statsmodels.tools.numdiff.approx_hess_cs

statsmodels.tools.numdiff.approx_hess_cs(x, f, epsilon=None, args=(), kwargs={})[source]

Calculate Hessian with complex-step derivative approximation

Parameters:

  • x (array_like) – value at which function derivative is evaluated

  • f (function) – function of one array f(x)

  • epsilon (float) – stepsize, if None, then stepsize is automatically chosen

Returns:

hess – array of partial second derivatives, Hessian

Return type:

ndarray

Notes

based on equation 10 in M. S. RIDOUT: Statistical Applications of the Complex-step Method of Numerical Differentiation, University of Kent, Canterbury, Kent, U.K.

The stepsize is the same for the complex and the finite difference part.