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Model averaging

Fletcher, David.

Model averaging

Record Type:	Electronic resources : Monograph/item
Title/Author:	Model averagingby David Fletcher.
Author:	Fletcher, David.
Published:	Berlin, Heidelberg :Springer Berlin Heidelberg :2018.
Description:	x, 107 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Averaging method (Differential equations)
Online resource:	https://doi.org/10.1007/978-3-662-58541-2
ISBN:	9783662585412$q(electronic bk.)

Model averaging
Fletcher, David.

Model averaging[electronic resource] /by David Fletcher. - Berlin, Heidelberg :Springer Berlin Heidelberg :2018. - x, 107 p. :ill., digital ;24 cm. - SpringerBriefs in statistics,2191-544X. - SpringerBriefs in statistics..

Why Model Averaging? -- Bayesian Model Averaging -- Frequentist Model Averaging -- Summary and Future Directions.

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.

ISBN: 9783662585412$q(electronic bk.)

Standard No.: 10.1007/978-3-662-58541-2doiSubjects--Topical Terms:

561172
Averaging method (Differential equations)

LC Class. No.: QA372 / .F548 2018

Dewey Class. No.: 519.533

Model averaging
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520 $a 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.
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