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]