statsmodels.regression.recursive_ls.RecursiveLS.score¶

RecursiveLS.score(params, *args, **kwargs)¶

Compute the score function at params.

Parameters:¶

paramsarray_like

Array of parameters at which to evaluate the score.

*args

Additional positional arguments to the loglike method.

**kwargs

Additional keyword arguments to the loglike method.

Returns:¶

scorendarray

Score, evaluated at params.

Notes

This is a numerical approximation, calculated using first-order complex step differentiation on the loglike method.

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).