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The Annals of Statistics, ISSN 0090-5364, 6/2003, Volume 31, Issue 3, pp. 705 - 741
Journal Article
IEEE Transactions on Signal Processing, ISSN 1053-587X, 06/2015, Volume 63, Issue 12, pp. 3123 - 3138
Journal Article
Journal of Machine Learning Research, ISSN 1532-4435, 03/2016, Volume 17
The Gibbs sampler is one of the most popular algorithms for inference in statistical models. In this paper, we introduce a herding variant of this algorithm,... 
Gibbs sampling | Herding | Deterministic sampling | deterministic sampling | herding | AUTOMATION & CONTROL SYSTEMS | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Journal Article
Bernoulli, ISSN 1350-7265, 08/2015, Volume 21, Issue 3, pp. 1855 - 1883
The particle Gibbs sampler is a Markov chain Monte Carlo (MCMC) algorithm to sample from the full posterior distribution of a state-space model. It does so by... 
Feynman-Kac formulae | Particle filtering | Sequential Monte Carlo | Gibbs sampling | Particle Markov chain Monte Carlo | sequential Monte Carlo | MONTE-CARLO METHODS | FILTER | particle Markov chain Monte Carlo | particle filtering | STATISTICS & PROBABILITY | Statistics - Computation | Statistics | Mathematics | Feynman–Kac formulae
Journal Article
Psychonomic Bulletin & Review, ISSN 1069-9384, 02/2018, Volume 25, Issue 1, pp. 143 - 154
Journal Article
Journal of Statistical Computation and Simulation, ISSN 0094-9655, 11/2011, Volume 81, Issue 11, pp. 1565 - 1578
Journal Article
1999, 1, MIT Press Books, ISBN 0262112388, Volume 1, xii, 297
Both state-space models and Markov switching models have been highly productive paths for empirical research in macroeconomics and finance. This book presents... 
Economics | Sampling (Statistics) | Mathematical models | State-space methods | Econometrics | Heteroscedasticity | regime switching; gibbs-sampling; posterior distributions; likelihood function
Book
IEEE Transactions on Signal Processing, ISSN 1053-587X, 06/2017, Volume 65, Issue 11, pp. 2814 - 2827
Journal Article
Annals of Applied Probability, ISSN 1050-5164, 06/2018, Volume 28, Issue 3, pp. 1793 - 1820
We describe the distribution of frequencies ordered by sample values in a random sample of size n from the two parameter GEM(alpha, theta) random discrete... 
Size-biased order | Species sampling | GEM distribution | Chinese restaurant construction | Random exchangeable partition | Gibbs’ partitions | PRIORS | ALLELES | REPRESENTATION | STATISTICS & PROBABILITY | DISTRIBUTIONS | Gibbs' partitions | random exchangeable partition | REVERSIBILITY | size-biased order | AGE
Journal Article
Computers and Geosciences, ISSN 0098-3004, 02/2018, Volume 111, pp. 190 - 199
Gibbs sampling is routinely used to sample truncated Gaussian distributions. These distributions naturally occur when associating latent Gaussian fields to... 
Gaussian Markov random fields | GMRF | Gibbs sampling | Truncated Gaussian | Category field | COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS | GEOSCIENCES, MULTIDISCIPLINARY | MARKOV RANDOM-FIELDS | SUBJECT | CONDITIONAL SIMULATION
Journal Article
Annals of Applied Probability, ISSN 1050-5164, 04/2018, Volume 28, Issue 2, pp. 1099 - 1135
The goal of importance sampling is to estimate the expected value of a given function with respect to a probability measure v using a random sample of size n... 
Gibbs measure | Monte Carlo methods | Importance sampling | Phase transition | STATISTICS & PROBABILITY | MONTE-CARLO METHODS | phase transition
Journal Article
Journal of Artificial Intelligence Research, ISSN 1076-9757, 01/2007, Volume 28, pp. 1 - 48
The paper presents a new sampling methodology for Bayesian networks that samples only a subset of variables and applies exact inference to the rest. Cutset... 
MONTE-CARLO | GRAPHICAL MODELS | MARKOV-CHAINS | GIBBS SAMPLER | EXPERT-SYSTEMS | BELIEF NETWORKS | PROBABILISTIC INFERENCE | DIRICHLET PROCESS PRIOR | SEQUENTIAL IMPUTATIONS | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | CONVERGENCE-RATES | Computer Science - Artificial Intelligence
Journal Article
Communications in Statistics - Simulation and Computation, ISSN 0361-0918, 01/2007, Volume 36, Issue 1, pp. 45 - 54
We provide a new approach to the sampling of the well known mixture of Dirichlet process model. Recent attention has focused on retention of the random... 
Slice sampling | Bayesian nonparametrics | Density estimation | Gibbs sampler | Primary 62G99, 62F15 | Dirichlet process | Secondary 65C60 | PRIORS | DISTRIBUTIONS | HIERARCHICAL-MODELS | CONJUGATE | STATISTICS & PROBABILITY | slice sampling | density estimation | BAYESIAN-ANALYSIS | CHAIN MONTE-CARLO
Journal Article
BMC Bioinformatics, ISSN 1471-2105, 10/2015, Volume 16, Issue 14, p. S6
Background: Even for moderate size inputs, there are a tremendous number of optimal rearrangement scenarios, regardless what the model is and which specific... 
Gibbs sampling | Computational complexity | Genome rearrangement | Single cut or join | BIOTECHNOLOGY & APPLIED MICROBIOLOGY | SORTING SIGNED PERMUTATIONS | BIOCHEMICAL RESEARCH METHODS | MATHEMATICAL & COMPUTATIONAL BIOLOGY | DOUBLE CUT | TREE | SCJ | Models, Genetic | Software | Genome | Gene Rearrangement | Humans | Evolution, Molecular
Journal Article
The Journal of Physical Chemistry B, ISSN 1520-6106, 08/2012, Volume 116, Issue 34, pp. 10342 - 10356
Journal Article
by Hamm, K
PROCEEDINGS OF THE EDINBURGH MATHEMATICAL SOCIETY, ISSN 0013-0915, 11/2019, Volume 62, Issue 4, pp. 1163 - 1171
We investigate the Gibbs-Wilbraham phenomenon for generalized sampling series, and related interpolation series arising from cardinal functions. We prove the... 
CARDINAL INTERPOLATION | MATHEMATICS | Gibbs phenomenon | generalized sampling kernels | cardinal functions | sampling expansions | Sampling | Interpolation
Journal Article
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