Project description
Pyrichlet is a package for doing density estimation and clustering using Gaussian mixtures with BNP weighting models
Installation
With pip:
pip install pyrichlet
For a specific version:
pip install pyrichlet==0.0.4
Usage
This is a quick guide. For a more detailed usage see https://pyrichlet.readthedocs.io/en/latest/index.html.
The mixture models that this package implements are
DirichletDistributionMixture
DirichletProcessMixture
PitmanYorMixture
GeometricProcessMixture
BetaInBetaMixture
BetaInDirichletMixture
BetaBernoulliMixture
BetaBinomialMixture
They can be fitted for an array or dataframe using a Gibbs sampler or variational Bayes methods,
from pyrichlet import mixture_models
mm = mixture_models.DirichletProcessMixture()
y = [1, 2, 3, 4]
mm.fit_gibbs(y)
mm.fit_variational(y, n_groups=2)
and use the fitted class to do density estimation
x = 2.5
f_x = mm.gibbs_eap_density(x)
f_x = mm.var_eap_density(x)
or clustering
mm.var_map_cluster()
mm.gibbs_map_cluster()
mm.gibbs_eap_spectral_consensus_cluster()