logLikelihoodcelda_G {celda} | R Documentation

## Calculate Celda_G log likelihood

### Description

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

### Usage

    logLikelihoodcelda_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.

### Value

The log-likelihood for the given cluster assignments.

### See Also

'celda_G()' for clustering features

### Examples

    data(celdaGSim)
    loglik <- logLikelihoodcelda_G(celdaGSim$counts,
        y = celdaGSim$y,
        L = celdaGSim$L,
        beta = celdaGSim$beta,
        delta = celdaGSim$delta,
        gamma = celdaGSim$gamma)

    loglik <- logLikelihood(celdaGSim$counts,
        model = "celda_G",
        y = celdaGSim$y,
        L = celdaGSim$L,
        beta = celdaGSim$beta,
        delta = celdaGSim$delta,
        gamma = celdaGSim$gamma)

[Package celda version 1.3.4 Index]