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Guide to empirical orthogonal functions for climate data analysis, Navarra, Antonio Simoncini, Valeria


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Автор: Navarra, Antonio Simoncini, Valeria
Название:  Guide to empirical orthogonal functions for climate data analysis
ISBN: 9789048137015
Издательство: Springer
Классификация:



ISBN-10: 9048137012
Обложка/Формат: Hardback
Страницы: 206
Вес: 0.38 кг.
Дата издания: 01.01.2010
Язык: English
Иллюстрации: Biography
Размер: 241 x 162 x 15
Читательская аудитория: Professional & vocational
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: A Guide to Empirical Orthogonal Functions for Climate Data Analysis introduces the reader to a practical application of the methods used in the field, including data sets from climate simulations and MATLAB codes for the algorithms.

Orthogonal Arrays

Автор: A.S. Hedayat; N.J.A. Sloane; John Stufken
Название: Orthogonal Arrays
ISBN: 1461271584 ISBN-13(EAN): 9781461271581
Издательство: Springer
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Цена: 149060.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Orthogonal arrays have played a vital role in improving the quality of products manufactured throughout the world. Anyone running experiments - whether in a chemistry lab or a manufacturing plant, or in agricultural or medical research - will find this book useful.

An Introduction to Data Analysis using Aggregation Functions in R

Автор: Simon James
Название: An Introduction to Data Analysis using Aggregation Functions in R
ISBN: 3319467611 ISBN-13(EAN): 9783319467610
Издательство: Springer
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Цена: 53100.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:

This textbook helps future data analysts comprehend aggregation function theory and methods in an accessible way, focusing on a fundamental understanding of the data and summarization tools. Offering a broad overview of recent trends in aggregation research, it complements any study in statistical or machine learning techniques. Readers will learn how to program key functions in R without obtaining an extensive programming background.
Sections of the textbook cover background information and context, aggregating data with averaging functions, power means, and weighted averages including the Borda count. It explains how to transform data using normalization or scaling and standardization, as well as log, polynomial, and rank transforms. The section on averaging with interaction introduces OWS functions and the Choquet integral, simple functions that allow the handling of non-independent inputs. The final chapters examine software analysis with an emphasis on parameter identification rather than technical aspects.
This textbook is designed for students studying computer science or business who are interested in tools for summarizing and interpreting data, without requiring a strong mathematical background. It is also suitable for those working on sophisticated data science techniques who seek a better conception of fundamental data aggregation. Solutions to the practice questions are included in the textbook.

Probabilistic Analysis of Belief Functions

Автор: Ivan Kramosil
Название: Probabilistic Analysis of Belief Functions
ISBN: 1461351456 ISBN-13(EAN): 9781461351450
Издательство: Springer
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Цена: 93160.00 T
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Transmission of Information by Orthogonal Functions

Автор: Henning F. Harmuth
Название: Transmission of Information by Orthogonal Functions
ISBN: 3642619762 ISBN-13(EAN): 9783642619762
Издательство: Springer
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Цена: 104480.00 T
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Описание: The orthogonality of functions has been exploited in communications since its very beginning. However, it may turn out that the most important change is one that appears rather theoretical on the surface and that concerns shift-invariant features strongly connected with sine-cosine functions.

Empirical Modeling and Data Analysis for Engineers and Appli

Автор: Pardo Scott
Название: Empirical Modeling and Data Analysis for Engineers and Appli
ISBN: 3319327674 ISBN-13(EAN): 9783319327679
Издательство: Springer
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Цена: 62410.00 T
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Описание: This textbook teaches advanced undergraduate and first-year graduate students in Engineering and Applied Sciences to gather and analyze empirical observations (data) in order to aid in making design decisions.

While science is about discovery, the primary paradigm of engineering and 'applied science' is design. Scientists are in the discovery business and want, in general, to understand the natural world rather than to alter it. In contrast, engineers and applied scientists design products, processes, and solutions to problems.
That said, statistics, as a discipline, is mostly oriented toward the discovery paradigm. Young engineers come out of their degree programs having taken courses such as 'Statistics for Engineers and Scientists' without any clear idea as to how they can use statistical methods to help them design products or processes. Many seem to think that statistics is only useful for demonstrating that a device or process actually does what it was designed to do. Statistics courses emphasize creating predictive or classification models - predicting nature or classifying individuals, and statistics is often used to prove or disprove phenomena as opposed to aiding in the design of a product or process. In industry however, Chemical Engineers use designed experiments to optimize petroleum extraction; Manufacturing Engineers use experimental data to optimize machine operation; Industrial Engineers might use data to determine the optimal number of operators required in a manual assembly process. This text teaches engineering and applied science students to incorporate empirical investigation into such design processes.
Much of the discussion in this book is about models, not whether the models truly represent reality but whether they adequately represent reality with respect to the problems at hand; many ideas focus on how to gather data in the most efficient way possible to construct adequate models.Includes chapters on subjects not often seen together in a single text (e.g., measurement systems, mixture experiments, logistic regression, Taguchi methods, simulation)Techniques and concepts introduced present a wide variety of design situations familiar to engineers and applied scientists and inspire incorporation of experimentation and empirical investigation into the design process.Software is integrally linked to statistical analyses with fully worked examples in each chapter; fully worked using several packages: SAS, R, JMP, Minitab, and MS Excel - also including discussion questions at the end of each chapter.
The fundamental learning objective of this textbook is for the reader to understand how experimental data can be used to make design decisions and to be familiar with the most common types of experimental designs and analysis methods.


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