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Communication Dans Un Congrès Année : 2006

Change-point detection in astronomical data by using a hierarchical model and a bayesian sampling approach

Change-point Detection in Astronomical Data by using a Hierarchical Model and a Bayesian Sampling Approach

Résumé

Detection of significant intensity variations in astronomical time-series can be achieved with a hierarchical Bayesian approach to a piecewise constant Poisson rate model. A Gibbs sampling strategy allows joint estimation of the unknown parameters and hyperparameters. Results with real and synthetic photon counting data illustrate the performance of the proposed algorithm. An extension to joint segmentation of multiple time series is also discussed.
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Dates et versions

hal-04251226 , version 1 (20-10-2023)

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Citer

Nicolas Dobigeon, Jean-Yves Tourneret, Jeffrey D. Scargle. Change-point Detection in Astronomical Data by using a Hierarchical Model and a Bayesian Sampling Approach. 13th Workshop on Statistical Signal Processing (IEEE/SP 2005), IEEE, Jul 2005, Bordeaux, France. (support électronique), ⟨10.1109/SSP.2005.1628623⟩. ⟨hal-04251226⟩
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