KDEMultivariate.cdf()

statsmodels.nonparametric.kernel_density.KDEMultivariate.cdf

KDEMultivariate.cdf(data_predict=None) [source]

Evaluate the cumulative distribution function.

Parameters:	data_predict: array_like, optional : Points to evaluate at. If unspecified, the training data is used.
Returns:	cdf_est: array_like : The estimate of the cdf.

Notes

See http://en.wikipedia.org/wiki/Cumulative_distribution_function For more details on the estimation see Ref. [5] in module docstring.

The multivariate CDF for mixed data (continuous and ordered/unordered discrete) is estimated by:

..math:: F(x^{c},x^{d})=n^{-1}sum_{i=1}^{n}left[G(

frac{x^{c}-X_{i}}{h})sum_{uleq x^{d}}L(X_{i}^{d},x_{i}^{d}, lambda)right]

where G() is the product kernel CDF estimator for the continuous and L() for the discrete variables.

Used bandwidth is self.bw.