statsmodels.nonparametric.kernel_density.KDEMultivariateConditional.pdf¶
-
KDEMultivariateConditional.pdf(endog_predict=
None
, exog_predict=None
)[source]¶ Evaluate the probability density function.
- Parameters:¶
- endog_predictarray_like,
optional
Evaluation data for the dependent variables. If unspecified, the training data is used.
- exog_predictarray_like,
optional
Evaluation data for the independent variables.
- endog_predictarray_like,
- Returns:¶
- pdfarray_like
The value of the probability density at endog_predict and exog_predict.
Notes
The formula for the conditional probability density is:
\[f(y|x)=\frac{f(x,y)}{f(x)}\]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.
Last update:
Oct 29, 2024