Computing Science and Statistics, Connie Page; Raoul LePage

Автор: Richard A. Johnson, Gouri K. Bhattacharyya
Название: Statistics: Principles and Methods, 7th Edition
ISBN: 0470904119 ISBN-13(EAN): 9780470904114
Издательство: Wiley
Рейтинг:
Цена: 35369.00 р.
Наличие на складе: Поставка под заказ.

Описание: Statistics: Principles and Methods, 7th Edition provides a comprehensive, accurate introduction to statistics for business professionals who need to learn how to apply key concepts. The chapters include real-world data, designed to make the material more relevant. The numerous examples clearly demonstrate the important points of the methods.

Автор: Lunn, David,
Название: The BUGS Book
ISBN: 1584888490 ISBN-13(EAN): 9781584888499
Издательство: Taylor&Francis
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Цена: 7042.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: Bayesian methods have become the widely used statistical methods for data analysis and modeling. The BUGS software has become the popular software for Bayesian analysis worldwide. This title provides a practical introduction to this program and its use. It covers the functionalities of BUGS, including prediction, missing data, and model criticism.

Автор: Giraud
Название: Introduction to High-Dimensional Statistics
ISBN: 1482237946 ISBN-13(EAN): 9781482237948
Издательство: Taylor&Francis
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Цена: 9645.00 р.
Наличие на складе: Нет в наличии.

Описание: Ever-greater computing technologies have given rise to an exponentially growing volume of data. Today massive data sets (with potentially thousands of variables) play an important role in almost every branch of modern human activity, including networks, finance, and genetics. However, analyzing such data has presented a challenge for statisticians and data analysts and has required the development of new statistical methods capable of separating the signal from the noise. Introduction to High-Dimensional Statistics is a concise guide to state-of-the-art models, techniques, and approaches for handling high-dimensional data. The book is intended to expose the reader to the key concepts and ideas in the most simple settings possible while avoiding unnecessary technicalities. Offering a succinct presentation of the mathematical foundations of high-dimensional statistics, this highly accessible text: Describes the challenges related to the analysis of high-dimensional data Covers cutting-edge statistical methods including model selection, sparsity and the lasso, aggregation, and learning theory Provides detailed exercises at the end of every chapter with collaborative solutions on a wikisite Illustrates concepts with simple but clear practical examples Introduction to High-Dimensional Statistics is suitable for graduate students and researchers interested in discovering modern statistics for massive data. It can be used as a graduate text or for self-study.