logLikelihood.celda_G: Calculate Celda_G log likelihood

In compbiomed/celda: CEllular Latent Dirichlet Allocation

Description

Calculates the log likelihood for user-provided feature module clusters using the 'celda_G()' model.

Usage

logLikelihood.celda_G(counts, y, L, beta, delta, gamma)

Arguments

counts	Integer matrix. Rows represent features and columns represent cells.
y	Numeric vector. Denotes feature module labels.
L	Integer. Number of feature modules.
beta	Numeric. Concentration parameter for Phi. Adds a pseudocount to each feature module in each cell. Default 1.
delta	Numeric. Concentration parameter for Psi. Adds a pseudocount to each feature in each module. Default 1.
gamma	Numeric. Concentration parameter for Eta. Adds a pseudocount to the number of features in each module. Default 1.
...	Additional parameters.

Value

The log-likelihood for the given cluster assignments

See Also

'celda_G()' for clustering features

Examples

loglik = logLikelihood(celda.G.sim$counts, model="celda_G", 
                       y=celda.G.sim$y, L=celda.G.sim$L,
                       beta=celda.G.sim$beta, delta=celda.G.sim$delta,
                       gamma=celda.G.sim$gamma)

compbiomed/celda documentation built on May 25, 2019, 3:58 a.m.