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
function function of one array f(x)
- epsilon
float stepsize, if None, then stepsize is automatically chosen
- args
tuple Arguments for function f.
- kwargs
dict 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.