statsmodels.nonparametric.kernel_density.KDEMultivariate.cdf¶
- KDEMultivariate.cdf(data_predict=None)[source]¶
Evaluate the cumulative distribution function.
- Parameters:
- data_predictarray_like,
optional
Points to evaluate at. If unspecified, the training data is used.
- data_predictarray_like,
- Returns:
- cdf_estarray_like
The estimate of the cdf.
Notes
See https://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:
\[F(x^{c},x^{d})=n^{-1}\sum_{i=1}^{n}\left[G(\frac{x^{c}-X_{i}}{h})\sum_{u\leq x^{d}}L(X_{i}^{d},x_{i}^{d}, \lambda)\right]\]where G() is the product kernel CDF estimator for the continuous and L() for the discrete variables.
Used bandwidth is
self.bw
.