statsmodels.tsa.statespace.dynamic_factor_mq.DynamicFactorMQ.hessian¶
- DynamicFactorMQ.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:
- hessian
ndarray
Hessian matrix evaluated at params
- hessian
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).