Search results for "Markov Chain Monte Carlo"

showing 10 items of 79 documents

Updated determination of the solar neutrino fluxes from solar neutrino data

2016

Journal of High Energy Physics 2016.3 (2016): 132 reproduced by permission of Scuola Internazionale Superiore di Studi Avanzati (SISSA)

Normalization (statistics)Particle physicsNuclear and High Energy PhysicsSolar and atmospheric neutrinosSolar neutrinoAstrophysics::High Energy Astrophysical PhenomenaBayesian probabilityPosterior probabilitySolar neutrinosFOS: Physical sciences7. Clean energy01 natural sciencesHigh Energy Physics - Experimentsymbols.namesakeHigh Energy Physics - Experiment (hep-ex)High Energy Physics - Phenomenology (hep-ph)Neutrins solars0103 physical sciencesAstrophysics::Solar and Stellar Astrophysics010306 general physicsNeutrino oscillationSolar and Stellar Astrophysics (astro-ph.SR)Physics010308 nuclear & particles physicsParticle physicsFísicaMarkov chain Monte CarloNeutrino physicsHigh Energy Physics - PhenomenologyDistribution functionAstrophysics - Solar and Stellar Astrophysics13. Climate actionPhysics::Space PhysicssymbolsAstrophysics::Earth and Planetary AstrophysicsNeutrinoFísica de partícules
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Multivariate exponential smoothing: A Bayesian forecast approach based on simulation

2009

This paper deals with the prediction of time series with correlated errors at each time point using a Bayesian forecast approach based on the multivariate Holt-Winters model. Assuming that each of the univariate time series comes from the univariate Holt-Winters model, all of them sharing a common structure, the multivariate Holt-Winters model can be formulated as a traditional multivariate regression model. This formulation facilitates obtaining the posterior distribution of the model parameters, which is not analytically tractable: simulation is needed. An acceptance sampling procedure is used in order to obtain a sample from this posterior distribution. Using Monte Carlo integration the …

Numerical AnalysisMultivariate statisticsGeneral Computer ScienceApplied MathematicsUnivariateMarkov chain Monte CarloTheoretical Computer ScienceNormal-Wishart distributionsymbols.namesakeUnivariate distributionModeling and SimulationStatisticssymbolsMultivariate t-distributionBayesian linear regressionGibbs samplingMathematicsMathematics and Computers in Simulation
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An Ordinal Joint Model for Breast Cancer

2017

We propose a Bayesian joint model to analyze the association between longitudinal measurements of an ordinal marker and time to a relevant event. The longitudinal process is defined in terms of a proportional-odds cumulative logit model and the time-to-event process through a left-truncated Cox proportional hazards model with information of the longitudinal marker and baseline covariates. Both longitudinal and survival processes are connected by a common vector of random effects.

Oncologymedicine.medical_specialtyProportional hazards modelComputer scienceBayesian probabilityPosterior probabilityMarkov chain Monte CarloRandom effects modelmedicine.diseasesymbols.namesakeBreast cancerInternal medicineCovariateStatisticsmedicinesymbolsEvent (probability theory)
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How to relax the cosmological neutrino mass bound

2019

We study the impact of non-standard momentum distributions of cosmic neutrinos on the anisotropy spectrum of the cosmic microwave background and the matter power spectrum of the large scale structure. We show that the neutrino distribution has almost no unique observable imprint, as it is almost entirely degenerate with the effective number of neutrino flavours, $N_{\mathrm{eff}}$, and the neutrino mass, $m_{\nu}$. Performing a Markov chain Monte Carlo analysis with current cosmological data, we demonstrate that the neutrino mass bound heavily depends on the assumed momentum distribution of relic neutrinos. The message of this work is simple and has to our knowledge not been pointed out cle…

Particle physicsCosmology and Nongalactic Astrophysics (astro-ph.CO)cosmological neutrinosPhysics::Instrumentation and DetectorsAstrophysics::High Energy Astrophysical PhenomenaCosmic microwave backgroundFOS: Physical sciencesAstrophysics::Cosmology and Extragalactic Astrophysicscosmological parameters from LSS01 natural sciencesCosmologyMomentumsymbols.namesakeHigh Energy Physics - Phenomenology (hep-ph)cosmological0103 physical sciencesPhysicsCOSMIC cancer database010308 nuclear & particles physicsMatter power spectrumHigh Energy Physics::Phenomenologycosmological parameters from CMBRAstronomy and AstrophysicsObservableMarkov chain Monte Carloneutrino masses from cosmologyHigh Energy Physics - Phenomenologyparameters from CMBRsymbolsHigh Energy Physics::ExperimentNeutrinoAstrophysics - Cosmology and Nongalactic Astrophysics
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$\texttt{HEPfit}$: a Code for the Combination of Indirect and Direct Constraints on High Energy Physics Models

2020

The European physical journal / C Particles and fields C80(5), 456 (2020). doi:10.1140/epjc/s10052-020-7904-z

