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Functional Data Analysis, James Ramsay; B. W. Silverman


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Цена: 20962.00р.
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Автор: James Ramsay; B. W. Silverman
Название:  Functional Data Analysis
ISBN: 9781441923004
Издательство: Springer
Классификация:
ISBN-10: 1441923004
Обложка/Формат: Paperback
Страницы: 450
Вес: 0.68 кг.
Дата издания: 2005
Серия: Springer Series in Statistics
Язык: English
Издание: 2nd ed. softcover of
Иллюстрации: 151 illustrations, black and white; xx, 428 p. 151 illus.
Размер: 234 x 156 x 23
Читательская аудитория: Professional & vocational
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: Scientists today collect samples of curves and other functional observations. This monograph presents many ideas and techniques for such data. Included are expressions in the functional domain of such classics as linear regression, principal components analysis, linear modelling, and canonical correlation analysis, as well as specifically functional techniques such as curve registration and principal differential analysis. Data arising in real applications are used throughout for both motivation and illustration, showing how functional approaches allow us to see new things, especially by exploiting the smoothness of the processes generating the data. The data sets exemplify the wide scope of functional data analysis; they are drwan from growth analysis, meterology, biomechanics, equine science, economics, and medicine. The book presents novel statistical technology while keeping the mathematical level widely accessible. It is designed to appeal to students, to applied data analysts, and to experienced researchers; it will have value both within statistics and across a broad spectrum of other fields. Much of the material is based on the authors own work, some of which appears here for the first time. Jim Ramsay is Professor of Psychology at McGill University and is an international authority on many aspects of multivariate analysis. He draws on his collaboration with researchers in speech articulation, motor control, meteorology, psychology, and human physiology to illustrate his technical contributions to functional data analysis in a wide range of statistical and application journals. Bernard Silverman, author of the highly regarded Density Estimation for Statistics and Data Analysis, and coauthor of Nonparametric Regression and Generalized Linear Models: A Roughness Penalty Approach, is Professor of Statistics at Bristol University. His published work on smoothing methods and other aspects of applied, computational, and theoretical statistics has been recognized by the Presidents Award of the Committee of Presidents of Statistical Societies, and the award of two Guy Medals by the Royal Statistical Society.


An Introduction to Multivariate Statistical Analysis, Third Edition

Автор: T. W. Anderson
Название: An Introduction to Multivariate Statistical Analysis, Third Edition
ISBN: 0471360910 ISBN-13(EAN): 9780471360919
Издательство: Wiley
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Цена: 27712.00 р.
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Описание: Uses the method of maximum likelihood to a large extent to ensure reasonable, and in some cases optimal procedures. This work treats the basic and important topics in multivariate statistics.

Data Analysis Using Stata, Third Edition

Автор: Kohler
Название: Data Analysis Using Stata, Third Edition
ISBN: 1597181102 ISBN-13(EAN): 9781597181105
Издательство: Taylor&Francis
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Цена: 11176.00 р.
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Описание:

Data Analysis Using Stata, Third Edition is a comprehensive introduction to both statistical methods and Stata. Beginners will learn the logic of data analysis and interpretation and easily become self-sufficient data analysts. Readers already familiar with Stata will find it an enjoyable resource for picking up new tips and tricks.

The book is written as a self-study tutorial and organized around examples. It interactively introduces statistical techniques such as data exploration, description, and regression techniques for continuous and binary dependent variables. Step by step, readers move through the entire process of data analysis and in doing so learn the principles of Stata, data manipulation, graphical representation, and programs to automate repetitive tasks. This third edition includes advanced topics, such as factor-variables notation, average marginal effects, standard errors in complex survey, and multiple imputation in a way, that beginners of both data analysis and Stata can understand.

Using data from a longitudinal study of private households, the authors provide examples from the social sciences that are relatable to researchers from all disciplines. The examples emphasize good statistical practice and reproducible research. Readers are encouraged to download the companion package of datasets to replicate the examples as they work through the book. Each chapter ends with exercises to consolidate acquired skills.

