def inverse(self, z):
    '\n        Inverse of the power transform link function\n\n        Parameters\n        ----------\n        `z` : array_like\n            Value of the transformed mean parameters at `p`\n\n        Returns\n        -------\n        `p` : ndarray\n            Mean parameters\n\n        Notes\n        -----\n        g^(-1)(z`) = `z`**(1/`power`)\n        '
    if (self.power == 1):
        return z
    else:
        return np.power(z, (1.0 / self.power))
Inverse of the power transform link function

Parameters
----------
`z` : array_like
    Value of the transformed mean parameters at `p`

Returns
-------
`p` : ndarray
    Mean parameters

Notes
-----
g^(-1)(z`) = `z`**(1/`power`)
def inverse(self, z):
    '\n        Inverse of the power transform link function\n\n        Parameters\n        ----------\n        `z` : array_like\n            Value of the transformed mean parameters at `p`\n\n        Returns\n        -------\n        `p` : ndarray\n            Mean parameters\n\n        Notes\n        -----\n        g^(-1)(z`) = `z`**(1/`power`)\n        '
    if (self.power == 1):
        return z
    else:
        return np.power(z, (1.0 / self.power))