Introduction to Unconstrained Optimization with R is popular PDF and ePub book, written by Shashi Kant Mishra in 2019-12-17, it is a fantastic choice for those who relish reading online the Mathematics genre. Let's immerse ourselves in this engaging Mathematics book by exploring the summary and details provided below. Remember, Introduction to Unconstrained Optimization with R can be Read Online from any device for your convenience.
Introduction to Unconstrained Optimization with R Book PDF Summary
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.
Detail Book of Introduction to Unconstrained Optimization with R PDF
- Author : Shashi Kant Mishra
- Release : 17 December 2019
- Publisher : Springer Nature
- ISBN : 9789811508943
- Genre : Mathematics
- Total Page : 309 pages
- Language : English
- PDF File Size : 7,7 Mb
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