condmixt: Conditional Density Estimation with Neural Network Conditional Mixtures

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.

Package details

AuthorJulie Carreau
MaintainerJulie Carreau <>
Package repositoryView on CRAN
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condmixt documentation built on July 1, 2020, 6:04 p.m.