logLikelihood.celda_C: Calculate Celda_C log likelihood

In compbiomed/celda: CEllular Latent Dirichlet Allocation

Description

Calculates the log likelihood for user-provided cell population clusters using the 'celda_C()' model.

Usage

logLikelihood.celda_C(counts, sample.label, z, K, alpha, beta)

Arguments

counts	Integer matrix. Rows represent features and columns represent cells.
sample.label	Vector or factor. Denotes the sample label for each cell (column) in the count matrix.
z	Numeric vector. Denotes cell population labels.
K	Integer. Number of cell populations.
alpha	Numeric. Concentration parameter for Theta. Adds a pseudocount to each cell population in each sample. Default 1.
beta	Numeric. Concentration parameter for Phi. Adds a pseudocount to each feature in each cell population. Default 1.
...	Additional parameters.

Value

Numeric. The log likelihood for the given cluster assignments

See Also

'celda_C()' for clustering cells

Examples

loglik = logLikelihood(celda.C.sim$counts, model="celda_C", 
                       sample.label=celda.C.sim$sample.label,
                       z=celda.C.sim$z, K=celda.C.sim$K,
                       alpha=celda.C.sim$alpha, beta=celda.C.sim$beta)

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