arXiv (OAI Expanded)
open access
Minimax properties of gamma kernel density estimators under $L^p$ loss and $β$-Hölder smoothness of the target
This paper considers the asymptotic behavior in $β$-Hölder spaces, and under $L^p$ loss, of the non-modified gamma kernel density estimator introduced by Chen (Annals of the Institute of Statistical Mathematics, 52, 471-480, 2000) for the analysis of nonnegative data, in the situation where the targ
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
- An Exact Tail Condition for the Largest Error in Estimating a Rank-One Direction#972182
- Saddle Point Approximation and Central Limit Theorem for Densities in High Dimensions#1155069
- On the Wasserstein distance between a hyperuniform point process and its mean#1062742
- Negative moments of the support function and applications to isotropic convex bodies#1064301
- Central Limit Theorems for Markov Chains from Wasserstein Convergence Rates#972354
Record · ID 1083035
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