A method for efficiently sampling from distributions with correlated dimensions.
暂无分享,去创建一个
[1] M. Stone. Models for choice-reaction time , 1960 .
[2] Roger Ratcliff,et al. A Theory of Memory Retrieval. , 1978 .
[3] C. D. Kemp,et al. Density Estimation for Statistics and Data Analysis , 1987 .
[4] S. Kullback,et al. Topics in statistical information theory , 1987 .
[5] Reiko Tanese,et al. Distributed Genetic Algorithms , 1989, ICGA.
[6] C. Pichot,et al. A Model-Based , 1991 .
[7] W. Gilks,et al. Adaptive Rejection Sampling for Gibbs Sampling , 1992 .
[8] David B. Dunson,et al. Bayesian Data Analysis , 2010 .
[9] W. Gilks,et al. Adaptive Rejection Metropolis Sampling Within Gibbs Sampling , 1995 .
[10] G. Roberts,et al. Updating Schemes, Correlation Structure, Blocking and Parameterization for the Gibbs Sampler , 1997 .
[11] A. Gupta,et al. A Bayesian Approach to , 1997 .
[12] Rainer Storn,et al. Differential Evolution – A Simple and Efficient Heuristic for global Optimization over Continuous Spaces , 1997, J. Glob. Optim..
[13] R. Storn,et al. Differential Evolution - A simple and efficient adaptive scheme for global optimization over continuous spaces , 2004 .
[14] Richard J. Patz,et al. A Straightforward Approach to Markov Chain Monte Carlo Methods for Item Response Models , 1999 .
[15] Understanding Memory , 1999 .
[16] Brian W. Junker,et al. Applications and Extensions of MCMC in IRT: Multiple Item Types, Missing Data, and Rated Responses , 1999 .
[17] A. U.S.,et al. Generalised Gibbs sampler and multigrid Monte Carlo for Bayesian computation , 2000 .
[18] Andrew Thomas,et al. WinBUGS - A Bayesian modelling framework: Concepts, structure, and extensibility , 2000, Stat. Comput..
[19] Jun S. Liu,et al. Generalised Gibbs sampler and multigrid Monte Carlo for Bayesian computation , 2000 .
[20] James L. McClelland,et al. The time course of perceptual choice: the leaky, competing accumulator model. , 2001, Psychological review.
[21] M. Peruggia,et al. Was it a car or a cat I saw? An Analysis of Response Times for Word Recognition , 2002 .
[22] Jeffrey N. Rouder,et al. A hierarchical bayesian statistical framework for response time distributions , 2003 .
[23] Christian P. Robert,et al. Monte Carlo Statistical Methods , 2005, Springer Texts in Statistics.
[24] Jerry Nedelman,et al. Book review: “Bayesian Data Analysis,” Second Edition by A. Gelman, J.B. Carlin, H.S. Stern, and D.B. Rubin Chapman & Hall/CRC, 2004 , 2005, Comput. Stat..
[25] Jun Lu,et al. An introduction to Bayesian hierarchical models with an application in the theory of signal detection , 2005, Psychonomic bulletin & review.
[26] Kam-Wah Tsui,et al. Distributed Evolutionary Monte Carlo with Applications to Bayesian Analysis , 2005 .
[27] Andrew Heathcote,et al. A ballistic model of choice response time. , 2005, Psychological review.
[28] Jeffrey N. Rouder,et al. A hierarchical model for estimating response time distributions , 2005, Psychonomic bulletin & review.
[29] Peter E. Rossi,et al. Hierarchical Bayes Models , 2006 .
[30] Michael D. Lee,et al. A Bayesian Approach to Diffusion Models of Decision-Making and Response Time , 2006, NIPS.
[31] Cajo J. F. ter Braak,et al. A Markov Chain Monte Carlo version of the genetic algorithm Differential Evolution: easy Bayesian computing for real parameter spaces , 2006, Stat. Comput..
[32] Thomas Hofmann,et al. A Bayesian Approach to Diffusion Models of Decision-Making and Response Time , 2007 .
[33] David B. Dunson,et al. Bayesian Structural Equation Modeling , 2007 .
[34] D. Spiegelhalter,et al. Allowing for correlations between correlations in random-effects meta-analysis of correlation matrices. , 2007, Psychological methods.
[35] Roger Ratcliff,et al. Application of the diffusion model to two-choice tasks for adults 75-90 years old. , 2007, Psychology and aging.
[36] van Hedderik Rijn,et al. Proceedings of the eight International Conference on Cognitive Modeling , 2007 .
[37] Kristopher J Preacher,et al. Item factor analysis: current approaches and future directions. , 2007, Psychological methods.
[38] Christophe Andrieu,et al. A tutorial on adaptive MCMC , 2008, Stat. Comput..
[39] Michael D. Lee,et al. A Bayesian approach to diffusion process models of decision-making , 2008 .
[40] K. R. Ridderinkhof,et al. Striatum and pre-SMA facilitate decision-making under time pressure , 2008, Proceedings of the National Academy of Sciences.
[41] Cajo J. F. ter Braak,et al. Differential Evolution Markov Chain with snooker updater and fewer chains , 2008, Stat. Comput..
