ENGLISH

Flexible regression and smoothing : using GAMLSS in R

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

Book information

Publisher
Chapman and Hall/CRC
Year
2017
ISBN
978-1-138-19790-9, 1138197904
Language
english
Format
PDF
Filesize
18 MB (19250133 bytes)
Series
Chapman & Hall/CRC the R series (CRC Press)
Edition
1
Pages
549\572
Time added
2017-06-25 19:00:00
Regression analysis;Data processing;Linear models

Description

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. GAMLSS allows any parametric distribution for the response variable and modelling all the parameters (location, scale and shape) of the distribution as linear or smooth functions of explanatory variables. 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 with code, data and additional materials.

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