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An Introduction to Generalized Additive Models with R

Generalized Additive Models: An Introduction with R imparts a thorough understanding of the theory and practical applications of GAMs and;

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Foundations of Linear and Generalized Linear Models

of linear mixed models and generalized linear mixed models with random effects for clustered correlated data, Bayesian modeling, and extensions to;

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Multivariate Generalized Linear Mixed Models Using R

Multivariate Generalized Linear Mixed Models Using R presents robust and methodologically sound models for analyzing large and complex data;

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Generalized Linear Mixed Models

and effects may be fixed or random. With numerous examples using SAS (R) PROC GLIMMIX, this book is ideal for graduate students;

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Interaction Effects in Linear and Generalized Linear Models: Examples and Applications Using Stata

Offering a clear set of workable examples with data and explanations, Interaction Effects in Linear and Generalized Linear Models is a;

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Advanced R Statistical Programming and Data Models

multiple examples using R to achieve results, and concludes with a case study. Written by Matt and Joshua F. Wiley, Advanced R Statistical;

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Generalized Linear Models with Random Effects

This is the second edition of a monograph on generalized linear models with random effects that extends the classic work of McCullagh and;

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Introduction to General and Generalized Linear Models

text, although other software packages are also discussed. Numerous examples show how the problems are solved with R. After describing the;

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Data Analysis Using Hierarchical Generalized Linear Models with R

advanced statistical modelling including generalized linear models with random effects, survival analysis and frailty models, multivariate HGLMs;

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Data Analysis Using Hierarchical Generalized Linear Models with R

advanced statistical modelling including generalized linear models with random effects, survival analysis and frailty models, multivariate HGLMs;

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Generalized Linear Models with Random Effects: Unified Analysis Via H-Likelihood, Second Edition

This is the second edition of a monograph on generalized linear models with random effects that extends the classic work of McCullagh and;

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Generalized Additive Models

book on the topic to be introductory in nature with a wealth of practical examples and software implementation. It is self-contained, providing;

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A First Course in Linear Model Theory

studying the theory and applications of both univariate and multivariate linear models. In addition to adding R functionality, this second edition;

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Extending The Linear Model With R

expanded both in popularity and in the number of packages available. Extending the Linear Model with R: Generalized Linear, Mixed Effects and;

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Generalized Linear Models With Examples in R

This textbook presents an introduction to generalized linear models, complete with real-world data sets and practice problems, making it;

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Generalized Linear Models

Maintaining the same nontechnical approach as its acclaimed predecessor, this second edition of Generalized Linear Models is now thoroughly;

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An Introduction to Generalized Linear Models

Continuing to emphasize numerical and graphical methods, An Introduction to Generalized Linear Models, Third Edition provides a cohesive;

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Generalized Linear Models

Explaining the theoretical underpinning of generalized linear models, this text enables researchers to decide how to select the best way to;

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Extending the Linear Model with R

. Faraway's critically acclaimed Linear Models with R examined regression and analysis of variance, demonstrated the different methods;

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Generalized Linear Models and Correlated Data Methods

Offers a unified discussion of generalized linear models and correlated data methods Provides information suitable for graduate non;

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Generalized Linear and Nonlinear Models for Correlated Data

analysis of correlated response data using SAS, with special emphasis on applications that require the use of generalized linear models or;

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Statistics for Linguists

Statistics for Linguists: An Introduction Using R is the first statistics textbook on linear models for linguistics. The book covers simple;

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Statistics for Linguists

Statistics for Linguists: An Introduction Using R is the first statistics textbook on linear models for linguistics. The book covers simple;

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Generalized, Linear, and Mixed Models

An accessible and self-contained introduction to statistical models-now in a modernized new edition Generalized, Linear, and Mixed Models;

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Linear Models

, calculus and linear algebra. The text includes numerous applied illustrations, numerical examples, and exercises, now augmented with computer;

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An Introduction to Generalized Linear Models

An Introduction to Generalized Linear Models, Fourth Edition provides a cohesive framework for statistical modelling, with an emphasis on;

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An Introduction to Generalized Linear Models

An Introduction to Generalized Linear Models, Fourth Edition provides a cohesive framework for statistical modelling, with an emphasis on;

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