Economics at your fingertips  

On Estimation for Brownian Motion Governed by Telegraph Process with Multiple Off States

V. Pozdnyakov (), L. M. Elbroch, C. Hu, T. Meyer and J. Yan
Additional contact information
V. Pozdnyakov: University of Connecticut
C. Hu: University of Connecticut
T. Meyer: University of Connecticut
J. Yan: University of Connecticut

Methodology and Computing in Applied Probability, 2020, vol. 22, issue 3, 1275-1291

Abstract: Abstract Brownian motion whose infinitesimal variance changes according to a three-state continuous-time Markov Chain is studied. This Markov Chain can be viewed as a telegraph process with one on state and two off states. We first derive the distribution of occupation time of the on state. Then the result is used to develop a likelihood estimation procedure when the stochastic process at hand is observed at discrete, possibly irregularly spaced time points. The likelihood function is evaluated with the forward algorithm in the general framework of hidden Markov models. The analytic results are confirmed with simulation studies. The estimation procedure is applied to analyze the position data from a mountain lion.

Keywords: Forward algorithm; Likelihood estimation; Markov process; Occupation time; 62M05; 62P10 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed

Downloads: (external link) 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:

Ordering information: This journal article can be ordered from

DOI: 10.1007/s11009-020-09774-1

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 ().

Page updated 2022-05-12
Handle: RePEc:spr:metcap:v:22:y:2020:i:3:d:10.1007_s11009-020-09774-1