statsmodels.genmod.generalized_linear_model.GLM.fit_constrained
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GLM.fit_constrained(constraints, start_params=None, **fit_kwds)
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fit the model subject to linear equality constraints
The constraints are of the form
R params = q
where R is the constraint_matrix and q is the vector of constraint_values.The estimation creates a new model with transformed design matrix, exog, and converts the results back to the original parameterization.
Parameters: constraints : formula expression or tuple
If it is a tuple, then the constraint needs to be given by two arrays (constraint_matrix, constraint_value), i.e. (R, q). Otherwise, the constraints can be given as strings or list of strings. see t_test for details
start_params : None or array_like
starting values for the optimization.
start_params
needs to be given in the original parameter space and are internally transformed.**fit_kwds : keyword arguments
fit_kwds are used in the optimization of the transformed model.
Returns: results : Results instance
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