zinb.loglik.dispersion: Log-likelihood of the zero-inflated negative binomial model,...
In zinbwave: Zero-Inflated Negative Binomial Model for RNA-Seq Data

Description Usage Arguments Value See Also Examples

Given a unique dispersion parameter and a set of counts, together with a corresponding set of mean parameters and probabilities of zero components, this function computes the sum of the log-probabilities of the counts under the ZINB model. The dispersion parameter is provided to the function through zeta = log(theta), where theta is sometimes called the inverse dispersion parameter. The probabilities of the zero components are provided through their logit, in order to better numerical stability.

1	zinb.loglik.dispersion(zeta, Y, mu, logitPi)

`zeta`	a scalar, the log of the inverse dispersion parameters of the negative binomial model
`Y`	a vector of counts
`mu`	a vector of mean parameters of the negative binomial
`logitPi`	a vector of logit of the probabilities of the zero component

the log-likelihood of the model.

zinb.loglik.

mu <- seq(10,50,length.out=10)
logitPi <- rnorm(10)
zeta <- rnorm(10)
Y <- rnbinom(n=10, size=exp(zeta), mu=mu)
zinb.loglik.dispersion(zeta, Y, mu, logitPi)