Modern applied regressions, Xu, Jun

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: 5859.00 р.
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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: Hooshang Nayebi
Название: Advanced Statistics for Testing Assumed Causal Relationships
ISBN: 3030547531 ISBN-13(EAN): 9783030547530
Издательство: Springer
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Описание: It presents that potential effects of each independent variable on the dependent variable are not limited to direct and indirect effects. The path analysis shows each independent variable has a pure effect on the dependent variable. So, it can be shown the unique contribution of each independent variable to the variation of the dependent variable.

Автор: John Fox
Название: Regression Diagnostics: An Introduction
ISBN: 1544375220 ISBN-13(EAN): 9781544375229
Издательство: Sage Publications
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Цена: 5859.00 р.
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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: T. M. V., Suryanarayana Mistry, P. B.
Название: Principal component regression for crop yield estimation
ISBN: 9811006628 ISBN-13(EAN): 9789811006623
Издательство: Springer
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Цена: 9141.00 р.
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Описание: This book highlights the estimation of crop yield in CentralGujarat, especially with regard to the development of Multiple RegressionModels and Principal Component Regression (PCR) models using climatologicalparameters as independent variables and crop yield as a dependent variable.

Автор: Zelterman, Daniel (yale University, Connecticut)
Название: Regression for health and social science
ISBN: 1108478182 ISBN-13(EAN): 9781108478182
Издательство: Cambridge Academ
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Цена: 7918.00 р.
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Описание: Using every-day examples and numerous exercises, this text covers the basics of linear models with a minimum of mathematics. The emphasis is on issues involved in the analysis and the interpretation of computer output. R code is provided and explained allowing readers to apply the methods to their own data.

Автор: Carroll, Raymond J. , Ruppert, David
Название: Transformation and Weighting in Regression
ISBN: 0367403374 ISBN-13(EAN): 9780367403379
Издательство: Taylor&Francis
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Цена: 9798.00 р.
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Описание:

This monograph provides a careful review of the major statistical techniques used to analyze regression data with nonconstant variability and skewness. The authors have developed statistical techniques--such as formal fitting methods and less formal graphical techniques-- that can be applied to many problems across a range of disciplines, including pharmacokinetics, econometrics, biochemical assays, and fisheries research.

While the main focus of the book in on data transformation and weighting, it also draws upon ideas from diverse fields such as influence diagnostics, robustness, bootstrapping, nonparametric data smoothing, quasi-likelihood methods, errors-in-variables, and random coefficients. The authors discuss the computation of estimates and give numerous examples using real data. The book also includes an extensive treatment of estimating variance functions in regression.

Автор: Miller
Название: Subset Selection in Regression
ISBN: 1584881712 ISBN-13(EAN): 9781584881711
Издательство: Taylor&Francis
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Цена: 27562.00 р.
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Описание: Deals with the techniques for fitting and choosing models that are linear in their parameters and to understanding and correcting the bias introduced by selecting a model. This title includes a chapter on Bayesian methods and an example from the field of near infrared spectroscopy. It emphasises on cross-validation and focuses on bootstrapping.

Автор: J.D. Jobson
Название: Applied Multivariate Data Analysis
ISBN: 1461269601 ISBN-13(EAN): 9781461269601
Издательство: Springer
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Цена: 6986.00 р.
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Описание: An easy to read survey of data analysis, linear regression models and analysis of variance. The extensive development of the linear model includes the use of the linear model approach to analysis of variance provides a strong link to statistical software packages, and is complemented by a thorough overview of theory.

Автор: Lawal Bayo, Famoye Felix
Название: Applied Statistics: Regression and Analysis of Variance
ISBN: 0761861718 ISBN-13(EAN): 9780761861713
Издательство: Неизвестно
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Цена: 24827.00 р.
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Описание: This book presents a thorough treatment of the methods of regression and analysis of variance. Applied Statistics requires an understanding of introductory statistics courses and is suitable for both junior and senior undergraduate students.

Автор: McGibney
Название: Applied Linear Regression for Business Analytics with R
ISBN: 303121479X ISBN-13(EAN): 9783031214790
Издательство: Springer
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Цена: 11179.00 р.
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Описание: Applied Linear Regression for Business Analytics with R introduces regression analysis to business students using the R programming language with a focus on illustrating and solving real-time, topical problems. Specifically, this book presents modern and relevant case studies from the business world, along with clear and concise explanations of the theory, intuition, hands-on examples, and the coding required to employ regression modeling. Each chapter includes the mathematical formulation and details of regression analysis and provides in-depth practical analysis using the R programming language.

Автор: Tan, Frans E.s. Jolani, Shahab
Название: Applied linear regression for longitudinal data
ISBN: 0367634317 ISBN-13(EAN): 9780367634315
Издательство: Taylor&Francis
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Цена: 15004.00 р.
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Описание: This book introduces best practices in longitudinal data analysis at intermediate level, with a minimum number of formulas without sacrificing depths. It meets the need to understand statistical concepts of longitudinal data analysis by visualizing important techniques instead of using abstract mathematical formulas.

Автор: Sengupta Ashis Et Al
Название: Statistical Paradigms: Recent Advances And Reconciliations
ISBN: 9814343951 ISBN-13(EAN): 9789814343954
Издательство: World Scientific Publishing
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Цена: 15840.00 р.
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Описание: A collection of research articles on classical and emerging Statistical Paradigms - parametric, non-parametric and semi-parametric, frequentist and Bayesian - encompassing both theoretical advances and emerging applications in a variety of scientific disciplines.