statsmodels.base.model.GenericLikelihoodModel.fit#
- GenericLikelihoodModel.fit(start_params=None, method='nm', maxiter=500, full_output=1, disp=1, callback=None, retall=0, **kwargs)[source]#
Fit the model via maximum likelihood
- Parameters:
- start_paramsarray_like,
optional Initial guess of the solution for the loglikelihood maximization. The default is an array of 0.1 for each parameter.
- method
str,optional The method determines which solver from scipy.optimize is used. See LikelihoodModel.fit for the available methods.
- maxiter
int,optional The maximum number of iterations to perform.
- full_outputbool,
optional Set to True to have all available output in the Results object’s mle_retvals attribute.
- dispbool,
optional Set to True to print convergence messages.
- callback
callablecallback(xk),optional Called after each iteration, as callback(xk), where xk is the current parameter vector.
- retallbool,
optional Set to True to return list of solutions at each iteration.
- **kwargs
Additional keyword arguments passed to LikelihoodModel.fit.
- start_paramsarray_like,
- Returns:
GenericLikelihoodModelResultsThe fitted model results.