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Flexible bayesian regression modelling

Contributor(s): Material type: TextTextPublication details: London Academic Press 2020Description: xiv, 288 p. : ill. includes indexISBN:
  • 9780128158623
Subject(s): DDC classification:
  • 519.536 F5
Summary: Flexible Bayesian Regression Modeling is a step-by-step guide to the Bayesian revolution in regression modeling, for use in advanced econometric and statistical analysis where datasets are characterized by complexity, multiplicity, and large sample sizes, necessitating the need for considerable flexibility in modeling techniques. It reviews three forms of flexibility: methods which provide flexibility in their error distribution; methods which model non-central parts of the distribution (such as quantile regression); and finally models that allow the mean function to be flexible (such as spline models). Each chapter discusses the key aspects of fitting a regression model. R programs accompany the methods. This book is particularly relevant to non-specialist practitioners with intermediate mathematical training seeking to apply Bayesian approaches in economics, biology, finance, engineering and medicine. https://shop.elsevier.com/books/flexible-bayesian-regression-modelling/fan/978-0-12-815862-3
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Books Vikram Sarabhai Library Rack 28-B / Slot 1409 (0 Floor, East Wing) Non-fiction General Stacks 519.536 F5 (Browse shelf(Opens below)) Checked out 24/07/2025 207837

Flexible Bayesian Regression Modeling is a step-by-step guide to the Bayesian revolution in regression modeling, for use in advanced econometric and statistical analysis where datasets are characterized by complexity, multiplicity, and large sample sizes, necessitating the need for considerable flexibility in modeling techniques. It reviews three forms of flexibility: methods which provide flexibility in their error distribution; methods which model non-central parts of the distribution (such as quantile regression); and finally models that allow the mean function to be flexible (such as spline models). Each chapter discusses the key aspects of fitting a regression model. R programs accompany the methods. This book is particularly relevant to non-specialist practitioners with intermediate mathematical training seeking to apply Bayesian approaches in economics, biology, finance, engineering and medicine.


https://shop.elsevier.com/books/flexible-bayesian-regression-modelling/fan/978-0-12-815862-3

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