The following pages link to (Q4828566):
Displaying 50 items.
- Multivariate dependence analysis via tree copula models: an application to one-year forward energy contracts (Q1749519) (← links)
- Efficient strategy for the Markov chain Monte Carlo in high-dimension with heavy-tailed target probability distribution (Q1750100) (← links)
- Complex-valued Bayesian parameter estimation via Markov chain Monte Carlo (Q1750426) (← links)
- Computationally efficient multivariate spatio-temporal models for high-dimensional count-valued data (with discussion) (Q1752017) (← links)
- The ABC of simulation estimation with auxiliary statistics (Q1754514) (← links)
- A model for analyzing spatially correlated binary data clustered in uncorrelated lattices (Q1756181) (← links)
- Joining and splitting models with Markov melding (Q1757664) (← links)
- Objective Bayesian analysis for Gaussian hierarchical models with intrinsic conditional autoregressive priors (Q1757670) (← links)
- Computational advances for and from Bayesian analysis (Q1766319) (← links)
- A quasi-Bayesian perspective to online clustering (Q1786586) (← links)
- Approximate models and robust decisions (Q1790356) (← links)
- Leave Pima Indians alone: binary regression as a benchmark for Bayesian computation (Q1790387) (← links)
- Specification tests based on MCMC output (Q1792489) (← links)
- Redefining the maximum sustainable yield for the Schaefer population model including multiplicative environmental noise (Q1797403) (← links)
- Estimating discrete Markov models from various incomplete data schemes (Q1927036) (← links)
- Simulated annealing for higher dimensional projection depth (Q1927183) (← links)
- Optimal scaling and diffusion limits for the Langevin algorithm in high dimensions (Q1931320) (← links)
- A Bayesian study for the comparison of generalized gamma model with its components (Q1936427) (← links)
- Statistical data analysis of the 1995 Ebola outbreak in the democratic republic of Congo (Q1944282) (← links)
- Adaptive Gibbs samplers and related MCMC methods (Q1948684) (← links)
- Quantitative approximations of evolving probability measures and sequential Markov chain Monte Carlo methods (Q1950384) (← links)
- Adaptive-modal Bayesian nonparametric regression (Q1950891) (← links)
- Construction of weakly CUD sequences for MCMC sampling (Q1951767) (← links)
- Bayesian adaptive B-spline estimation in proportional hazards frailty models (Q1952074) (← links)
- Penalized wavelets: embedding wavelets into semiparametric regression (Q1952243) (← links)
- Credit portfolios, credibility theory, and dynamic empirical Bayes (Q1952686) (← links)
- Information driven search for point sources of gamma radiation (Q1957245) (← links)
- Classification of linear and non-linear modulations using the Baum-Welch algorithm and MCMC methods (Q1957930) (← links)
- Monte Carlo methods in Bayesian computation (Q1968817) (← links)
- Bayesian model selection in the \(\mathcal{M}\)-open setting -- approximate posterior inference and subsampling for efficient large-scale leave-one-out cross-validation via the difference estimator (Q1981162) (← links)
- Non-parametric stochastic subset optimization for reliability-based importance ranking of bridges in transportation networks (Q1985208) (← links)
- A Bayesian inference for the penalized spline joint models of longitudinal and time-to-event data: a prior sensitivity analysis (Q1985373) (← links)
- Generation and application of multivariate polynomial quadrature rules (Q1986197) (← links)
- Goal-oriented adaptive surrogate construction for stochastic inversion (Q1986228) (← links)
- Uncertainty estimation in equality-constrained MAP and maximum likelihood estimation with applications to system identification and state estimation (Q1987286) (← links)
- Fast sampling of parameterised Gaussian random fields (Q1987947) (← links)
- Multiple parameter determination in textile material design: a Bayesian inference approach based on simulation (Q1997121) (← links)
- Weak convergence and optimal tuning of the reversible jump algorithm (Q1997557) (← links)
- A Metropolis-Hastings-within-Gibbs sampler for nonlinear hierarchical-Bayesian inverse problems (Q2001214) (← links)
- Approximate Bayesian computational methods for the inference of unknown parameters (Q2001254) (← links)
- Deep UQ: learning deep neural network surrogate models for high dimensional uncertainty quantification (Q2002273) (← links)
- Emulation of CPU-demanding reactive transport models: a comparison of Gaussian processes, polynomial chaos expansion, and deep neural networks (Q2009855) (← links)
- A robust solution of a statistical inverse problem in multiscale computational mechanics using an artificial neural network (Q2020855) (← links)
- The statistical finite element method (statFEM) for coherent synthesis of observation data and model predictions (Q2022037) (← links)
- Fast sampling from \(\beta \)-ensembles (Q2029088) (← links)
- Ensemble Kalman inversion: mean-field limit and convergence analysis (Q2029092) (← links)
- Convergence rates for optimised adaptive importance samplers (Q2029096) (← links)
- Finite mixtures of multivariate scale-shape mixtures of skew-normal distributions (Q2029226) (← links)
- Pricing discretely-monitored double barrier options with small probabilities of execution (Q2029343) (← links)
- Safe adaptive importance sampling: a mixture approach (Q2039792) (← links)
