- GLM.fit_constrained(constraints, start_params=None, **fit_kwds)¶
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.
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
starting values for the optimization. start_params needs to be given in the original parameter space and are internally transformed.
fit_kwds are used in the optimization of the transformed model.