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 69 tok/s
Gemini 2.5 Pro 52 tok/s Pro
GPT-5 Medium 37 tok/s Pro
GPT-5 High 28 tok/s Pro
GPT-4o 119 tok/s Pro
Kimi K2 218 tok/s Pro
GPT OSS 120B 456 tok/s Pro
Claude Sonnet 4.5 33 tok/s Pro
2000 character limit reached

Bi-$s^*$-Concave Distributions (2006.03989v2)

Published 6 Jun 2020 in math.ST and stat.TH

Abstract: We introduce new shape-constrained classes of distribution functions on R, the bi-$s*$-concave classes. In parallel to results of D\"umbgen, Kolesnyk, and Wilke (2017) for what they called the class of bi-log-concave distribution functions, we show that every $s$-concave density $f$ has a bi-$s*$-concave distribution function $F$ for $s*\leq s/(s+1)$. Confidence bands building on existing nonparametric bands, but accounting for the shape constraint of bi-$s*$-concavity, are also considered. The new bands extend those developed by D\"umbgen et al. (2017) for the constraint of bi-log-concavity. We also make connections between bi-$s*$-concavity and finiteness of the Cs\"org\H{o} - R\'ev\'esz constant of $F$ which plays an important role in the theory of quantile processes.

Summary

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

Lightbulb Streamline Icon: https://streamlinehq.com

Continue Learning

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

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

Collections

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