dmm.model: Create a model

In nsdumont/jDirichletMixtureModels: Dirichlet Mixture Models for Clustering using Julia backend

Description

Make a model object to be passed to dmm.cluster. If not passed any argurments a conjugate multivariate normal likelihood model with default parameters will be used.

Usage

dmm.model(...)

Details

Depending on what argurments are passed to dmm.model() either a BaseModel (see dmm.BaseModel), a RModel (see dmm.RModel), or JModel (see dmm.JModel) will be made.

*NOTE: The use of RModels is not avaible in the current version of jDirichletMixtureModels*

Value

A model object which can be passed to dmm.cluster.

Examples

## Not run: 
# Example of using a multivariate normal conjugate prior (the default)
model <- dmm.model()

# Example of using a bulit-in conjugate prior
model <- dmm.model(typename, params)

# Using a user specified R functions
model <- dmm.model(pdf_fct, sample_fct, marg_fct, params, isconjugate=TRUE)

# Using a user specified Julia functions located in a .jl file called filename
dmm.addfile(filename)
model <- dmm.model(pdf_name, sample_name, marg_name, params, isconjugate=TRUE)

## End(Not run)

nsdumont/jDirichletMixtureModels documentation built on May 23, 2019, 2:51 p.m.