A Block Minorization--Maximization Algorithm for Heteroscedastic Regression

The computation of the maximum likelihood (ML) estimator for heteroscedastic regression models is considered. The traditional Newton algorithms for the problem require matrix multiplications and inversions, which are bottlenecks in modern Big Data contexts. A new Big Data-appropriate minorization--m...

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Bibliographic Details

Published in:	arXiv.org
Main Authors:	Nguyen, Hien D, Lloyd-Jones, Luke R, McLachlan, Geoffrey J
Format:	Paper
Language:	English
Published:	Ithaca Cornell University Library, arXiv.org 30.05.2016
Subjects:	Algorithms Big Data Computation Computer simulation Data management Inversions Maximization Maximum likelihood estimators Optimization Regression models
ISSN:	2331-8422
Online Access:	Get full text
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