Skip to content Skip to navigation
University of Warwick
  • Study
  • |
  • Research
  • |
  • Business
  • |
  • Alumni
  • |
  • News
  • |
  • About

University of Warwick
Publications service & WRAP

Highlight your research

  • WRAP
    • Home
    • Search WRAP
    • Browse by Warwick Author
    • Browse WRAP by Year
    • Browse WRAP by Subject
    • Browse WRAP by Department
    • Browse WRAP by Funder
    • Browse Theses by Department
  • Publications Service
    • Home
    • Search Publications Service
    • Browse by Warwick Author
    • Browse Publications service by Year
    • Browse Publications service by Subject
    • Browse Publications service by Department
    • Browse Publications service by Funder
  • Help & Advice
University of Warwick

The Library

  • Login
  • Admin

Bayesian modelling of skewness and kurtosis with Two-Piece Scale and shape distributions

Tools
- Tools
+ Tools

Rubio, Francisco J. and Steel, Mark F. J. (2015) Bayesian modelling of skewness and kurtosis with Two-Piece Scale and shape distributions. Electronic Journal of Statistics, 9 (2). pp. 1884-1912. doi:10.1214/15-EJS1060

[img]
Preview
PDF
WRAP_euclid.ejs.1440680330.pdf - Published Version - Requires a PDF viewer.
Available under License Creative Commons Attribution 2.0..

Download (656Kb) | Preview
Official URL: http://dx.doi.org/10.1214/15-EJS1060

Request Changes to record.

Abstract

We formalise and generalise the definition of the family of univariate double two–piece distributions, obtained by using a density–based transformation of unimodal symmetric continuous distributions with a shape parameter. The resulting distributions contain five interpretable parameters that control the mode, as well as the scale and shape in each direction. Four-parameter subfamilies of this class of distributions that capture different types of asymmetry are discussed. We propose interpretable scale and location-invariant benchmark priors and derive conditions for the propriety of the corresponding posterior distribution. The prior structures used allow for meaningful comparisons through Bayes factors within flexible families of distributions. These distributions are applied to data from finance, internet traffic and medicine, comparing them with appropriate competitors.

Item Type: Journal Article
Subjects: H Social Sciences > HA Statistics
Divisions: Faculty of Science > Statistics
Library of Congress Subject Headings (LCSH): Bayesian statistical decision theory
Journal or Publication Title: Electronic Journal of Statistics
Publisher: Institute of Mathematical Statistics
ISSN: 1935-7524
Official Date: 27 August 2015
Dates:
DateEvent
27 August 2015Available
5 August 2015Accepted
January 2015Submitted
Volume: 9
Number: 2
Page Range: pp. 1884-1912
DOI: 10.1214/15-EJS1060
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Open Access

Request changes or add full text files to a record

Repository staff actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics

twitter

Email us: wrap@warwick.ac.uk
Contact Details
About Us