Estimating Conditional Distributions with Neural Networks Using R Package deeptrafo
Contemporary empirical applications frequently require flexible regression models for complex response types and large tabular or non-tabular, including image or text, data. Classical regression models either break down under the computational load of processing such data or require additional manu...
Saved in:
| Main Authors: | Lucas Kook, Philipp F. M. Baumann, Oliver Dürr, Beate Sick, David Rügamer |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Foundation for Open Access Statistics
2024-12-01
|
| Series: | Journal of Statistical Software |
| Online Access: | https://www.jstatsoft.org/index.php/jss/article/view/5244 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
deepregression: A Flexible Neural Network Framework for Semi-Structured Deep Distributional Regression
by: David Rügamer, et al.
Published: (2023-01-01) -
BEKKs: An R Package for Estimation of Conditional Volatility of Multivariate Time Series
by: Markus J. Fülle, et al.
Published: (2024-11-01) -
sparsegl: An R Package for Estimating Sparse Group Lasso
by: Xiaoxuan Liang, et al.
Published: (2024-08-01) -
bayesnec: An R Package for Concentration-Response Modeling and Estimation of Toxicity Metrics
by: Rebecca Fisher, et al.
Published: (2024-08-01) -
The R Package markets: Estimation Methods for Markets in Equilibrium and Disequilibrium
by: Pantelis Karapanagiotis
Published: (2024-02-01)