Bayesian nonparametric approach for clustering that is capable to combine different types of variables (continuous, ordinal and nominal) and also accommodates for different sampling probabilities in a complex survey design. The model is based on a location mixture model with a Poisson-Dirichlet process prior on the location parameters of the associated latent variables. The package performs the clustering model described in Carmona, C., Nieto-Barajas, L. E., Canale, A. (2016) <arXiv:1612.00083>.
Rcpp (>= 0.12.12), matrixcalc, truncnorm, mvtnorm, plyr, MASS,
compiler

Rcpp, matrixcalc, truncnorm, mvtnorm, plyr, MASS, compiler

compiler, gplots, MASS, matrixcalc, mvtnorm, plyr, Rcpp,
truncnorm

c(person("Christian", "Carmona", role = c("aut", "cre"), email = "carmona@stats.ox.ac.uk", comment = c(ORCID = "0000-0003-0224-4968")),
person("Luis", "Nieto-Barajas", role = "aut", email = " lnieto@itam.mx", comment = c(ORCID = "0000-0002-0859-7679")),
person("Antonio", "Canale", role = "ctb", email = "antonio.canale@unito.it", comment = c(ORCID = "0000-0002-5403-0040"))
)
Model-based approach for clustering of multivariate data, capable of combining different types of variables (continuous, ordinal and nominal) and accommodating for different sampling probabilities in a complex survey design. The model is based on a location mixture model with a Poisson-Dirichlet process prior on the location parameters of the associated latent variables. Details of the underlying model is described in Carmona, C., Nieto-Barajas, L. E., Canale, A. (2016) <arXiv:1612.00083>.
compiler, gplots, MASS, matrixcalc, mvtnorm, plyr, Rcpp (>=
1.0.5), truncnorm
Christian Carmona [aut, cre] (<https://orcid.org/0000-0003-0224-4968>),
Luis Nieto-Barajas [aut] (<https://orcid.org/0000-0002-0859-7679>),
Antonio Canale [ctb] (<https://orcid.org/0000-0002-5403-0040>)

Bayesian Nonparametric Method for Mediation
Provides the Bayesian nonparametric inference for the causal effects of mediation. The function bnpmediation()
gives the posterior means and credible intervals of the effects of mediation on the data. Full details: Kim, C., Daniels, M. J., Marcus, B. H. and Roy, J. A. (2017) <doi:10.1111/biom.12575>.
DPpackage (>= 1.0.0), mnormt (>= 1.4.0), condMVNorm