Skip to main content
Duke University Libraries
DukeSpace Scholarship by Duke Authors
  • Login
  • Ask
  • Menu
  • Login
  • Ask a Librarian
  • Search & Find
  • Using the Library
  • Research Support
  • Course Support
  • Libraries
  • About
View Item 
  •   DukeSpace
  • Duke Scholarly Works
  • Scholarly Articles
  • View Item
  •   DukeSpace
  • Duke Scholarly Works
  • Scholarly Articles
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

Heavy-Tailed Density Estimation

Thumbnail
View / Download
620.6 Kb
Date
2022-01-01
Authors
Tokdar, ST
Jiang, S
Cunningham, EL
Repository Usage Stats
3
views
1
downloads
Abstract
A novel statistical method is proposed and investigated for estimating a heavy tailed density under mild smoothness assumptions. Statistical analyses of heavy-tailed distributions are susceptible to the problem of sparse information in the tail of the distribution getting washed away by unrelated features of a hefty bulk. The proposed Bayesian method avoids this problem by incorporating smoothness and tail regularization through a carefully specified semiparametric prior distribution, and is able to consistently estimate both the density function and its tail index at near minimax optimal rates of contraction. A joint, likelihood driven estimation of the bulk and the tail is shown to help improve uncertainty assessment in estimating the tail index parameter and offer more accurate and reliable estimates of the high tail quantiles compared to thresholding methods. Supplementary materials for this article are available online.
Type
Journal article
Subject
Logistic Gaussian processes
Posterior contraction
Regular variation
Semiparametric estimation
Tail index estimation
Permalink
https://hdl.handle.net/10161/26277
Published Version (Please cite this version)
10.1080/01621459.2022.2104727
Publication Info
Tokdar, ST; Jiang, S; & Cunningham, EL (2022). Heavy-Tailed Density Estimation. Journal of the American Statistical Association. pp. 1-13. 10.1080/01621459.2022.2104727. Retrieved from https://hdl.handle.net/10161/26277.
This is constructed from limited available data and may be imprecise. To cite this article, please review & use the official citation provided by the journal.
Collections
  • Scholarly Articles
More Info
Show full item record

Scholars@Duke

Tokdar

Surya Tapas Tokdar

Professor of Statistical Science
Open Access

Articles written by Duke faculty are made available through the campus open access policy. For more information see: Duke Open Access Policy

Rights for Collection: Scholarly Articles


Works are deposited here by their authors, and represent their research and opinions, not that of Duke University. Some materials and descriptions may include offensive content. More info

Make Your Work Available Here

How to Deposit

Browse

All of DukeSpaceCommunities & CollectionsAuthorsTitlesTypesBy Issue DateDepartmentsAffiliations of Duke Author(s)SubjectsBy Submit DateThis CollectionAuthorsTitlesTypesBy Issue DateDepartmentsAffiliations of Duke Author(s)SubjectsBy Submit Date

My Account

LoginRegister

Statistics

View Usage Statistics
Duke University Libraries

Contact Us

411 Chapel Drive
Durham, NC 27708
(919) 660-5870
Perkins Library Service Desk

Digital Repositories at Duke

  • Report a problem with the repositories
  • About digital repositories at Duke
  • Accessibility Policy
  • Deaccession and DMCA Takedown Policy

TwitterFacebookYouTubeFlickrInstagramBlogs

Sign Up for Our Newsletter
  • Re-use & Attribution / Privacy
  • Harmful Language Statement
  • Support the Libraries
Duke University