Bayesian and Frequentist Regression Methodsย provides a modern account of both Bayesian and frequentist methods of regression analysis. Many texts cover one or the other of the approaches, but this is the most comprehensive combination of Bayesian and frequentist methods that exists in one place. The
[Springer Series in Statistics] Bayesian and Frequentist Regression Methods || Frequentist Inference
โ Scribed by Wakefield, Jon
- Book ID
- 118234435
- Publisher
- Springer New York
- Year
- 2012
- Tongue
- English
- Weight
- 654 KB
- Edition
- 2013
- Category
- Article
- ISBN
- 1441909257
No coin nor oath required. For personal study only.
โฆ Synopsis
Bayesian and Frequentist Regression Methodsย provides a modern account of both Bayesian and frequentist methods of regression analysis. Many texts cover one or the other of the approaches, but this is the most comprehensive combination of Bayesian and frequentist methods that exists in one place. The two philosophical approaches to regression methodology are featured here as complementary techniques, with theory and data analysis providing supplementary components of the discussion. In particular, methods are illustrated using a variety of data sets. The majority of the data sets are drawn from biostatistics but the techniques are generalizable to a wide range of other disciplines.
๐ SIMILAR VOLUMES
Bayesian and Frequentist Regression Methodsย provides a modern account of both Bayesian and frequentist methods of regression analysis. Many texts cover one or the other of the approaches, but this is the most comprehensive combination of Bayesian and frequentist methods that exists in one place. The
Bayesian and Frequentist Regression Methodsย provides a modern account of both Bayesian and frequentist methods of regression analysis. Many texts cover one or the other of the approaches, but this is the most comprehensive combination of Bayesian and frequentist methods that exists in one place. The
Scientific Data Gathering -- Displaying And Summarizing Data -- Logic, Probability, And Uncertainty -- Discrete Random Variables -- Bayesian Inference For Discrete Random Variables -- Continuous Random Variables -- Bayesian Inference For Binomial Proportion -- Comparing Bayesian And Frequentist Infe
## Comparing Bayesian and Frequentist Inferences for Proportion The posterior distribution of the parameter given the data gives the complete inference from the Bayesian point of view. It summarizes our belief about the parameter after we have analyzed the data. However, from the frequentist point