Package: condmixt
Type: Package
Title: Conditional Density Estimation with Neural Network Conditional
        Mixtures
Version: 1.1
Date: 2020-05-09
Author: Julie Carreau
Maintainer: Julie Carreau <julie.carreau@ird.fr>
Description: 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.
Depends: evd
License: GPL-2
LazyLoad: yes
NeedsCompilation: yes
Packaged: 2020-05-10 09:07:01 UTC; lili
Repository: CRAN
Date/Publication: 2020-05-11 09:10:08 UTC
Built: R 4.0.2; x86_64-apple-darwin17.0; 2020-07-15 11:12:12 UTC; unix
Archs: condmixt.so.dSYM
