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Uniform strong consistency of histogram density estimation for dependent process

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  • Xin Yang

Abstract

Histogram density estimator is very intuitive and easy to compute and has been widely adopted. Especially in today's big data environment, people pay more attention to the computational cost and are more willing to choose estimators with less to compute. And so, many scholars have been interested in the various estimates based on the histogram technique. Under strong mixing process, this article studies the uniform strong consistency of histogram density estimator and the convergence rate. Our conditions on the mixing coefficient and the bin width are very mild.

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  • Xin Yang, 2017. "Uniform strong consistency of histogram density estimation for dependent process," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 46(4), pages 1709-1719, February.
    • Handle: RePEc:taf:lstaxx:v:46:y:2017:i:4:p:1709-1719
    DOI: 10.1080/03610926.2015.1026994
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