arXiv (All)
open access
Objective Model Prior Probabilities in Variable Selection
For many years it was routine to use equal model prior probabilities in Bayesian model uncertainty analysis. At least twenty years ago it became clear that this was problematic, leading to support of much too large models in the increasingly huge model spaces being considered in genomics and other f
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
- Overcoming Model Misspecification in Bayesian Inference of Molecular Signalling Networks#1051000
- Efficient model exploration with the integrated nested Laplace approximation#975334
- Advanced Bayesian kernel machine regression for large-scale exposome studies: Making the impossible possible.#4124
- A Least-Squares Approach to Sample-Based Prior Elicitation#1048771
- Conformal risk control for model-form uncertainty in parametric non-intrusive reduced-order models#1050924
Record · ID 1035431
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