Bayesian analysis with Stata /
Thompson, John
Bayesian analysis with Stata / John Thompson. - College Station, Texas : Stata Press, 2014 - xx, 279 p.
Bibliografía: p. 265-272.
Preface -- 1. The problem of priors -- 2. Evaluating the posterior -- 3. Metropolis-Hastings -- 4. Gibbs sampling -- 5. Assessing convergence -- 6. Validating the Stata code and summarizing the results -- 7. Bayesian analysis with Mata -- 8. Using WinBUGS for model fitting -- 9. Model checking -- 10. Model selection -- 11. Further case studies -- 12. Writing Stata programs for specific Bayesian analysis -- A. Standard distributions.
Bayesian analysis with Stata is written for anyone interested in applying Bayesian methods to real data easly. The book shows how modern analyses based on Markov chain Monte Carlo (MCMC) methods are implemented in Stata both directly and by passing Stata datasets to OpenBUGS or WinBUGS for computation, allowing Stata's data management and graphing capability to be used with OpenBUGS/WinBUGS speed and reliability. The book emphasizes practical data analysis from the Bayesian persepctive, and hence covers the selection of realistic priors, computational efficiency and speed, the assessment of convergence, the evaluation of models, and the presentation of the results.
9781597181419
ANALISIS BAYESIANO
STATA
ANALISIS ESTADISTICO
ESTUDIOS DE CASOS
PROGRAMAS DE COMPUTADORA
519.542
Bayesian analysis with Stata / John Thompson. - College Station, Texas : Stata Press, 2014 - xx, 279 p.
Bibliografía: p. 265-272.
Preface -- 1. The problem of priors -- 2. Evaluating the posterior -- 3. Metropolis-Hastings -- 4. Gibbs sampling -- 5. Assessing convergence -- 6. Validating the Stata code and summarizing the results -- 7. Bayesian analysis with Mata -- 8. Using WinBUGS for model fitting -- 9. Model checking -- 10. Model selection -- 11. Further case studies -- 12. Writing Stata programs for specific Bayesian analysis -- A. Standard distributions.
Bayesian analysis with Stata is written for anyone interested in applying Bayesian methods to real data easly. The book shows how modern analyses based on Markov chain Monte Carlo (MCMC) methods are implemented in Stata both directly and by passing Stata datasets to OpenBUGS or WinBUGS for computation, allowing Stata's data management and graphing capability to be used with OpenBUGS/WinBUGS speed and reliability. The book emphasizes practical data analysis from the Bayesian persepctive, and hence covers the selection of realistic priors, computational efficiency and speed, the assessment of convergence, the evaluation of models, and the presentation of the results.
9781597181419
ANALISIS BAYESIANO
STATA
ANALISIS ESTADISTICO
ESTUDIOS DE CASOS
PROGRAMAS DE COMPUTADORA
519.542