On minimum L1-norm estimate of the parameter of the Ornstein--Uhlenbeck process

Y. Kutoyants and P. Pilibossian

Statistics & Probability Letters, 1994, vol. 20, issue 2, 117-123

Abstract: We consider the problem of [theta]-parameter estimation by observations of the linear process dXt=[theta]Xt dt+[var epsilon]dWt, XO=xO, O[less-than-or-equals, slant]t[less-than-or-equals, slant]T, where [var epsilon] is a "small" parameter. The asymptotics ([var epsilon] --> 0) of minimum L1-norm estimate is investigated. Here xt([theta]) = x0exp([theta]t). It is proved that this estimate is consistant and the difference [var epsilon]-1([theta]*[var epsilon] - [theta]) converges in probability to a random variable which is (for large T) asymptotically normal.

Keywords: Ornstein--Uhlenbeck; process; Minimum; distance; estimation; L1-norm (search for similar items in EconPapers)
Date: 1994
References: Add references at CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/0167-7152(94)90026-4
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:stapro:v:20:y:1994:i:2:p:117-123

Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
https://shop.elsevie ... _01_ooc_1&version=01

Access Statistics for this article

Statistics & Probability Letters is currently edited by Somnath Datta and Hira L. Koul

More articles in Statistics & Probability Letters from Elsevier
Bibliographic data for series maintained by Catherine Liu ().