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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.
Package details 


Author  Luis M. Avila [aut, cre], Michael R. May [aut], Jeff RossIbarra [aut] 
Maintainer  Luis M. Avila <[email protected]> 
License  MIT + file LICENSE 
Version  0.1.2 
Package repository  View on CRAN 
Installation 
Install the latest version of this package by entering the following in R:

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