Nonparametric density estimators based on nonstationary absolutely regular random sequences

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Date

1996

Authors

Journal Title

Journal ISSN

Volume Title

Publisher

Journal of Applied Mathematics and Stochastic Analysis

Permanent Link

https://hdl.handle.net/2022/22082

Abstract

In this paper, the central limit theorems for the density estimator and for the integrated square error are proved for the case when the underlying sequence of random variables is nonstationary. Applications to Markov processes and ARMA processes are provided.

Description

Publisher's, offprint version

Keywords

Density Estimators, Nonstationary Absolutely Regular Random Sequences, Strong Mixing, p-Mixing, Markov Processes, ARMA Processes

Citation

Puri, M. L. “Nonparametric density estimators based on nonstationary absolutely regular random sequences.” Journal of Applied Mathematics and Stochastic Analysis (1996), Volume 9 Issue 3, 233–254. Co-author: Michel Harel.

Journal

DOI

https://doi.org/10.1155/S1048953396000238

Link(s) to data and video for this item

https://www.hindawi.com/journals/ijsa/1996/189689/abs/

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Article

Collections

Madan Lal Puri Collection