Bayesian inference using least median of squares and least trimmed squares in models with independent or correlated errors and outliers

Tsionas, Mike (2023) Bayesian inference using least median of squares and least trimmed squares in models with independent or correlated errors and outliers. Communications in Statistics - Theory and Methods. ISSN 0361-0926

[thumbnail of paper_REVISED]
Text (paper_REVISED)
paper_REVISED.pdf - Accepted Version
Available under License Creative Commons Attribution-NonCommercial-NoDerivs.

Download (633kB)

Abstract

We provide Bayesian inference in the context of Least Median of Squares and Least Trimmed Squares, two well-known techniques that are highly robust to outliers. We apply the new Bayesian techniques to linear models whose errors are independent or AR and ARMA. Model comparison is performed using posterior model probabilities, and the new techniques are examined using Monte Carlo experiments as well as an application to four portfolios of asset returns.

Item Type:
Journal Article
Journal or Publication Title:
Communications in Statistics - Theory and Methods
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/2600/2613
Subjects:
?? bayesian inferenceleast median of squaresleast trimmed squaresstochastic volatilityarma modelsoutliersstatistics and probability ??
ID Code:
200169
Deposited By:
Deposited On:
07 Aug 2023 15:35
Refereed?:
Yes
Published?:
Published
Last Modified:
05 Jan 2024 00:31