaigle, A. & Gijbels, I., 2004. "Practical bandwidth selection in deconvolution kernel density estimation," Computational Statistics & Data Analysis, Elsevier, Elsevier, vol. 45(2), pages 249-267, March.
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    Cited by:
    1. Wang, B. & Wertelecki, W., 2013. "Density estimation for data with rounding errors," Computational Statistics & Data Analysis, Elsevier, Elsevier, vol. 65(C), pages 4-12.
    2. Johanna Kappus & Gwennaelle Mabon, 2013. "Adaptive Density Estimation in Deconvolution Problems with Unknown Error Distribution," Working Papers 2013-31, Centre de Recherche en Economie et Statistique.
    3. Julie McIntyre & Leonard Stefanski, 2011. "Density Estimation with Replicate Heteroscedastic Measurements," Annals of the Institute of Statistical Mathematics, Springer, Springer, vol. 63(1), pages 81-99, February.
    4. Adriano Z. Zambom & Ronaldo Dias, 2013. "A Review of Kernel Density Estimation with Applications to Econometrics," International Econometric Review (IER), Econometric Research Association, Econometric Research Association, vol. 5(1), pages 20-42, April.
    5. Delaigle, Aurore & Hall, Peter, 2006. "On optimal kernel choice for deconvolution," Statistics & Probability Letters, Elsevier, vol. 76(15), pages 1594-1602, September.
    6. William Horrace & Christopher Parmeter, 2011. "Semiparametric deconvolution with unknown error variance," Journal of Productivity Analysis, Springer, vol. 35(2), pages 129-141, April.
    7. Delaigle, A. & Gijbels, I., 2006. "Data-driven boundary estimation in deconvolution problems," Computational Statistics & Data Analysis, Elsevier, Elsevier, vol. 50(8), pages 1965-1994, April.

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