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:¶

hessianndarray

Hessian matrix evaluated at params

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).