Package: copre
Type: Package
Title: Tools for Nonparametric Martingale Posterior Sampling
Version: 0.2.0
Authors@R: c(
    person("Blake", "Moya", email = "blakemoya@utexas.edu",
           role = c("cre", "aut")),
    person("The University of Texas at Austin", role = c("cph", "fnd")))
Description: Performs Bayesian nonparametric density estimation using Martingale
 posterior distributions including the Copula Resampling (CopRe) algorithm. 
 Also included are a Gibbs sampler for the marginal Gibbs-type mixture model and
 an extension to include full uncertainty quantification via a predictive 
 sequence resampling (SeqRe) algorithm. The CopRe and SeqRe samplers generate 
 random nonparametric distributions as output, leading to complete nonparametric 
 inference on posterior summaries. Routines for calculating arbitrary 
 functionals from the sampled distributions are included as well as an important 
 algorithm for finding the number and location of modes, which can then be used 
 to estimate the clusters in the data using, for example, k-means.
 Implements work developed in Moya B., Walker S. G. (2022).
 <doi:10.48550/arxiv.2206.08418>, Fong, E., Holmes, C., Walker, S. G. (2021) 
 <doi:10.48550/arxiv.2103.15671>, and Escobar M. D., West, M. (1995) 
 <doi:10.1080/01621459.1995.10476550>.
License: GPL (>= 2)
Encoding: UTF-8
RoxygenNote: 7.2.2
LinkingTo: Rcpp, RcppArmadillo, BH
Imports: Rcpp, pracma, abind, dirichletprocess
Suggests: ggplot2
NeedsCompilation: yes
Packaged: 2023-01-31 16:39:11 UTC; blakemoya
Author: Blake Moya [cre, aut],
  The University of Texas at Austin [cph, fnd]
Maintainer: Blake Moya <blakemoya@utexas.edu>
Repository: CRAN
Date/Publication: 2023-01-31 17:00:11 UTC
Built: R 4.1.3; x86_64-w64-mingw32; 2023-04-17 17:28:33 UTC; windows
Archs: i386, x64
