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[1] N. Metropolis,et al. The Monte Carlo method. , 1949 .
[2] David B. Dunson,et al. Bayesian Data Analysis , 2010 .
[3] J. Nocedal,et al. A Limited Memory Algorithm for Bound Constrained Optimization , 1995, SIAM J. Sci. Comput..
[4] Andrew Thomas,et al. WinBUGS - A Bayesian modelling framework: Concepts, structure, and extensibility , 2000, Stat. Comput..
[5] Andreas Griewank,et al. Evaluating derivatives - principles and techniques of algorithmic differentiation, Second Edition , 2000, Frontiers in applied mathematics.
[6] Martyn Plummer,et al. JAGS: A program for analysis of Bayesian graphical models using Gibbs sampling , 2003 .
[7] M. David. Semiautomatic Differentiation for Efficient Gradient Computations , 2004 .
[8] S. Rabe-Hesketh,et al. Maximum likelihood estimation of limited and discrete dependent variable models with nested random effects , 2005 .
[9] Martin Bücker,et al. Automatic differentiation : applications, theory, and implementations , 2006 .
[10] Andrew Thomas,et al. The BUGS project: Evolution, critique and future directions , 2009, Statistics in medicine.
[11] Ss Beal,et al. NONMEM User’s Guides. (1989–2009) , 2009 .
[12] Dorota Kurowicka,et al. Generating random correlation matrices based on vines and extended onion method , 2009, J. Multivar. Anal..
[13] John K Kruschke,et al. Bayesian data analysis. , 2010, Wiley interdisciplinary reviews. Cognitive science.
[14] David Huard,et al. PyMC: Bayesian Stochastic Modelling in Python. , 2010, Journal of statistical software.
[15] Andrew Gelman,et al. Handbook of Markov Chain Monte Carlo , 2011 .
[16] Radford M. Neal. MCMC Using Hamiltonian Dynamics , 2011, 1206.1901.
[17] Jeffrey S. Rosenthal,et al. Optimal Proposal Distributions and Adaptive MCMC , 2011 .
[18] Andrew D. Martin,et al. MCMCpack: Markov chain Monte Carlo in R , 2011 .
[19] David B. Dunson,et al. Bayesian data analysis, third edition , 2013 .
[20] M. Betancourt. Generalizing the No-U-Turn Sampler to Riemannian Manifolds , 2013, 1304.1920.
[21] Aki Vehtari,et al. GPstuff: Bayesian modeling with Gaussian processes , 2013, J. Mach. Learn. Res..
[22] A. Gelman,et al. The Great Society, Reagan's Revolution, and Generations of Presidential Voting , 2022, American Journal of Political Science.
[23] Andrew Gelman,et al. The No-U-turn sampler: adaptively setting path lengths in Hamiltonian Monte Carlo , 2011, J. Mach. Learn. Res..
[24] Andrew Gelman,et al. Automatic Variational Inference in Stan , 2015, NIPS.