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Model-Free Prediction and Regression, Dimitris N. Politis


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Цена: 83850.00T
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Автор: Dimitris N. Politis
Название:  Model-Free Prediction and Regression
ISBN: 9783319213460
Издательство: Springer
Классификация:




ISBN-10: 3319213466
Обложка/Формат: Hardcover
Страницы: 246
Вес: 0.55 кг.
Дата издания: 23.11.2015
Серия: Frontiers in Probability and the Statistical Sciences
Язык: English
Издание: 1st ed. 2015
Иллюстрации: 10 tables, black and white; xvii, 246 p.
Размер: 234 x 156 x 16
Читательская аудитория: Professional & vocational
Основная тема: Statistics
Подзаголовок: A Transformation-Based Approach to Inference
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: Model-Free Prediction and Regression

A Distribution-Free Theory of Nonparametric Regression

Автор: L?szl? Gy?rfi; Michael Kohler; Adam Krzyzak; Harro
Название: A Distribution-Free Theory of Nonparametric Regression
ISBN: 1441929983 ISBN-13(EAN): 9781441929983
Издательство: Springer
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Цена: 181670.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book provides a systematic in-depth analysis of nonparametric regression with random design. It covers almost all known estimates. The emphasis is on distribution-free properties of the estimates.

Model-Free Prediction and Regression

Автор: Dimitris N. Politis
Название: Model-Free Prediction and Regression
ISBN: 3319352490 ISBN-13(EAN): 9783319352497
Издательство: Springer
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Цена: 79190.00 T
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Описание: Prediction: some heuristic notions.- The Model-free Prediction Principle.- Model-based prediction in regression.- Model-free prediction in regression.- Model-free vs. model-based confidence intervals.- Linear time series and optimal linear prediction.- Model-based prediction in autoregression.- Model-free inference for Markov processes.- Predictive inference for locally stationary time series.- Model-free vs. model-based volatility prediction.

The Linear Regression Model Under Test

Автор: W. Kraemer; H. Sonnberger
Название: The Linear Regression Model Under Test
ISBN: 3642958788 ISBN-13(EAN): 9783642958786
Издательство: Springer
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Цена: 102480.00 T
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Описание: Similar credits are due to Adrian Pagan, Roberto Mariano and Garry Phillips, the econometrics guest professors at the Institute in the 1982 - 1984 period, who through their lectures and advice have contributed greatly to our effort.

Regression, ANOVA, and the General Linear Model

Название: Regression, ANOVA, and the General Linear Model
ISBN: 1412997356 ISBN-13(EAN): 9781412997355
Издательство: Sage Publications
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Цена: 140450.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The author demonstrates basic statistical concepts from two different perspectives, giving the reader a conceptual understanding of how to interpret statistics and their use

Quantile Regression

Автор: Koenker
Название: Quantile Regression
ISBN: 0521845734 ISBN-13(EAN): 9780521845731
Издательство: Cambridge Academ
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Цена: 104550.00 T
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Описание: Quantiles provide a natural description of statistical variability in diverse populations; quantile regression offers a unified statistical methodology for studying how these measures of diversity depend upon other influences.

Bayesian and Frequentist Regression Methods

Автор: Wakefield
Название: Bayesian and Frequentist Regression Methods
ISBN: 1441909249 ISBN-13(EAN): 9781441909244
Издательство: Springer
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Цена: 102480.00 T
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Описание: Bayesian and Frequentist Regression Methods provides a modern account of both Bayesian and frequentist methods of regression analysis.

Statistical Methods in Biology: Desing and Analysis of Experiments and Regression 1st Edition, S.J.Welham, S.A. Gezan, S.J. Clark, A. Mead.- Chapman and Hall/CRC; 1 edition (August 22, 2014), 608 pages, Hardover

Название: Statistical Methods in Biology: Desing and Analysis of Experiments and Regression 1st Edition, S.J.Welham, S.A. Gezan, S.J. Clark, A. Mead.- Chapman and Hall/CRC; 1 edition (August 22, 2014), 608 pages, Hardover
ISBN: 1439808783 ISBN-13(EAN): 9781439808788
Издательство: Taylor&Francis
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Цена: 91860.00 T
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Описание:

Written in simple language with relevant examples, Statistical Methods in Biology: Design and Analysis of Experiments and Regression is a practical and illustrative guide to the design of experiments and data analysis in the biological and agricultural sciences. The book presents statistical ideas in the context of biological and agricultural sciences to which they are being applied, drawing on relevant examples from the authors' experience.

