Search results for " statistics"

showing 10 items of 1891 documents

On singular integral and martingale transforms

2007

Linear equivalences of norms of vector-valued singular integral operators and vector-valued martingale transforms are studied. In particular, it is shown that the UMD(p)-constant of a Banach space X equals the norm of the real (or the imaginary) part of the Beurling-Ahlfors singular integral operator, acting on the X-valued L^p-space on the plane. Moreover, replacing equality by a linear equivalence, this is found to be the typical property of even multipliers. A corresponding result for odd multipliers and the Hilbert transform is given.

46B09General Mathematics46B20 (Secondary)Banach space42B15 (Primary) 42B2001 natural sciencesUpper and lower bounds010104 statistics & probabilitysymbols.namesakeCorollary60G46; 42B15 (Primary) 42B20; 46B09; 46B20 (Secondary)Classical Analysis and ODEs (math.CA)FOS: Mathematics60G460101 mathematicsMathematicsNormed vector spaceDiscrete mathematicsApplied MathematicsProbability (math.PR)010102 general mathematicsSingular integralSingular valueMathematics - Classical Analysis and ODEssymbolsHilbert transformMartingale (probability theory)Mathematics - ProbabilityTransactions of the American Mathematical Society
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Constraining Uncertainty in Projected Gross Primary Production With Machine Learning

2020

The terrestrial biosphere is currently slowing down global warming by absorbing about 30% of human emissions of carbon dioxide (CO2). The largest flux of the terrestrial carbon uptake is gross primary production (GPP) defined as the production of carbohydrates by photosynthesis. Elevated atmospheric CO2 concentration is expected to increase GPP (“CO2 fertilization effect”). However, Earth system models (ESMs) exhibit a large range in simulated GPP projections. In this study, we combine an existing emergent constraint on CO2 fertilization with a machine learning approach to constrain the spatial variations of multimodel GPP projections. In a first step, we use observed changes in the CO2 sea…

551.6Atmospheric Science010504 meteorology & atmospheric sciencesComputer scienceSoil ScienceAquatic Science01 natural sciences7. Clean energy010104 statistics & probabilityEconometricsErdsystemmodell -Evaluation und -Analyse[MATH]Mathematics [math]0101 mathematics0105 earth and related environmental sciencesWater Science and TechnologyEcologyEarth System ModelsPaleontologyPrimary productionmodelingForestryGross Primary Production15. Life on landCMIPFuture Climate Projections13. Climate actionEnvironmental scienceJournal of Geophysical Research: Biogeosciences
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Rough McKean-Vlasov dynamics for robust ensemble Kalman filtering

2021

Motivated by the challenge of incorporating data into misspecified and multiscale dynamical models, we study a McKean-Vlasov equation that contains the data stream as a common driving rough path. This setting allows us to prove well-posedness as well as continuity with respect to the driver in an appropriate rough-path topology. The latter property is key in our subsequent development of a robust data assimilation methodology: We establish propagation of chaos for the associated interacting particle system, which in turn is suggestive of a numerical scheme that can be viewed as an extension of the ensemble Kalman filter to a rough-path framework. Finally, we discuss a data-driven method bas…

60L20 60L90 60H10 60F99 65C35 62M05Probability (math.PR)FOS: MathematicsMathematics - Statistics TheoryMathematics - Numerical AnalysisNumerical Analysis (math.NA)Statistics Theory (math.ST)Mathematics - Probability
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Separation of uncorrelated stationary time series using autocovariance matrices

2014

Blind source separation (BSS) is a signal processing tool, which is widely used in various fields. Examples include biomedical signal separation, brain imaging and economic time series applications. In BSS, one assumes that the observed $p$ time series are linear combinations of $p$ latent uncorrelated weakly stationary time series. The aim is then to find an estimate for an unmixing matrix, which transforms the observed time series back to uncorrelated latent time series. In SOBI (Second Order Blind Identification) joint diagonalization of the covariance matrix and autocovariance matrices with several lags is used to estimate the unmixing matrix. The rows of an unmixing matrix can be deriv…

62H05 62H10Asymptotic Normality ; Blind Source Separation ; Joint Diagonalization ; Linear Process ; SobiFOS: MathematicsMathematics - Statistics TheoryStatistics Theory (math.ST)
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On the stability of some controlled Markov chains and its applications to stochastic approximation with Markovian dynamic

2015

We develop a practical approach to establish the stability, that is, the recurrence in a given set, of a large class of controlled Markov chains. These processes arise in various areas of applied science and encompass important numerical methods. We show in particular how individual Lyapunov functions and associated drift conditions for the parametrized family of Markov transition probabilities and the parameter update can be combined to form Lyapunov functions for the joint process, leading to the proof of the desired stability property. Of particular interest is the fact that the approach applies even in situations where the two components of the process present a time-scale separation, w…

65C05FOS: Computer and information sciencesStatistics and ProbabilityLyapunov functionStability (learning theory)Markov processContext (language use)Mathematics - Statistics Theorycontrolled Markov chainsStatistics Theory (math.ST)Stochastic approximation01 natural sciencesMethodology (stat.ME)010104 statistics & probabilitysymbols.namesake60J05stochastic approximationFOS: MathematicsComputational statisticsApplied mathematics60J220101 mathematicsStatistics - MethodologyMathematicsSequenceMarkov chain010102 general mathematicsStability Markov chainssymbolsStatistics Probability and Uncertaintyadaptive Markov chain Monte Carlo
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Coupled conditional backward sampling particle filter

