Inference of Parameters of Normal Distributions from a Mixture of Normals
tools:::Rd_package_title("DPP")
A Reference Class that provides DPP functionality
Calculate the expected number of clusters from the number of individua...
Class "GammaModel"
Class "NormalModel"
Simulate a discrete distribution as in the chinese restaurant problem
This MCMC method takes a data numeric vector (Y) and assigns the elements of Y to a (potentially infinite) number of normal distributions. The individual normal distributions from a mixture of normals can be inferred. Following the method described in Escobar (1994) <doi:10.2307/2291223> we use a Dirichlet Process Prior (DPP) to describe stochastically our prior assumptions about the dimensionality of the data.