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:
xarray_like

value at which function derivative is evaluated

ffunction

function of one array f(x)

epsilonfloat

stepsize, if None, then stepsize is automatically chosen

Returns:
hessndarray

array of partial second derivatives, Hessian

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.


Last update: May 17, 2023