Spectral Estimation using Reversible Jump Markov Chain Monte Carlo
Published in in preparation, 2022
Abstract
In this report I apply a reversible jump Markov chain Monte Carlo technique to the problem of estimating an autoregressive (AR) model to data. In doing this I focus on the proposed poles of the AR model. A review of relevant background material is included. And a full specification of the implementation is provided. At this time the attempt has been unsuccessful and only partial results are reported.