Gradient of the log-likelihood of the NB regression model

This function computes the gradient of the log-likelihood of a NB regression model given a vector of counts.

Usage

nb.loglik.regression.gradient(
  alpha,
  Y,
  A.mu = matrix(nrow = length(Y), ncol = 0),
  C.theta = matrix(0, nrow = length(Y), ncol = 1)
)

Arguments

alpha

the vectors of parameters a.mu concatenated

Y

the vector of counts

A.mu

matrix of the model (see Details, default=empty)

C.theta

matrix of the model (see Details, default=zero)

Value

The gradient of the log-likelihood.

Details

The regression model is described in nb.loglik.regression.

See also

nb.loglik.regression