Regression and Other Stories, Andrew Gelman, Jennifer Hill, Aki Vehtari

Автор: Andrew Gelman, Jennifer Hill, Aki Vehtari
Название: Regression and Other Stories
ISBN: 110702398X ISBN-13(EAN): 9781107023987
Издательство: Cambridge Academ
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Цена: 86590.00 T
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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.

Автор: Jo?o Lita da Silva; Frederico Caeiro; Isabel Nat?r
Название: Advances in Regression, Survival Analysis, Extreme Values, Markov Processes and Other Statistical Applications
ISBN: 3642446299 ISBN-13(EAN): 9783642446290
Издательство: Springer
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Цена: 194730.00 T
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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: Jo?o Lita da Silva; Frederico Caeiro; Isabel Nat?r
Название: Advances in Regression, Survival Analysis, Extreme Values, Markov Processes and Other Statistical Applications
ISBN: 364234903X ISBN-13(EAN): 9783642349034
Издательство: Springer
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Цена: 139750.00 T
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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: Schroeder Larry D., Sjoquist David L., Stephan Pau
Название: Understanding Regression Analysis: An Introductory Guide
ISBN: 1506332889 ISBN-13(EAN): 9781506332888
Издательство: Sage Publications
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Цена: 39060.00 T
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Описание: Presents the fundamentals of regression analysis, from its meaning to uses, in a concise, easy-to-read, and non-technical style.

Автор: Darlington Richard B., Hayes Andrew F.
Название: Regression Analysis and Linear Models: Concepts, Applications, and Implementation
ISBN: 1462521134 ISBN-13(EAN): 9781462521135
Издательство: Taylor&Francis
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Цена: 83690.00 T
Наличие на складе: Невозможна поставка.
Описание: Ephasizing conceptual understanding over mathematics, this user-friendly text introduces linear regression analysis to students and researchers across the social, behavioral, consumer, and health sciences. Coverage includes model construction and estimation, quantification and measurement of multivariate and partial associations, statistical control, group comparisons, moderation analysis, mediation and path analysis, and regression diagnostics, among other important topics. Engaging worked-through examples demonstrate each technique, accompanied by helpful advice and cautions. The use of SPSS, SAS, and STATA is emphasized, with an appendix on regression analysis using R. The companion website (www.afhayes.com) provides datasets for the book`s examples as well as the RLM macro for SPSS and SAS. Pedagogical Features: *Chapters include SPSS, SAS, or STATA code pertinent to the analyses described, with each distinctively formatted for easy identification. *An appendix documents the RLM macro, which facilitates computations for estimating and probing interactions, dominance analysis, heteroscedasticity-consistent standard errors, and linear spline regression, among other analyses. *Students are guided to practice what they learn in each chapter using datasets provided online. *Addresses topics not usually covered, such as ways to measure a variable`s importance, coding systems for representing categorical variables, causation, and myths about testing interaction.

Автор: Arkes J.
Название: Regression Analysis: A Practical Introduction, 1st Edition
ISBN: 1138541435 ISBN-13(EAN): 9781138541436
Издательство: Taylor&Francis
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Цена: 68390.00 T
Наличие на складе: Нет в наличии.
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 Ruppert
Название: Semiparametric Regression
ISBN: 0521785162 ISBN-13(EAN): 9780521785167
Издательство: Cambridge Academ
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Цена: 54910.00 T
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Описание: This user-friendly 2003 book explains the techniques and benefits of semiparametric regression in a concise and modular fashion.

Автор: John Fox
Название: Regression Diagnostics: An Introduction
ISBN: 1544375220 ISBN-13(EAN): 9781544375229
Издательство: Sage Publications
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Цена: 39060.00 T
Наличие на складе: Нет в наличии.
Описание:

Regression diagnostics are methods for determining whether a regression model that has been fit to data adequately represents the structure of the data. For example, if the model assumes a linear (straight-line) relationship between the response and an explanatory variable, is the assumption of linearity warranted? Regression diagnostics not only reveal deficiencies in a regression model that has been fit to data but in many instances may suggest how the model can be improved. The Second Edition of this bestselling volume by John Fox considers two important classes of regression models: the normal linear regression model (LM), in which the response variable is quantitative and assumed to have a normal distribution conditional on the values of the explanatory variables; and generalized linear models (GLMs) in which the conditional distribution of the response variable is a member of an exponential family. R code and data sets for examples within the text can be found on an accompanying website at https://tinyurl.com/RegDiag. 

Автор: Wakefield
Название: Bayesian and Frequentist Regression Methods
ISBN: 1441909249 ISBN-13(EAN): 9781441909244
Издательство: Springer
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Цена: 102480.00 T
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Описание: Bayesian and Frequentist Regression Methods provides a modern account of both Bayesian and frequentist methods of regression analysis.

Автор: Fahrmeir Ludwig
Название: Regression
ISBN: 3642343325 ISBN-13(EAN): 9783642343322
Издательство: Springer
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Цена: 93160.00 T
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Описание: Thus, the book primarily targets an audience that includes students, teachers and practitioners in social, economic, and life sciences, as well as students and teachers in statistics programs, and mathematicians and computer scientists with interests in statistical modeling and data analysis.

Автор: Paul D Allison
Название: Fixed Effects Regression Models
ISBN: 0761924973 ISBN-13(EAN): 9780761924975
Издательство: Sage Publications
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Цена: 39060.00 T
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Описание: This book demonstrates how to estimate and interpret fixed-effects models in a variety of different modeling contexts.

Автор: David G. T. Denison
Название: Bayesian Methods for Nonlinear Classification and Regression
ISBN: 0471490369 ISBN-13(EAN): 9780471490364
Издательство: Wiley
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Цена: 137230.00 T
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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.