Parallel multivariate slice sampling

DOI10.1007/s11222-010-9178-zzbMath1253.60082OpenAlexW2027235634MaRDI QIDQ1927292

John C. Liechty, Murali Haran, Matthew M. Tibbits

Publication date: 31 December 2012

Published in: Statistics and Computing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11222-010-9178-z

zbMATH Keywords

Gaussian processesMarkov chain Monte Carloparallel computingadaptive Markov chain Monte Carloslice samplingspatial model\texttt{Cuda}\texttt{ScaLAPACK}

Mathematics Subject Classification ID

Computational methods in Markov chains (60J22) Linear regression; mixed models (62J05) Markov processes: estimation; hidden Markov models (62M05) Parallel algorithms in computer science (68W10)

Related Items (6)

SIMD parallel MCMC sampling with applications for big-data Bayesian analytics ⋮ Graphics processing units and high-dimensional optimization ⋮ Quantitative spectral gap estimate and Wasserstein contraction of simple slice sampling ⋮ Particle MCMC algorithms and architectures for accelerating inference in state-space models ⋮ Parallel statistical computing for statistical inference ⋮ Unnamed Item

Uses Software

• ScaLAPACK
• CUDA
• PLAPACK
• spBayes

Cites Work

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• ScaLAPACK: A portable linear algebra library for distributed memory computers -- design issues and performance
• An introduction to MCMC for machine learning
• Slice sampling. (With discussions and rejoinder)
• The polar slice sampler
• Practical Markov Chain Monte Carlo
• Gibbs Sampling for Bayesian Non-Conjugate and Hierarchical Models by Using Auxiliary Variables
• Convergence of Slice Sampler Markov Chains
• Covariance structure of the Gibbs sampler with applications to the comparisons of estimators and augmentation schemes
• Efficiency and Convergence Properties of Slice Samplers
• Fixed and Random Effects Selection in Linear and Logistic Models

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