Search results for "102"

showing 10 items of 2892 documents

On 1-Laplacian Elliptic Equations Modeling Magnetic Resonance Image Rician Denoising

2015

Modeling magnitude Magnetic Resonance Images (MRI) rician denoising in a Bayesian or generalized Tikhonov framework using Total Variation (TV) leads naturally to the consideration of nonlinear elliptic equations. These involve the so called $1$-Laplacian operator and special care is needed to properly formulate the problem. The rician statistics of the data are introduced through a singular equation with a reaction term defined in terms of modified first order Bessel functions. An existence theory is provided here together with other qualitative properties of the solutions. Remarkably, each positive global minimum of the associated functional is one of such solutions. Moreover, we directly …

Statistics and ProbabilityFOS: Computer and information sciencesComputer scienceNoise reductionComputer Vision and Pattern Recognition (cs.CV)Bayesian probabilityComputer Science - Computer Vision and Pattern Recognition02 engineering and technology01 natural sciencesTikhonov regularizationsymbols.namesakeMathematics - Analysis of PDEsOperator (computer programming)Rician fading0202 electrical engineering electronic engineering information engineeringFOS: MathematicsApplied mathematicsMathematics - Numerical Analysis0101 mathematicsApplied Mathematics010102 general mathematicsNumerical Analysis (math.NA)Condensed Matter PhysicsNonlinear systemModeling and Simulationsymbols020201 artificial intelligence & image processingGeometry and TopologyComputer Vision and Pattern RecognitionLaplace operatorBessel functionAnalysis of PDEs (math.AP)
researchProduct

Multivariate nonparametric estimation of the Pickands dependence function using Bernstein polynomials

2017

Abstract Many applications in risk analysis require the estimation of the dependence among multivariate maxima, especially in environmental sciences. Such dependence can be described by the Pickands dependence function of the underlying extreme-value copula. Here, a nonparametric estimator is constructed as the sample equivalent of a multivariate extension of the madogram. Shape constraints on the family of Pickands dependence functions are taken into account by means of a representation in terms of Bernstein polynomials. The large-sample theory of the estimator is developed and its finite-sample performance is evaluated with a simulation study. The approach is illustrated with a dataset of…

Statistics and ProbabilityFOS: Computer and information sciencesMultivariate statisticsNONPARAMETRIC ESTIMATIONMULTIVARIATE MAX-STABLE DISTRIBUTION01 natural sciencesCopula (probability theory)Methodology (stat.ME)010104 statistics & probabilityStatisticsStatistics::Methodology0101 mathematicsExtreme-value copulaEXTREMAL DEPENDENCEEXTREMEVALUE COPULA[SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces environmentStatistics - MethodologyComputingMilieux_MISCELLANEOUSMathematics[SDU.OCEAN]Sciences of the Universe [physics]/Ocean AtmosphereApplied Mathematics010102 general mathematicsNonparametric statisticsEstimatorExtremal dependenceHEAVY RAINFALLBernstein polynomialBERNSTEIN POLYNOMIALS EXTREMAL DEPENDENCE EXTREMEVALUE COPULA HEAVY RAINFALL NONPARAMETRIC ESTIMATION MULTIVARIATE MAX-STABLE DISTRIBUTION PICKANDS DEPENDENCE FUNCTION13. Climate actionDependence functionStatistics Probability and UncertaintyMaximaSettore SECS-S/01 - StatisticaBERNSTEIN POLYNOMIALSPICKANDS DEPENDENCE FUNCTION
researchProduct

Importance sampling correction versus standard averages of reversible MCMCs in terms of the asymptotic variance

2017

We establish an ordering criterion for the asymptotic variances of two consistent Markov chain Monte Carlo (MCMC) estimators: an importance sampling (IS) estimator, based on an approximate reversible chain and subsequent IS weighting, and a standard MCMC estimator, based on an exact reversible chain. Essentially, we relax the criterion of the Peskun type covariance ordering by considering two different invariant probabilities, and obtain, in place of a strict ordering of asymptotic variances, a bound of the asymptotic variance of IS by that of the direct MCMC. Simple examples show that IS can have arbitrarily better or worse asymptotic variance than Metropolis-Hastings and delayed-acceptanc…

