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An Introduction to MCMC for Machine Learning [PDF]
Machine Learning, 2003 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Christophe Andrieu +3 more
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Globally Centered Autocovariances in MCMC [PDF]
Journal of Computational and Graphical Statistics, 2022 Autocovariances are a fundamental quantity of interest in Markov chain Monte Carlo (MCMC) simulations with autocorrelation function (ACF) plots being an integral visualization tool for performance assessment. Unfortunately, for slow-mixing Markov chains, the empirical autocovariance can highly underestimate the truth.
Medha Agarwal, Dootika Vats
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TI-Stan: Adaptively Annealed Thermodynamic Integration with HMC †
Proceedings, 2019 We present a novel implementation of the adaptively annealed thermodynamic integration technique using Hamiltonian Monte Carlo (HMC). Thermodynamic integration with importance sampling and adaptive annealing is an especially useful method for estimating ...
R. Wesley Henderson, Paul M. Goggans
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MCMC and GLMs for estimating regression parameters: Evidence from non-life Egyptian insurance sector [PDF]
Journal of Humanities and Applied Social Sciences, 2019 Purpose – The purpose of this study is to estimate the linear regression parameters using two alternative techniques. First technique is to apply the generalized linear model (GLM) and the second technique is the Markov Chain Monte Carlo (MCMC) method ...
Mahmoud ELsayed, Amr Soliman
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CoRR, 2014 Markov Chain Monte Carlo (MCMC) algorithms are a workhorse of probabilistic modeling and inference, but are difficult to debug, and are prone to silent failure if implemented naively. We outline several strategies for testing the correctness of MCMC algorithms.
Roger B. Grosse +1 more
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An MCMC approach to classical estimation [PDF]
Journal of Econometrics, 2003 This is an archival version of the article "An MCMC approach to classical estimation", Journal of econometrics 115 (2), August 2003, pages 293-346. This version does not reflect the corrections made to the article during the publication process; it contains additional two remarks added, as indicated in the text.
Chernozhukov, Victor, Hong, Han
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Open Physics, 2017 The coefficient of variation [CV] has several applications in applied statistics. So in this paper, we adopt Bayesian and non-Bayesian approaches for the estimation of CV under type-II censored data from extension exponential distribution [EED].
Bakoban Rana A.
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MCMC genome rearrangement [PDF]
Bioinformatics, 2003 Abstract Motivation: As more and more genomes have been sequenced, genomic data is rapidly accumulating. Genome-wide mutations are believed more neutral than local mutations such as substitutions, insertions and deletions, therefore phylogenetic investigations based on inversions, transpositions and inverted transpositions are less ...
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A Classical and Bayesian Approach for Parameter Estimation in Structural Equation Models
Journal of New Theory, 2020 Structural Equation Models (SEMs) with latent variables provide a general framework for modelling relationships in multivariate data. Although SEMs are most commonly used in studies involving intrinsically latent variables, such as happiness, quality of ...
Naci Murat, Mehmet Ali Cengiz
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Nuevo Itinerario, 2021 The article that we present here is part of a research / extension process that lasted for more than two years in the Puna and Chaco of Salta, in northern Argentina, with significant interaction with the Kolla de Hurcuro and Wichí de El peoples.
Facundo Gonzalez
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