000			01627nam a22002537a 4500
003			OSt
005			20221215104001.0
008			221215b |||||||| |||| 00| 0 eng d
020			_a0412039915
040			_aECOPH _cECOPH
245			_aBayesian data analysis / _c Andrew Gelman ... [et al].
260			_aLondon : _bChapman & Hall, _c1995.
300			_axix, 526 pages : _b illustrations _c24 cm
490			_aTexts in statistical science.
500			_aReprint 1997.
504			_aIncludes bibliographical references (pages 489-512) and indexes.
505			_aPart I. Fundamentals of Bayesian Inference -- 1. Background -- 2. Single-parameter models -- 3. Introduction to multiparameter models -- 4. Large-sample inference and connections to standard statistical methods -- Part II. Fundamentals of Bayesian Data Analysis -- 5. Hierarchical models -- 6. Model checking and sensitivity analysis -- 7. Study design in Bayesian analysis -- 8. Introduction to regression models -- Part III. Advanced computation -- 9. Approximations based on posterior modes -- 10. Posterior simulation and integration -- 11. Markov chain simulation -- Part IV. Specific models -- 12. Models for robust inference and sensitivity analysis -- 13. Hierarchical linear models -- 14. Generalized linear models -- 15. Multivariate models -- 16. Mixture models -- 17. Models for missing data -- 18. Concluding advice.
650			_xBayesian statistical decision theory.
650			_xMathematical statistics.
650			_xBayesian methods
700			_aGelman, Andrew.
830			_aTexts in statistical science.
942			_2lcc _cBook
999			_c335 _d335