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.
| Version: |
1.1 |
| Depends: |
evd |
| Published: |
2020-05-11 |
| Author: |
Julie Carreau |
| Maintainer: |
Julie Carreau <julie.carreau at ird.fr> |
| License: |
GPL-2 |
| NeedsCompilation: |
yes |
| CRAN checks: |
condmixt results |
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