condmixt: Conditional Density Estimation with Neural Network Conditional
Neural network conditional mixtures are mixture models whose parameters are predicted by a neural network. The mixture model can thus change its parameters in response to changes in predictive covariates. Mixtures included are gaussian, log-normal and hybrid Pareto mixtures. The latter relies on the generalized Pareto distribution to account for the presence of large extreme events. The unconditional mixtures are also available.
||Julie Carreau <julie.carreau at ird.fr>
Please use the canonical form
to link to this page.