Generate the MPE of (mu,Sigma) in following GaussianNIW structure:
mu,Sigma|m,k,v,S \sim NIW(m,k,v,S)
x|mu,Sigma \sim Gaussian(mu,Sigma)
Where NIW() is the Normal-Inverse-Wishart distribution, Gaussian() is the Gaussian distribution. See
dGaussian for the definitions of these distribution.
The model structure and prior parameters are stored in a "GaussianNIW" object.
The MPE estimates are:
(mu_MPE,Sigma_MPE) = E(mu,Sigma|m,k,v,S,x)
A "GaussianNIW" object.
Additional arguments to be passed to other inherited types.
A named list, the MPE estimate of mu and Sigma.
Murphy, Kevin P. "Conjugate Bayesian analysis of the Gaussian distribution." def 1.22 (2007): 16.
Gelman, Andrew, et al. "Bayesian Data Analysis Chapman & Hall." CRC Texts in Statistical Science (2004).
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