[42] Rainer Storn,et al. Differential Evolution Research – Trends and Open Questions , 2008 .
[43] Casimir J. H. Ludwig,et al. Bayesian and maximum likelihood estimation of hierarchical response time models , 2008, Psychonomic bulletin & review.
[44] Richard D. Morey,et al. A statistical model for discriminating between subliminal and near-liminal performance , 2008 .
[45] Scott D. Brown,et al. The simplest complete model of choice response time: Linear ballistic accumulation , 2008, Cognitive Psychology.
[46] Kevin J. Grimm,et al. Modeling life-span growth curves of cognition using longitudinal data with multiple samples and changing scales of measurement. , 2009, Psychological methods.
[47] Wolf Vanpaemel,et al. BayesGCM: Software for Bayesian inference with the generalized context model , 2009, Behavior research methods.
[48] D. Higdon,et al. Accelerating Markov Chain Monte Carlo Simulation by Differential Evolution with Self-Adaptive Randomized Subspace Sampling , 2009 .
[49] J. Rouder,et al. A Truncated-Probit Item Response Model for Estimating Psychophysical Thresholds , 2009 .
[50] Francis Tuerlinckx,et al. A Hierarchical Ornstein–Uhlenbeck Model for Continuous Repeated Measurement Data , 2009 .
[51] Ying Yuan,et al. Bayesian mediation analysis. , 2009, Psychological methods.
[52] A. Heathcote,et al. Is the Linear Ballistic Accumulator Model Really the Simplest Model of Choice Response Times: A Bayesian Model Complexity Analysis , 2009 .
[53] Jean-Paul Fox,et al. Evaluating cognitive theory: a joint modeling approach using responses and response times. , 2009, Psychological methods.
[54] Andrew Heathcote,et al. Getting more from accuracy and response time data: Methods for fitting the linear ballistic accumulator , 2009, Behavior research methods.
[55] E. Wagenmakers,et al. A diffusion model decomposition of the practice effect , 2009, Psychonomic bulletin & review.
[56] M. Bensebti,et al. Statistical Model , 2005 .
[57] Bo Hu,et al. Distributed evolutionary Monte Carlo for Bayesian computing , 2010, Comput. Stat. Data Anal..
[58] By W. R. GILKSt,et al. Adaptive Rejection Sampling for Gibbs Sampling , 2010 .
[59] R. Ratcliff,et al. The effects of aging on the speed-accuracy compromise: Boundary optimality in the diffusion model. , 2010, Psychology and aging.
[60] Michael C. Edwards,et al. A Markov Chain Monte Carlo Approach to Confirmatory Item Factor Analysis , 2010 .
[61] Peter F. Craigmile,et al. Hierarchical Bayes Models for Response Time Data , 2010 .
[62] F. Tuerlinckx,et al. A crossed random effects diffusion model for speeded semantic categorization decisions. , 2010, Acta psychologica.
[63] Scott D. Brown,et al. Cortico-striatal connections predict control over speed and accuracy in perceptual decision making , 2010, Proceedings of the National Academy of Sciences.
[64] Uday K. Chakraborty,et al. Advances in Differential Evolution , 2010 .
[65] Herbert Hoijtink,et al. Bayesian evaluation of inequality and equality constrained hypotheses for contingency tables. , 2010, Psychological methods.
[66] Andrew Gelman,et al. Handbook of Markov Chain Monte Carlo , 2011 .
[67] M. Lee,et al. Understanding memory impairment with memory models and hierarchical Bayesian analysis , 2011 .
[68] Michael D. Lee,et al. A Model-Based Approach to Measuring Expertise in Ranking Tasks , 2011, CogSci.
[69] Radford M. Neal. MCMC Using Hamiltonian Dynamics , 2011, 1206.1901.
[70] David M. Blei,et al. A topographic latent source model for fMRI data , 2011, NeuroImage.
[71] Andrew Heathcote,et al. Drawing conclusions from choice response time models: A tutorial using the linear ballistic accumulator , 2011 .
[72] M. Lee,et al. Hierarchical diffusion models for two-choice response times. , 2011, Psychological methods.
[73] E. Wagenmakers,et al. The Speed-Accuracy Tradeoff in the Elderly Brain: A Structural Model-Based Approach , 2011, The Journal of Neuroscience.
[74] Brandon M. Turner,et al. Approximate Bayesian computation with differential evolution , 2012 .
[75] Sik-Yum Lee,et al. A tutorial on the Bayesian approach for analyzing structural equation models , 2012 .
[76] Bengt Muthén,et al. Bayesian structural equation modeling: a more flexible representation of substantive theory. , 2012, Psychological methods.
[77] Brandon M. Turner,et al. Likelihood-free Bayesian analysis of memory models. , 2013, Psychological review.
[78] Richard P. Heitz,et al. The speed-accuracy tradeoff: history, physiology, methodology, and behavior , 2014, Front. Neurosci..
[79] Andrew Gelman,et al. The No-U-turn sampler: adaptively setting path lengths in Hamiltonian Monte Carlo , 2011, J. Mach. Learn. Res..