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Foundations of Statistical Algorithms

With References to R Packages

By: Claus Weihs,Olaf Mersmann,Uwe Ligges

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Foundations of Statistical Algorithms

With References to R Packages

By: Claus Weihs,Olaf Mersmann,Uwe Ligges

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.

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Page Count

495

Publisher

CRC Press

Published Date

ISBN 10

1439878870

ISBN 13

9781439878873

Foundations of Statistical Algorithms

With References to R Packages

By: Claus Weihs,Olaf Mersmann,Uwe Ligges

Write a review Read reviews Take a Quiz Solve Book Puzzle

Foundations of Statistical Algorithms

With References to R Packages

By: Claus Weihs,Olaf Mersmann,Uwe Ligges

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.

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Page Count

502

Publisher

CRC Press

Published Date

ISBN 10

1439878854

ISBN 13

9781439878859