Posterior property of Student-t linear regression model using objective priors

Min Wang and Mingan Yang

Statistics & Probability Letters, 2016, vol. 113, issue C, 23-29

Abstract: We derive objective priors for linear model with independent Student-t errors with unknown degrees of freedom v. It is shown that most of them preclude the existence of a proper posterior distribution unless we are willing to truncate the possible values of va priori.

Keywords: Bayesian inference; Objective priors; Robustness to outliers (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0167715215302893
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:stapro:v:113:y:2016:i:c:p:23-29

Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
https://shop.elsevie ... _01_ooc_1&version=01

DOI: 10.1016/j.spl.2016.02.003

Access Statistics for this article

Statistics & Probability Letters is currently edited by Somnath Datta and Hira L. Koul

More articles in Statistics & Probability Letters from Elsevier
Bibliographic data for series maintained by Catherine Liu ().