mig_loglik_grad: Gradient of the MIG log likelihood with respect to data

In mig: Multivariate Inverse Gaussian Distribution

Gradient of the MIG log likelihood with respect to data

Description

This function returns the gradient vector of the log likelihood with respect to the argument x.

Usage

mig_loglik_grad(x, xi, Omega, beta)

Arguments

x	n by d matrix of quantiles
xi	d vector of location parameters \boldsymbol{\xi}, giving the expected value
Omega	d by d positive definite scale matrix \boldsymbol{\Omega}
beta	d vector \boldsymbol{\beta} defining the half-space through \boldsymbol{\beta}^{\top}\boldsymbol{\xi}>0

Value

an n by d matrix of first derivatives for the gradient, observation by observation, or a d vector if x is a vector.

mig documentation built on April 11, 2025, 5:45 p.m.