A quasi-Newton acceleration for high-dimensional optimization algorithms

DOI10.1007/s11222-009-9166-3zbMath1284.90095OpenAlexW2076007362WikidataQ34607331 ScholiaQ34607331MaRDI QIDQ692972

M. C. Fu

Publication date: 6 December 2012

Published in: Statistics and Computing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11222-009-9166-3

zbMATH Keywords

generalized eigenvaluesmaximum likelihoodmultivariate timagingadmixture models

Mathematics Subject Classification ID

Software, source code, etc. for problems pertaining to statistics (62-04) Applications of statistics to biology and medical sciences; meta analysis (62P10) Numerical optimization and variational techniques (65K10) Newton-type methods (49M15) Methods of quasi-Newton type (90C53) Approximations to statistical distributions (nonasymptotic) (62E17)

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Uses Software

• SQUAREM

Cites Work

• Maximum likelihood estimation via the ECM algorithm: A general framework
• The EM Algorithm and Extensions, 2E
• Simple and Globally Convergent Methods for Accelerating the Convergence of Any EM Algorithm
• Parameter expansion to accelerate EM: the PX-EM algorithm
• Numerical Analysis for Statisticians
• The ECME algorithm: A simple extension of EM and ECM with faster monotone convergence
• Conjugate Gradient Acceleration of the EM Algorithm
• A curious likelihood identity for the multivariate t-distribution
• A Statistical Model for Positron Emission Tomography
• RELATIONS BETWEEN TWO SETS OF VARIATES
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