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Bayesian Thinking, Modeling and Computation: Volume 25
Contributor(s): Dey, Dipak K., Rao, C. R.
ISBN: 0444515399     ISBN-13: 9780444515391
Publisher: North-Holland
OUR PRICE:   $332.50  
Product Type: Hardcover
Published: September 2005
Qty:
Temporarily out of stock - Will ship within 2 to 5 weeks
Annotation: This volume describes how to develop Bayesian thinking, modelling and computation both from philosophical, methodological and application point of view. It further describes parametric and nonparametric Bayesian methods for modelling and how to use modern computational methods to summarize inferences using simulation. The book covers wide range of topics including objective and subjective Bayesian inferences with a variety of applications in modelling categorical, survival, spatial, spatiotemporal, Epidemiological, software reliability, small area and micro array data. The book concludes with a chapter on how to teach Bayesian thoughts to nonstatisticians.


Key Features:


-Critical thinking on causal effects
-Objective Bayesian philosophy
-Nonparametric Bayesian methodology
-Simulation based computing techniques
-Bioinformatics and Biostatistics
Key Features:


??Critical thinking on causal effects
??Objective Bayesian philosophy
??Nonparametric Bayesian methodology
??Simulation based computing techniques
??Bioinformatics and Biostatistics
Additional Information
BISAC Categories:
- Technology & Engineering | Quality Control
- Medical
- Mathematics | Probability & Statistics - General
Dewey: 519.542
LCCN: 2005049839
Series: Handbook of Statistics
Physical Information: 1.81" H x 7" W x 9.6" (4.50 lbs) 1062 pages
 
Descriptions, Reviews, Etc.
Publisher Description:
This volume describes how to develop Bayesian thinking, modelling and computation both from philosophical, methodological and application point of view. It further describes parametric and nonparametric Bayesian methods for modelling and how to use modern computational methods to summarize inferences using simulation. The book covers wide range of topics including objective and subjective Bayesian inferences with a variety of applications in modelling categorical, survival, spatial, spatiotemporal, Epidemiological, software reliability, small area and micro array data. The book concludes with a chapter on how to teach Bayesian thoughts to nonstatisticians.