Cargando…
Bayesian data analysis /
"Preface This book is intended to have three roles and to serve three associated audiences: an introductory text on Bayesian inference starting from first principles, a graduate text on effective current approaches to Bayesian modeling and computation in statistics and related fields, and a han...
| Clasificación: | Libro Electrónico |
|---|---|
| Autores principales: | , , , , , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Boca Raton :
CRC Press,
[2014]
|
| Edición: | Third edition. |
| Colección: | Texts in statistical science.
|
| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
Tabla de Contenidos:
- Part I:
- Fundamentals of Bayesian inference.
- Probability and inference
- Single-parameter models
- Introduction to multiparameter models
- Asymptotics and connections to non-Bayesian approaches
- Hierarchical models Part II: Fundamentals of Bayesian data analysis.
- Model checking
- Evaluating, comparing, and expanding models
- Modeling accounting for data collection
- Decision analysis Part III:
- Advanced computation.
- Introduction to Bayesian computation
- Basics of Markov chain simulation
- Computationally efficient Markov chain simulation
- Modal and distributional approximations Part IV:
- Regression models.
- Introduction to regression models
- Hierarchical linear models
- Generalized linear models
- Models for robust inference
- Models for missing data Part V:
- Nonlinear and nonparametric models.
- Parametric nonlinear models
- Basis function models
- Gaussian process models
- Finite mixture models
- Dirichlet process models
- A. Standard probability distributions
- B. Outline of proofs of limit theorems
- Computation in R and Stan.