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Wavelet linear estimation for derivatives of a density from observations of mixtures with varying mixing proportions

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  • B. L. S. Prakasa Rao

    (University of Hyderabad)

Abstract

A wavelet based linear estimator is proposed for the derivatives of a probability density function based on a sample from a finite mixture of components with varying mixing proportions. It extends the linear estimator of a probability density function proposed by Pokhyl’ko (Theor. Probability and Math. Statist, 70 (2005) 135–145). Upper bounds on L 2 and L ∞ losses are obtained for such estimators.

Suggested Citation

  • B. L. S. Prakasa Rao, 2010. "Wavelet linear estimation for derivatives of a density from observations of mixtures with varying mixing proportions," Indian Journal of Pure and Applied Mathematics, Springer, vol. 41(1), pages 275-291, February.
    • Handle: RePEc:spr:indpam:v:41:y:2010:i:1:d:10.1007_s13226-010-0013-1
    DOI: 10.1007/s13226-010-0013-1
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    References listed on IDEAS

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    1. K. Tribouley, 1995. "Practical estimation of multivariate densities using wavelet methods," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 49(1), pages 41-62, March.
    2. Leblanc, Frédérique, 1996. "Wavelet linear density estimator for a discrete-time stochastic process: Lp-losses," Statistics & Probability Letters, Elsevier, vol. 27(1), pages 71-84, March.
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