Multivariate Kernel Smoothing and Its Applications, Chacуn Josй E., Duong Tarn

Автор: Chacon
Название: Multivariate Kernel Smoothing And I
ISBN: 1498763014 ISBN-13(EAN): 9781498763011
Издательство: Taylor&Francis
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Описание: Kernel smoothing has greatly evolved since its inception to become an essential methodology in the Data Science tool kit for the 21st century. Its widespread adoption is due to its fundamental role for multivariate exploratory data analysis, as well as the crucial role it plays in composite solutions to complex data challenges.

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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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: 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: Jeffrey S. Simonoff
Название: Smoothing Methods in Statistics
ISBN: 1461284724 ISBN-13(EAN): 9781461284727
Издательство: Springer
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Цена: 23058.00 р.
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Описание: Focussing on applications, this book covers a very broad range, including simple and complex univariate and multivariate density estimation, nonparametric regression estimation, categorical data smoothing, and applications of smoothing to other areas of statistics.

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: 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: 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: Hu, Xiaolong
Название: Smoothing a critical transition
ISBN: 9811540349 ISBN-13(EAN): 9789811540349
Издательство: Springer
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Цена: 6986.00 р.
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Описание: Introduction.- Advice to graduate students.- Understand research.- Engage literature.- Writing.- Publish papers.- Present research results.- Interact with advisors.- Collaborate with other researchers.- Work in a laboratory.- File patents.- Handle difficult time in research.- Research ethics and responsibilities.- What can we learn from the history of science.- Concluding remarks.

Автор: Paul H.C. Eilers, Brian D. Marx
Название: Practical Smoothing: The Joys of P-splines
ISBN: 1108482953 ISBN-13(EAN): 9781108482950
Издательство: Cambridge Academ
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Цена: 8554.00 р.
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Описание: P-splines are widely used in statistics and machine learning for smoothing out noise in data and to avoid overtraining. This practical guide covers theory and a range of standard and non-standard applications with code in R for professionals and researchers looking for a simple, flexible and powerful smoothing tool.

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: 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.