Package: dirichletprocess
Type: Package
Title: Build Dirichlet Process Objects for Bayesian Modelling
Version: 0.3.1.1
Authors@R: c(
            person("Gordon", "J. Ross", email="gordon@gordonjross.co.uk", role=c("aut")),
            person("Dean", "Markwick", email="dean.markwick@talk21.com", role=c("aut", "cre")),
            person("Kees", "Mulder", email="keestimmulder@gmail.com", role=c("ctb"), 
            comment = c(ORCID = "0000-0002-5387-3812"))
          )
Maintainer: Dean Markwick <dean.markwick@talk21.com>
Description: Perform nonparametric Bayesian analysis using Dirichlet 
    processes without the need to program the inference algorithms. 
    Utilise included pre-built models or specify custom 
    models and allow the 'dirichletprocess' package to handle the 
    Markov chain Monte Carlo sampling. 
    Our Dirichlet process objects can act as building blocks for a variety 
    of statistical models including and not limited to: density estimation, 
    clustering and prior distributions in hierarchical models.
    See Teh, Y. W. (2011) 
    <https://www.stats.ox.ac.uk/~teh/research/npbayes/Teh2010a.pdf>, 
    among many other sources.
Depends: R (>= 2.10)
License: GPL-3
Encoding: UTF-8
LazyData: true
Suggests: testthat, knitr, rmarkdown, tidyr, dplyr
Imports: gtools, ggplot2, mvtnorm
URL: https://github.com/dm13450/dirichletprocess
BugReports: https://github.com/dm13450/dirichletprocess/issues
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2020-03-30 11:54:51 UTC; hornik
Author: Gordon J. Ross [aut],
  Dean Markwick [aut, cre],
  Kees Mulder [ctb] (<https://orcid.org/0000-0002-5387-3812>)
Repository: CRAN
Date/Publication: 2020-04-03 06:49:26 UTC
Built: R 3.5.3; ; 2020-04-22 08:13:33 UTC; windows
