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Important Applications of the Behrens-Fisher Statistic and the False Discovery Rate, Desai, Tejas A.


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Автор: Desai, Tejas A.
Название:  Important Applications of the Behrens-Fisher Statistic and the False Discovery Rate
ISBN: 9783030998875
Издательство: Springer
Классификация:
ISBN-10: 3030998878
Обложка/Формат: Paperback
Страницы: 83
Вес: 0.16 кг.
Дата издания: 18.06.2022
Серия: Springerbriefs in statistics
Язык: English
Издание: 1st ed. 2022
Иллюстрации: Vi, 83 p.
Размер: 235 x 155
Читательская аудитория: Professional & vocational
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: This book discusses important applications of the Behrens-Fisher statistic and the False Discovery Rate (FDR). Covered applications include ANOVA and MANOVA under potentially non-normal errors and heteroscedasticity; This book also explores the novel possibility that these applications may be deemed nonparametric.


The Elements of Statistical Learning

Автор: Trevor Hastie; Robert Tibshirani; Jerome Friedman
Название: The Elements of Statistical Learning
ISBN: 0387848576 ISBN-13(EAN): 9780387848570
Издательство: Springer
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Цена: 10480.00 р.
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Описание: This major new edition features many topics not covered in the original, including graphical models, random forests, and ensemble methods. As before, it covers the conceptual framework for statistical data in our rapidly expanding computerized world.

Computer Age Statistical Inference, Student Edition

Автор: Bradley Efron , Trevor Hastie
Название: Computer Age Statistical Inference, Student Edition
ISBN: 1108823416 ISBN-13(EAN): 9781108823418
Издательство: Cambridge Academ
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Цена: 5069.00 р.
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Описание: Computing power has revolutionized the theory and practice of statistical inference. Now in paperback, and fortified with 130 class-tested exercises, this book explains modern statistical thinking from classical theories to state-of-the-art prediction algorithms. Anyone who applies statistical methods to data will value this landmark text.

Statistical Rethinking

Автор: McElreath, Richard
Название: Statistical Rethinking
ISBN: 036713991X ISBN-13(EAN): 9780367139919
Издательство: Taylor&Francis
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Цена: 12554.00 р.
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Описание: Statistical Rethinking: A Bayesian Course with Examples in R and Stan, Second Edition builds knowledge/confidence in statistical modeling. Pushes readers to perform step-by-step calculations (usually automated.) Unique, computational approach.

Handbook of spatial statistics

Автор: Gelfand, Alan E. Fuentes, Montserrat Guttorp, Pete
Название: Handbook of spatial statistics
ISBN: 1420072870 ISBN-13(EAN): 9781420072877
Издательство: Taylor&Francis
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Цена: 15541.00 р. 22202.00 -30%
Наличие на складе: Есть (2 шт.)
Описание: Offers an introduction detailing the evolution of the field of spatial statistics. This title focuses on the three main branches of spatial statistics: continuous spatial variation (point referenced data); discrete spatial variation, including lattice and areal unit data; and, spatial point patterns.

Data Management Essentials Using SAS and JMP

Автор: Kezik
Название: Data Management Essentials Using SAS and JMP
ISBN: 1107535034 ISBN-13(EAN): 9781107535039
Издательство: Cambridge Academ
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Цена: 6019.00 р.
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Описание: This book is designed for the first time or occasional SAS user who needs immediate guidance in navigating, exploring, visualizing, cleaning and reporting on data. It teaches the basic SAS skills essential to data management, including practical exercises with solutions. No formal or informal training is required.

A Course in Mathematical and Statistical Ecology

Автор: Anil Gore; S.A. Paranjpe
Название: A Course in Mathematical and Statistical Ecology
ISBN: 9048156165 ISBN-13(EAN): 9789048156160
Издательство: Springer
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Цена: 12577.00 р.
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Описание: A Course in Mathematical and Statistical Ecology

Advanced Data Analysis in Neuroscience

Автор: Daniel Durstewitz
Название: Advanced Data Analysis in Neuroscience
ISBN: 3319867504 ISBN-13(EAN): 9783319867502
Издательство: Springer
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Цена: 7965.00 р.
Наличие на складе: Поставка под заказ.

Описание: This book is intended for use in advanced graduate courses in statistics / machine learning, as well as for all experimental neuroscientists seeking to understand statistical methods at a deeper level, and theoretical neuroscientists with a limited background in statistics.

An Introduction to nonparametric statistics

Автор: Kolassa, John E.
Название: An Introduction to nonparametric statistics
ISBN: 0367194848 ISBN-13(EAN): 9780367194840
Издательство: Taylor&Francis
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Цена: 14086.00 р.
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Описание: This book presents the theory and practice of non-parametric statistics, with an emphasis on motivating principals. The course is a combination of traditional rank based methods and more computationally-intensive topics like density estimation, kernel smoothers in regression, and robustness. The text is aimed at MS students.

