rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Introduction to Unconstrained Optimization with R
  name:
    name part: Mishra, Shashi Kant.
    role:
      role term: creator
    role:
      role term: author.
    role:
      role term: aut
    role:
      role term: http://id.loc.gov/vocabulary/relators/aut
  name:
    name part: Ram, Bhagwat.
    role:
      role term: author.
    role:
      role term: aut
    role:
      role term: http://id.loc.gov/vocabulary/relators/aut
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: si
    date issued: 2019
    edition: 1st ed. 2019.
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XVI, 304 p. 765 illus., 50 illus. in color. online resource.
  abstract: 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.
  table of contents: 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.
  note: by Shashi Kant Mishra, Bhagwat Ram.
  subject:
    topic: Mathematical optimization
  subject:
    topic: Computer mathematics
  subject:
    topic: Optimization
  subject:
    topic: Computational Mathematics and Numerical Analysis
  classification: QA402.5-402.6
  classification: 519.6
  related item:
    title info:
      title: Springer eBooks
  identifier: 9789811508943
  identifier: https://doi.org/10.1007/978-981-15-0894-3
  record info:
    record creation date: 191217
    record change date: 20191218111548.0
    record identifier: 978-981-15-0894-3