zinbOptimizeDispersion {zinbwave}R Documentation

Optimize the dispersion parameters of a ZINB regression model

Description

The dispersion parameters of the model are optimized by penalized maximum likelihood on the count matrix given as argument.

Usage

zinbOptimizeDispersion(J, mu, logitPi, epsilon, Y,
  commondispersion = TRUE, BPPARAM = BiocParallel::bpparam())

Arguments

J

The number of genes.

mu

the matrix containing the mean of the negative binomial.

logitPi

the matrix containing the logit of the probability parameter of the zero-inflation part of the model.

epsilon

the regularization parameter.

Y

The matrix of counts.

commondispersion

Whether or not a single dispersion for all features is estimated (default TRUE)

BPPARAM

object of class bpparamClass that specifies the back-end to be used for computations. See bpparam for details.

Value

An object of class ZinbModel similar to the one given as argument with modified parameters zeta.

Examples

Y = matrix(10, 3, 5)
m = zinbModel(n=NROW(Y), J=NCOL(Y))
m = zinbInitialize(m, Y)
m = zinbOptimizeDispersion(NROW(Y), getMu(m), getLogitPi(m), getEpsilon_zeta(m), Y)

[Package zinbwave version 1.6.0 Index]