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| + | |||
| + | ===== 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]] | ||
