Автор: Thorsten Dickhaus Название: Simultaneous Statistical Inference ISBN: 3642451810 ISBN-13(EAN): 9783642451812 Издательство: Springer Рейтинг: Цена: 22203.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This monograph offers an in-depth mathematical treatment of modern multiple test procedures controlling the false discovery rate and related error measures, particularly addressing applications to such fields as genetics, proteomics and neuroscience.
Автор: Thorsten Dickhaus Название: Simultaneous Statistical Inference ISBN: 3662510065 ISBN-13(EAN): 9783662510063 Издательство: Springer Рейтинг: Цена: 19589.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This monograph offers an in-depth mathematical treatment of modern multiple test procedures controlling the false discovery rate and related error measures, particularly addressing applications to such fields as genetics, proteomics and neuroscience.
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.
Описание: This book contains chapters providing interpretations of principles in ICH E17 and new ideas of implementing MRCTs. Authors are from different regions, and from academia and industry. This book will be of particular interest to biostatisticians working in late stage clinical development of medical products.
Описание: In their review of the "Bayesian analysis of simultaneous equation systems", Dr ze and Richard (1983) - hereafter DR - express the following viewpoint about the present state of development of the Bayesian full information analysis of such sys- tems i) the method allows "a flexible specification of the prior density, including well defined noninformative prior measures"; ii) it yields "exact finite sample posterior and predictive densities". However, they call for further developments so that these densities can be eval- uated through 'numerical methods, using an integrated software packa e. To that end, they recommend the use of a Monte Carlo technique, since van Dijk and Kloek (1980) have demonstrated that "the integrations can be done and how they are done". In this monograph, we explain how we contribute to achieve the developments suggested by Dr ze and Richard. A basic idea is to use known properties of the porterior density of the param- eters of the structural form to design the importance functions, i. e. approximations of the posterior density, that are needed for organizing the integrations.
Описание: This book provides statistics instructors and students with complete classroom material for a one- or two-semester course on applied regression and causal inference. It is built around 52 stories, 52 class-participation activities, 52 hands-on computer demonstrations, and 52 discussion problems that allow instructors and students to explore in a fun way the real-world complexity of the subject. The book fosters an engaging 'flipped classroom' environment with a focus on visualization and understanding. The book provides instructors with frameworks for self-study or for structuring the course, along with tips for maintaining student engagement at all levels, and practice exam questions to help guide learning. Designed to accompany the authors' previous textbook Regression and Other Stories, its modular nature and wealth of material allow this book to be adapted to different courses and texts or be used by learners as a hands-on workbook.
Название: Sage handbook of regression analysis and causal inference ISBN: 1446252442 ISBN-13(EAN): 9781446252444 Издательство: Sage Publications Рейтинг: Цена: 21384.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Dimitris N. Politis Название: Model-Free Prediction and Regression ISBN: 3319213466 ISBN-13(EAN): 9783319213460 Издательство: Springer Рейтинг: Цена: 12577.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Model-Free Prediction and Regression
Автор: Srivastava, Virendera K. , Giles, David E.A. Название: Seemingly Unrelated Regression Equations Models ISBN: 0367451484 ISBN-13(EAN): 9780367451486 Издательство: Taylor&Francis Рейтинг: Цена: 6736.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book brings together the scattered literature associated with the seemingly unrelated regression equations (SURE) model used by econometricians and others. It focuses on the theoretical statistical results associated with the SURE model.
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