statsmodels.othermod.betareg.BetaModel.score_hessian_factor¶
- BetaModel.score_hessian_factor(params, return_hessian=False, observed=True)[source]¶
Derivatives of loglikelihood function w.r.t. linear predictors.
This calculates score and hessian factors at the same time, because there is a large overlap in calculations.
- Parameters:
- params
ndarray
Parameter at which score is evaluated.
- return_hessianbool
If False, then only score_factors are returned If True, the both score and hessian factors are returned
- observedbool
If True, then the observed Hessian is returned (default). If False, then the expected information matrix is returned.
- params
- Returns:
- score_factor
ndarray
, 2-D A 2d weight vector used in the calculation of the score_obs.
- (-jbb, -jbg, -jgg)
tuple
A tuple with 3 hessian factors, corresponding to the upper triangle of the Hessian matrix. TODO: check why there are minus
- score_factor