Sequential piecewise PCE approximation of likelihood functions in Bayesian inference
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Stefano Marelli | Bruno Sudret | Paul-Remo Wagner | Christos Lataniotis | Paul Wagner | S. Marelli | C. Lataniotis | B. Sudret
[1] Jonathan R Goodman,et al. Ensemble samplers with affine invariance , 2010 .
[2] Christian P. Robert,et al. Monte Carlo Statistical Methods , 2005, Springer Texts in Statistics.
[3] Dongbin Xiu,et al. The Wiener-Askey Polynomial Chaos for Stochastic Differential Equations , 2002, SIAM J. Sci. Comput..
[4] Sylvain Arlot,et al. A survey of cross-validation procedures for model selection , 2009, 0907.4728.
[5] Robert Tibshirani,et al. The Elements of Statistical Learning: Data Mining, Inference, and Prediction, 2nd Edition , 2001, Springer Series in Statistics.
[6] Jinglai Li,et al. Adaptive Construction of Surrogates for the Bayesian Solution of Inverse Problems , 2013, SIAM J. Sci. Comput..
[7] W. Gautschi. Orthogonal Polynomials: Computation and Approximation , 2004 .
[8] W. K. Hastings,et al. Monte Carlo Sampling Methods Using Markov Chains and Their Applications , 1970 .
[9] Y. Marzouk,et al. A stochastic collocation approach to Bayesian inference in inverse problems , 2009 .
[10] N. Metropolis,et al. Equation of State Calculations by Fast Computing Machines , 1953, Resonance.
[11] Bruno Sudret,et al. Spectral likelihood expansions for Bayesian inference , 2015, J. Comput. Phys..
[12] Roger G. Ghanem,et al. Physical Systems with Random Uncertainties: Chaos Representations with Arbitrary Probability Measure , 2005, SIAM J. Sci. Comput..
[13] M. Lemaire,et al. Stochastic finite element: a non intrusive approach by regression , 2006 .
[14] H. Haario,et al. An adaptive Metropolis algorithm , 2001 .
[15] Bruno Sudret,et al. Adaptive sparse polynomial chaos expansion based on least angle regression , 2011, J. Comput. Phys..
[16] J. Freidman,et al. Multivariate adaptive regression splines , 1991 .
[17] Stefan M. Wild,et al. A Bayesian approach for parameter estimation and prediction using a computationally intensive model , 2014, Journal of Physics G: Nuclear and Particle Physics.