In this paper, we propose a Bayesian methodology for receiver function analysis, a key tool in determining the deep structure of the Earth’s crust.We exploit the assumption of sparsity for receiver functions to develop a Bayesian deconvolution

Using SAS/IML : This code uses the EM algorithm to estimate the maximum likelihood (ML) covariance matrix and mean vector in the presence of missing data. This implementation of the EM algorithm or any similar ML approach assumes that the data are

Performs EM update for iterative calculation of Bayesian multiscale MAP estimate in Nowak/Kolaczyk algorithm. Called by BMSPoisInv.m -Performs EM update for iterative calculation of Bayesian multiscale MAP estimate in Nowak/Kolaczy