Model Discrimination for Nonlinear Regression Models, Borowiak, Dale S.

Автор: Davies, Patrick Laurie
Название: Data Analysis and Approximate Models
ISBN: 1482215861 ISBN-13(EAN): 9781482215861
Издательство: Taylor&Francis
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Цена: 163330.00 T
Наличие на складе: Нет в наличии.

Автор: Wang Qiying
Название: Limit Theorems For Nonlinear Cointegrating Regression
ISBN: 9814675628 ISBN-13(EAN): 9789814675628
Издательство: World Scientific Publishing
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Цена: 103490.00 T
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Описание: This book provides the limit theorems that can be used in the development of nonlinear cointegrating regression.

Автор: Knafl
Название: Adaptive Regression for Modeling Nonlinear Relationships
ISBN: 3319339443 ISBN-13(EAN): 9783319339443
Издательство: Springer
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Цена: 65210.00 T
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Описание: This book presents methods for investigating whether relationships are linear or nonlinear and for adaptively fitting appropriate models when they are nonlinear. The book also provides a comparison of adaptive modeling to generalized additive modeling (GAM) and multiple adaptive regression splines (MARS) for univariate outcomes.

Автор: S. Johansen
Название: Functional Relations, Random Coefficients, and Nonlinear Regression with Application to Kinetic Data
ISBN: 0387909680 ISBN-13(EAN): 9780387909684
Издательство: Springer
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Цена: 107130.00 T
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Описание: The most important statistical concepts are the general linear model for Gaussian variables and the general methods of maximum likelihood estimation as well as the likelihood ratio test.

Автор: A.A. Ivanov
Название: Asymptotic Theory of Nonlinear Regression
ISBN: 0792343352 ISBN-13(EAN): 9780792343356
Издательство: Springer
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Цена: 102480.00 T
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Описание: Presents mathematical results in asymptotic theory on nonlinear regression on the basis of various asymptotic expansions of least squares, its characteristics, and its distribution functions of functionals of Least Squares Estimator. This title indicates conditions for Least Moduli Estimator asymptotic normality.

Автор: Sylvie Huet; Anne Bouvier; Marie-Anne Poursat; Emm
Название: Statistical Tools for Nonlinear Regression
ISBN: 1441923012 ISBN-13(EAN): 9781441923011
Издательство: Springer
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Цена: 75420.00 T
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Описание: The examples are analyzed with the free software nls2 updated to deal with the new models included in the second edition. Several additional tools are included in the package for calculating confidence regions for functions of parameters or calibration intervals, using classical methodology or bootstrap.

Автор: Knafl George J., Ding Kai
Название: Adaptive Regression for Modeling Nonlinear Relationships
ISBN: 3319816381 ISBN-13(EAN): 9783319816388
Издательство: Springer
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Цена: 74830.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book presents methods for investigating whether relationships are linear or nonlinear and for adaptively fitting appropriate models when they are nonlinear. The book also provides a comparison of adaptive modeling to generalized additive modeling (GAM) and multiple adaptive regression splines (MARS) for univariate outcomes.

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.

Автор: Fox John
Название: Applied Regression Analysis and Generalized Linear Models
ISBN: 1452205663 ISBN-13(EAN): 9781452205663
Издательство: Sage Publications
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Цена: 166850.00 T
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Описание: Providing a modern treatment of regression analysis, linear models and closely related methods, this book introduces students to one of the most useful and widely used statistical tools for social research.

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.

Название: Regression Modeling Strategies
ISBN: 3319194240 ISBN-13(EAN): 9783319194240
Издательство: Springer
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Цена: 83850.00 T
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Описание: Most of the methods in this text apply to all regression models, but special emphasis is given to multiple regression using generalised least squares for longitudinal data, the binary logistic model, models for ordinal responses, parametric survival regression models and the Cox semi parametric survival model.

Автор: Eric Vittinghoff; David V. Glidden; Stephen C. Shi
Название: Regression Methods in Biostatistics
ISBN: 1489998543 ISBN-13(EAN): 9781489998545
Издательство: Springer
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Цена: 79190.00 T
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Описание: This fresh edition, substantially revised and augmented, provides a unified, in-depth, readable introduction to the multipredictor regression methods most widely used in biostatistics. The examples used, analyzed using Stata, can be applied to other areas.