Distributions for modeling location, scale, and shape: using GAMLSS in R

Rigby, Robert A., Stasinopoulos, Mikis D., Heller, Gillian Z. and De Bastiani, Fernanda (2019) Distributions for modeling location, scale, and shape: using GAMLSS in R. The R Series . Chapman & Hall/CRC, Boca Raton, Florida. ISBN 9780367278847

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Abstract / Description

This is a book about statistical distributions, their properties, and their application to modelling the dependence of the location, scale, and shape of the distribution of a response variable on explanatory variables. It will be especially useful to applied statisticians and data scientists in a wide range of application areas, and also to those interested in the theoretical properties of distributions. This book follows the earlier book ‘Flexible Regression and Smoothing: Using GAMLSS in R’, [Stasinopoulos et al., 2017], which focused on the GAMLSS model and software. GAMLSS (the Generalized Additive Model for Location, Scale, and Shape, [Rigby and Stasinopoulos, 2005]), is a regression framework in which the response variable can have any parametric distribution and all the distribution parameters can be modelled as linear or smooth functions of explanatory variables. The current book focuses on distributions and their application.

Item Type: Book
Additional Information: "Distributions for Modeling Location, Scale, and Shape: Using GAMLSS in R" is a Book available on request for the Reviewer.
Uncontrolled Keywords: Generalized Additive Models for Location, Scale and Shape (GAMLSS); Generalized Linear Models (GLMs); Generalized Additive Models (GAMs); Regression analysis -- Data processing; Linear models (Statistics)
Subjects: 500 Natural Sciences and Mathematics > 510 Mathematics
Department: School of Computing and Digital Media
Depositing User: Robert Rigby
Date Deposited: 22 Jul 2019 08:56
Last Modified: 28 Nov 2019 10:04
URI: http://repository.londonmet.ac.uk/id/eprint/4993

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