Smoothing Methods in Statistics, Jeffrey S. Simonoff

Автор: Hyndman
Название: Forecasting with Exponential Smoothing
ISBN: 3540719164 ISBN-13(EAN): 9783540719168
Издательство: Springer
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Цена: 13974.00 р.
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Описание: However, a modeling framework incorporating stochastic models, likelihood calculation, prediction intervals and procedures for model selection, was not developed until recently. More advanced topics are covered in Part 3, including the mathematical properties of the models and extensions of the models for specific problems.

Автор: Howard L. Weinert
Название: Fixed Interval Smoothing for State Space Models
ISBN: 0792372999 ISBN-13(EAN): 9780792372998
Издательство: Springer
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Цена: 21655.00 р.
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Описание: Fixed-interval smoothing is a method of extracting information from inaccurate data. This monograph addresses problems for which a linear stochastic state space model is available, in which case the objective is to compute the linear least-squares estimate of the state vector in a fixed interval, using observations collected in that interval.

Автор: Chong Gu
Название: Smoothing Spline ANOVA Models
ISBN: 1461453682 ISBN-13(EAN): 9781461453680
Издательство: Springer
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Цена: 20962.00 р.
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Описание: Updated to include the latest computational methods, this second edition explains how to use the `gss` R package and features expanded empirical studies, a reorganized content, and a further new appendix analyzing new and controversial topics in smoothing.

Автор: Wolfgang H?rdle
Название: Smoothing Techniques
ISBN: 1461287685 ISBN-13(EAN): 9781461287681
Издательство: Springer
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Цена: 19564.00 р.
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Описание: A principal feature of smoothing, the averaging of data points in a prescribed neighborhood, is not really practicable in dimensions greater than three if we have just one hundred data points.

Автор: Horova Ivanka Et Al
Название: Kernel Smoothing In Matlab: Theory And Practice Of Kernel Smoothing
ISBN: 9814405485 ISBN-13(EAN): 9789814405485
Издательство: World Scientific Publishing
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Цена: 12830.00 р.
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Описание: Offers a comprehensive overview of statistical theory and emphases the implementation of presented methods in Matlab. This title contains various Matlab scripts useful for kernel smoothing of density, cumulative distribution function, regression function, hazard function, indices of quality and bivariate density.

Автор: Chong Gu
Название: Smoothing Spline ANOVA Models
ISBN: 1489989846 ISBN-13(EAN): 9781489989840
Издательство: Springer
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Цена: 18167.00 р.
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Описание: Updated to include the latest computational methods, this second edition explains how to use the `gss` R package and features expanded empirical studies, a reorganized content, and a further new appendix analyzing new and controversial topics in smoothing.

Автор: Wolfgang H?rdle; Michael Schimek
Название: Statistical Theory and Computational Aspects of Smoothing
ISBN: 3790809306 ISBN-13(EAN): 9783790809305
Издательство: Springer
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Цена: 12157.00 р.
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Описание: One of the main applications of statistical smoothing techniques is nonparametric regression. Smoothing techniques in regression as well as other statistical methods are increasingly applied in biosciences and economics. Introduced are new developments in scatterplot smoothing and applications in statistical modelling.

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