Next Article in Journal
Isothermal Oxidation of Aluminized Coatings on High-Entropy Alloys
Next Article in Special Issue
Explicit Formula of Koszul–Vinberg Characteristic Functions for a Wide Class of Regular Convex Cones
Previous Article in Journal
On the Virtual Cell Transmission in Ultra Dense Networks
Previous Article in Special Issue
From Tools in Symplectic and Poisson Geometry to J.-M. Souriau’s Theories of Statistical Mechanics and Thermodynamics
Article Menu
Issue 10 (October) cover image

Export Article

Open AccessArticle
Entropy 2016, 18(10), 375; doi:10.3390/e18100375

Non-Asymptotic Confidence Sets for Circular Means

Institut für Mathematik, Technische Universität Ilmenau, 98684 Ilmenau, Germany
This paper is an extended version of our paper published in Proceedings of the 2nd International Conference on Geometric Science of Information, Palaiseau, France, 28–30 October 2015; Nielsen, F., Barbaresco, F., Eds.; Lecture Notes in Computer Science, Volume 9389; Springer International Publishing: Cham, Switzerland, 2015; pp. 635–642.
These authors contributed equally to this work.
*
Author to whom correspondence should be addressed.
Academic Editors: Frédéric Barbaresco and Frank Nielsen
Received: 15 July 2016 / Revised: 10 October 2016 / Accepted: 13 October 2016 / Published: 20 October 2016
(This article belongs to the Special Issue Differential Geometrical Theory of Statistics)
View Full-Text   |   Download PDF [345 KB, uploaded 25 October 2016]   |  

Abstract

The mean of data on the unit circle is defined as the minimizer of the average squared Euclidean distance to the data. Based on Hoeffding’s mass concentration inequalities, non-asymptotic confidence sets for circular means are constructed which are universal in the sense that they require no distributional assumptions. These are then compared with asymptotic confidence sets in simulations and for a real data set. View Full-Text
Keywords: directional data; circular mean; universal confidence sets; non-asymptotic confidence sets; mass concentration inequalities; Hoeffding’s inequality directional data; circular mean; universal confidence sets; non-asymptotic confidence sets; mass concentration inequalities; Hoeffding’s inequality
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Hotz, T.; Kelma, F.; Wieditz, J. Non-Asymptotic Confidence Sets for Circular Means. Entropy 2016, 18, 375.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Entropy EISSN 1099-4300 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top