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Modelling coloured residual noise in gravitational-wave signal processing

MPG-Autoren
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Röver,  Christian
Observational Relativity and Cosmology, AEI-Hannover, MPI for Gravitational Physics, Max Planck Society;

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Volltexte (frei zugänglich)

0804.3853v2.pdf
(Preprint), 488KB

CQG_28_1_015010.pdf
(beliebiger Volltext), 501KB

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Zitation

Röver, C., Meyer, R., & Christensen, N. (2011). Modelling coloured residual noise in gravitational-wave signal processing. Classical and quantum gravity, 28(1): 015010. doi:10.1088/0264-9381/28/1/015010.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-0013-600E-4
Zusammenfassung
This paper introduces a novel approach to modelling non-white residual noise in discrete time series. We present a Markov chain Monte Carlo (MCMC) algorithm for combined posterior inference on signal and noise parameters. By choosing a conjugate prior distribution for the noise parameters, the additional Gibbs sampling steps have a particularly simple form and are easy to implement as well as fast to run. Furthermore, the sampling-based approach allows for easy inference on the autocovariance function. The model is illustrated using a well-known sunspot dataset as well as a simulated dataset of a chirp signal embedded in non-Normal, coloured noise where the spectrum is regarded as a nuisance parameter.