statsmodels.regression.recursive_ls.RecursiveLS.score_obs#
- RecursiveLS.score_obs(params, method='approx', transformed=True, includes_fixed=False, approx_complex_step=None, approx_centered=False, **kwargs)#
Compute the score per observation, evaluated at params
- Parameters:
- paramsarray_like
Array of parameters at which to evaluate the score.
- method{‘approx’, ‘harvey’},
optional The method by which the score is calculated. Default is ‘approx’.
- transformedbool,
optional Whether or not params is already transformed. Default is True.
- includes_fixedbool,
optional If parameters were previously fixed with the fix_params method, this argument describes whether or not params also includes the fixed parameters, in addition to the free parameters. Default is False.
- approx_complex_stepbool,
optional Whether or not to approximate the derivatives of the loglikelihood using complex step differentiation. Default is True.
- approx_centeredbool,
optional Whether or not to use a centered approximation for finite difference derivatives, when approx_complex_step is False. Default is False.
- **kwargs
Additional arguments to the loglike method.
- Returns:
- score
ndarray Score per observation, evaluated at params.
- score
Notes
This is a numerical approximation, calculated using first-order complex step differentiation on the loglikeobs method.