Linear models with R, Faraway Julian J

Автор: Faraway, Julian J. (university Of Bath, Uk)
Название: Linear models with r
ISBN: 1032583983 ISBN-13(EAN): 9781032583983
Издательство: Taylor&Francis
Цена: 81650 T

Автор: Nachtsheim;Neter;Kutner
Название: Applied Linear Statistical Models with Student CD
ISBN: 0071122214 ISBN-13(EAN): 9780071122214
Издательство: McGraw-Hill
Рейтинг:
Цена: 61770.00 T
Наличие на складе: Поставка под заказ.
Описание: "Applied Linear Statistical Models", 5e, is the long established leading authoritative text and reference on statistical modeling. For students in most any discipline where statistical analysis or interpretation is used, ALSM serves as the standard work. The text includes brief introductory and review material, and then proceeds through regression and modeling for the first half, and through ANOVA and Experimental Design in the second half. All topics are presented in a precise and clear style supported with solved examples, numbered formulae, graphic illustrations, and "Notes" to provide depth and statistical accuracy and precision. Applications used within the text and the hallmark problems, exercises, and projects are drawn from virtually all disciplines and fields providing motivation for students in virtually any college. The Fifth edition provides an increased use of computing and graphical analysis throughout, without sacrificing concepts or rigor. In general, the 5e uses larger data sets in examples and exercises, and where methods can be automated within software without loss of understanding, it is so done.

Название: An Introduction to Generalized Linear Models, Third Edition
ISBN: 1584889500 ISBN-13(EAN): 9781584889502
Издательство: Taylor&Francis
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Цена: 47970.00 T
Наличие на складе: Поставка под заказ.
Описание: Offers a cohesive framework for statistical modeling. Emphasizing numerical and graphical methods, this work enables readers to understand the unifying structure that underpins GLMs. It discusses common concepts and principles of advanced GLMs, including nominal and ordinal regression, survival analysis, and longitudinal analysis.