Introduction to Unconstrained Optimization with R
Shashi Kant Mishra, Bhagwat Ram
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.
Catégories:
Année:
2019
Edition:
1
Editeur::
Springer
Langue:
english
Pages:
309
ISBN 10:
9811508941
ISBN 13:
9789811508943
Fichier:
PDF, 5.03 MB
IPFS:
,
english, 2019
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