This Book Focuses On Bayesian Multivariate Inference, Which Is Defined As Any Inference That Involves A Multivariate Marginal Posterior Distribution And Is Distinct From Frequentist Multivariate Inference In That That Is Defined As Any Analysis With A Multivariate Response Variable This Text Features Multivariate Models, Including The Mutivariate Normal And T Distributions, Dirichlet Multinomial And Gamma Poisson Models, And Generalized Mixed Linear Models Experimental Design Techniques Are Also Covered And Include Blocking And Repeated Measures Experimental Planning Principles Bayesian Stopping And Decision Rules In Experiments To Prove And Risk Assessments Such As A Priori Type I And Type II Error Risks In Such Experiments Decision Analysis Is Presented In This Context As A Coherent Way To Compute Stopping Boundaries And Terminal Decisions Planning Principles For Experiments Include Information Maximization Each Chapter Includes Problem Sets And Computer Exercises.
Is a well-known author, some of his books are a fascination for readers like in the
- 416 pages
- Biostatistics: Intermediate Bayesian Inference
- George G. Woodworth
- 25 May 2017 George G. Woodworth