An Adaptive Derivative Free Method for Bayesian Posterior Approximation
Raitoharju, Matti; Ali-Löytty, Simo (2012)
Julkaisun pysyvä osoite on
In the Gaussian mixture approach a Bayesian posterior probability distribution function is approximated using a weighted sum of Gaussians. This work presents a novel method for generating a Gaussian mixture by splitting the prior taking the direction of maximum nonlinearity into account. The proposed method is computationally feasible and does not require analytical differentiation. Tests show that the method approximates the posterior better with fewer Gaussian components than existing methods.
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