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• W2989752013 abstract "We consider the recursive estimation of the probability density function of continuous random variables from a strongly mixing random sample. We revisit here earlier research on this subject by considering a more general class of recursive estimators, including the usual ones. We derive the quadratic mean error of the considered class of estimators. Moreover, we establish a central limit theorem by using Lindeberg’s method resulting in a simplification of the existing assumptions on the sequence of smooth parameters and the mixing coefficient. This is the main contribution of this paper. Finally, the feasibility of the proposed estimator is illustrated throughout an empirical study." @default.
• W2989752013 created "2019-12-05" @default.
• W2989752013 creator A5059752910 @default.
• W2989752013 creator A5067351099 @default.
• W2989752013 date "2019-11-21" @default.
• W2989752013 modified "2023-10-17" @default.
• W2989752013 title "Recursive kernel density estimation for time series" @default.
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• W2989752013 hasPublicationYear "2019" @default.
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