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Generalized Additive Models

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Generalized Additive Models

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Author : Simon N. Wood
language : en
Publisher: CRC Press
Release Date : 2006-02-27

Generalized Additive Models written by Simon N. Wood and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-02-27 with Mathematics categories.

Generalized Additive Models

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Author : T.J. Hastie
language : en
Publisher: CRC Press
Release Date : 1990-06-01

Generalized Additive Models written by T.J. Hastie and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1990-06-01 with Mathematics categories.

This book describes an array of power tools for data analysis that are based on nonparametric regression and smoothing techniques. These methods relax the linear assumption of many standard models and allow analysts to uncover structure in the data that might otherwise have been missed. While McCullagh and Nelder's Generalized Linear Models shows how to extend the usual linear methodology to cover analysis of a range of data types, Generalized Additive Models enhances this methodology even further by incorporating the flexibility of nonparametric regression. Clear prose, exercises in each chapter, and case studies enhance this popular text.

Generalized Additive Models

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Author : Simon N. Wood
language : en
Publisher: CRC Press
Release Date : 2017-05-18

The first edition of this book has established itself as one of the leading references on generalized additive models (GAMs), and the only book on the topic to be introductory in nature with a wealth of practical examples and software implementation. It is self-contained, providing the necessary background in linear models, linear mixed models, and generalized linear models (GLMs), before presenting a balanced treatment of the theory and applications of GAMs and related models. The author bases his approach on a framework of penalized regression splines, and while firmly focused on the practical aspects of GAMs, discussions include fairly full explanations of the theory underlying the methods. Use of R software helps explain the theory and illustrates the practical application of the methodology. Each chapter contains an extensive set of exercises, with solutions in an appendix or in the book’s R data package gamair, to enable use as a course text or for self-study.

Generalized Additive Models

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Author : T.J. Hastie
language : en
Publisher: Routledge
Release Date : 2017-10-19

Generalized Additive Models written by T.J. Hastie and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-10-19 with Mathematics categories.

Generalized Additive Models

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Author : Simon Wood
language : en
Publisher: CRC Press
Release Date : 2006-02-27

Generalized Additive Models written by Simon Wood and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-02-27 with Mathematics categories.

Now in widespread use, generalized additive models (GAMs) have evolved into a standard statistical methodology of considerable flexibility. While Hastie and Tibshirani's outstanding 1990 research monograph on GAMs is largely responsible for this, there has been a long-standing need for an accessible introductory treatment of the subject that also emphasizes recent penalized regression spline approaches to GAMs and the mixed model extensions of these models. Generalized Additive Models: An Introduction with R imparts a thorough understanding of the theory and practical applications of GAMs and related advanced models, enabling informed use of these very flexible tools. The author bases his approach on a framework of penalized regression splines, and builds a well-grounded foundation through motivating chapters on linear and generalized linear models. While firmly focused on the practical aspects of GAMs, discussions include fairly full explanations of the theory underlying the methods. Use of the freely available R software helps explain the theory and illustrates the practicalities of linear, generalized linear, and generalized additive models, as well as their mixed effect extensions. The treatment is rich with practical examples, and it includes an entire chapter on the analysis of real data sets using R and the author's add-on package mgcv. Each chapter includes exercises, for which complete solutions are provided in an appendix. Concise, comprehensive, and essentially self-contained, Generalized Additive Models: An Introduction with R prepares readers with the practical skills and the theoretical background needed to use and understand GAMs and to move on to other GAM-related methods and models, such as SS-ANOVA, P-splines, backfitting and Bayesian approaches to smoothing and additive modelling.

Generalized Additive Models For Location Scale And Shape

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Author : Mikis D. Stasinopoulos
language : en
Publisher: Cambridge University Press
Release Date : 2024-02-29

Generalized Additive Models For Location Scale And Shape written by Mikis D. Stasinopoulos and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-29 with Mathematics categories.

