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Activity Number: 256 - Contributed Poster Presentations: Section on Bayesian Statistical Science
Type: Contributed
Date/Time: Monday, July 30, 2018 : 2:00 PM to 3:50 PM
Sponsor: Section on Bayesian Statistical Science
Abstract #333064
Title: Simultaneous Bayesian Model Search and Change-Points Detection for Non-Stationary Oscillatory Processes
Author(s): Beniamino Hadj-Amar* and Barbel Finkenstadt
Companies: The University of Warwick and The University of Warwick
Keywords: Change-points; Spectral analysis; RJMCMC

The analysis of time series that show oscillatory and - more or less - periodic behaviour is a common task in many sciences. In particular, the non-stationary analysis of cyclical data that show regime shifts in periodicity, amplitude and phase is challenging as the timing and number of such changes is usually unknown. We propose a methodology for detecting such regime shifts using several Bayesian transdimensional Markov chain Monte Carlo algorithms which allow for model searches between parameters subspaces of different dimensionality. Our algorithm incorporates mutiple model searches, namely the number of regimes and the harmonic models that capture the relevant frequencies along with their amplitudes and phases within each regime. We illustrate the use of the methodology for data from experiments on rodents to detect instances of sleep apnoea.

Authors who are presenting talks have a * after their name.

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