Statistics and ProbabilityFOS: Computer and information sciencesdelayed-acceptanceMarkovin ketjut01 natural sciencesStatistics - Computationasymptotic variance010104 statistics & probabilitysymbols.namesake60J22 65C05unbiased estimatorFOS: MathematicsApplied mathematics0101 mathematicsComputation (stat.CO)stokastiset prosessitestimointiMathematicsnumeeriset menetelmätpseudo-marginal algorithmApplied Mathematics010102 general mathematicsProbability (math.PR)EstimatorMarkov chain Monte CarloCovarianceInfimum and supremumWeightingMarkov chain Monte CarloMonte Carlo -menetelmätDelta methodimportance samplingModeling and SimulationBounded functionsymbolsImportance samplingMathematics - Probability
researchProduct

Rough linear PDE's with discontinuous coefficients - existence of solutions via regularization by fractional Brownian motion

2020

We consider two related linear PDE's perturbed by a fractional Brownian motion. We allow the drift to be discontinuous, in which case the corresponding deterministic equation is ill-posed. However, the noise will be shown to have a regularizing effect on the equations in the sense that we can prove existence of solutions for almost all paths of the fractional Brownian motion.

Statistics and ProbabilityFractional Brownian motion010102 general mathematicsMathematical analysisProbability (math.PR)fractional Brownian motionlocal times01 natural sciencesRegularization (mathematics)VDP::Matematikk og Naturvitenskap: 400::Matematikk: 410010104 statistics & probabilityDeterministic equation60H05FOS: Mathematics60H1560J5560H1060G220101 mathematicsStatistics Probability and Uncertaintystochastic PDEsrough pathsregularization by noiseMathematics - ProbabilityMathematics
researchProduct

Sharp dimension free quantitative estimates for the Gaussian isoperimetric inequality

2017

We provide a full quantitative version of the Gaussian isoperimetric inequality: the difference between the Gaussian perimeter of a given set and a half-space with the same mass controls the gap between the norms of the corresponding barycenters. In particular, it controls the Gaussian measure of the symmetric difference between the set and the half-space oriented so to have the barycenter in the same direction of the set. Our estimate is independent of the dimension, sharp on the decay rate with respect to the gap and with optimal dependence on the mass.

Statistics and ProbabilityGaussianGaussian isoperimetric inequality01 natural sciencesPerimeterSet (abstract data type)symbols.namesakeMathematics - Analysis of PDEsDimension (vector space)quantitative isoperimetric inequalityFOS: MathematicsMathematics::Metric Geometry0101 mathematicsSymmetric differenceGaussian isoperimetric inequalityQuantitative estimatesMathematics010102 general mathematicsMathematical analysisProbability (math.PR)49Q20Gaussian measure010101 applied mathematicssymbolsHigh Energy Physics::Experiment60E15Statistics Probability and UncertaintyMathematics - ProbabilityAnalysis of PDEs (math.AP)
researchProduct

A Galton–Watson process with a threshold

2016

Abstract In this paper we study a special class of size dependent branching processes. We assume that for some positive integer K as long as the population size does not exceed level K, the process evolves as a discrete-time supercritical branching process, and when the population size exceeds level K, it evolves as a subcritical or critical branching process. It is shown that this process does die out in finite time T. The question of when the mean value E(T) is finite or infinite is also addressed.

Statistics and ProbabilityGeneral MathematicsPopulation size010102 general mathematicsMean valueProcess (computing)01 natural sciencesGalton–Watson processBranching (linguistics)010104 statistics & probabilityIntegerStatistical physics0101 mathematicsStatistics Probability and UncertaintyFinite timeMathematicsBranching processJournal of Applied Probability
researchProduct

Modular Structures on Trace Class Operators and Applications to Landau Levels

2009

The energy levels, generally known as the Landau levels, which characterize the motion of an electron in a constant magnetic field, are those of the one-dimensional harmonic oscillator, with each level being infinitely degenerate. We show in this paper how the associated von Neumann algebra of observables displays a modular structure in the sense of the Tomita–Takesaki theory, with the algebra and its commutant referring to the two orientations of the magnetic field. A Kubo–Martin–Schwinger state can be built which, in fact, is the Gibbs state for an ensemble of harmonic oscillators. Mathematically, the modular structure is shown to arise as the natural modular structure associated with the…

