Academic Journal

The Safety Belt estimator under multivariate linear models with inequality constraints

Bibliographic Details
Title: The Safety Belt estimator under multivariate linear models with inequality constraints
Authors: Filipiak, Katarzyna, von Rosen, Dietrich, Rejchel, Wojciech, Singull, Martin
Source: Journal of Statistical Planning and Inference. 241
Subject Terms: Convex optimization theory, Inequality constraints, MANOVA model, Maximum likelihood estimation
Description: The main goal of this paper is to determine maximum likelihood estimators under a multivariate linear model with prior information introduced via inequality restrictions on the mean parameters. The restrictions are in the form of quadratic inequalities. Methods from convex optimization theory play a fundamental role in determining the estimators. A characteristic of the new estimators, called Safety Belt estimators, is that depending on the observed data, there are two alternative solutions to the likelihood equations.
File Description: electronic
Access URL: https://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-217538
https://doi.org/10.1016/j.jspi.2025.106335
Database: SwePub
Description
ISSN:03783758
18731171
DOI:10.1016/j.jspi.2025.106335