arXiv (All)
open access
Testing for patterns and structures in covariance and correlation matrices
Covariance matrices of random vectors contain information that is crucial for modelling. Specific structures and patterns of the covariances (or correlations) may be used to justify parametric models, e.g., autoregressive models. Until now, there have been only a few approaches for testing such cova
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
- PCA on correlation or covariance?#787294
- Reduced-Rank Autoregressive Models for Matrix Time Series#1076497
- Maps, Simulations, Spaces and Dynamics: On Distinguishing Types of Structural Representations#100456
- Nonlinear spectral graph theory#984843
- Performance in Symmetry-Restricted Searches for Post-Quantum Correlations#1109679
Record · ID 997901
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