Flexible Bayesian Regression Modelling
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,...
Leider schon ausverkauft
158.99 €
versandkostenfrei
79 DeutschlandCard Punkte
sammeln
- Lastschrift, Kreditkarte, Paypal, Rechnung
- Kostenlose Rücksendung
- Ratenzahlung möglich
Produktdetails
Produktinformationen zu „Flexible Bayesian Regression Modelling “
Weitere Produktinformationen zu „Flexible Bayesian Regression Modelling “
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.
Bibliographische Angaben
- Herausgegeben:Fan, Yanan; Nott, David; Smith, Mike S.; Dortet-Bernadet, Jean-Luc
- Verlag: Academic Press
- EAN: 9780128158623
Autoren-Porträt
Dr. Yanan Fan is Associate Professor of statistics at the University of New South Wales, Sydney, Australia. Her research focuses on the development of efficient Bayesian computational methods, approximate inferences and nonparametric regression methods.Dr. David Nott is Associate Professor of Statistics at the National University of Singapore. His research focuses on Bayesian likelihood-free inference and other approximate inference methods, and on complex Bayesian nonparametric models.
Inhaltsverzeichnis zu „Flexible Bayesian Regression Modelling “
1. Bayesian quantile regression with the asymmetric Laplace distribution2. A vignette on model-based quantile regression: analysing excess zero response
3. Bayesian nonparametric density regression for ordinal responses
4. Bayesian nonparametric methods for financial and macroeconomic time series analysis
5. Bayesian mixed binary-continuous copula regression with an application to childhood undernutrition
6. Nonstandard flexible regression via variational Bayes
7. Scalable Bayesian variable selection regression models for count data
8. Bayesian spectral analysis regression
9. Flexible regression modelling under shape constraints
Kommentar zu "Flexible Bayesian Regression Modelling"
0 Gebrauchte Artikel zu „Flexible Bayesian Regression Modelling“
| Zustand | Preis | Porto | Zahlung | Verkäufer | Rating |
|---|
Schreiben Sie einen Kommentar zu "Flexible Bayesian Regression Modelling".
Kommentar verfassen