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Book
NeuroImage, ISSN 1053-8119, 11/2013, Volume 81, pp. 96 - 109
Journal Article
Journal of the Royal Statistical Society: Series B (Statistical Methodology), ISSN 1369-7412, 11/2016, Volume 78, Issue 5, pp. 1103 - 1130
Journal Article
Annals of Statistics, ISSN 0090-5364, 02/2019, Volume 47, Issue 1, pp. 67 - 92
Journal Article
HEARING RESEARCH, ISSN 0378-5955, 07/2007, Volume 229, Issue 1-2, pp. 3 - 13
Journal Article
The Annals of Statistics, ISSN 0090-5364, 4/2000, Volume 28, Issue 2, pp. 500 - 531
Journal Article
JACC (Journal of the American College of Cardiology), ISSN 0735-1097, 2017, Volume 69, Issue 10, pp. 1257 - 1269
Journal Article
Bayesian Analysis, ISSN 1936-0975, 2010, Volume 5, Issue 1, pp. 171 - 188
This paper considers the effects of placing an absolutely continuous prior distribution on the regression coefficients of a linear model. We show that the... 
Markov chain monte carlo | Posterior moments | Bayesian lasso | p ≥ n | Scale mixture of normals | Shrinkage | Normal-gamma prior | Multiple regression | "Spike-and-slab" prior | Bayesian Lasso | p > n | SCALE MIXTURES | STATISTICS & PROBABILITY | Normal-Gamma prior | VARIABLE SELECTION | MATHEMATICS, INTERDISCIPLINARY APPLICATIONS | Markov chain Monte Carlo
Journal Article
International Statistical Review / Revue Internationale de Statistique, ISSN 0306-7734, 4/2013, Volume 81, Issue 1, pp. 3 - 39
Journal Article
Mathematics of Computation of the American Mathematical Society, ISSN 0025-5718, 03/2018, Volume 87, Issue 310, pp. 721 - 753
We study the use of Gaussian process emulators to approximate the parameter-to-observation map or the negative log-likelihood in Bayesian inverse problems. We... 
Gaussian process regression | Bayesian approach | Surrogate model | Posterior consistency | Inverse problem | CALIBRATION | MATHEMATICS, APPLIED | MCMC | INTERPOLATION | surrogate model | MODELS | posterior consistency | UNCERTAINTY | SIMULATIONS | EFFICIENT
Journal Article
Journal of the American Statistical Association, ISSN 0162-1459, 04/2018, Volume 113, Issue 522, pp. 675 - 685
We introduce a Bayesian approach to predictive density calibration and combination that accounts for parameter uncertainty and model set incompleteness through... 
Forecast calibration | Bayesian nonparametrics | Posterior consistency | Forecast combination | Density forecast | PRICES | DENSITY-ESTIMATION | RISK | STATISTICS & PROBABILITY | INFERENCE | MIXTURES | MODELS | DIRICHLET PROCESSES | PROBABILITY FORECASTS
Journal Article
Journal of Computational and Applied Mathematics, ISSN 0377-0427, 12/2015, Volume 290, pp. 459 - 475
The use of approximate methods such as MCMC is widespread in Bayesian Analysis. Due to efficient and flexibility of those methods most of the literature in... 
Exact posterior distribution | Non-conjugate models | H-function | Special functions | Bayesian computation | MATHEMATICS, APPLIED | Algorithms | Approximation | Computation | Mathematical analysis | Mathematical models | Bayesian analysis | Flexibility | Convergence
Journal Article