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Bayesian curve fitting using MCMC with applications to signal segmentation

Abstract:

We propose some Bayesian methods to address the problem of fitting a signal modeled by a sequence of piecewise constant linear (in the parameters) regression models, for example, autoregressive or Volterra models. A joint prior distribution is set up over the number of the changepoints/knots, their positions, and over the orders of the linear regression models within each segment if these are unknown. Hierarchical priors are developed and, as the resulting posterior probability distributions ...

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Publication status:
Published

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Publisher copy:
10.1109/78.984776

Authors


Punskaya, E More by this author
Andrieu, C More by this author
More by this author
Institution:
University of Oxford
Department:
Oxford, MPLS, Statistics
Fitzgerald, WJ More by this author
Journal:
IEEE TRANSACTIONS ON SIGNAL PROCESSING
Volume:
50
Issue:
3
Pages:
747-758
Publication date:
2002-03-05
DOI:
ISSN:
1053-587X
URN:
uuid:f5a3962e-d1b9-4903-9c5c-905bec48f950
Source identifiers:
190610
Local pid:
pubs:190610

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