Flexible Regression and Smoothing - Couverture souple

Stasinopoulos, Mikis D.; Rigby, Robert A.; Heller, Gillian Z.; Voudouris, Vlasios; De Bastiani, Fernanda

Couverture souple

ISBN 10 : 0367658062 ISBN 13 : 9780367658069

Editeur : Chapman and Hall/CRC, 2020

Synopsis

This book is about learning from data using the Generalized Additive Models for Location, Scale and Shape (GAMLSS). GAMLSS extends the Generalized Linear Models (GLMs) and Generalized Additive Models (GAMs) to accommodate large complex datasets, which are increasingly prevalent.

In particular, the GAMLSS statistical framework enables flexible regression and smoothing models to be fitted to the data. The GAMLSS model assumes that the response variable has any parametric (continuous, discrete or mixed) distribution which might be heavy- or light-tailed, and positively or negatively skewed. In addition, all the parameters of the distribution (location, scale, shape) can be modelled as linear or smooth functions of explanatory variables.

Key Features:

Provides a broad overview of flexible regression and smoothing techniques to learn from data whilst also focusing on the practical application of methodology using GAMLSS software in R.

Includes a comprehensive collection of real data examples, which reflect the range of problems addressed by GAMLSS models and provide a practical illustration of the process of using flexible GAMLSS models for statistical learning.

R code integrated into the text for ease of understanding and replication.

Supplemented by a website with code, data and extra materials.

This book aims to help readers understand how to learn from data encountered in many fields. It will be useful for practitioners and researchers who wish to understand and use the GAMLSS models to learn from data and also for students who wish to learn GAMLSS through practical examples.

A propos du livre

À propos de l'auteur

Mikis D. Stasinopoulos, Robert A. Rigby, Gillian Z. Heller, Vlasios Voudouris, Fernanda De Bastiani

À propos de la quatrième de couverture

This book provides a broad overview of GAMLSS methodology and how it is implemented in R. It includes a comprehensive collection of real data examples, integrated code, and figures to illustrate the methods, and is supplemented by a website.

Détails de l'édition

• Éditeur: Chapman and Hall/CRC
• Date d'édition: 2020
• Langue: anglais
• ISBN 10: 0367658062
• ISBN 13: 9780367658069
• Reliure: Broché
• Nombre de pages: 549
• Coordonnées du fabricant: non disponible
• Personne responsable: GPSR Kontakt; gpsr@libri.de; ; Europaallee 1; Bad Hersfeld; 36244; Allemagne