3.8.5.3.4.1.5. statsmodels.nonparametric.kernel_density.KDEMultivariateConditional.pdf

KDEMultivariateConditional.pdf(endog_predict=None, exog_predict=None)

Evaluate the probability density function.

Parameters:

endog_predict: array_like, optional

Evaluation data for the dependent variables. If unspecified, the training data is used.

exog_predict: array_like, optional

Evaluation data for the independent variables.

Returns:

pdf: array_like

The value of the probability density at endog_predict and exog_predict.

Notes

The formula for the conditional probability density is:

\[f(X|Y)=\frac{f(X,Y)}{f(Y)}\]

with

\[f(X)=\prod_{s=1}^{q}h_{s}^{-1}k \left(\frac{X_{is}-X_{js}}{h_{s}}\right)\]

where \(k\) is the appropriate kernel for each variable.