arXiv (All)
open access
Resampling-Based Inference for Incomplete Paired Functional Data
We consider testing equality of mean functions for paired functional data, where one entire function is missing. To use all available information from the paired and unpaired observations, we propose globalized test statistics that are based on a weighted sum of point-wise paired-$t$ and Welch-$t$-t
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
- Effects of Tele-prehabilitation in Patients Waiting for Knee Replacement#806251
- Mean estimation in spatial functional data#1447316
- Teaching Vampire New Tricks: An Experimental Study of Neural Clause Selection#1110602
- Immediate Versus Optional Delayed Surgical Repair for Treatment of Acute ACL Injuries#992179
- Automated selection of $r$ in $r$-largest order statistics models: finite-sample performance and return-level inference#1423793
Record · ID 1448293
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