STATISTICS COLLOQUIUM
Vladimir Pozdnyakov, Professor
Department of Statistics
University of Connecticut
Discretely Observed Brownian Motion Governed by a Telegraph Process: Estimation
Abstract
A Brownian motion whose infinitesimal variance alternates according to a telegraph process is considered. This stochastic process can be employed to model variety of real-word situations. In this work we applied our findings for animal movement analysis. The main goal is to develop an estimation procedure for underlying model parameters when the Brownian Motion governed by telegraph process is observed discretely. Resulting sequence of observations is not Markov. But since the location-state process is Markov, the likelihood estimation can be done with help of Hidden Markov Model tools. Further extensions of the model are discussed. More specifically, we consider (1) introducing an additional hidden state and (2) incorporating measurement errors into the model. (joint work with Chaoran Hu, Mark Elbroch, Tom Meyer, and Jun Yan)
Event address for attendees:
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Access code: 120 157 9936 Date and Time: Wednesday, September 30, 2020 4:00 p.m. Duration: 1 hour | | |
For more information, contact: Tracy Burke at tracy.burke@uconn.edu