Bayesian evidence computation for model selection in non-linear geoacoustic inference problems
This paper applies a general Bayesian inference approach, based on Bayesian evidence computation, to geoacoustic inversion of interface-wave dispersion data. Quantitative model selection is carried out by computing the evidence (normalizing constants) for several model parameterizations using annealed importance sampling. The resulting posterior probability density estimate is compared to estimates obtained from Metropolis-Hastings sampling to ensure consistent results. The approach is applied...[Show more]
|Collections||ANU Research Publications|
|Source:||Journal of the Acoustical Society of America|
|01_Dettmer_Bayesian_evidence_computation_2010.pdf||2.19 MB||Adobe PDF||Request a copy|
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