English

Using Markov chain Monte Carlo methods for estimating parameters with gravitational radiation data

General Relativity and Quantum Cosmology 2009-11-07 v1

Abstract

We present a Bayesian approach to the problem of determining parameters for coalescing binary systems observed with laser interferometric detectors. By applying a Markov Chain Monte Carlo (MCMC) algorithm, specifically the Gibbs sampler, we demonstrate the potential that MCMC techniques may hold for the computation of posterior distributions of parameters of the binary system that created the gravity radiation signal. We describe the use of the Gibbs sampler method, and present examples whereby signals are detected and analyzed from within noisy data.

Keywords

Cite

@article{arxiv.gr-qc/0102018,
  title  = {Using Markov chain Monte Carlo methods for estimating parameters with gravitational radiation data},
  author = {Nelson Christensen and Renate Meyer},
  journal= {arXiv preprint arXiv:gr-qc/0102018},
  year   = {2009}
}

Comments

21 pages, 10 figures