Statistical measures for least squares using the αQβR algorithm

Journal article

Peer reviewed

R. E KALABA, J JOHNSON and H. H NATSUYAMA

Journal of optimization theory and applications, Vol.127(3), pp.515-522

2005

Abstract

Miscellaneous

Operational research and scientific management

Exact sciences and technology

Applied sciences

Control theory. Systems

Modelling and identification

Operational research. Management science

Mathematical programming

Computer science; control theory; systems

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Collaboration types: Domestic collaboration
Citation topics: 9 Mathematics; 9.207 Comvergence & Optimization; 9.207.584 Moore-Penrose Inverse
Web Of Science research areas: Mathematics, Applied; Operations Research & Management Science
ESI research areas: Engineering

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Title: Statistical measures for least squares using the αQβR algorithm
Creators: R. E KALABA - Electrical Engineering, and Economics, University of Southern California, Los Angeles, California, United States
J JOHNSON - School of Business, University of Miami, Coral Gables, Florida, United States
H. H NATSUYAMA - School of Engineering, California State University, Fullerton, California, United States
Publication Details: Journal of optimization theory and applications, Vol.127(3), pp.515-522
Publisher: Springer; New York, NY
Academic Unit: Miami Herbert Business School; MHBS - Marketing
Language: English
Resource Type: Journal article
Record Identifier: 991031578562302976