Bayesian Statistical Methods-Test Bank

Check Financial institution For Bayesian Statistical Methods

1. ISBN-10

   0815378645
2. ISBN-13

   978-0815378648Bayesian Statistical Methods gives information scientists with the foundational and computational instruments wanted to hold out a Bayesian evaluation. This guide focuses on Bayesian strategies utilized routinely in apply together with a number of linear regression, combined results fashions and generalized linear fashions (GLM). The authors embody many examples with full R code and comparisons with analogous frequentist procedures.

   Along with the essential ideas of Bayesian inferential strategies, the guide covers many basic subjects:

    

   • Recommendation on deciding on prior distributions

    

   • Computational strategies together with Markov chain Monte Carlo (MCMC)

    

   • Mannequin-comparison and goodness-of-fit measures, together with sensitivity to priors

    

   • Frequentist properties of Bayesian strategies

   Case research overlaying superior subjects illustrate the flexibleness of the Bayesian method:

    

   • Semiparametric regression

    

   • Dealing with of lacking information utilizing predictive distributions

    

   • Priors for high-dimensional regression fashions

    

   • Computational strategies for big datasets

    

   • Spatial information evaluation

   The superior subjects are introduced with ample conceptual depth that the reader will be capable to perform such evaluation and argue the relative deserves of Bayesian and classical strategies. A repository of R code, motivating information units, and full information analyses can be found on the guide’s web site.

   Brian J. Reich, Affiliate Professor of Statistics at North Carolina State College, is presently the editor-in-chief of the Journal of Agricultural, Organic, and Environmental Statistics and was awarded the LeRoy & Elva Martin Instructing Award.

   Sujit Okay. Ghosh, Professor of Statistics at North Carolina State College, has over 22 years of analysis and educating expertise in conducting Bayesian analyses, acquired the Cavell Brownie mentoring award, and served because the Deputy Director on the Statistical and Utilized Mathematical Sciences Institute.