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Authors: Neil J. Cornish, Tyson B. Littenberg

Date: 13 Apr 2007

Abstract: An important class of gravitational wave sources for the Laser Interferometer Space Antenna (LISA) are the millions of low-mass binary systems within our own galaxy, tens of thousands of which will be detectable. Because the number of resolvable galactic binaries is unknown, we are faced with a model selection problem. Not only are the number of sources unknown, but also the number of parameters required to model the waveforms. A significant subset of the resolvable galactic binaries will exhibit orbital frequency evolution, while a smaller number will have measurable eccentricity. In the Bayesian approach to model selection one needs to compute the Bayes factor for competing models. Here we explore various methods for computing Bayes factors in the context of determining which systems have measurable frequency evolution. The methods explored include a Reverse Jump Markov Chain Monte Carlo (RJMCMC) algorithm, Savage-Dickie density ratios, the Schwarz-Bayes Information Criteria (BIC), and the Laplace approximation to the model evidence. We find good agreement between all of the approaches.

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