def __init__(self, model, ncats, alpha_lambda=<NUM_LIT:1.0>, beta_lambda=<NUM_LIT>,<EOL>freeparams=['<STR_LIT>', '<STR_LIT>']):
<EOL>new_max_beta = DiscreteGamma(self.PARAMLIMITS["<STR_LIT>"][<NUM_LIT:1>],<EOL>self.PARAMLIMITS["<STR_LIT>"][<NUM_LIT:0>], ncats)[-<NUM_LIT:1>]<EOL>new_limits = model.PARAMLIMITS<EOL>new_limits["<STR_LIT>"] = (new_limits["<STR_LIT>"][<NUM_LIT:0>], new_max_beta)<EOL>model.PARAMLIMITS = new_limits<EOL>super(GammaDistributedBetaModel, self).__init__(model, "<STR_LIT>",<EOL>ncats, alpha_lambda=<NUM_LIT:1.0>, beta_lambda=<NUM_LIT>,<EOL>freeparams=['<STR_LIT>', '<STR_LIT>'])<EOL>assert all([scipy.allclose(new_max_beta, m.PARAMLIMITS["<STR_LIT>"][<NUM_LIT:1>])<EOL>for m in self._models]), ("<STR_LIT>".format(<EOL>new_max_beta, '<STR_LIT:\n>'.join([m.PARAMLIMITS["<STR_LIT>"][<NUM_LIT:1>]<EOL>for m in self._models])))<EOL>
Initialize an `GammaDistributedModel` object.

        The `lambda_param` is set to "beta".

        Args:
            `model` `ncats`,`alpha_lambda`, `beta_lambda`, `freeparams`
                Meaning described in main class doc string for
                `GammaDistributedModel`.