Fractional and Multivariable Calculus

Model Building and Optimization Problems

  • A.M. Mathai
  • H.J. Haubold

Part of the Springer Optimization and Its Applications book series (SOIA, volume 122)

Table of contents

  1. Front Matter
    Pages i-xiii
  2. A. M. Mathai, H. J. Haubold
    Pages 1-37
  3. A. M. Mathai, H. J. Haubold
    Pages 39-88
  4. A. M. Mathai, H. J. Haubold
    Pages 89-106
  5. A. M. Mathai, H. J. Haubold
    Pages 107-181
  6. A. M. Mathai, H. J. Haubold
    Pages 183-208
  7. A. M. Mathai, H. J. Haubold
    Pages 209-229
  8. Back Matter
    Pages 231-234

About this book

Introduction

This textbook presents a rigorous approach to multivariable calculus in the context of model building and optimization problems. This comprehensive overview is based on lectures given at five SERC Schools from 2008 to 2012 and covers a broad range of topics that will enable readers to understand and create deterministic and nondeterministic models.  Researchers, advanced undergraduate, and graduate students in mathematics, statistics, physics, engineering, and biological sciences will find this book to be a valuable resource for finding appropriate models to describe real-life situations.

The first chapter begins with an introduction to fractional calculus moving on to discuss fractional integrals, fractional derivatives, fractional differential equations and their solutions.  Multivariable calculus is covered in the second chapter and introduces the fundamentals of multivariable calculus (multivariable functions, limits and continuity, differentiability, directional derivatives and expansions of multivariable functions). Illustrative examples, input-output process, optimal recovery of functions and approximations are given; each section lists an ample number of exercises to heighten understanding of the material. Chapter three  discusses deterministic/mathematical and optimization models evolving from differential equations, difference equations, algebraic models, power function models, input-output models and pathway models. Fractional integral and derivative models are examined.  Chapter four covers non-deterministic/stochastic models. The random walk model, branching process model, birth and death process model, time series models, and regression type models are examined. The fifth chapter covers optimal design. General linear models from a statistical point of view are introduced; the Gauss–Markov theorem, quadratic forms, and generalized inverses of matrices are covered. Pathway, symmetric, and asymmetric models are covered in chapter six, the concepts are illustrated with graphs.

 


Keywords

Mittag-Leer and Wright's functions fractional order dierential and integral equations fractional calculus multivariable calculus deterministic models linear and non-linear analysis non-deterministic models regression type prediction models prediction models matrix-variate calculus Canonical Correlation Analysis Analysis of Variance

Authors and affiliations

  • A.M. Mathai
    • 1
  • H.J. Haubold
    • 2
  1. 1.Centre for Mathematical and Statistical SciencesPeechi CampusIndia
  2. 2.Vienna International CentreOffice for Outer Space AffairsUnited Nations, ViennaAustria

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-59993-9
  • Copyright Information Springer International Publishing AG 2017
  • Publisher Name Springer, Cham
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-3-319-59992-2
  • Online ISBN 978-3-319-59993-9
  • Series Print ISSN 1931-6828
  • Series Online ISSN 1931-6836
  • About this book
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