Téléchargez le livre : Model Averaging
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Description

This book provides a concise and accessible overview of model averaging, with a focus on applications. Model averaging is a common means of allowing for model uncertainty when analysing data, and has been used in a wide range of application areas, such as ecology, econometrics, meteorology and pharmacology. The book presents an overview of the methods developed in this area, illustrating many of them with examples from the life sciences involving real-world data. It also includes an extensive list of references and suggestions for further research. Further, it clearly demonstrates the links between the methods developed in statistics, econometrics and machine learning, as well as the connection between the Bayesian and frequentist approaches to model averaging. The book appeals to statisticians and scientists interested in what methods are available, how they differ and what is known about their properties. It is assumed that readers are familiar with the basic concepts of statistical theory and modelling, including probability, likelihood and generalized linear models.
Pages
107 pages
Collection
SpringerBriefs in Statistics
Parution
2019-01-17
Marque
Springer
EAN papier
9783662585405
EAN PDF
9783662585412
Informations sur l'ebook
Nombre pages copiables
1
Nombre pages imprimables
10
Taille du fichier
2181 Ko
Ce livre est accessible aux handicaps Voir les informations sur l'accessibilité
Prix
73,84 €
EAN EPUB
9783662585412
Informations sur l'ebook
Nombre pages copiables
1
Nombre pages imprimables
10
Taille du fichier
1710 Ko
Ce livre est accessible aux handicaps Voir les informations sur l'accessibilité
Prix
73,84 €

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