commonCondLogLikDerDelta {edgeR} | R Documentation

## Conditional Log-Likelihoods in Terms of Delta

### Description

Common conditional log-likelihood parameterized in terms of delta (`phi / (phi+1)`)

### Usage

    commonCondLogLikDerDelta(y, delta, der = 0)

### Arguments

`y` | list with elements comprising the matrices of count data (or pseudocounts) for the different groups
`delta` | delta (`phi / (phi+1)`) parameter of negative binomial
`der` | derivative, either 0 (the function), 1 (first derivative) or 2 (second derivative)

### Details

The common conditional log-likelihood is constructed by summing over all of the individual genewise conditional log-likelihoods. The common conditional log-likelihood is taken as a function of the dispersion parameter (`phi`), and here parameterized in terms of delta (`phi / (phi+1)`). The value of delta that maximizes the common conditional log-likelihood is converted back to the `phi` scale, and this value is the estimate of the common dispersion parameter used by all genes.

### Value

numeric scalar of function/derivative evaluated at given delta

### Author(s)

Davis McCarthy

### See Also

`estimateCommonDisp` is the user-level function for estimating the common dispersion parameter.

### Examples

    counts<-matrix(rnbinom(20,size=1,mu=10),nrow=5)
    d<-DGEList(counts=counts,group=rep(1:2,each=2),lib.size=rep(c(1000:1001),2))
    y<-splitIntoGroups(d)
    ll1<-commonCondLogLikDerDelta(y,delta=0.5,der=0)
    ll2<-commonCondLogLikDerDelta(y,delta=0.5,der=1)

[Package edgeR version 3.36.0 Index]