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disciplinas:ce718 [2011/07/16 20:15]
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 ===== Links ===== ===== Links =====
  
 +== Aproximação de Laplace ==
   * {{http://​www.stats.ox.ac.uk/​~steffen/​teaching/​bs2HT9/​laplace.pdf|Laplace'​s Method of Integration - Ste en Lauritzen}};​   * {{http://​www.stats.ox.ac.uk/​~steffen/​teaching/​bs2HT9/​laplace.pdf|Laplace'​s Method of Integration - Ste en Lauritzen}};​
   * {{http://​www.stanford.edu/​~mch/​harding-hausman-laplace.pdf|Using a Laplace Approximation to Estimate the Random Coefficients Logit Model by Non-linear Least Squares}};   * {{http://​www.stanford.edu/​~mch/​harding-hausman-laplace.pdf|Using a Laplace Approximation to Estimate the Random Coefficients Logit Model by Non-linear Least Squares}};
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   * {{http://​dirk.eddelbuettel.com/​blog/​2011/​07/​14/#​rcpp_gibbs_example|MCMC and faster Gibbs Sampling using Rcpp}};   * {{http://​dirk.eddelbuettel.com/​blog/​2011/​07/​14/#​rcpp_gibbs_example|MCMC and faster Gibbs Sampling using Rcpp}};
   * {{http://​darrenjw.wordpress.com/​2011/​07/​16/​gibbs-sampler-in-various-languages-revisited|Gibbs sampler in various languages (revisited)}};​   * {{http://​darrenjw.wordpress.com/​2011/​07/​16/​gibbs-sampler-in-various-languages-revisited|Gibbs sampler in various languages (revisited)}};​
 +
 +== Métodos Monte Carlo ==
 +  * {{http://​elsa.berkeley.edu/​reprints/​misc/​understanding.pdf|Understanding the Metropolis-Hastings Algorithm}};​
 +  * {{http://​www.econ.upenn.edu/​~jesusfv/​LectureNotes_7_MH|Metropolis-Hasting Algorithm - Jesús Fernández-Villaverde}};​
 +  * {{http://​www.dme.ufrj.br/​marina/​MCMC.pdf| MCMC - Marina}};
 +  * {{http://​www.maths.bris.ac.uk/​~manpw/​teaching/​folien1.pdf|Monte Carlo Methods: Lecture 1: Introduction - Nick Whiteley}};
 +  * {{http://​www.maths.bris.ac.uk/​~manpw/​teaching/​folien2.pdf|Monte Carlo Methods: Lecture 2: Transformation and Rejection - Nick Whiteley}};
 +  * {{http://​www.maths.bris.ac.uk/​~manpw/​teaching/​folien3.pdf|Monte Carlo Methods: Lecture 3: Importance Sampling - Nick Whiteley}};
 +  * {{http://​www.maths.bris.ac.uk/​~manpw/​teaching/​folien45.pdf|Monte Carlo Methods: Lectures 5 & 6: The Gibbs Sampler - Nick Whiteley}};
 +  * {{http://​www.maths.bris.ac.uk/​~manpw/​teaching/​folien6.pdf|Monte Carlo Methods: Lecture 7: The Metropolis-Hastings Algorithm - Nick Whiteley}};
 +  * {{http://​www.maths.bris.ac.uk/​~manpw/​teaching/​folien78.pdf|Monte Carlo Methods:: Lectures 9 & 10: Combining Kernels, Convergence Diagnostics - Nick Whiteley}};
 +  * {{http://​www.maths.bris.ac.uk/​~manpw/​teaching/​folien9.pdf|Monte Carlo Methods: Reversible Jump MCMC - Nick Whiteley}};
 +  * {{http://​www.maths.bris.ac.uk/​~manpw/​teaching/​notes.pdf|Monte Carlo Methods - Lecture Notes - Edited by Nick Whiteley}};
 +  * {{http://​www.icmc.usp.br/​~ehlers/​SME0809/​praticas/​node18.html|Algoritmo de Metropolis-Hastings}};​
 +  * {{http://​www.people.fas.harvard.edu/​~plam/​teaching/​methods/​mcmc/​mcmc.pdf|MCMC Methods: Gibbs Sampling and the Metropolis-Hastings Algorithm - Patrick Lam}};
 +  * {{http://​www.maths.manchester.ac.uk/​~pneal/​CIS/​CIS2007.html|Computationally Intensive Statistics 2010/​2011}};​
 +  * {{http://​www.maths.manchester.ac.uk/​~pneal/​statscomp.html|Statistical Computing 2010/​2011}};​
 +  * {{http://​www.lisa.stat.vt.edu/?​q=node/​1784|Bayesian Methods for Regression in R - Nels Johnson}};
 +
 +== Algorítmo EM ==
 +  * [[http://​www.leg.ufpr.br/​~paulojus/​EM|Link para diversos artigos e materiais sobre EM]]
 +  * Outros em modelos não lineares:
 +    * [[http://​www.jstor.org/​stable/​2533054|Walker]]:​ An EM Algorithm for Nonlinear Random Effects Models
 +    * [[http://​bmsr.usc.edu/​Core%20Research/​dzd/​6614.pdf|Wang et al.]]: Nonlinear random effects mixture models: Maximum likelihood estimation via the EM algorithm
 +    * [[http://​dl.acm.org/​citation.cfm?​id=1225091|Wang]]:​ EM algorithms for nonlinear mixed effects models
 +    * [[http://​fedc.wiwi.hu-berlin.de/​xplore/​ebooks/​html/​csa/​node45.html|material online]]
  

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