nbinomUnitDeviance: Negative Binomial Unit Deviance

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

Description

Compute unit deviances for the negative binomial distribution.

Usage

nbinomUnitDeviance(y, mean, dispersion = 0)

Arguments

y	numeric vector or matrix containing negative binomial counts.
mean	numeric vector or matrix of expected values. If a matrix, then of same dimensions as y.
dispersion	numeric vector or matrix of negative binomial dispersions. Can be a scalar, a vector of length nrow(y) or a matrix of same dimensions as y.

Details

The unit deviance of the negative binomial distribution is a measure of the distance between y and mean. If mean and dispersion are the true mean and dispersion of the negative binomial distribution, then the unit deviance follows an approximate chisquare distribution on 1 degree of freedom.

This function computes the unit deviance for each y observation. Care is taken to ensure accurate computation in limiting cases when the dispersion is near zero or mean*dispersion is very large.

Value

Numeric vector or matrix of the same size as y containing unit deviances.

Author(s)

Gordon Smyth, Yunshun Chen, Aaron Lun. C++ code by Aaron Lun.

References

Dunn PK, Smyth GK (2018). Generalized linear models with examples in R. Springer, New York, NY. doi: 10.1007/978-1-4419-0118-7

Jorgensen B (2013). Generalized linear models. Encyclopedia of Environmetrics 3, Wiley. doi: 10.1002/9780470057339.vag010.pub2

McCarthy DJ, Chen Y, Smyth GK (2012). Differential expression analysis of multifactor RNA-Seq experiments with respect to biological variation. Nucleic Acids Research 40, 4288-4297. doi: 10.1093/nar/gks042

Examples

y <- 1:4
names(y) <- letters[1:4]
nbinomUnitDeviance(y,mean=2.5,dispersion=0.2)

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