Model-Free Prediction and Regression, Dimitris N. Politis
Название: Regression, ANOVA, and the General Linear Model ISBN: 1412997356 ISBN-13(EAN): 9781412997355 Издательство: Sage Publications Рейтинг: Цена: 21067.00 р. 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
Автор: Dimitris N. Politis Название: Model-Free Prediction and Regression ISBN: 3319352490 ISBN-13(EAN): 9783319352497 Издательство: Springer Рейтинг: Цена: 11878.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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.
Автор: W. Kraemer; H. Sonnberger Название: The Linear Regression Model Under Test ISBN: 3642958788 ISBN-13(EAN): 9783642958786 Издательство: Springer Рейтинг: Цена: 15372.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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.
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 Рейтинг: Цена: 27251.00 р. 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.
Автор: Wakefield Название: Bayesian and Frequentist Regression Methods ISBN: 1441909249 ISBN-13(EAN): 9781441909244 Издательство: Springer Рейтинг: Цена: 15372.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Bayesian and Frequentist Regression Methods provides a modern account of both Bayesian and frequentist methods of regression analysis.
Автор: David Ruppert Название: Semiparametric Regression ISBN: 0521785162 ISBN-13(EAN): 9780521785167 Издательство: Cambridge Academ Рейтинг: Цена: 8237.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This user-friendly 2003 book explains the techniques and benefits of semiparametric regression in a concise and modular fashion.
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.
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: 5859.00 р. 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.
Автор: Koenker Название: Quantile Regression ISBN: 0521845734 ISBN-13(EAN): 9780521845731 Издательство: Cambridge Academ Рейтинг: Цена: 15682.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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.
Автор: Fox John Название: Applied Regression Analysis and Generalized Linear Models ISBN: 1452205663 ISBN-13(EAN): 9781452205663 Издательство: Sage Publications Рейтинг: Цена: 25027.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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.
Автор: Peter Goos, David Meintrup Название: Statistics with JMP: Hypothesis Tests, ANOVA and Regression ISBN: 1119097150 ISBN-13(EAN): 9781119097150 Издательство: Wiley Рейтинг: Цена: 9654.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Statistics with JMP: Hypothesis Tests, ANOVA and Regression
Peter Goos, University of Leuven and University of Antwerp, Belgium
David Meintrup, University of Applied Sciences Ingolstadt, Germany
A first course on basic statistical methodology using JMP
This book provides a first course on parameter estimation (point estimates and confidence interval estimates), hypothesis testing, ANOVA and simple linear regression. The authors approach combines mathematical depth with numerous examples and demonstrations using the JMP software.
Key features:
Provides a comprehensive and rigorous presentation of introductory statistics that has been extensively classroom tested.
Pays attention to the usual parametric hypothesis tests as well as to non-parametric tests (including the calculation of exact p-values).
Discusses the power of various statistical tests, along with examples in JMP to enable in-sight into this difficult topic.
Promotes the use of graphs and confidence intervals in addition to p-values.
Course materials and tutorials for teaching are available on the book's companion website.
Masters and advanced students in applied statistics, industrial engineering, business engineering, civil engineering and bio-science engineering will find this book beneficial. It also provides a useful resource for teachers of statistics particularly in the area of engineering.
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.
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