m2loglik.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

    m2loglik.normexp(theta,foreground,background=NULL,background.matrix=NULL)
    sumloglik(theta,foreground,background)
    grsumloglik(theta,foreground,background)

### Arguments

`theta` | numeric vector of parameters
`foreground` | numeric vector of foreground intensities
`background` | optional vector of background intensity values
`background.matrix` | option design matrix for regression on background 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 $μ=β_1$.

`m2loglik.normexp` is minus-twice the log-likelihood. `sumloglik` is minus the log-likelihood. `grsumloglik` is the gradient vector and `grloglik` the gradient components for individual spots.

### Value

Numeric scalar giving minus twice the log-likelihood

### Bugs

There are undocumented arguments in the function `grloglik`. These will disappear soon.

### Author(s)

Jeremy Silver and Gordon Smyth

### See Also

`fit.normexp`, `signal.normexp`

An overview of normalization and background correction functions is given in `4.Normalization`.

[Package limma version 1.9.6 Index]