Flexible Regression and Smoothing

Using Gamlss in R

Mikis D. Stasinopoulos, Robert A. Rigby, Gillian Z. Heller, Vlasios Voudouris (Autoren)

Buch | Hardcover

547 Seiten

2017
CRC Press (Verlag)
978-1-138-19790-9 (ISBN)

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Generalized Linear Models (GLMs) and Generalized Additive Models (GAMs) are very popular statistical tools, but, they have been shown to break down for large complex datasets, which are increasingly prevalent. The authors of this book have developed the Generalized Additive Model for Location, Scale and Shape (GAMLSS) methodology, with an associated R package, that extends GAMs for more complex problems. This book provides a broad overview of methodology and how it can be implemented using GAMLSS in R. It uses lots of data examples, integrated code, and figures to illustrate the methods, and is supplemented by a website with all code, data and additional materials

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

Part I Introduction to models and packages
Why GAMLSS?
Introduction to the gamlss packages

Part II The R implementation: algorithms and functions
The Algorithms
The gamlss() function
Methods for fitted gamlss objects

Part III Distributions
The gamlss.family of distributions
Finite mixture distributions

Part IV Additive terms
Linear parametric additive terms
Additive Smoothing Terms
Random effects

Part V Model selection and diagnostics
Model selection techniques
Diagnostics

Part VI Applications
Centile Estimation
Further Applications

Erscheinungsdatum	04.06.2017
Reihe/Serie	Chapman & Hall/CRC: The R Series
Zusatzinfo	164 black & white illustrations, 16 black & white tables, 112 black & white halftones, 52 black & white line drawings
Verlagsort	London
Sprache	englisch
Maße	178 x 254 mm
Gewicht	1238 g
Themenwelt	Mathematik / Informatik ► Mathematik ► Computerprogramme / Computeralgebra
Themenwelt	Wirtschaft ► Volkswirtschaftslehre ► Ökonometrie
ISBN-10	1-138-19790-4 / 1138197904
ISBN-13	978-1-138-19790-9 / 9781138197909
Zustand	Neuware