Nonparametric density estimators based on nonstationary absolutely regular random sequences
type: Item
instance of: scholarly article
title: Nonparametric density estimators based on nonstationary absolutely regular random sequences
zbMATH Open document ID: 0897.62036
DOI: 10.1155/S1048953396000238
author: Michel Harel
author: Madan L. Puri
published in: Journal of Applied Mathematics and Stochastic Analysis
publication date: 1996-11-18T00:00:00Z
full work available at URL: https://eudml.org/doc/47991
review text: Summary: 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.
Mathematics Subject Classification ID: 62G07
Mathematics Subject Classification ID: 60F05
Mathematics Subject Classification ID: 62G20
Mathematics Subject Classification ID: 62M05
Mathematics Subject Classification ID: 62M10
zbMATH DE Number: 947008
zbMATH Keywords: density estimators
zbMATH Keywords: nonstationary absolutely regular random sequences
zbMATH Keywords: strong mixing
zbMATH Keywords: phi-mixing
zbMATH Keywords: central limit theorems
zbMATH Keywords: ARMA processes
MaRDI profile type: Publication
description: scientific article; zbMATH DE number 947008