statsmodels.regression.recursive_ls.RecursiveLS.fit_constrained¶
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RecursiveLS.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})