copula.py 文件源码

def _logpdf(self, samples):
        if self.theta >= 1.0:
            vals = np.zeros(samples.shape[0])
            vals[samples[:, 0] == samples[:, 1]] = np.inf
        elif self.theta <= -1.0:
            vals = np.zeros(samples.shape[0])
            vals[samples[:, 0] == 1 - samples[:, 1]] = np.inf
        else:
            nrvs = norm.ppf(samples)
            vals = 2 * self.theta * nrvs[:, 0] * nrvs[:, 1] - self.theta**2 \
                * (nrvs[:, 0]**2 + nrvs[:, 1]**2)
            vals /= 2 * (1 - self.theta**2)
            vals -= np.log(1 - self.theta**2) / 2
        return vals