MoM: Mixture of Multinomial Model Prior description class

In comeetie/greed: Clustering and Model Selection with the Integrated Classification Likelihood

Mixture of Multinomial Model Prior description class

Description

An S4 class to represent a Mixture of Multinomial model. Such model can be used to cluster a data matrix X with the following generative model :

π \sim Dirichlet(α)

Z_i \sim \mathcal{M}(1,π)

θ_{k} \sim Dirichlet(β)

X_{i.}|Z_{ik}=1 \sim \mathcal{M}(L_i,θ_{k})

With L_i=∑_d=1^DX_{id}. These classes mainly store the prior parameters value (α,β) of this generative model. The MoM-class must be used when fitting a simple Mixture of Multinomials whereas the MoMPrior-class must be sued when fitting a CombinedModels-class.

Usage

MoMPrior(beta = 1)

MoM(alpha = 1, beta = 1)

Arguments

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

Value

a MoMPrior-class object

a MoM-class object

See Also

MoMFit-class, MoMPath-class

Other DlvmModels: CombinedModels, DcLbm, DcSbm, DiagGmm, DlvmPrior-class, Gmm, Lca, MoR, MultSbm, Sbm, greed()

Examples

MoMPrior()
MoMPrior(beta = 0.5)
MoM()
MoM(beta = 0.5)

comeetie/greed documentation built on Oct. 10, 2022, 5:37 p.m.