Normal-Block Model with Known Clustering

R6 class for a normal-block model with known clustering.

Super class

NormalBlockVarBase -> NormalBlockVarKnownClusters

Active bindings

posterior_par

a list with the parameters of posterior distribution W | Y

entropy

Entropy of the conditional distribution

fitted

Y values predicted by the model, in Y's original units

who_am_I

a method to print what model is being fitted

Methods

Public methods

• NormalBlockVarKnownClusters$new()

• NormalBlockVarKnownClusters$clone()

Inherited methods

• NormalBlockVarBase$best_of_inits()
• NormalBlockVarBase$candidates_merge()
• NormalBlockVarBase$candidates_split()
• NormalBlockVarBase$latent_network()
• NormalBlockVarBase$merge()
• NormalBlockVarBase$optimize()
• NormalBlockVarBase$plot()
• NormalBlockVarBase$plot_loglik()
• NormalBlockVarBase$plot_network()
• NormalBlockVarBase$predict()
• NormalBlockVarBase$print()
• NormalBlockVarBase$split()
• NormalBlockVarBase$update()
• NormalBlockVarBase$warm_start_from()

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NormalBlockVarKnownClusters$new()

Create a new [`NormalBlockVarKnownClusters`] object.

Usage

NormalBlockVarKnownClusters$new(data, C, sparsity = 0, control = NB_control())

Arguments

data

object of NormalBlockVarData class, with responses and design matrix

C

clustering matrix C_jk = 1 if species j belongs to cluster k

sparsity

to apply on variance matrix when calling GLASSO

control

structured list of more specific parameters, to generate with NB_control

Returns

A new [`NormalBlockVarKnownClusters`] object

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NormalBlockVarKnownClusters$clone()

The objects of this class are cloneable with this method.

Usage

NormalBlockVarKnownClusters$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.