statsmodels.tsa.statespace.mlemodel.MLEModel.fit_constrained¶
- MLEModel.fit_constrained(constraints, start_params=None, **fit_kwds)[source]¶
 Fit the model with some parameters subject to equality constraints.
- Parameters:¶
 - constraints
dict Dictionary of constraints, of the form param_name: fixed_value. See the param_names property for valid parameter names.
- start_paramsarray_like, 
optional Initial guess of the solution for the loglikelihood maximization. If None, the default is given by Model.start_params.
- **fit_kwds
keywordarguments fit_kwds are used in the optimization of the remaining parameters.
- constraints
 - Returns:¶
 - results
Resultsinstance 
- results
 
Examples
>>> mod = sm.tsa.SARIMAX(endog, order=(1, 0, 1)) >>> res = mod.fit_constrained({'ar.L1': 0.5})
  
    
      Last update:
      Jun 10, 2024