arXiv (All)
open access
Stochastic Variational Inference for Vine Copula Distributional Regression
Structured additive distributional regression flexibly relates all parameters of a conditional response distribution to covariates, but multivariate extensions remain challenging when dependence is complex. We propose a multivariate structured additive distributional regression model based on regula
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Fast inference methods for high-dimensional factor copulas#144989
- Valid and Expressive Copulas for Irregular Multivariate Time Series#222603
- Stochastic Variational Inference for Structured Additive Distributional Regression#684193
- Stochastic Variational Inference for Structured Additive Distributional Regression#682418
- Conditional Distribution Estimation Given Functional Covariates Using Deep Operator Networks#926241
Record · ID 1142297
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive