Detecting Extra-solar Planets with a Bayesian hybrid MCMC Kepler periodogram
Abstract
A Bayesian re-analysis of published radial velocity data sets is providing evidence for additional planetary candidates. The nonlinear model fitting is accomplished with a new hybrid Markov chain Monte Carlo (HMCMC) algorithm which incorporates parallel tempering, simulated annealing and genetic crossover operations. Each of these features facilitate the detection of a global minimum in chi^2. By combining all three, the HMCMC greatly increases the probability of realizing this goal. When applied to the Kepler problem it acts as a powerful multi-planet Kepler periodogram for both parameter estimation and model selection. The HMCMC algorithm is embedded in a unique two stage adaptive control system that automates the tuning of the MCMC proposal distributions through an annealing operation.
Cite
@article{arxiv.0902.2014,
title = {Detecting Extra-solar Planets with a Bayesian hybrid MCMC Kepler periodogram},
author = {P. C. Gregory},
journal= {arXiv preprint arXiv:0902.2014},
year = {2009}
}
Comments
In JSM Proceedings, Denver, CO, Aug. 3, 2008: American Statistical Association