Distributions for Modeling Location, Scale, and Shape: Using GAMLSS in R

ISBN-13: 9781032089423 / Angielski / Miękka / 2021 / 588 str.

Mikis D. Stasinopoulos; Gillian Z. Heller; Fernanda de Bastiani

Opis

This is the second volume in a series of books about using the GAMLSS R package developed by the authors. This volume presents a broad overview of statistical distributions and how they can be used in practical applications.

Spis treści

Part I: Parametric distributions and the GAMLSS family of distributions Types of distributions Properties of distributions The GAMLSS Family of Distributions Continuous distributions on (-8,8) Continuous distributions on (0, 8) Continuous distributions on (0, 1) Discrete count distributionsBinomial type distributions Mixed distributions Part II: Advanced Topics Statistical inferenceMaximum likelihood estimationRobustness of parameter estimation to outlier contaminationMethods of generating distributionsDiscussion of skewnessDiscussion of kurtosisSkewness and kurtosis comparisons of continuous distributionsHeaviness of tails of distributionsPart III: Reference Guide Continuous distributions on (-8,8) Continuous distributions on (0, 8) Mixed distributions on [0 to 8) Continuous and mixed distributions on [0, 1] Discrete count distributionsBinomial type distributions and multinomial distributionsAppendices

O autorze

Robert Rigby was researching in Statistics at London Metropolitan University for over 30 years  specializing in distributions and advanced regression and smoothing models (for supervised learning). He is one of the two original developers of GAMLSS models. He is currently a freelance consultant.

Mikis Stasinopoulos is a statistician. He has a considerable experience in  applied statistics and he is one of the two creators of  GAMLSS. He worked as the director of STORM, the statistics and mathematics research centre of  London Metropolitan University and now he is working as an independent statistical consultant.

Gillian Heller is Professor of Statistics at Macquarie University, Sydney. Her research interests are mainly in flexible regression models for heavy-tailed count data, with applications in biostatistics and insurance.

Fernanda De Bastiani is a permanent lecturer in the Statistics Department at Universidade Federal de Pernambuco, Brazil. Her research interests are mainly in flexible regression models, spatial data analysis and influential diagnostics in regression models.