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Found 4 papers, 0 papers with code
Geometric Ergodicity in Modified Variations of Riemannian Manifold and Lagrangian Monte Carlo
Unlike Euclidean Hamiltonian Monte Carlo (EHMC) and the Metropolis-adjusted Langevin algorithm (MALA), the geometric ergodicity of these Riemannian algorithms has not been extensively studied.
Analyzing Relevance Vector Machines using a single penalty approach
Currently in the literature, the sufficient conditions for posterior propriety of RVM do not allow improper priors over the multiple penalty parameters.
Block Gibbs samplers for logistic mixed models: convergence properties and a comparison with full Gibbs samplers
The logistic linear mixed model (LLMM) is one of the most widely used statistical models.
Data Augmentation
Methodology
60J05, 62-08
Model Based Screening Embedded Bayesian Variable Selection for Ultra-high Dimensional Settings
We develop a Bayesian variable selection method, called SVEN, based on a hierarchical Gaussian linear model with priors placed on the regression coefficients as well as on the model space.
Methodology Computation
