ECP Reading Tools

Deviation inequalities and moderate deviations for estimators of parameters in an Ornstein-Uhlenbeck process with linear drift

Dublin Core		PKP Metadata Items	Metadata for this Document
1.	Title	Title of document	Deviation inequalities and moderate deviations for estimators of parameters in an Ornstein-Uhlenbeck process with linear drift
2.	Creator	Author's name, affiliation, country	Fuqing Gao; Wuhan University
2.	Creator	Author's name, affiliation, country	Hui Jiang; Nanjing University of Aeronautics
3.	Subject	Discipline(s)
3.	Subject	Keyword(s)	Deviation inequality;logarithmic Sobolev inequality;moderate deviations;Ornstein-Uhlenbeck process
3.	Subject	Subject classification	60F12;62F12;62N02
4.	Description	Abstract	Some deviation inequalities and moderate deviation principles for the maximum likelihood estimators of parameters in an Ornstein-Uhlenbeck process with linear drift are established by the logarithmic Sobolev inequality and the exponential martingale method.
5.	Publisher	Organizing agency, location
6.	Contributor	Sponsor(s)	Research supported by the National Natural Science Foundation of China (10871153)
7.	Date	(YYYY-MM-DD)	2009-05-24
8.	Type	Status & genre	Peer-reviewed Article
8.	Type	Type
9.	Format	File format	PDF
10.	Identifier	Uniform Resource Identifier	http://ecp.ejpecp.org/article/view/1466
10.	Identifier	Digital Object Identifier	10.1214/ECP.v14-1466
11.	Source	Journal/conference title; vol., no. (year)	Electronic Communications in Probability; Vol 14
12.	Language	English=en
14.	Coverage	Geo-spatial location, chronological period, research sample (gender, age, etc.)
15.	Rights	Copyright and permissions	The Electronic Journal of Probability applies the Creative Commons Attribution License (CCAL) to all articles we publish in this journal. Under the CCAL, authors retain ownership of the copyright for their article, but authors allow anyone to download, reuse, reprint, modify, distribute, and/or copy articles published in EJP, so long as the original authors and source are credited. This broad license was developed to facilitate open access to, and free use of, original works of all types. Applying this standard license to your work will ensure your right to make your work freely and openly available. Summary of the Creative Commons Attribution License You are free to copy, distribute, display, and perform the work to make derivative works to make commercial use of the work under the following condition of Attribution: others must attribute the work if displayed on the web or stored in any electronic archive by making a link back to the website of EJP via its Digital Object Identifier (DOI), or if published in other media by acknowledging prior publication in this Journal with a precise citation including the DOI. For any further reuse or distribution, the same terms apply. Any of these conditions can be waived by permission of the Corresponding Author.