M. Antónia Amaral Turkman, Carlos Daniel Paulino, Peter Müller

Computational Bayesian Statistics

• Broschiertes Buch

Produktbeschreibung

This integrated introduction to fundamentals, computation, and software is your key to understanding and using advanced Bayesian methods.

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Produktdetails

• Verlag: Cambridge University Press
• Seitenzahl: 256
• Erscheinungstermin: 28. Februar 2019
• Englisch
• Abmessung: 229mm x 152mm x 15mm
• Gewicht: 376g
• ISBN-13: 9781108703741
• ISBN-10: 1108703747
• Artikelnr.: 54148247

Autorenporträt

M. Antónia Amaral Turkman was, until 2013, full-time Professor in the Department of Statistics and Operations Research, Faculty of Sciences, University of Lisbon. Though retired from the university, she is still a member of its Center of Statistics and Applications, where she held the position of scientific coordinator until 2017. Her research interests are Bayesian statistics, medical and environmental statistics, and spatiotemporal modeling, with recent publications on computational methods in Bayesian statistics, with an emphasis on applications in health and forest fires. She has served as vice president of the Portuguese Statistical Society. She has taught courses on Bayesian statistics and computational statistics, among many others.

Inhaltsangabe

1. Bayesian inference
2. Representation of prior information
3. Bayesian inference in basic problems
4. Inference by Monte Carlo methods
5. Model assessment
6. Markov chain Monte Carlo methods
7. Model selection and transdimensional MCMC
8. Methods based on analytic approximations
9. Software.