Bayesian Estimation of Time Delays Between Unevenly Sampled Signals

A method for estimating time delays between signals that are irregularly sampled is presented. The approach is based on postulating a latent variable model from which the observed signals have been generated and computing the posterior distribution of the delay. This is achieved partly by exact marginalisation and partly by using MCMC methods. Experiments with artificial data show the effectiveness of the proposed approach while results with real-world gravitational lens data provide the main motivation for this work.