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 ====== CE-718: Métodos Computacionalmente Intensivos ====== ====== CE-718: Métodos Computacionalmente Intensivos ======
 +
 +<note>
 +Arquivos/páginas serão atualizados durante o curso.
 +</note>
  
 ===== Detalhes da oferta da disciplina ===== ===== Detalhes da oferta da disciplina =====
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 ===== Referências Bibliográficas ===== ===== Referências Bibliográficas =====
- 
-__**ATENÇÃO:**__ arquivos/páginas poderão atualizados durante o curso. 
  
 <bibtex> <bibtex>
 +@book{robert_introducing_2009,
 + edition = {1},
 + title = {Introducing Monte Carlo Methods with R},
 + isbn = {9781441915757},
 + publisher = {Springer Verlag},
 + author = {Christian P. Robert and George Casella},
 + month = dec,
 + year = {2009}
 +},
 +
 +
 +@book{gamerman_markov_2006,
 + edition = {2},
 + title = {Markov Chain Monte Carlo: Stochastic Simulation for Bayesian Inference, Second Edition},
 + isbn = {1584885874},
 + shorttitle = {Markov Chain Monte Carlo},
 + publisher = {Chapman and {Hall/CRC}},
 + author = {Dani Gamerman and Hedibert F. Lopes},
 + month = may,
 + year = {2006}
 +},
 +
 @book{albert_bayesian_2009, @book{albert_bayesian_2009,
  edition = {2nd ed.},  edition = {2nd ed.},
Linha 78: Linha 102:
 }, },
  
-@book{gamerman_markov_2006+ 
- edition = {2}, +@book{robert_monte_2004
- title = {Markov Chain Monte Carlo: Stochastic Simulation for Bayesian Inference, Second Edition}, + edition = {2nd}, 
- isbn = {1584885874}, + title = {Monte Carlo Statistical Methods}, 
- shorttitle = {Markov Chain Monte Carlo},+ isbn = {0387212396}, 
 + publisher = {Springer}, 
 + author = {Christian Robert and George Casella}, 
 + month = jul, 
 + year = {2004} 
 +}, 
 + 
 +@book{manly_randomization_2006, 
 + edition = {3}, 
 + title = {Randomization, Bootstrap and Monte Carlo Methods in Biology, Third Edition}, 
 + isbn = {9781584885412},
  publisher = {Chapman and {Hall/CRC}},  publisher = {Chapman and {Hall/CRC}},
- author = {Dani Gamerman and Hedibert F. Lopes}, + author = {Bryan {F.J.} Manly}, 
- month = may,+ month = aug,
  year = {2006}  year = {2006}
 } }
 +
 +
 +@book{gentle_handbook_2004,
 + edition = {1},
 + title = {Handbook of Computational Statistics},
 + isbn = {3540404643},
 + publisher = {Springer},
 + author = {{J.E.} Gentle and Wolfgang {HSrdle}},
 + month = aug,
 + year = {2004}
 +},
 +
 +@book{kroese_handbook_2011,
 + edition = {1},
 + title = {Handbook of Monte Carlo Methods},
 + isbn = {9780470177938},
 + publisher = {Wiley},
 + author = {Dirk P. Kroese and Thomas Taimre and Zdravko I. Botev},
 + month = mar,
 + year = {2011}
 +},
 +
 +@book{suess_introduction_2010,
 + edition = {1st Edition.},
 + title = {Introduction to Probability Simulation and Gibbs Sampling with R},
 + isbn = {{038740273X}},
 + publisher = {Springer},
 + author = {Eric A. Suess and Bruce E. Trumbo},
 + month = jun,
 + year = {2010}
 +},
 +
 +@book{kalos_monte_2008,
 + edition = {2},
 + title = {Monte Carlo Methods},
 + isbn = {{352740760X}},
 + publisher = {{Wiley-VCH}},
 + author = {Malvin H. Kalos and Paula A. Whitlock},
 + month = nov,
 + year = {2008}
 +},
 +
 +@book{monahan_numerical_2011,
 + edition = {2},
 + title = {Numerical Methods of Statistics},
 + isbn = {0521139511},
 + publisher = {Cambridge University Press},
 + author = {John F. Monahan},
 + month = apr,
 + year = {2011}
 +},
 +
 +@book{gentle_random_2003,
 + edition = {2nd},
 + title = {Random Number Generation and Monte Carlo Methods},
 + isbn = {0387001786},
 + publisher = {Springer},
 + author = {James E. Gentle},
 + month = jun,
 + year = {2003}
 +}
 +
 </bibtex> </bibtex>
  
