Sequential Maximum Likelihood Estimation for the Hyperbolic Diffusion Process

Nenghui Kuang () and Huantian Xie
Additional contact information
Nenghui Kuang: Hunan University of Science and Technology
Huantian Xie: Wuhan University

Methodology and Computing in Applied Probability, 2015, vol. 17, issue 2, 373-381

Abstract: Abstract This paper investigates the properties of a sequential maximum likelihood estimator (SMLE) of the unknown parameter for the hyperbolic diffusion process. We derive the explicit formulas for the sequential estimator and its mean squared error (MSE). The estimator is proved to be closed, unbiased, normally distributed and strongly consistent. Finally a simulation study is presented to illustrate the efficiency of the estimator.

Keywords: Sequential maximum likelihood estimator; Hyperbolic diffusion process; Unbiasedness; Mean squared error; Efficiency; 60H10; 62F99 (search for similar items in EconPapers)
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://link.springer.com/10.1007/s11009-013-9362-7 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

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:spr:metcap:v:17:y:2015:i:2:d:10.1007_s11009-013-9362-7

Ordering information: This journal article can be ordered from
https://www.springer.com/journal/11009

DOI: 10.1007/s11009-013-9362-7

Access Statistics for this article

Methodology and Computing in Applied Probability is currently edited by Joseph Glaz

More articles in Methodology and Computing in Applied Probability from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().