Nonparametric Functional Data Analysis

Автор: Fr?d?ric Ferraty; Philippe Vieu
Название: Nonparametric Functional Data Analysis
ISBN: 1441921419 ISBN-13(EAN): 9781441921413
Издательство: Springer
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Цена: 18167.00 р.
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Описание: At the same time it shows how functional data can be studied through parameter-free statistical ideas, and offers an original presentation of new nonparametric statistical methods for functional data analysis.

Recent Advances in Functional Data Analysis and Related Topics

Автор: Fr?d?ric Ferraty
Название: Recent Advances in Functional Data Analysis and Related Topics
ISBN: 3790828335 ISBN-13(EAN): 9783790828337
Издательство: Springer
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Цена: 25853.00 р.
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Описание: The failure of standard multivariate statistics to analyze such functional data has led the statistical community to develop appropriate statistical methodologies, called Functional Data Analysis (FDA).

Functional and Shape Data Analysis

Автор: Srivastava
Название: Functional and Shape Data Analysis
ISBN: 149394018X ISBN-13(EAN): 9781493940189
Издательство: Springer
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Цена: 11878.00 р.
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Описание: This textbook for courses on function data analysis and shape data analysis describes how to define, compare, and mathematically represent shapes, with a focus on statistical modeling and inference. It is aimed at graduate students in analysis in statistics, engineering, applied mathematics, neuroscience, biology, bioinformatics, and other related areas. The interdisciplinary nature of the broad range of ideas covered—from introductory theory to algorithmic implementations and some statistical case studies—is meant to familiarize graduate students with an array of tools that are relevant in developing computational solutions for shape and related analyses. These tools, gleaned from geometry, algebra, statistics, and computational science, are traditionally scattered across different courses, departments, and disciplines; Functional and Shape Data Analysis offers a unified, comprehensive solution by integrating the registration problem into shape analysis, better preparing graduate students for handling future scientific challenges.Recently, a data-driven and application-oriented focus on shape analysis has been trending. This text offers a self-contained treatment of this new generation of methods in shape analysis of curves. Its main focus is shape analysis of functions and curves—in one, two, and higher dimensions—both closed and open. It develops elegant Riemannian frameworks that provide both quantification of shape differences and registration of curves at the same time. Additionally, these methods are used for statistically summarizing given curve data, performing dimension reduction, and modeling observed variability. It is recommended that the reader have a background in calculus, linear algebra, numerical analysis, and computation.

Categorical Data Analysis

Автор: Agresti Alan
Название: Categorical Data Analysis
ISBN: 0470463635 ISBN-13(EAN): 9780470463635
Издательство: Wiley
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Цена: 20109.00 р.
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Описание: Praise for the Second Edition "A must-have book for anyone expecting to do research and/or applications in categorical data analysis. " Statistics in Medicine "It is a total delight reading this book.

Data Reduction And Error Analysis For The Physical Sciences

Автор: Bevington; Robinson
Название: Data Reduction And Error Analysis For The Physical Sciences
ISBN: 0071199268 ISBN-13(EAN): 9780071199261
Издательство: McGraw-Hill
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Цена: 7377.00 р.
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Описание: Provides an introduction to the concepts of statistical analysis of data for students at undergraduate and graduate level. This text also provides tools for data reduction and error analysis commonly required in the physical sciences. It features a variety of numerical and graphical techniques, and emphasizes methods of handling data than theory.

Analysis of longitudinal data

Название: Analysis of longitudinal data
ISBN: 0199676755 ISBN-13(EAN): 9780199676750
Издательство: Oxford Academ
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Цена: 8395.00 р.
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Описание: This second edition has been completely revised and expanded to become the most up-to-date and thorough professional reference text in this fast-moving area of biostatistics. It contains an additional two chapters on fully parametric models for discrete repeated measures data and statistical models for time-dependent predictors.


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