arXiv (All)
open access
Limiting moments of sample covariance matrices from large fold tensor vectors
We study the moments of sample covariance matrices $M_{n,k,m}$ formed from independent $k$-fold tensor products of $n$-dimensional random vectors. The base vectors have independent and identically distributed centered complex entries with unit variance and finite moments of all orders. For every fix
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
- Edgeworth Expansion and Large Deviations for the Coefficients of Products of Positive Random Matrices#1250985
- Bootstrapping Tensor Integrals#996897
- Limit theorems for spectra of random matrices with martingale structure#492600
- Optimal Sobolev Rate for Gaussian Density Approximation of Wiener Chaos Vectors#975130
- Convergence to Stable Laws and a Local Limit Theorem for Products of Positive Random Matrices#144847
Record · ID 1456510
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