Efficient density estimation for ergodic diffusion processes
type: Item
instance of: scholarly article
title: Efficient density estimation for ergodic diffusion processes
zbMATH Open document ID: 0953.62085
DOI: 10.1023/A:1009919612081
published in: Statistical Inference for Stochastic Processes
publication date: 2001-01-08T00:00:00Z
review text: The problem of asymptotically efficient estimation of the density of the invariant measure of a diffusion process is considered. An efficient estimator is defined by the minimax lower bound on the risk of all estimators. The author shows that the local-time and kernel-type estimators are asymptotically efficient for the loss functions with polynomial majorants. The asymptotic behavior of a wide class of unbiased estimators with the same limit variances is also discussed.
Mathematics Subject Classification ID: 62M05
Mathematics Subject Classification ID: 62G07
Mathematics Subject Classification ID: 62G20
zbMATH DE Number: 1396070
zbMATH Keywords: diffusion processes
zbMATH Keywords: density estimation
zbMATH Keywords: minimax bound
author: Yu. A. Kutoyants
reviewed by: Yu. N. Lin'kov
MaRDI profile type: Publication
full work available at URL: a:1009919612081
OpenAlex ID: W1493032750
Recommended article: On efficient estimation of invariant density for ergodic diffusion processes
Recommended article: On unbiased density estimation for ergodic diffusion
Recommended article: On density estimation from ergodic processes
Recommended article: Q4251571
Recommended article: Q3645225
Recommended article: Efficiency of the empirical distribution for ergodic diffusion
description: scientific article; zbMATH DE number 1396070