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＜電子ブック＞
Introduction to Unconstrained Optimization with R / by Shashi Kant Mishra, Bhagwat Ram

版	1st ed. 2019.
出版者	(Singapore : Springer Nature Singapore : Imprint: Springer)
出版年	2019
本文言語	英語
大きさ	XVI, 304 p. 765 illus., 50 illus. in color : online resource
著者標目	*Mishra, Shashi Kant author Ram, Bhagwat author SpringerLink (Online service)
件　名	LCSH:Mathematical optimization LCSH:Mathematics -- Data processing  全ての件名で検索 FREE:Optimization FREE:Computational Mathematics and Numerical Analysis
一般注記	1. Introduction -- 2. Mathematical Foundations -- 3. Basics of R -- 4. First Order and Second Order Necessary Conditions -- 5. One Dimensional Optimization Methods -- 6. Steepest Descent Method -- 7. Newton’s Method -- 8. Conjugate Direction Methods -- 9. Quasi-Newton Methods 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 HTTP:URL=https://doi.org/10.1007/978-981-15-0894-3

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