arXiv (All)
open access
W-Kernel and Its Principal Space for Frequentist Evaluation of Bayesian Estimators
Evaluating the variability of posterior estimates is a key aspect of Bayesian model assessment. In this study, we focus on the posterior covariance matrix W, defined through the log likelihoods of individual observations. Previous studies, notably MacEachern and Peruggia (2002) and Thomas et al. (20
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
- Estimation Associated with Linear Models: A Revisitation#1149659
- Subgroup analyses and effect modification with Bayesian kernel machine regression.#1354
- Prior-Amortized In-Context Bayesian Inference for Generalized Linear Mixed-Effects Models#1050600
- Influence Diagnostics in High-dimensional M-estimation: Precise Asymptotics#1106009
- Bayesian Effective Dimension from Information Growth#820314
Record · ID 972850
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