def deriv2(self, p):
    "\n        Second derivative of the power transform\n\n        Parameters\n        ----------\n        p : array_like\n            Mean parameters\n\n        Returns\n        -------\n        g''(p) : ndarray\n            Second derivative of the power transform of `p`\n\n        Notes\n        -----\n        g''(`p`) = `power` * (`power` - 1) * `p`**(`power` - 2)\n        "
    if (self.power == 1):
        return np.zeros_like(p)
    else:
        return ((self.power * (self.power - 1)) * np.power(p, (self.power - 2)))
Second derivative of the power transform

Parameters
----------
p : array_like
    Mean parameters

Returns
-------
g''(p) : ndarray
    Second derivative of the power transform of `p`

Notes
-----
g''(`p`) = `power` * (`power` - 1) * `p`**(`power` - 2)
def deriv2(self, p):
    "\n        Second derivative of the power transform\n\n        Parameters\n        ----------\n        p : array_like\n            Mean parameters\n\n        Returns\n        -------\n        g(p) : ndarray\n            Second derivative of the power transform of `p`\n\n        Notes\n        -----\n        g(`p`) = `power` * (`power` - 1) * `p`**(`power` - 2)\n        "
    if (self.power == 1):
        return np.zeros_like(p)
    else:
        return ((self.power * (self.power - 1)) * np.power(p, (self.power - 2)))