Описание: This volume of the Selected Papers from Portugal is a product of the Seventeenth Congress of the Portuguese Statistical Society, held at the beautiful resort seaside city of Sesimbra, Portugal, from September 30 to October 3, 2009.
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.
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: Andrew Gelman, Jennifer Hill, Aki Vehtari Название: Regression and Other Stories ISBN: 1107676517 ISBN-13(EAN): 9781107676510 Издательство: Cambridge Academ Рейтинг: Цена: 6494.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Real statistical problems are complex and subtle. This text is about using regression to solve real problems of comparison, estimation, prediction, and causal inference, based on real stories from the authors` experience. It offers practical advice for understanding assumptions and implementing methods through graphics and computing in R and Stan.
Описание: This volume of the Selected Papers from Portugal is a product of the Seventeenth Congress of the Portuguese Statistical Society, held at the beautiful resort seaside city of Sesimbra, Portugal, from September 30 to October 3, 2009.
Описание: With the rise of "big data," there is an increasing demand to learn the skills needed to undertake sound quantitative analysis without requiring students to spend too much time on high-level math and proofs. This book provides an efficient alternative approach, with more time devoted to the practical aspects of regression analysis and how to recognize the most common pitfalls. By doing so, the book will better prepare readers for conducting, interpreting, and assessing regression analyses, while simultaneously making the material simpler and more enjoyable to learn. Logical and practical in approach, Regression Analysis teaches: (1) the tools for conducting regressions; (2) the concepts needed to design optimal regression models (based on avoiding the pitfalls); and (3) the proper interpretations of regressions. Furthermore, this book emphasizes honesty in research, with a prevalent lesson being that statistical significance is not the goal of research. This book is an ideal introduction to regression analysis for anyone learning quantitative methods in the social sciences, business, medicine, and data analytics. It will also appeal to researchers and academics looking to better understand what regressions do, what their limitations are, and what they can tell us. This will be the most engaging book on regression analysis (or Econometrics) you will ever read!
Автор: David G. T. Denison Название: Bayesian Methods for Nonlinear Classification and Regression ISBN: 0471490369 ISBN-13(EAN): 9780471490364 Издательство: Wiley Рейтинг: Цена: 20584.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Regression analysis models the relationship between a set of responses and another variable: for example, to estimate the true position of a line through a number of observed points. Unfortunately, data rarely conforms to simple curves and straight lines - parametric models - and this text examines more complex - or nonparametric - models.
Автор: Wang Qiying Название: Limit Theorems For Nonlinear Cointegrating Regression ISBN: 9814675628 ISBN-13(EAN): 9789814675628 Издательство: World Scientific Publishing Рейтинг: Цена: 15523.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book provides the limit theorems that can be used in the development of nonlinear cointegrating regression.
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