Distributions for Modeling Location, Scale, and Shape Using GAMLSS in R
-
- Hardcover
- Taschenbuch ausgewählt
- eBook
-
Sprache:Englisch
75,99 €
UVP
98,80 €
inkl. gesetzl. MwSt.,
Beschreibung
Produktdetails
Einband
Taschenbuch
Erscheinungsdatum
30.06.2021
Abbildungen
191 SW-Abb.
Verlag
Taylor & FrancisSeitenzahl
590
Maße (L/B/H)
25,4/17,8/3,1 cm
Gewicht
1094 g
Sprache
Englisch
ISBN
978-1-03-208942-3
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.
Key features:
- Describes over 100 distributions, (implemented in the GAMLSS packages in R), including continuous, discrete and mixed distributions.
- Comprehensive summary tables of the properties of the distributions.
- Discusses properties of distributions, including skewness, kurtosis, robustness and an important classification of tail heaviness.
- Includes mixed distributions which are continuous distributions with additional specific values with point probabilities.
- Includes many real data examples, with R code integrated in the text for ease of understanding and replication.
- Supplemented by the gamlss website.
This book will be useful for applied statisticians and data scientists in selecting a distribution for a univariate response variable and modelling its dependence on explanatory variables, and to those interested in the properties of distributions.
Noch keine Bewertungen vorhanden
Verfassen Sie die erste Bewertung zu diesem Artikel
Helfen Sie anderen Kundinnen und Kunden durch Ihre Meinung.
Kurze Frage zu unserer Seite
Vielen Dank für dein Feedback
Wir nutzen dein Feedback, um unsere Produktseiten zu verbessern. Bitte habe Verständnis, dass wir dir keine Rückmeldung geben können. Falls du Kontakt mit uns aufnehmen möchtest, kannst du dich aber gerne an unseren Kund*innenservice wenden.
zum Kundenservice