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On the asymptotic normality of multistage integrated density derivatives kernel estimators

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  • Tenreiro, Carlos

Abstract

The estimation of integrated density derivatives is a crucial problem which arises in data-based methods for choosing the bandwidth of kernel and histogram estimators. In this paper, we establish the asymptotic normality of a multistage kernel estimator of such quantities, by showing that under some regularity conditions on the underlying density function and on the kernels used on the multistage estimation procedure, the multistage kernel estimator with at least one step of estimation is asymptotically equivalent in probability to the kernel estimator with associated optimal bandwidth. An application to kernel density bandwidth selection is also presented. In particular, we conclude that the common used plug-in bandwidth do not attempt the optimal rate of convergence to the optimal bandwidth.

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  • Tenreiro, Carlos, 2003. "On the asymptotic normality of multistage integrated density derivatives kernel estimators," Statistics & Probability Letters, Elsevier, vol. 64(3), pages 311-322, September.
    • Handle: RePEc:eee:stapro:v:64:y:2003:i:3:p:311-322
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    2. Lejeune, Michel & Sarda, Pascal, 1992. "Smooth estimators of distribution and density functions," Computational Statistics & Data Analysis, Elsevier, vol. 14(4), pages 457-471, November.
    3. Hall, Peter & Marron, J. S., 1987. "Estimation of integrated squared density derivatives," Statistics & Probability Letters, Elsevier, vol. 6(2), pages 109-115, November.
    4. Tenreiro, Carlos, 2001. "On the asymptotic behaviour of the integrated square error of kernel density estimators with data-dependent bandwidth," Statistics & Probability Letters, Elsevier, vol. 53(3), pages 283-292, June.
    5. Jones, M. C., 1990. "The performance of kernel density functions in kernel distribution function estimation," Statistics & Probability Letters, Elsevier, vol. 9(2), pages 129-132, February.
    6. Jones, M. C. & Sheather, S. J., 1991. "Using non-stochastic terms to advantage in kernel-based estimation of integrated squared density derivatives," Statistics & Probability Letters, Elsevier, vol. 11(6), pages 511-514, June.
    7. Hall, Peter, 1984. "Central limit theorem for integrated square error of multivariate nonparametric density estimators," Journal of Multivariate Analysis, Elsevier, vol. 14(1), pages 1-16, February.
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    Cited by:

    1. José E. Chacón & Carlos Tenreiro, 2012. "Exact and Asymptotically Optimal Bandwidths for Kernel Estimation of Density Functionals," Methodology and Computing in Applied Probability, Springer, vol. 14(3), pages 523-548, September.
    2. Christopher Withers & Saralees Nadarajah, 2011. "Nonparametric confidence intervals for the integral of a function of an unknown density," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 23(4), pages 943-966.

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