statsmodels.tools.numdiff.approx_hess_cs#
- statsmodels.tools.numdiff.approx_hess_cs(x, f, epsilon=None, args=(), kwargs=None)[source]#
Calculate Hessian with complex-step derivative approximation
- Parameters:
- xarray_like
value at which function derivative is evaluated
- f
callable function of one array f(x)
- epsilon
float,optional stepsize, if None, then stepsize is automatically chosen
- args
tuple,optional Arguments for function f.
- kwargs
dict,optional Keyword arguments for function f.
- Returns:
- hess
ndarray array of partial second derivatives, Hessian
- hess
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.