Results 31 to 40 of about 182,801 (272)
Efficient Gibbs Sampling for Markov Switching GARCH Models [PDF]
, 2012 We develop efficient simulation techniques for Bayesian inference on switching GARCH models. Our contribution to existing literature is manifold. First, we discuss different multi-move sampling techniques for Markov Switching (MS) state space models with
Billio, Monica +2 more
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Fast algorithms for band-limited extrapolation by over sampling and Fourier series
EURASIP Journal on Advances in Signal Processing, 2023 In this paper, fast algorithms for the extrapolation of band-limited signals are presented by the sampling theorem and Fourier series in the case of over sampling. Assume the band-limited signal is known in a finite interval. We update the signal outside
Weidong Chen
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PhyloGibbs: a Gibbs sampling motif finder that incorporates phylogeny.
PLoS Computational Biology, 2005 A central problem in the bioinformatics of gene regulation is to find the binding sites for regulatory proteins. One of the most promising approaches toward identifying these short and fuzzy sequence patterns is the comparative analysis of orthologous ...
Rahul Siddharthan +2 more
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Gibbs Sampling gives Quantum Advantage at Constant Temperatures with O(1)-Local Hamiltonians [PDF]
QuantumSampling from Gibbs states – states corresponding to system in thermal equilibrium – has recently been shown to be a task for which quantum computers are expected to achieve super-polynomial speed-up compared to classical computers, provided the locality
Joel Rajakumar, James D. Watson
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Jurnal Matematika Integratif, 2022 Parameter dari suatu distribusi biasanya belum diketahui nilainya, untuk mengetahuinya dilakukan estimasi terhadap parameter tersebut. Metode estimasi parameter ada dua macam, yaitu metode klasik dan metode Bayesian.
Rahmayanti Putri Desiresta +2 more
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Improved techniques for sampling complex pedigrees with the Gibbs sampler
Genetics Selection Evolution, 2007 Markov chain Monte Carlo (MCMC) methods have been widely used to overcome computational problems in linkage and segregation analyses. Many variants of this approach exist and are practiced; among the most popular is the Gibbs sampler.
Fernando Rohan L +2 more
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Near-Optimal Detection in MIMO Systems using Gibbs Sampling [PDF]
, 2009 In this paper we study a Markov Chain Monte Carlo (MCMC) Gibbs sampler for solving the integer least-squares problem. In digital communication the problem is equivalent to performing Maximum Likelihood (ML) detection in Multiple-Input Multiple-Output ...
Dimakis, Alexandros G. +3 more
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Empirical Bayes Gibbs sampling [PDF]
Biostatistics, 2001 The wide applicability of Gibbs sampling has increased the use of more complex and multi-level hierarchical models. To use these models entails dealing with hyperparameters in the deeper levels of a hierarchy. There are three typical methods for dealing with these hyperparameters: specify them, estimate them, or use a 'flat' prior.
openaire +3 more sources
Posterior analysis of stochastic frontier models using Gibbs sampling [PDF]
, 1992 In this paper we describe the use of Gibbs sampling methods for making posterior inferences in stochastic frontier models with composed error. We show how the Gibbs sampler can greatly reduce the computational difficulties involved in analyzing such ...
Koop, Gary +2 more
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On Bayesian Estimation in Mixed Linear Models Using the Gibbs Sampler [PDF]
المجلة العراقية للعلوم الاحصائية, 2008 This paper tackles the estimation of parameters of linear mixed random effect one–classification model by Bayesian technique which includes Gibbs sampling. Gibbs sampling is a special case of Monte Carlo Method which uses Markov Chain and so called MCMC (
doaj +1 more source