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Multivariate wavelet density estimation for strong mixing stratified size-biased sample

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  • Junke Kou
  • Kaili Cui

Abstract

This paper considers wavelet estimations of a multivariate density function based on stratified size-biased and strong mixing data. We provide upper bounds of the mean integrated squared error for linear and nonlinear wavelet estimators in Besov space Bp,qs(Rd). It is shown that the linear estimator achieves the optimal convergence rate in the case of p≥2. Moreover, the convergence rate of nonlinear estimator coincides with the optimal convergence rate up to a ln N factor for p∈[1,+∞). In addition, the nonlinear wavelet estimator is adaptive.

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  • Junke Kou & Kaili Cui, 2023. "Multivariate wavelet density estimation for strong mixing stratified size-biased sample," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 52(6), pages 1888-1904, March.
    • Handle: RePEc:taf:lstaxx:v:52:y:2023:i:6:p:1888-1904
    DOI: 10.1080/03610926.2021.1941111
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