Bayesian mixed binary-continuous copula regression with an application to childhood undernutrition
2020 | book part. A publication with affiliation to the University of Göttingen.
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Bayesian mixed binary-continuous copula regression with an application to childhood undernutrition
Klein, N.; Kneib, T. ; Marra, G.& Radice, R. (2020)
In:Dortet-Bernadet, Jean-Luc; Fan, Yanan; Nott, David; Smith, Mike S. (Eds.), Flexible Bayesian Regression Modelling pp. 121-152. Elsevier. DOI: https://doi.org/10.1016/B978-0-12-815862-3.00011-1
Documents & Media
Details
- Authors
- Klein, Nadja; Kneib, Thomas ; Marra, Giampiero; Radice, Rosalba
- Editors
- Dortet-Bernadet, Jean-Luc; Fan, Yanan; Nott, David; Smith, Mike S.
- Abstract
- 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.
- Issue Date
- 2020
- Publisher
- Elsevier
- ISBN
- 978-0-12-815862-3
- Language
- English