A Basic Bayesian Object is with following conditional dependency structure:
theta|gamma \sim H(gamma)
X|theta \sim F(theta)
Where H(gamma) is usually called "the prior distribution", F(theta) is called "the observation distribution". Objects of type "LinearGaussianGaussian", "GaussianGaussian", "GaussianInvWishart", "GaussianNIW", "GaussianNIG", "CatDirichlet" and "CatDP" are all "BasicBayesian"s.
The environment where you want to create the BasicBayesian object
An object of class "BasicBayesian".
LinearGaussianGaussian for Linear Gaussian and Gaussian conjugate structure,
GaussianGaussian for Gaussian-Gaussian conjugate structure,
GaussianInvWishart for Gaussian-Inverse-Wishart conjugate structure,
GaussianNIW for Gaussian-NIW conjugate structure,
GaussianNIG for Gaussian-NIG conjugate structure,
CatDirichlet for Categorical-Dirichlet conjugate structure,
CatDP for Categorical-DP conjugate structure ...
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