statsmodels.tsa.exponential_smoothing.ets.ETSModel.fit_constrained¶
- ETSModel.fit_constrained(constraints, start_params=None, **fit_kwds)¶
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})