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Monte Carlo methods / Statistical theory / Estimation theory / Markov chain Monte Carlo / Metropolis–Hastings algorithm / Maximum a posteriori estimation / Normal distribution / Random walk / Probability distribution / Statistics / Probability and statistics / Bayesian statistics


Monte Carlo sampling of solutions to inverse problems Klaus Mosegaard Niels Bohr Institute for Astronomy, Physics and Geophysics, Copenhagen
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Document Date: 2004-10-25 00:36:05

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Company

Knudsen / /

Facility

Klaus Mosegaard Niels Bohr Institute / /

IndustryTerm

search method / maximum likelihood solution / travel times / inefficient algorithm / thermodynamic energy / simulated annealing algorithm / possible solutions / likely solution / exhaustive search / local search / search methods / inefficient algorithms / energy / /

OperatingSystem

Fermi / /

Organization

Klaus Mosegaard Niels Bohr Institute for Astronomy / Physics and Geophysics / Copenhagen Albert Tarantola Institut de Physique / /

Person

Koren / Albert Tarantola / Chapman / Cary / /

Position

model data uncertainties / random walker / /

Product

Samsung Gravity 3 Cellular Phone / Metropolis / /

PublishedMedium

Journal of Geophysical Research / /

Technology

sampling algorithm / Geophysics / Multistep Iterations An algorithm / simulated annealing algorithm / dom / extremely inefficient algorithms / Metropolis algorithm / /

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