copulas/univariate/kde.py
def cumulative_distribution(self, X, U=0):
        """Computes the integral of a 1-D pdf between two bounds

        Args:
            X(float): a datapoint.
            U(float): cdf value in [0,1], only used in get_ppf

        Returns:
            float: estimated cumulative distribution.
        """
        self.check_fit()

        low_bounds = self.model.dataset.mean() - (5 * self.model.dataset.std())
        return self.model.integrate_box_1d(low_bounds, X) - U
Computes the integral of a 1-D pdf between two bounds

        Args:
            X(float): a datapoint.
            U(float): cdf value in [0,1], only used in get_ppf

        Returns:
            float: estimated cumulative distribution.
        
Computes the integral of a 1-D pdf between two bounds
Computes the integral of a 1 - D pdf between two bounds
def cumulative_distribution(self, X, U=0):
        self.check_fit()
        low_bounds = self.model.dataset.mean() - (5 * self.model.dataset.std())
        return self.model.integrate_box_1d(low_bounds, X) - U
def cumulative_distribution ( self , X , U = 0 ) : self . check_fit ( ) low_bounds = self . model . dataset . mean ( ) - ( 5 * self . model . dataset . std ( ) ) return self . model . integrate_box_1d ( low_bounds , X ) - U
Computes the integral of a 1-D pdf between two bounds
Computes the integral of a 1 - D pdf between two bounds
"""Computes the integral of a 1-D pdf between two bounds

        Args:
            X(float): a datapoint.
            U(float): cdf value in [0,1], only used in get_ppf

        Returns:
            float: estimated cumulative distribution.
        """
estimated cumulative distribution.
estimated cumulative distribution .
float
self
X
None
U
cdf value in [0,1], only used in get_ppf
cdf value in [ 0 1 ] only used in get_ppf