Taking a practical and intuitive approach, the book only uses mathematical formulae to formalize the methods where necessary and appropriate. The text features extended discussions of examples that include real data sets arising from research. The authors analyze data in detail to illustrate the use of basic formulae for simple examples while using the GenStat(R) statistical package for more complex examples. Each chapter offers instructions on how to obtain the example analyses in GenStat and R.

By the time you reach the end of the book (and online material) you will have gained:

  • A clear appreciation of the importance of a statistical approach to the design of your experiments,
  • A sound understanding of the statistical methods used to analyse data obtained from designed experiments and of the regression approaches used to construct simple models to describe the observed response as a function of explanatory variables,
  • Sufficient knowledge of how to use one or more statistical packages to analyse data using the approaches described, and most importantly,
  • An appreciation of how to interpret the results of these statistical analyses in the context of the biological or agricultural science within which you are working.

The book concludes with a guide to practical design and data analysis. It gives you the understanding to better interact with consultant statisticians and to identify statistical approaches to add value to your scientific research.


Applied Regression Analysis and Generalized Linear Models

Автор: Fox John
Название: Applied Regression Analysis and Generalized Linear Models
ISBN: 1452205663 ISBN-13(EAN): 9781452205663
Издательство: Sage Publications
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Цена: 166850.00 T
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Описание: Providing a modern treatment of regression analysis, linear models and closely related methods, this book introduces students to one of the most useful and widely used statistical tools for social research.

Interpolation and Extrapolation Optimal Designs V1: Polynomial Regression and Approximation Theory

Автор: Giorgio Celant, Michel Broniatowski
Название: Interpolation and Extrapolation Optimal Designs V1: Polynomial Regression and Approximation Theory
ISBN: 1848219954 ISBN-13(EAN): 9781848219953
Издательство: Wiley
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Цена: 146730.00 T
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Описание:

This book is the first of a series which focuses on the interpolation and extrapolation of optimal designs, an area with significant applications in engineering, physics, chemistry and most experimental fields.

In this volume, the authors emphasize the importance of problems associated with the construction of design. After a brief introduction on how the theory of optimal designs meets the theory of the uniform approximation of functions, the authors introduce the basic elements to design planning and link the statistical theory of optimal design and the theory of the uniform approximation of functions.

The appendices provide the reader with material to accompany the proofs discussed throughout the book.


Regression Analysis and Linear Models: Concepts, Applications, and Implementation

Автор: Darlington Richard B., Hayes Andrew F.
Название: Regression Analysis and Linear Models: Concepts, Applications, and Implementation
ISBN: 1462521134 ISBN-13(EAN): 9781462521135
Издательство: Taylor&Francis
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Цена: 83690.00 T
Наличие на складе: Невозможна поставка.
Описание: Ephasizing conceptual understanding over mathematics, this user-friendly text introduces linear regression analysis to students and researchers across the social, behavioral, consumer, and health sciences. Coverage includes model construction and estimation, quantification and measurement of multivariate and partial associations, statistical control, group comparisons, moderation analysis, mediation and path analysis, and regression diagnostics, among other important topics. Engaging worked-through examples demonstrate each technique, accompanied by helpful advice and cautions. The use of SPSS, SAS, and STATA is emphasized, with an appendix on regression analysis using R. The companion website (www.afhayes.com) provides datasets for the book`s examples as well as the RLM macro for SPSS and SAS. Pedagogical Features: *Chapters include SPSS, SAS, or STATA code pertinent to the analyses described, with each distinctively formatted for easy identification. *An appendix documents the RLM macro, which facilitates computations for estimating and probing interactions, dominance analysis, heteroscedasticity-consistent standard errors, and linear spline regression, among other analyses. *Students are guided to practice what they learn in each chapter using datasets provided online. *Addresses topics not usually covered, such as ways to measure a variable`s importance, coding systems for representing categorical variables, causation, and myths about testing interaction.

Semiparametric Regression

Автор: David Ruppert
Название: Semiparametric Regression
ISBN: 0521785162 ISBN-13(EAN): 9780521785167
Издательство: Cambridge Academ
Рейтинг:
Цена: 54910.00 T
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Описание: This user-friendly 2003 book explains the techniques and benefits of semiparametric regression in a concise and modular fashion.

Applied Regression: An Introduction

Автор: Lewis-Beck Michael S. Professor, Lewis-Beck Colin
Название: Applied Regression: An Introduction
ISBN: 1483381471 ISBN-13(EAN): 9781483381473
Издательство: Sage Publications
Рейтинг:
Цена: 39060.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Updates to this new edition include: more coverage of regression assumptions and model fit; additional material on residual analysis; more examples of transformations; and the inclusion of the measures of tolerance and VIF within the discussion about collinearity.


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