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Essential Bayesian Models
 
 

Essential Bayesian Models, 1st Edition

 
Essential  Bayesian Models, 1st Edition,C.R. Rao,Dipak Dey,ISBN9780444537324
 
 
 

  &      

North Holland

9780444537324

586

152 X 229

This accessible reference includes selected contributions from Bayesian Thinking - Modeling and Computation, Volume 25 in the Handbook of Statistics Series, with a focus on key methodologies and applications for Bayesian models and computation.

Print Book

Hardcover

In Stock

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USD 85.95
 
 

Key Features

  • Aids critical thinking on causal effects
  • Provides simulation based computing techniques
  • Covers Bioinformatics and Biostatistics

Description

This accessible reference includes selected contributions from Bayesian Thinking - Modeling and Computation, Volume 25 in the Handbook of Statistics Series, with a focus on key methodologies and applications for Bayesian models and computation. It describes parametric and nonparametric Bayesian methods for modeling, and how to use modern computational methods to summarize inferences using simulation. The book covers a wide range of topics including objective and subjective Bayesian inferences, with a variety of applications in modeling categorical, survival, spatial, spatiotemporal, Epidemiological, small area and micro array data.

Readership

Professionals and Researchers in a variety of fields, including: Biomedical Engineering, Molecular Biology, Computer Engineering, Software Engineering and Biological Sciences.

C.R. Rao

C. R. Rao, born in India is one of this century's foremost statisticians, received his education in statistics at the Indian Statistical Institute (ISI), Calcutta. Rao is currently at Penn State as Eberly Professor of Statistics and Director of the Center for Multivariate Analysis. His research has influenced not only statistics, but also the physical, social and natural sciences and engineering.

Affiliations and Expertise

The Pennsylvania State University, PA, USA

View additional works by C.R. Rao

Dipak Dey

Affiliations and Expertise

University of Connecticut, CT, USA

Essential Bayesian Models, 1st Edition

1. Model Selection and Hypothesis Testing based on Objective Probabilities and Bayes Factors; 2. Bayesian Model Checking and Model Diagnostics; 3. Bayesian Nonparametric Modeling and Data Analysis: An Introduction; 4. Some Bayesian Nonparametric Models; 5. Bayesian Modeling in the Wavelet Domain; 6. Bayesian Methods for Function Estimation; 7. MCMC Methods to Estimate Bayesian Parametric Models; 8. Bayesian Computation: From Posterior Densities to Bayes Factors, Marginal Likelihoods, and Posterior Model Probabilities; 9. Bayesian Modelling and Inference on Mixtures of Distributions; 10. Variable Selection and Covariance Selection in Multivariate Regression Models; 11. Dynamic Models; 12. Elliptical Measurement Error Models – A Bayesian Approach; 13. Bayesian Sensitivity Analysis in Skew-elliptical Models; 14. Bayesian Methods for DNA Microarray Data Analysis; 15. Bayesian Biostatistics; 16. Innovative Bayesian Methods for Biostatistics and Epidemiology; 17. Modeling and Analysis for Categorical Response Data; 18. Bayesian Methods and Simulation-Based Computation for Contingency Tables; 19. Teaching Bayesian Thought to Nonstatisticians

 
 
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