2020

The conditional particle filter (CPF) is a promising algorithm for general hidden Markov model smoothing. Empirical evidence suggests that the variant of CPF with backward sampling (CBPF) performs well even with long time series. Previous theoretical results have not been able to demonstrate the improvement brought by backward sampling, whereas we provide rates showing that CBPF can remain effective with a fixed number of particles independent of the time horizon. Our result is based on analysis of a new coupling of two CBPFs, the coupled conditional backward sampling particle filter (CCBPF). We show that CCBPF has good stability properties in the sense that with fixed number of particles, …

65C05FOS: Computer and information sciencesStatistics and ProbabilityunbiasedMarkovin ketjutTime horizonStatistics - Computation01 natural sciencesStability (probability)backward sampling65C05 (Primary) 60J05 65C35 65C40 (secondary)010104 statistics & probabilityconvergence rateFOS: MathematicsApplied mathematics0101 mathematicscouplingHidden Markov model65C35Computation (stat.CO)Mathematicsstokastiset prosessitBackward samplingSeries (mathematics)Probability (math.PR)Sampling (statistics)conditional particle filterMonte Carlo -menetelmätRate of convergence65C6065C40numeerinen analyysiStatistics Probability and UncertaintyParticle filterMathematics - ProbabilitySmoothing
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From Feynman–Kac formulae to numerical stochastic homogenization in electrical impedance tomography

2016

In this paper, we use the theory of symmetric Dirichlet forms to derive Feynman–Kac formulae for the forward problem of electrical impedance tomography with possibly anisotropic, merely measurable conductivities corresponding to different electrode models on bounded Lipschitz domains. Subsequently, we employ these Feynman–Kac formulae to rigorously justify stochastic homogenization in the case of a stochastic boundary value problem arising from an inverse anomaly detection problem. Motivated by this theoretical result, we prove an estimate for the speed of convergence of the projected mean-square displacement of the underlying process which may serve as the theoretical foundation for the de…

65C05Statistics and Probability65N21stochastic homogenizationquantitative convergence result01 natural sciencesHomogenization (chemistry)78M40general reflecting diffusion process010104 statistics & probabilitysymbols.namesakeFeynman–Kac formula60J4535Q60Applied mathematicsFeynman diagramBoundary value problemSkorohod decomposition0101 mathematicsElectrical impedance tomographyBrownian motionMathematicsrandom conductivity field65N75010102 general mathematicsFeynman–Kac formulaLipschitz continuityBounded functionstochastic forward problemsymbols60J55Statistics Probability and Uncertainty60H30electrical impedance tomographyThe Annals of Applied Probability
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"Table 7" of "Measurement of the differential cross-section of highly boosted top quarks as a function of their transverse momentum in $\sqrt{s}$ = 8…

2016

Correlation matrix between the bins of the particle-level differential cross-section as a function of $p_{T,ptcl}$.

8000.0educationfood and beveragesTopAstrophysics::Cosmology and Extragalactic AstrophysicsPhysics::Data Analysis; Statistics and ProbabilityP P --> TOP TOPBAR Xbody regionsInclusiveSingle Differential Cross SectionProton-Proton Scatteringnatural sciencesDSIG/DPTTransverse Momentum Dependence
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Field rules and bias in random surveys with quota samples : an assessment of CIS surveys

2018

Surveys applying quota sampling in their final step are widely used in opinion and market research all over the world. This is also the case in Spain, where the surveys carried out by CIS (a public institution for sociological research supported by the government) have become a point of reference. The rules used by CIS to select individuals within quotas, however, could be improved as they lead to biases in age distributions. Analysing more than 545,000 responses collected in the 220 monthly barometers conducted between 1997 and 2016 by CIS, we compare the empirical distributions of the barometers with the expected distributions from the sample design and/or target populations. Among other …

:62 Statistics [Classificació AMS]Fieldwork rulesQuota samplingInter-quota distributions:Matemàtiques i estadística::Estadística matemàtica [Àrees temàtiques de la UPC]Age and gender groups62D05Centre for Sociological Research quota sampling fieldwork rules age and gender groups inter-quota distributions intra-quota distributionsCentre for sociological research:62 Statistics::62D05 Sampling theory sample surveys [Classificació AMS]Intra-quota distributions
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Roadmap on optical rogue waves and extreme events

2016

Nail Akhmediev et al. ; 38 págs.; 28 figs.

:Ciències de la visió::Òptica física [Àrees temàtiques de la UPC]extreme eventsNonlinear opticsFreak-wavesProcess (engineering)Subject (philosophy)Supercontinuum generationPeregrine soliton01 natural sciences010309 opticsOptics0103 physical sciencesZero-dispersion wavelength[NLIN]Nonlinear Sciences [physics]Rogue wave010306 general physicsModulation instabilityComputingMilieux_MISCELLANEOUSPhysicsÒptica no lineal:Física [Àrees temàtiques de la UPC]Nonlinear schrodinger-equationbusiness.industryGinzburg-Landau equationnonlinear opticsRogue wavesOptical rogue wavesrogue wavesextreme events; nonlinear optics; rogue wavesExtreme eventsValue statisticsAtomic and Molecular Physics and OpticsElectronic Optical and Magnetic MaterialsVariety (cybernetics)Photonic crystal fibersWork (electrical)Noise-like pulsesPeregrine solitonbusinessScientific terminology
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