Handbook Of Meta-Analysis

Автор: Christopher H Schmid
Название: Handbook Of Meta-Analysis
ISBN: 1498703984 ISBN-13(EAN): 9781498703987
Издательство: Taylor&Francis
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Цена: 24499.00 р.
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Описание: Meta-analysis is the application of statistics to combine results from multiple studies and draw appropriate inferences. Its use and importance have exploded over the years as the need for a robust evidence base has become clear in many scientific areas like medicine and health, social sciences, education, psychology, ecology and economics.

Fundamental Statistical Inference: A Computational Approach

Автор: Marc S. Paolella
Название: Fundamental Statistical Inference: A Computational Approach
ISBN: 1119417864 ISBN-13(EAN): 9781119417866
Издательство: Wiley
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Цена: 15674.00 р.
Наличие на складе: Поставка под заказ.

Описание:

A hands-on approach to statistical inference that addresses the latest developments in this ever-growing field

This clear and accessible book for beginning graduate students offers a practical and detailed approach to the field of statistical inference, providing complete derivations of results, discussions, and MATLAB programs for computation. It emphasizes details of the relevance of the material, intuition, and discussions with a view towards very modern statistical inference. In addition to classic subjects associated with mathematical statistics, topics include an intuitive presentation of the (single and double) bootstrap for confidence interval calculations, shrinkage estimation, tail (maximal moment) estimation, and a variety of methods of point estimation besides maximum likelihood, including use of characteristic functions, and indirect inference. Practical examples of all methods are given. Estimation issues associated with the discrete mixtures of normal distribution, and their solutions, are developed in detail. Much emphasis throughout is on non-Gaussian distributions, including details on working with the stable Paretian distribution and fast calculation of the noncentral Student's t. An entire chapter is dedicated to optimization, including development of Hessian-based methods, as well as heuristic/genetic algorithms that do not require continuity, with MATLAB codes provided.

The book includes both theory and nontechnical discussions, along with a substantial reference to the literature, with an emphasis on alternative, more modern approaches. The recent literature on the misuse of hypothesis testing and p-values for model selection is discussed, and emphasis is given to alternative model selection methods, though hypothesis testing of distributional assumptions is covered in detail, notably for the normal distribution.

Presented in three parts--Essential Concepts in Statistics; Further Fundamental Concepts in Statistics; and Additional Topics--Fundamental Statistical Inference: A Computational Approach offers comprehensive chapters on: Introducing Point and Interval Estimation; Goodness of Fit and Hypothesis Testing; Likelihood; Numerical Optimization; Methods of Point Estimation; Q-Q Plots and Distribution Testing; Unbiased Point Estimation and Bias Reduction; Analytic Interval Estimation; Inference in a Heavy-Tailed Context; The Method of Indirect Inference; and, as an appendix, A Review of Fundamental Concepts in Probability Theory, the latter to keep the book self-contained, and giving material on some advanced subjects such as saddlepoint approximations, expected shortfall in finance, calculation with the stable Paretian distribution, and convergence theorems and proofs.

Dynamic Documents with R and knitr, Second Edition

Автор: Xie Y.
Название: Dynamic Documents with R and knitr, Second Edition
ISBN: 1498716962 ISBN-13(EAN): 9781498716963
Издательство: Taylor&Francis
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Цена: 11789.00 р.
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Описание:

Quickly and Easily Write Dynamic Documents

Suitable for both beginners and advanced users, Dynamic Documents with R and knitr, Second Edition makes writing statistical reports easier by integrating computing directly with reporting. Reports range from homework, projects, exams, books, blogs, and web pages to virtually any documents related to statistical graphics, computing, and data analysis. The book covers basic applications for beginners while guiding power users in understanding the extensibility of the knitr package.

New to the Second Edition

  • A new chapter that introduces R Markdown v2
  • Changes that reflect improvements in the knitr package
  • New sections on generating tables, defining custom printing methods for objects in code chunks, the C/Fortran engines, the Stan engine, running engines in a persistent session, and starting a local server to serve dynamic documents

Boost Your Productivity in Statistical Report Writing and Make Your Scientific Computing with R Reproducible

Like its highly praised predecessor, this edition shows you how to improve your efficiency in writing reports. The book takes you from program output to publication-quality reports, helping you fine-tune every aspect of your report.

All of statistics: A Concise Course in Statistical Inference

Автор: Wasserman, Larry
Название: All of statistics: A Concise Course in Statistical Inference
ISBN: 1441923225 ISBN-13(EAN): 9781441923226
Издательство: Springer
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Цена: 7965.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: Taken literally, the title "All of Statistics" is an exaggeration. But in spirit, the title is apt, as the book does cover a much broader range of topics than a typical introductory book on mathematical statistics. Statistics, data mining, and machine learning are all concerned with collecting and analysing data.


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