| Ambos lados da revisão anteriorRevisão anteriorPróxima revisão | Revisão anterior |
| disciplinas:ce718 [2011/07/07 22:55] – [section 11] walmes | disciplinas:ce718 [2016/07/01 15:23] (atual) – a revisão anterior foi restaurada (2011/09/06 13:32) paulojus |
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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}}; |
| * {{http://actuaryzhang.com/seminar/topic5_mcmc.pdf|Markov Chain Monte Carlo Methods}}; | * {{http://actuaryzhang.com/seminar/topic5_mcmc.pdf|Markov Chain Monte Carlo Methods}}; |
| * 8-O{{http://dirk.eddelbuettel.com/blog/2011/07/05/#rcppeigen_introduction|Even faster linear model fits with R using RcppEigen}}; | * 8-O{{http://dirk.eddelbuettel.com/blog/2011/07/05/#rcppeigen_introduction|Even faster linear model fits with R using RcppEigen}}; |
| | * {{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)}}; |
| | |
| | == 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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