MstepNB: M-step

In cz-ye/DECENT: Differential Expression with Capture Efficiency adjustmeNT

M-step

Description

Calculate negative complete data log-likelihood of DECENT model

Usage

MstepNB(p, y, sf, status, ct)

Arguments

p	vector of the following parameters: log odds-ratio of pi0, log mean of the first cell type, log fold-change for the mean parameter and log of dispersion (1/size) parameter.
y	vector containing the expected number of molecules as output from the E-step.
sf	vector of size factor estimates
status	the estimated probability of non-zero pre-dropout count, output of the E-step.
ct	A factor or a integer/numeric vector starting from 1 giving cell-type labels

Value

negative complete data log-likelihood evaluated at the parameter values.

cz-ye/DECENT documentation built on Jan. 25, 2023, 5:57 a.m.