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| Próxima revisão | Revisão anterior | ||
| projetos:ehlers:spacetime [2007/04/12 12:56] – criada ehlers | projetos:ehlers:spacetime [2009/03/23 19:49] (atual) – ehlers | ||
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| - | === Abstract === | + | This is part of Luiz Ledo's MSc dissertation. |
| - | In this project we use Markov chain Monte Carlo (MCMC) methods in order to estimate and compare stochastic production frontier models from a Bayesian perspective. We consider a number of competing models in terms of different production functions and the distribution of the asymetric error term. All MCMC simulations are done using the package JAGS (Just Another Gibbs Sampler), a clone of the classic BUGS package which works closely with the R package where all the statistical computations | + | === Participants === |
| + | - [[pessoais: | ||
| - | Key Words: Markov chain Monte Carlo, Gibbs sampler, JAGS, Bayesian model averaging, model comparison. | + | === Some references |
| - | + | ||
| - | === Participantes === | + | |
| - | - [[pessoais: | + | |
| - | + | ||
| - | In this project we use Markov chain Monte Carlo (MCMC) methods in order to estimate and compare stochastic production frontier models from a Bayesian perspective. We consider a number of competing models in terms of different production functions and the distribution of the asymetric error term. All MCMC simulations are done using the package JAGS (Just Another Gibbs Sampler), a clone of the classic BUGS package which works closely with the R package where all the statistical computations and graphics are done. | + | |
| - | + | ||
| - | Key Words: Markov chain Monte Carlo, Gibbs sampler, JAGS, Bayesian model averaging, model comparison. | + | |
| - | + | ||
| - | === Participantes === | + | |
| - | - [[pessoais: | + | |
| - | + | ||
| - | === Bibliografia | + | |
| < | < | ||
| + | @Article{nobresl05, | ||
| + | author = {Nobre, A.A. and Schmidt, A.M. and Lopes, H. F.}, | ||
| + | title = {Spatio-temporal models for mapping the Incidence of | ||
| + | malaria in Para}, | ||
| + | journal = {Environmetrics}, | ||
| + | year = {2005}, | ||
| + | volume = {16}, | ||
| + | pages = {291-304} | ||
| + | } | ||
| </ | </ | ||
| - | |||
