PDF for Inverse Gamma prior

        Parameters
        ----------
        x : float
            Latent variable for which the prior is being formed over

        Returns
        ----------
        - p(x)

def pdf(self, x):
        """
        PDF for Inverse Gamma prior

        Parameters
        ----------
        x : float
            Latent variable for which the prior is being formed over

        Returns
        ----------
        - p(x)
        """
        if self.transform is not None:
            x = self.transform(x)               
        return (x**(-self.alpha-1))*np.exp(-(self.beta/float(x)))