Notes on drift estimation for certain non-recurrent diffusion processes from sampled data

Research output: Contribution to journalArticle

10 Citations (Scopus)

Abstract

Given discrete samples from Ornstein-Uhlenbeck processes, we consider two kinds of approximated MLE's for the drift parameter, which are asymptotically efficient in ergodic case. Our interest is the rate of convergence of those estimators when the process is non-recurrent. We add a remark when the underlying process has a slightly more general drift.

Original languageEnglish
Pages (from-to)2200-2207
Number of pages8
JournalStatistics and Probability Letters
Volume79
Issue number20
DOIs
Publication statusPublished - 2009 Oct 15
Externally publishedYes

Fingerprint

Diffusion Process
Ornstein-Uhlenbeck Process
Rate of Convergence
Estimator
Diffusion process
Ornstein-Uhlenbeck process
Rate of convergence

ASJC Scopus subject areas

  • Statistics, Probability and Uncertainty
  • Statistics and Probability

Cite this

Notes on drift estimation for certain non-recurrent diffusion processes from sampled data. / Shimizu, Yasutaka.

In: Statistics and Probability Letters, Vol. 79, No. 20, 15.10.2009, p. 2200-2207.

Research output: Contribution to journalArticle

@article{f407d03d335c43b481e6ac688481c4d0,
title = "Notes on drift estimation for certain non-recurrent diffusion processes from sampled data",
abstract = "Given discrete samples from Ornstein-Uhlenbeck processes, we consider two kinds of approximated MLE's for the drift parameter, which are asymptotically efficient in ergodic case. Our interest is the rate of convergence of those estimators when the process is non-recurrent. We add a remark when the underlying process has a slightly more general drift.",
author = "Yasutaka Shimizu",
year = "2009",
month = "10",
day = "15",
doi = "10.1016/j.spl.2009.07.015",
language = "English",
volume = "79",
pages = "2200--2207",
journal = "Statistics and Probability Letters",
issn = "0167-7152",
publisher = "Elsevier",
number = "20",

}

TY - JOUR

T1 - Notes on drift estimation for certain non-recurrent diffusion processes from sampled data

AU - Shimizu, Yasutaka

PY - 2009/10/15

Y1 - 2009/10/15

N2 - Given discrete samples from Ornstein-Uhlenbeck processes, we consider two kinds of approximated MLE's for the drift parameter, which are asymptotically efficient in ergodic case. Our interest is the rate of convergence of those estimators when the process is non-recurrent. We add a remark when the underlying process has a slightly more general drift.

AB - Given discrete samples from Ornstein-Uhlenbeck processes, we consider two kinds of approximated MLE's for the drift parameter, which are asymptotically efficient in ergodic case. Our interest is the rate of convergence of those estimators when the process is non-recurrent. We add a remark when the underlying process has a slightly more general drift.

UR - http://www.scopus.com/inward/record.url?scp=70149120709&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=70149120709&partnerID=8YFLogxK

U2 - 10.1016/j.spl.2009.07.015

DO - 10.1016/j.spl.2009.07.015

M3 - Article

AN - SCOPUS:70149120709

VL - 79

SP - 2200

EP - 2207

JO - Statistics and Probability Letters

JF - Statistics and Probability Letters

SN - 0167-7152

IS - 20

ER -