Projects per year
Bayesian analysis of Laser Interferometer Space Antenna (LISA) data sets based on Markov chain Monte Carlo methods has been shown to be a challenging problem, in part due to the complicated structure of the likelihood function consisting of several isolated local maxima that dramatically reduces the efficiency of the sampling techniques. Here we introduce a new fully Markovian algorithm, a delayed rejection Metropolis-Hastings Markov chain Monte Carlo method, to efficiently explore these kind of structures and we demonstrate its performance on selected LISA data sets containing a known number of stellar-mass binary signals embedded in Gaussian stationary noise.
|Number of pages||1|
|Journal||Classical and Quantum Gravity|
|Publication status||Published - 1 Oct 2009|
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- 1 Finished
Birmingham Astrophysics - Rolling Grant 2007-2012
Ponman, T., Cruise, M., Freise, A., Raychaudhury, S., Smith, G., Speake, C., Stevens, I. & Vecchio, A.
SCIENCE & TECHNOLOGY FACILITIES COUNCIL
1/04/07 → 31/03/12
Project: Research Councils