The key point of the Bayesian estimation model is that the scaling pattern of species distribution, measured by occupancy and spatial pattern, can be extrapolated across scales.
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A similar analysis can be performed for the general case of the multivariate regression and part of this provides for Bayesian estimation of covariance matrices : see Bayesian multivariate linear regression.
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Time-dependency of team strengths was analyzed by Knorr-Held in 1999 . He used recursive Bayesian estimation to rate football teams : this method was more realistic in comparison to soccer prediction based on common average statistics.
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In the time they were here they created the following articles : Computational anatomy, Group actions in computational anatomy, Bayesian estimation of templates in computational anatomy, Riemannian metric and Lie-bracket in computational anatomy, Large deformation diffeomorphic metric mapping.
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In this estimation, one-shot learning deviates sharply from more traditional Bayesian estimation models which approximate the integral as \ delta ( \ theta ^ { ML } ), in favor of a variational approach which makes use of prior information from previously learnt categories.
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Variational Bayes can be seen as an extension of the EM ( expectation-maximization ) algorithm from maximum a posteriori estimation ( MAP estimation ) of the single most probable value of each parameter to fully Bayesian estimation which computes ( an approximation to ) the entire posterior distribution of the parameters and latent variables.