Statistics and ProbabilityGeneral Physics and AstronomyFOS: Physical sciencesGibbs state01 natural sciencessymbols.namesake0103 physical sciences0101 mathematics010306 general physicsSettore MAT/07 - Fisica MatematicaHarmonic oscillatorMathematical PhysicsMathematical physicsPhysicsNuclear operatorMathematics::Operator AlgebrasLandau level010102 general mathematicsDegenerate energy levelsHilbert spaceStatistical and Nonlinear PhysicsObservableLandau quantizationMathematical Physics (math-ph)Von Neumann algebraModeling and Simulationsymbolsmodular structure
researchProduct

A differential-geometric approach to generalized linear models with grouped predictors

2016

We propose an extension of the differential-geometric least angle regression method to perform sparse group inference in a generalized linear model. An efficient algorithm is proposed to compute the solution curve. The proposed group differential-geometric least angle regression method has important properties that distinguish it from the group lasso. First, its solution curve is based on the invariance properties of a generalized linear model. Second, it adds groups of variables based on a group equiangularity condition, which is shown to be related to score statistics. An adaptive version, which includes weights based on the Kullback-Leibler divergence, improves its variable selection fea…

Statistics and ProbabilityGeneralized linear modelStatistics::TheoryMathematical optimizationProper linear modelGeneral MathematicsORACLE PROPERTIESGeneralized linear modelSPARSITYGeneralized linear array model01 natural sciencesGeneralized linear mixed modelCONSISTENCY010104 statistics & probabilityScore statistic.LEAST ANGLE REGRESSIONLinear regressionESTIMATORApplied mathematicsDifferential geometry0101 mathematicsDivergence (statistics)MathematicsVariance functionDifferential-geometric least angle regressionPATH ALGORITHMApplied MathematicsLeast-angle regressionScore statistic010102 general mathematicsAgricultural and Biological Sciences (miscellaneous)Group lassoGROUP SELECTIONStatistics Probability and UncertaintyGeneral Agricultural and Biological SciencesSettore SECS-S/01 - Statistica
researchProduct

p-harmonic coordinates for Hölder metrics and applications

2017

We show that on any Riemannian manifold with H¨older continuous metric tensor, there exists a p-harmonic coordinate system near any point. When p = n this leads to a useful gauge condition for regularity results in conformal geometry. As applications, we show that any conformal mapping between manifolds having C α metric tensors is C 1+α regular, and that a manifold with W1,n ∩ C α metric tensor and with vanishing Weyl tensor is locally conformally flat if n ≥ 4. The results extend the works [LS14, LS15] from the case of C 1+α metrics to the H¨older continuous case. In an appendix, we also develop some regularity results for overdetermined elliptic systems in divergence form. peerReviewed

Statistics and ProbabilityHarmonic coordinatesSmoothness (probability theory)010102 general mathematicsMathematical analysista111p-harmonic coordinatesHölder metrics01 natural sciencesGeometry and Topology0101 mathematicsStatistics Probability and UncertaintyAnalysisMathematicsCommunications in Analysis and Geometry
researchProduct

The smallest singular value of a shifted $d$-regular random square matrix

2017

We derive a lower bound on the smallest singular value of a random d-regular matrix, that is, the adjacency matrix of a random d-regular directed graph. Specifically, let $$C_1<d< c n/\log ^2 n$$ and let $$\mathcal {M}_{n,d}$$ be the set of all $$n\times n$$ square matrices with 0 / 1 entries, such that each row and each column of every matrix in $$\mathcal {M}_{n,d}$$ has exactly d ones. Let M be a random matrix uniformly distributed on $$\mathcal {M}_{n,d}$$ . Then the smallest singular value $$s_{n} (M)$$ of M is greater than $$n^{-6}$$ with probability at least $$1-C_2\log ^2 d/\sqrt{d}$$ , where c, $$C_1$$ , and $$C_2$$ are absolute positive constants independent of any other parameter…

Statistics and ProbabilityIdentity matrixAdjacency matrices01 natural sciencesSquare matrixCombinatorics010104 statistics & probabilityMatrix (mathematics)Mathematics::Algebraic GeometryFOS: MathematicsMathematics - Combinatorics60B20 15B52 46B06 05C80Adjacency matrix0101 mathematicsCondition numberCondition numberMathematicsRandom graphsRandom graphLittlewood–Offord theorySingularity010102 general mathematicsProbability (math.PR)InvertibilityRegular graphsSingular valueSmallest singular valueAnti-concentrationSingular probabilitySparse matricesCombinatorics (math.CO)Statistics Probability and UncertaintyRandom matricesRandom matrixMathematics - ProbabilityAnalysis
researchProduct