Papers
Topics
Authors
Recent
Assistant
AI Research Assistant
Well-researched responses based on relevant abstracts and paper content.
Custom Instructions Pro
Preferences or requirements that you'd like Emergent Mind to consider when generating responses.
Gemini 2.5 Flash
Gemini 2.5 Flash 144 tok/s
Gemini 2.5 Pro 50 tok/s Pro
GPT-5 Medium 24 tok/s Pro
GPT-5 High 28 tok/s Pro
GPT-4o 124 tok/s Pro
Kimi K2 210 tok/s Pro
GPT OSS 120B 433 tok/s Pro
Claude Sonnet 4.5 37 tok/s Pro
2000 character limit reached

A moderate deviation principle for empirical bootstrap measure (1206.1459v2)

Published 7 Jun 2012 in math.ST and stat.TH

Abstract: We prove two Large deviations principles (LDP) in the zone of moderate deviation probabilities. First we establish LDP for the conditional distributions of moderate deviations of empirical bootstrap measures given empirical probability measures. Second we establish LDP for the joint distributions of empirical measure and bootstrap empirical measures. Using these LDPs, similar LDPs for statistical differentiable functionals can be established. The LDPs for moderate deviations of empirical quantile processes and empirical bootstrap copula function are provided as illustration of these results.

Summary

We haven't generated a summary for this paper yet.

Dice Question Streamline Icon: https://streamlinehq.com

Open Problems

We haven't generated a list of open problems mentioned in this paper yet.

Lightbulb Streamline Icon: https://streamlinehq.com

Continue Learning

We haven't generated follow-up questions for this paper yet.

Authors (1)

List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.