def fit(self, X):
    '[summary]\n\n        Args:\n            X ([type]): [description]\n\n        Returns:\n            [type]: [description]\n        '
    self.sX_N = X.shape[0]
    if (self.car and (X.shape[(- 1)] > 4)):
        X = (X.copy() - np.mean(X, (- 1), keepdims=True))
    self.sX = np.sum(X, axis=0)
    self.sXX_N = X.shape[0]
    self.sXX = np.sum(((X - (self.sX / self.sX_N)) ** 2), axis=0)
    return self.power()
[summary]

Args:
    X ([type]): [description]

Returns:
    [type]: [description]
def fit(self, X):
    '[summary]\n\n        Args:\n            X ([type]): [description]\n\n        Returns:\n            [type]: [description]\n        '
    self.sX_N = X.shape[0]
    if (self.car and (X.shape[(- 1)] > 4)):
        X = (X.copy() - np.mean(X, (- 1), keepdims=True))
    self.sX = np.sum(X, axis=0)
    self.sXX_N = X.shape[0]
    self.sXX = np.sum(((X - (self.sX / self.sX_N)) ** 2), axis=0)
    return self.power()