Foundations of Statistical Algorithms : With References to R Packages

Claus Weihs

ISBN 10: 1439878854 / ISBN 13: 9781439878859

Published by CRC Press Dez 2013, 2013

About this Item

Neuware - Reviewing the historical development of basic algorithms to illuminate the evolution of today's more powerful statistical algorithms, this comprehensive textbook emphasizes recurring themes in all statistical algorithms including computation, assessment and verification, iteration, intuition, randomness, repetition and parallelization, and scalability. Unique in scope, it touches on topics not usually covered in similar books, namely, systematic verification and the scaling of many established techniques to very large databases. Broadly accessible, it offers examples, exercises, and selected solutions in each chapter as well as access to a supplementary website.

Seller Inventory # 9781439878859

Bibliographic Details

• Title: Foundations of Statistical Algorithms : With References to R Packages
• Publisher: CRC Press Dez 2013
• Publication Date: 2013
• Language: English
• ISBN 10: 1439878854
• ISBN 13: 9781439878859
• Binding: Buch
• Condition: Neu

About this title

Synopsis

A new and refreshingly different approach to presenting the foundations of statistical algorithms, Foundations of Statistical Algorithms: With References to R Packages reviews the historical development of basic algorithms to illuminate the evolution of today’s more powerful statistical algorithms. It emphasizes recurring themes in all statistical algorithms, including computation, assessment and verification, iteration, intuition, randomness, repetition and parallelization, and scalability. Unique in scope, the book reviews the upcoming challenge of scaling many of the established techniques to very large data sets and delves into systematic verification by demonstrating how to derive general classes of worst case inputs and emphasizing the importance of testing over a large number of different inputs.

Broadly accessible, the book offers examples, exercises, and selected solutions in each chapter as well as access to a supplementary website. After working through the material covered in the book, readers should not only understand current algorithms but also gain a deeper understanding of how algorithms are constructed, how to evaluate new algorithms, which recurring principles are used to tackle some of the tough problems statistical programmers face, and how to take an idea for a new method and turn it into something practically useful.

About the Author

Weihs, Claus; Mersmann, Olaf ; Ligges, Uwe