AntMAN: Anthology of Mixture Analysis Tools
Fits finite Bayesian mixture models with a random number of components. The MCMC algorithm implemented is based on point processes as proposed by Argiento and De Iorio (2019) <doi:10.48550/arXiv.1904.09733> and offers a more computationally efficient alternative to reversible jump. Different mixture kernels can be specified: univariate Gaussian, multivariate Gaussian, univariate Poisson, and multivariate Bernoulli (latent class analysis). For the parameters characterising the mixture kernel, we specify conjugate priors, with possibly user specified hyper-parameters. We allow for different choices for the prior on the number of components: shifted Poisson, negative binomial, and point masses (i.e. mixtures with fixed number of components).
| Version: |
1.1.0 |
| Imports: |
stats, graphics, grDevices, Rcpp (≥ 0.12.3), salso, mvtnorm, mcclust, GGally, bayesplot, Rdpack |
| LinkingTo: |
Rcpp, RcppArmadillo |
| Suggests: |
dendextend, ggdendro, ggplot2, jpeg |
| Published: |
2021-07-23 |
| DOI: |
10.32614/CRAN.package.AntMAN |
| Author: |
Priscilla Ong [aut, edt],
Raffaele Argiento [aut],
Bruno Bodin [aut, cre],
Maria De Iorio [aut] |
| Maintainer: |
Bruno Bodin <bruno.bodin at yale-nus.edu.sg> |
| License: |
MIT + file LICENSE |
| URL: |
https://github.com/bbodin/AntMAN |
| NeedsCompilation: |
yes |
| CRAN checks: |
AntMAN results |
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