mig_loglik_hessian function

Hessian of the MIG log likelihood with respect to data

This function returns the hessian, i.e., the matrix of second derivatives of the log likelihood with respect to the argument x.

mig_loglik_hessian(x, beta, xi, Omega)

Arguments

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

Returns

a d by d matrix of second derivatives if x has length d, else an n by d by d array if x is an n by d matrix