Model selection and Bayesian inference for high resolution seabed reflection inversion
This paper applies Bayesian inference, including model selection and posterior parameter inference, to inversion of seabed reflection data to resolve sediment structure at a spatial scale below the pulse length of the acoustic source. A practical approach to model selection is used, employing the Bayesian information criterion to decide on the number of sediment layers needed to sufficiently fit the data while satisfying parsimony to avoid overparametrization. Posterior parameter inference is...[Show more]
|Collections||ANU Research Publications|
|Source:||Journal of the Acoustical Society of America|
|01_Dettmer_Model_selection_and_Bayesian_2009.pdf||2.43 MB||Adobe PDF||Request a copy|
Items in Open Research are protected by copyright, with all rights reserved, unless otherwise indicated.