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 [[disciplinas:ce718:aberto2011|Página aberta]] para edição pelos participantes do curso. [[disciplinas:ce718:aberto2011|Página aberta]] para edição pelos participantes do curso.
 +
 +===== 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.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.cemmap.ac.uk/wps/cwp0601.pdf|USING A LAPLACE APPROXIMATION TO ESTIMATE THE RANDOM COEFFICIENTS LOGIT MODEL BY NON-LINEAR LEAST SQUARES}};
 +  * {{http://www.cs.berkeley.edu/~jordan/courses/260-spring10/lectures/lecture16.pdf|Laplace approximation review}};
 +  * {{http://www.cs.toronto.edu/~mackay/itprnn/ps/343.344.pdf|Laplace's Method}};
 +  * {{http://www.ece.rice.edu/~vc3/elec633/graphical_models_notes_091108.pdf|Laplace Approximation}};
 +  * {{http://galton.uchicago.edu/~pmcc/pubs/paper26.pdf|Laplace approximation of high dimensional integrals}};
 +  * {{http://support.sas.com/documentation/cdl/en/statug/63347/HTML/default/viewer.htm#statug_glimmix_a0000001432.htm|Maximum Likelihood Estimation Based on Laplace Approximation}};
 +  * {{http://statmath.wu.ac.at/research/talks/resources/MultIRT.pdf|Fitting Multidimensional Latent Variable Models using an Efficient Laplace Approximation}};
 +  * {{http://prin08.uniud.it/tl_files/prin08/upload/papers/2010_3.pdf|LAPLACE APPROXIMATION IN MEASUREMENT ERROR MODELS}};
 +  * {{http://www.unc.edu/~vangelis/files/sglmmlapl.pdf|Asymptotic inference for Spatial GLMM using high order Laplace approximation}};
 +  * {{http://www.jstor.org/pss/1390617}};
 +  * {{http://digitalcommons.unl.edu/cgi/viewcontent.cgi?article=1003&context=statisticsdiss&sei-redir=1#search=%22laplace%20approximation%20integral%22|FULLY EXPONENTIAL LAPLACE APPROXIMATION EM ALGORITHM FOR NONLINEAR MIXED EFFECTS MODELS}};
 +  * {{http://proquest.umi.com/pqdlink?Ver=1&Exp=07-02-2016&FMT=7&DID=1188875391&RQT=309&attempt=1&cfc=1|Applications of Laplace approximation for hierarchical generalized linear models in educational research}};
 +  * {{http://people.math.aau.dk/~rw/Undervisning/Topics/Handouts/6.hand.pdf|Computation of the likelihood function for GLMMs}};
 +  * {{http://www.ansci.wisc.edu/morota/beamer/computing.pdf|Computing: Generalized, Linear, and Mixed Models}};
 +  * {{http://jmlr.csail.mit.edu/papers/volume12/cseke11a/cseke11a.pdf|Approximate Marginals in Latent Gaussian Models}};
 +  * {{http://biowww.dfci.harvard.edu/~yili/spa1.pdf|Modeling Spatial Survival Data Using Semiparametric Frailty Models}};
 +  * {{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}};
 +  * {{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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