Package: DPP
Type: Package
Title: Inference of Parameters of Normal Distributions from a Mixture
        of Normals
Version: 0.1.2
Authors@R: c(
    person("Luis M.", "Avila", email = "lmavila@gmail.com", role = c("aut","cre")),
    person("Michael R.", "May", email = "mikeryanmay@ucdavis.edu", role = "aut"),
    person("Jeff", "Ross-Ibarra", email = "rossibarra@ucdavis.edu", role = "aut"))
Description: 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.
License: MIT + file LICENSE
Depends: methods, Rcpp (>= 0.12.4), coda, stats
Suggests: R.rsp
VignetteBuilder: R.rsp
LinkingTo: Rcpp
RcppModules: DPPmcmc,Models
RoxygenNote: 6.0.1
NeedsCompilation: yes
Packaged: 2026-10-08 12:16:33 UTC; root
Author: Luis M. Avila [aut, cre], Michael R. May [aut], Jeff
        Ross-Ibarra [aut]
Maintainer: Luis M. Avila <lmavila@gmail.com>
Repository: https://lmavila.r-universe.dev
Date/Publication: 2018-05-24 07:38:30 UTC
RemoteUrl: https://github.com/cran/DPP
RemoteRef: HEAD
RemoteSha: 31e67d35a2d3ea718043261cbe97d7ada4efae9a