logLikelihoodcelda_C {celda} | R Documentation

## Calculate Celda_C log likelihood

### Description

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

### Usage

    logLikelihoodcelda_C(counts, sampleLabel, z, K, alpha, beta)

### Arguments

`counts` | Integer matrix. Rows represent features and columns represent cells.
`sampleLabel` | 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.

### Value

Numeric. The log likelihood for the given cluster assignments

### See Also

'celda_C()' for clustering cells

### Examples

    data(celdaCSim)
    loglik <- logLikelihoodcelda_C(celdaCSim$counts,
        sampleLabel = celdaCSim$sampleLabel,
        z = celdaCSim$z,
        K = celdaCSim$K,
        alpha = celdaCSim$alpha,
        beta = celdaCSim$beta)

    loglik <- logLikelihood(celdaCSim$counts,
        model = "celda_C",
        sampleLabel = celdaCSim$sampleLabel,
        z = celdaCSim$z,
        K = celdaCSim$K,
        alpha = celdaCSim$alpha,
        beta = celdaCSim$beta)

[Package celda version 1.3.4 Index]