perplexity.celda_CG: Calculate the perplexity on new data with a celda_CG model

In compbiomed/celda: CEllular Latent Dirichlet Allocation

Description

Perplexity is a statistical measure of how well a probability model can predict new data. Lower perplexity indicates a better model.

Usage

## S3 method for class 'celda_CG'
perplexity(counts, celda.mod, new.counts = NULL)

Arguments

counts	Integer matrix. Rows represent features and columns represent cells. This matrix should be the same as the one used to generate 'celda.mod'.
celda.mod	Celda object of class "celda_C", "celda_G" or "celda_CG".
new.counts	A new counts matrix used to calculate perplexity. If NULL, perplexity will be calculated for the 'counts' matrix. Default NULL.

Value

Numeric. The perplexity for the provided count data and model.

See Also

'celda_CG()' for clustering features and cells

Examples

perplexity = perplexity(celda.CG.sim$counts, celda.CG.mod)

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