condLogLikDerSize: Conditional Log-Likelihood of the Dispersion for a Single...

In hiraksarkar/edgeR_fork: Empirical Analysis of Digital Gene Expression Data in R

Description

Derivatives of the negative-binomial log-likelihood with respect to the dispersion parameter for each gene, conditional on the mean count, for a single group of replicate libraries of the same size.

Usage

condLogLikDerSize(y, r, der=1L)
condLogLikDerDelta(y, delta, der=1L)

Arguments

y	matrix of counts, all counts in each row having the same population mean
r	numeric vector or scalar, size parameter of negative binomial distribution, equal to 1/dispersion
delta	numeric vector or scalar, delta parameter of negative binomial, equal to dispersion/(1+dispersion)
der	integer specifying derivative required, either 0 (the function), 1 (first derivative) or 2 (second derivative)

Details

The library sizes must be equalized before running this function. This function carries out the actual mathematical computations for the conditional log-likelihood and its derivatives, calculating the conditional log-likelihood for each gene. Derivatives are with respect to either the size (r) or the delta parametrization (delta) of the dispersion.

Value

vector of row-wise derivatives with respect to r or delta

Author(s)

Mark Robinson, Davis McCarthy, Gordon Smyth

Examples

y <- matrix(rnbinom(10,size=1,mu=10),nrow=5)
condLogLikDerSize(y,r=1,der=1)
condLogLikDerDelta(y,delta=0.5,der=1)

hiraksarkar/edgeR_fork documentation built on Dec. 20, 2021, 3:52 p.m.