Physics and Astronomy (miscellaneous)Physics beyond the Standard ModelMonte Carlo methoddoublet: 2 [Higgs particle]Parameter space01 natural sciencesMonte Carlo: Markov chainHigh Energy Physics - ExperimentHigh Energy Physics - Experiment (hep-ex)effective field theoryHigh Energy Physics - Phenomenology (hep-ph)[PHYS.HEXP]Physics [physics]/High Energy Physics - Experiment [hep-ex]Statistical physicsStandard model (cryptography)Physicsnew physicsHiggs particle: doublet: 2statistical analysis: BayesianObservablehep-phHigh Energy Physics - PhenomenologysymbolsParticle Physics - Experimentcorrection: obliqueBayesian probabilityFOS: Physical scienceslcsh:AstrophysicsMarkov chain [Monte Carlo]Bayesian [statistical analysis]530programmingSet (abstract data type)oblique [correction]symbols.namesake0103 physical scienceslcsh:QB460-466operator: dimension: 6ddc:530lcsh:Nuclear and particle physics. Atomic energy. Radioactivity010306 general physicsnumerical calculationsEngineering (miscellaneous)Particle Physics - Phenomenology010308 nuclear & particles physicshep-exMarkov chain Monte Carlomanual[PHYS.HPHE]Physics [physics]/High Energy Physics - Phenomenology [hep-ph]lcsh:QC770-798dimension: 6 [operator]
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Equation of State for Macromolecules of Variable Flexibility in Good Solvents: A Comparison of Techniques for Monte Carlo Simulations of Lattice Mode…

2007

The osmotic equation of state for the athermal bond fluctuation model on the simple cubic lattice is obtained from extensive Monte Carlo simulations. For short macromolecules (chain length N=20) we study the influence of various choices for the chain stiffness on the equation of state. Three techniques are applied and compared in order to critically assess their efficiency and accuracy: the repulsive wall method, the thermodynamic integration method (which rests on the feasibility of simulations in the grand canonical ensemble), and the recently advocated sedimentation equilibrium method, which records the density profile in an external (e.g. gravitation-like) field and infers, via a local …

Physics010304 chemical physicsQuantum Monte CarloMonte Carlo methodFOS: Physical sciencesMarkov chain Monte CarloCondensed Matter - Soft Condensed Matter01 natural sciences3. Good healthHybrid Monte CarloCondensed Matter::Soft Condensed Mattersymbols.namesakeGrand canonical ensemble0103 physical sciencessymbolsDynamic Monte Carlo methodSoft Condensed Matter (cond-mat.soft)Monte Carlo method in statistical physicsStatistical physics010306 general physicsMonte Carlo molecular modeling
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Simple sampling Monte Carlo methods

2005

PhysicsComputer scienceMonte Carlo methodSampling (statistics)Markov chain Monte CarloHybrid Monte Carlosymbols.namesakeSimple (abstract algebra)symbolsDynamic Monte Carlo methodMonte Carlo integrationMonte Carlo method in statistical physicsQuasi-Monte Carlo methodStatistical physicsMonte Carlo molecular modeling
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More on importance sampling Monte Carlo methods for lattice systems

2009

PhysicsHybrid Monte Carlosymbols.namesakeMonte Carlo methodsymbolsDynamic Monte Carlo methodMarkov chain Monte CarloMonte Carlo method in statistical physicsMonte Carlo integrationStatistical physicsQuasi-Monte Carlo methodImportance samplingMonte Carlo molecular modeling
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Monte Carlo Markov Chain DEM reconstruction of isothermal plasmas

2012

In this paper, we carry out tests on the Monte Carlo Markov Chain (MCMC) technique with the aim of determining: 1) its ability to retrieve isothermal plasmas from a set of spectral line intensities, with and without random noise; 2) to what extent can it discriminate between an isothermal solution and a narrow multithermal distribution; and 3) how well it can detect multiple isothermal components along the line of sight. We also test the effects of 4) atomic data uncertainties on the results, and 5) the number of ions whose lines are available for the DEM reconstruction. We find that the MCMC technique is unable to retrieve isothermal plasmas to better than Delta log T = 0.05. Also, the DEM…

PhysicsLine-of-sightGaussianmethods: data analysis techniques: spectroscopic Sun: corona Sun: UV radiationFOS: Physical sciencesAstronomy and AstrophysicsMarkov chain Monte CarloPlasmaAstrophysicsSpectral lineIsothermal processComputational physicsIondata analysis techniques: spectroscopic Sun: corona Sun: UV radiation [methods]symbols.namesakeDistribution (mathematics)Settore FIS/05 - Astronomia E AstrofisicaAstrophysics - Solar and Stellar AstrophysicsSpace and Planetary SciencesymbolsSolar and Stellar Astrophysics (astro-ph.SR)
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Chain length dependence of the state diagram of a single stiff-chain macromolecule: Theory and Monte Carlo simulation

2003

We present a Monte Carlo computer simulation and theoretical results for the dependence of the state diagram of a single semiflexible chain on the chain length. The calculated transition lines between different structures in the state diagrams for both studied chain lengths N=40 and N=80 can be described by theoretical predictions which include chain length dependence explicitly. The stability criteria of different structures are discussed. The theoretically predicted exponent in the dependence of the toroid size on the chain length is compatible with computer simulation results.

PhysicsQuantum Monte CarloMonte Carlo methodGeneral Physics and AstronomyMarkov chain Monte CarloHybrid Monte Carlosymbols.namesakeDynamic Monte Carlo methodsymbolsKinetic Monte CarloParallel temperingStatistical physicsPhysical and Theoretical ChemistryMonte Carlo molecular modelingThe Journal of Chemical Physics
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