Logo - springer
Slogan - springer

Statistics - Statistical Theory and Methods | Optimization

Optimization

Series: Springer Texts in Statistics, Vol. 95

Lange, Kenneth

2nd ed. 2013, XVII, 529 p. 19 illus., 3 illus. in color.

Available Formats:
eBook
Information

Springer eBooks may be purchased by end-customers only and are sold without copy protection (DRM free). Instead, all eBooks include personalized watermarks. This means you can read the Springer eBooks across numerous devices such as Laptops, eReaders, and tablets.

You can pay for Springer eBooks with Visa, Mastercard, American Express or Paypal.

After the purchase you can directly download the eBook file or read it online in our Springer eBook Reader. Furthermore your eBook will be stored in your MySpringer account. So you can always re-download your eBooks.

 
$69.95

(net) price for USA

ISBN 978-1-4614-5838-8

digitally watermarked, no DRM

Included Format: PDF and EPUB

download immediately after purchase


learn more about Springer eBooks

add to marked items

Hardcover
Information

Hardcover version

You can pay for Springer Books with Visa, Mastercard, American Express or Paypal.

Standard shipping is free of charge for individual customers.

 
$89.95

(net) price for USA

ISBN 978-1-4614-5837-1

free shipping for individuals worldwide

usually dispatched within 3 to 5 business days


add to marked items

  • ​Provides an integration of mathematical theory and development of numerical algorithms for applied optimization
  • Includes new chapters on calculus of variations, integration, and block relaxation
  • Showcases balance between presentation of mathematical theory and development of numerical algorithms

Finite-dimensional optimization problems occur throughout the mathematical sciences. The majority of these problems cannot be solved analytically. This introduction to optimization attempts to strike a balance between presentation of mathematical theory and development of numerical algorithms. Building on students’ skills in calculus and linear algebra, the text provides a rigorous exposition without undue abstraction. Its stress on statistical applications will be especially appealing to graduate students of statistics and biostatistics. The intended audience also includes students in applied mathematics, computational biology, computer science, economics, and physics who want to see rigorous mathematics combined with real applications.

 

In this second edition, the emphasis remains on finite-dimensional optimization. New material has been added on the MM algorithm, block descent and ascent, and the calculus of variations. Convex calculus is now treated in much greater depth.  Advanced topics such as the Fenchel conjugate, subdifferentials, duality, feasibility, alternating projections, projected gradient methods, exact penalty methods, and Bregman iteration will equip students with the essentials for understanding modern data mining techniques in high dimensions.

Content Level » Research

Keywords » Convexity - Differentiation - Gauge Integral - Integration - Optimization - Statistical variance

Related subjects » Mathematics - Operations Research & Decision Theory - Physical & Information Science - Statistical Theory and Methods

Table of contents / Preface / Sample pages 

Popular Content within this publication 

 

Articles

Read this Book on Springerlink

Services for this book

New Book Alert

Get alerted on new Springer publications in the subject area of Statistical Theory and Methods.