normexp {limma}R Documentation

Normal + Exponential Log-Likelihood

Description

Marginal log-likelihood of foreground values for normal + exponential model and its derivatives. This function is called by backgroundCorrect and is not normally called directly by the user.

Usage

normexp.m2loglik(theta,foreground,background=0)
normexp.grad(theta,foreground,background=0)

Arguments

theta numeric vector of parameters
foreground numeric vector of foreground intensities
background optional vector of background intensity values

Details

Computes minus twice the log-likelihood based on the $normal(μ,σ^2)+exponential(α)$ convolution model for the foreground intensities. The last two elements of theta are $log(σ)$ and $log(α)$. The other elements are the vector $β$.

The vector $β$ is related to $μ$ through $μ=Xβ$ if $X=$background.matrix is non-null. Otherwise $μ=β_1+β_2$background if background is non-null. If both background and background.matrix are null, then $μ=β_1$.

normexp.m2loglik is minus-twice the log-likelihood. normexp.grad is the gradient vector.

Value

Numeric scalar giving minus twice the log-likelihood

Author(s)

Jeremy Silver and Gordon Smyth

See Also

An overview of normalization and background correction functions is given in 05.Normalization.


[Package limma version 2.2.0 Index]