statsmodels.regression.recursive_ls.RecursiveLS.hessian

method

RecursiveLS.hessian(params, *args, **kwargs)

Hessian matrix of the likelihood function, evaluated at the given parameters

Parameters

paramsarray_like

Array of parameters at which to evaluate the hessian.

args

Additional positional arguments to the loglike method.

kwargs

Additional keyword arguments to the loglike method.

Returns

hessianarray

Hessian matrix evaluated at params

Notes

This is a numerical approximation.

Both args and kwargs are necessary because the optimizer from fit must call this function and only supports passing arguments via args (for example scipy.optimize.fmin_l_bfgs).