A subsampling approach for Bayesian model selection
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Publication:2105562
DOI10.1016/j.ijar.2022.08.018OpenAlexW4295528345MaRDI QIDQ2105562
Aliaksandr Hubin, Jon Lachmann, Geir Storvik, Florian Frommlet
Publication date: 8 December 2022
Published in: International Journal of Approximate Reasoning (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2201.13198
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- A Stochastic Quasi-Newton Method for Large-Scale Optimization
- The pseudo-marginal approach for efficient Monte Carlo computations
- Convergence of adaptive and interacting Markov chain Monte Carlo algorithms
- Estimating the dimension of a model
- Mode jumping MCMC for Bayesian variable selection in GLMM
- Quantitative bounds on convergence of time-inhomogeneous Markov chains
- Optimal predictive model selection.
- Subsampling MCMC -- an introduction for the survey statistician
- Random optimization
- Mode Jumping Proposals in MCMC
- Approximate Bayesian Inference for Latent Gaussian models by using Integrated Nested Laplace Approximations
- Marginal Likelihood from the Gibbs Output
- Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images
- Accurate Approximations for Posterior Moments and Marginal Densities
- Minimization by Random Search Techniques
- On the existence and uniqueness of the maximum likelihood estimates for certain generalized linear models
- Prediction Via Orthogonalized Model Mixing
- Optimization Methods for Large-Scale Machine Learning
- The Fitting of Power Series, Meaning Polynomials, Illustrated on Band-Spectroscopic Data
- An Iterative Technique for Absolute Deviations Curve Fitting
- Bayes Factors
- Bayesian Model Selection and Statistical Modeling
- A Stochastic Approximation Method
- On Stochastic Limit and Order Relationships