An emerging field in statistics, distributional regression facilitates the modelling of the complete conditional distribution, rather than just the mean. This book introduces generalized additive models for location, scale and shape (GAMLSS) – one of the most important classes of distributional regression. Taking a broad perspective, the authors consider penalized likelihood inference, Bayesian inference, and boosting as potential ways of estimating models and illustrate their usage in complex applications. Written by the international team who developed GAMLSS, the text's focus on practical questions and problems sets it apart. Case studies demonstrate how researchers in statistics and other data-rich disciplines can use the model in their work, exploring examples ranging from fetal ultrasounds to social media performance metrics. The R code and data sets for the case studies are available on the book's companion website, allowing for replication and further study.

Generalized Linear Models For Insurance Data

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Author : Piet de Jong
language : en
Publisher: Cambridge University Press
Release Date : 2008-04-02

Generalized Linear Models For Insurance Data written by Piet de Jong and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-04-02 with Business & Economics categories.

All techniques illustrated on data sets relevant to insurance; SAS code and output, data sets, exercise solutions on website

Non Life Insurance Pricing With Generalized Linear Models

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Author : Esbjörn Ohlsson
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-03-18

Non Life Insurance Pricing With Generalized Linear Models written by Esbjörn Ohlsson and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-03-18 with Mathematics categories.

Non-life insurance pricing is the art of setting the price of an insurance policy, taking into consideration varoius properties of the insured object and the policy holder. Introduced by British actuaries generalized linear models (GLMs) have become today a the standard aproach for tariff analysis. The book focuses on methods based on GLMs that have been found useful in actuarial practice and provides a set of tools for a tariff analysis. Basic theory of GLMs in a tariff analysis setting is presented with useful extensions of standarde GLM theory that are not in common use. The book meets the European Core Syllabus for actuarial education and is written for actuarial students as well as practicing actuaries. To support reader real data of some complexity are provided at www.math.su.se/GLMbook.

Vector Generalized Linear And Additive Models

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Author : Thomas W. Yee
language : en
Publisher: Springer
Release Date : 2015-09-11

Vector Generalized Linear And Additive Models written by Thomas W. Yee and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-09-11 with Mathematics categories.

This book presents a greatly enlarged statistical framework compared to generalized linear models (GLMs) with which to approach regression modelling. Comprising of about half-a-dozen major classes of statistical models, and fortified with necessary infrastructure to make the models more fully operable, the framework allows analyses based on many semi-traditional applied statistics models to be performed as a coherent whole. Since their advent in 1972, GLMs have unified important distributions under a single umbrella with enormous implications. However, GLMs are not flexible enough to cope with the demands of practical data analysis. And data-driven GLMs, in the form of generalized additive models (GAMs), are also largely confined to the exponential family. The methodology here and accompanying software (the extensive VGAM R package) are directed at these limitations and are described comprehensively for the first time in one volume. This book treats distributions and classical models as generalized regression models, and the result is a much broader application base for GLMs and GAMs. The book can be used in senior undergraduate or first-year postgraduate courses on GLMs or categorical data analysis and as a methodology resource for VGAM users. In the second part of the book, the R package VGAM allows readers to grasp immediately applications of the methodology. R code is integrated in the text, and datasets are used throughout. Potential applications include ecology, finance, biostatistics, and social sciences. The methodological contribution of this book stands alone and does not require use of the VGAM package.

Applied Regression Analysis And Generalized Linear Models

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Author : John Fox
language : en
Publisher: SAGE Publications
Release Date : 2015-03-18

Applied Regression Analysis And Generalized Linear Models written by John Fox and has been published by SAGE Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-03-18 with Social Science categories.

Combining a modern, data-analytic perspective with a focus on applications in the social sciences, the Third Edition of Applied Regression Analysis and Generalized Linear Models provides in-depth coverage of regression analysis, generalized linear models, and closely related methods, such as bootstrapping and missing data. Updated throughout, this Third Edition includes new chapters on mixed-effects models for hierarchical and longitudinal data. Although the text is largely accessible to readers with a modest background in statistics and mathematics, author John Fox also presents more advanced material in optional sections and chapters throughout the book. Accompanying website resources containing all answers to the end-of-chapter exercises. Answers to odd-numbered questions, as well as datasets and other student resources are available on the author′s website. NEW! Bonus chapter on Bayesian Estimation of Regression Models also available at the author′s website.

Generalized Additive Models

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