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:
- score
ndarray Score, evaluated at params.
- score
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).