Mixed Models classes

An S4 class to represent a mixed clustering models, where sevral models are used to model different datasets. A conditional independence assumption between the view knowing the cluster is made.

MixedModels(models, alpha = 1)

Arguments

models

a named list of DlvmPrior's object

alpha

Dirichlet prior parameter over the cluster proportions (default to 1)

Value

a MixedModels-class object

Details

The filed name in the models list must match the name of the list use to provide the datasets to cluster together.

Functions

• MixedModels: MixedModels class constructor

Slots

models

a named list of DlvmModels Emission prior such as (GmmPrior,LcaPrior,SbmPrior,...)

See also

Other DlvmModels: DcLbmPrior-class, DcSbmPrior-class, DiagGmmPrior-class, DlvmPrior-class, Gmm, LcaPrior-class, MoMPrior-class, MoRPrior-class, MultSbmPrior-class, SbmPrior-class, greed()

Examples

MixedModels(models = list(continuous = GmmPrior(), discrete = LcaPrior()))
#> An object of class "MixedModels"
#> Slot "models":
#> $continuous
#> An object of class "GmmPrior"
#> Slot "tau":
#> [1] 0.01
#> 
#> Slot "mu":
#>      [,1]
#> [1,]  NaN
#> 
#> Slot "epsilon":
#>      [,1]
#> [1,]  NaN
#> 
#> Slot "N0":
#> [1] NaN
#> 
#> 
#> $discrete
#> An object of class "LcaPrior"
#> Slot "beta":
#> [1] 1
#> 
#> 
#> 
#> Slot "alpha":
#> [1] 1
#>