Introduction to Robust Estimation and Hypothesis Testing,, Rand R. Wilcox
Новое издание
Автор: Huber, Peter J. Ronchetti, Elvezio M. Название: Robust statistics ISBN: 0470129905 ISBN-13(EAN): 9780470129906 Издательство: Wiley Рейтинг: Цена: 130890.00 T Наличие на складе: Поставка под заказ. Описание: Robust Statistics, Second Edition includes four new chapters on the following topics: robust tests; small sample asymptotics; breakdown point; and Bayesian robustness. A new section on time series has also been included. The first edition of this book was the first systematic, book-length treatment of robust statistics.
Автор: Peter Goos, David Meintrup Название: Statistics with JMP: Hypothesis Tests, ANOVA and Regression ISBN: 1119097150 ISBN-13(EAN): 9781119097150 Издательство: Wiley Рейтинг: Цена: 64360.00 T 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.
Автор: Agostinelli Название: Recent Advances in Robust Statistics: Theory and Applications ISBN: 8132236416 ISBN-13(EAN): 9788132236412 Издательство: Springer Рейтинг: Цена: 111790.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book offers a collection of recent contributions and emerging ideas in the areas of robust statistics presented at the International Conference on Robust Statistics 2015 (ICORS 2015) held in Kolkata during 12–16 January, 2015. The book explores the applicability of robust methods in other non-traditional areas which includes the use of new techniques such as skew and mixture of skew distributions, scaled Bregman divergences, and multilevel functional data methods; application areas being circular data models and prediction of mortality and life expectancy. The contributions are of both theoretical as well as applied in nature. Robust statistics is a relatively young branch of statistical sciences that is rapidly emerging as the bedrock of statistical analysis in the 21st century due to its flexible nature and wide scope. Robust statistics supports the application of parametric and other inference techniques over a broader domain than the strictly interpreted model scenarios employed in classical statistical methods.The aim of the ICORS conference, which is being organized annually since 2001, is to bring together researchers interested in robust statistics, data analysis and related areas. The conference is meant for theoretical and applied statisticians, data analysts from other fields, leading experts, junior researchers and graduate students. The ICORS meetings offer a forum for discussing recent advances and emerging ideas in statistics with a focus on robustness, and encourage informal contacts and discussions among all the participants. They also play an important role in maintaining a cohesive group of international researchers interested in robust statistics and related topics, whose interactions transcend the meetings and endure year round.
Автор: Liu Название: Robust Rank-Based and Nonparametric Methods ISBN: 3319390635 ISBN-13(EAN): 9783319390635 Издательство: Springer Рейтинг: Цена: 102480.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The contributors to this volume include many of the distinguished researchers in this area. Many of these scholars have collaborated with Joseph McKean to develop underlying theory for these methods, obtain small sample corrections, and develop efficient algorithms for their computation. The papers cover the scope of the area, including robust nonparametric rank-based procedures through Bayesian and big data rank-based analyses. Areas of application include biostatistics and spatial areas. Over the last 30 years, robust rank-based and nonparametric methods have developed considerably. These procedures generalize traditional Wilcoxon-type methods for one- and two-sample location problems. Research into these procedures has culminated in complete analyses for many of the models used in practice including linear, generalized linear, mixed, and nonlinear models. Settings are both multivariate and univariate. With the development of R packages in these areas, computation of these procedures is easily shared with readers and implemented. This book is developed from the International Conference on Robust Rank-Based and Nonparametric Methods, held at Western Michigan University in April 2015.
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