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Publicado por Springer Verlag, Singapore, SG, 2020
ISBN 10: 9811508933 ISBN 13: 9789811508936
Idioma: Inglés
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Añadir al carritoHardback. Condición: New. 2019 ed. This book discusses unconstrained optimization with R-a free, open-source computing environment, which works on several platforms, including Windows, Linux, and macOS. The book highlights methods such as the steepest descent method, Newton method, conjugate direction method, conjugate gradient methods, quasi-Newton methods, rank one correction formula, DFP method, BFGS method and their algorithms, convergence analysis, and proofs. Each method is accompanied by worked examples and R scripts. To help readers apply these methods in real-world situations, the book features a set of exercises at the end of each chapter. Primarily intended for graduate students of applied mathematics, operations research and statistics, it is also useful for students of mathematics, engineering, management, economics, and agriculture.
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Añadir al carritoCondición: New. pp. XVI, 304 765 illus., 50 illus. in color. 1 Edition NO-PA16APR2015-KAP.
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Añadir al carritoCondición: New. Discusses all major aspects of unconstrained optimization with RPresents important, basic methods with their algorithms, analysis, and proofsIncludes manually worked examples, R scripts, and real-world applicationsProvides exercises .
Publicado por Springer Nature Singapore, Springer Nature Singapore Jan 2020, 2020
ISBN 10: 9811508933 ISBN 13: 9789811508936
Idioma: Inglés
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Añadir al carritoBuch. Condición: Neu. Neuware -This book discusses unconstrained optimization with R¿a free, open-source computing environment, which works on several platforms, including Windows, Linux, and macOS. The book highlights methods such as the steepest descent method, Newton method, conjugate direction method, conjugate gradient methods, quasi-Newton methods, rank one correction formula, DFP method, BFGS method and their algorithms, convergence analysis, and proofs. Each method is accompanied by worked examples and R scripts. To help readers apply these methods in real-world situations, the book features a set of exercises at the end of each chapter. Primarily intended for graduate students of applied mathematics, operations research and statistics, it is also useful for students of mathematics, engineering, management, economics, and agriculture.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 320 pp. Englisch.
Publicado por Springer Nature Singapore, Springer Nature Singapore, 2020
ISBN 10: 9811508933 ISBN 13: 9789811508936
Idioma: Inglés
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Añadir al carritoBuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book discusses unconstrained optimization with R-a free, open-source computing environment, which works on several platforms, including Windows, Linux, and macOS. The book highlights methods such as the steepest descent method, Newton method, conjugate direction method, conjugate gradient methods, quasi-Newton methods, rank one correction formula, DFP method, BFGS method and their algorithms, convergence analysis, and proofs. Each method is accompanied by worked examples and R scripts. To help readers apply these methods in real-world situations, the book features a set of exercises at the end of each chapter. Primarily intended for graduate students of applied mathematics, operations research and statistics, it is also useful for students of mathematics, engineering, management, economics, and agriculture.
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Añadir al carritoBuch. Condición: Neu. Introduction to Unconstrained Optimization with R | Shashi Kant Mishra (u. a.) | Buch | xvi | Englisch | 2020 | Springer Singapore | EAN 9789811508936 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Publicado por Springer Verlag, Singapore, SG, 2020
ISBN 10: 9811508933 ISBN 13: 9789811508936
Idioma: Inglés
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Añadir al carritoHardback. Condición: New. 2019 ed. This book discusses unconstrained optimization with R-a free, open-source computing environment, which works on several platforms, including Windows, Linux, and macOS. The book highlights methods such as the steepest descent method, Newton method, conjugate direction method, conjugate gradient methods, quasi-Newton methods, rank one correction formula, DFP method, BFGS method and their algorithms, convergence analysis, and proofs. Each method is accompanied by worked examples and R scripts. To help readers apply these methods in real-world situations, the book features a set of exercises at the end of each chapter. Primarily intended for graduate students of applied mathematics, operations research and statistics, it is also useful for students of mathematics, engineering, management, economics, and agriculture.
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Añadir al carritoCondición: New. Print on Demand pp. XVI, 304 765 illus., 50 illus. in color.
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Añadir al carritoCondición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Discusses all major aspects of unconstrained optimization with RPresents important, basic methods with their algorithms, analysis, and proofsIncludes manually worked examples, R scripts, and real-world applicationsProvides exercises .