Search results for "Dimension"

showing 10 items of 2766 documents

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)
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Extended differential geometric LARS for high-dimensional GLMs with general dispersion parameter

2018

A large class of modeling and prediction problems involves outcomes that belong to an exponential family distribution. Generalized linear models (GLMs) are a standard way of dealing with such situations. Even in high-dimensional feature spaces GLMs can be extended to deal with such situations. Penalized inference approaches, such as the $$\ell _1$$ or SCAD, or extensions of least angle regression, such as dgLARS, have been proposed to deal with GLMs with high-dimensional feature spaces. Although the theory underlying these methods is in principle generic, the implementation has remained restricted to dispersion-free models, such as the Poisson and logistic regression models. The aim of this…

Statistics and ProbabilityGeneralized linear modelMathematical optimizationGeneralized linear modelsPredictor-€“corrector algorithmGeneralized linear model02 engineering and technologyPoisson distributionDANTZIG SELECTOR01 natural sciencesCross-validationHigh-dimensional inferenceTheoretical Computer Science010104 statistics & probabilitysymbols.namesakeExponential familyLEAST ANGLE REGRESSION0202 electrical engineering electronic engineering information engineeringApplied mathematicsStatistics::Methodology0101 mathematicsCROSS-VALIDATIONMathematicsLeast-angle regressionLinear model020206 networking & telecommunicationsProbability and statisticsVARIABLE SELECTIONEfficient estimatorPredictor-corrector algorithmComputational Theory and MathematicsDispersion paremeterLINEAR-MODELSsymbolsSHRINKAGEStatistics Probability and UncertaintySettore SECS-S/01 - StatisticaStatistics and Computing
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Weighting Elementary Prices in Consumer Price Index Construction Using Spatial Autocorrelation

2013

The Consumer Price Indexes (CPI) are used in current economic systems to measure inflation. When constructing CPIs, however, official institutions have systematically overlooked the spatial dimension of elementary prices. Ignoring the fact that prices are collected at geographical locations implicitly implies considering prices as spatially independent, when in fact they are not. To solve this problem, this article proposes to weight basic price data by taking into account the spatial correlation they display. The weighted geometric and arithmetic means suggested generalize and improve the simple geometric and arithmetic means currently in use.

Statistics and ProbabilityInflationComputer Science::Computer Science and Game TheorySpatial correlationmedia_common.quotation_subjectWeightingPrice indexStatisticsEconometricsConsumer price indexDimension (data warehouse)Spatial analysisArithmetic meanmedia_commonMathematicsCommunications in Statistics - Theory and Methods
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Vortex length, vortex energy and fractal dimension of superfluid turbulence at very low temperature

2010

By assuming a self-similar structure for Kelvin waves along vortex loops with successive smaller scale features, we model the fractal dimension of a superfluid vortex tangle in the zero temperature limit. Our model assumes that at each step the total energy of the vortices is conserved, but the total length can change. We obtain a relation between the fractal dimension and the exponent describing how the vortex energy per unit length changes with the length scale. This relation does not depend on the specific model, and shows that if smaller length scales make a decreasing relative contribution to the energy per unit length of vortex lines, the fractal dimension will be higher than unity. F…

Statistics and ProbabilityLength scalePhysicsfractal dimensionScale (ratio)TurbulenceFOS: Physical sciencesGeneral Physics and AstronomyStatistical and Nonlinear PhysicsMechanicsFractal dimensionSuperfluid turbulenceVortexCondensed Matter - Other Condensed MatterSuperfluiditysymbols.namesakeModeling and SimulationsymbolsKelvin waveScalingSettore MAT/07 - Fisica MatematicaMathematical PhysicsOther Condensed Matter (cond-mat.other)vortice
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Generalized Symmetry Models for Hypercubic Concordance Tables

2000

Summary Frequency data obtained classifying a sample of 'units' by the same categorical variable repeatedly over 'components', can be arranged in a hypercubic concordance table (h.c.t.). This kind of data naturally arises in a number of different areas such as longitudinal studies, studies using matched and clustered data, item-response analysis, agreement analysis. In spite of the substantial diversity of the mechanisms that can generate them, data arranged in a h.c.t. can all be analyzed via models of symmetry and quasi-symmetry, which exploit the special structure of the h.c.t. The paper extends the definition of such models to any dimension, introducing the class of generalized symmetry…

Statistics and ProbabilityLongitudinal dataItem-response analysiStructure (category theory)InferenceClass (philosophy)Statistical modelClusteringAgreementAlgebraGeneralized symmetry modelMatchingDimension (data warehouse)Statistical theoryStatistics Probability and UncertaintySettore SECS-S/01 - StatisticaLikelihood functionCategorical variableAlgorithmMathematicsInternational Statistical Review / Revue Internationale de Statistique
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Fractal eigenstates in disordered systems

1990

Abstract The wave functions of the non-interacting electrons in disordered systems described by a tight-binding model with site-diagonal disorder are investigated by means of the inverse participation ratio. The wave functions are shown to be fractal objects. In three-dimensional samples, a critical fractal dimension can be defined for the mobility edge in the band centre, which yields the mobility edge trajectory in the whole energy range in good agreement with previous calculations based on the investigation of the exponentially decaying transmission coefficient.

Statistics and ProbabilityMathematical analysisInverseElectronCondensed Matter PhysicsFractal dimensionsymbols.namesakeFractalFractal derivativesymbolsTransmission coefficientStatistical physicsWave functionHamiltonian (quantum mechanics)MathematicsPhysica A: Statistical Mechanics and its Applications
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Multivariate GARCH estimation via a Bregman-proximal trust-region method

2011

The estimation of multivariate GARCH time series models is a difficult task mainly due to the significant overparameterization exhibited by the problem and usually referred to as the "curse of dimensionality". For example, in the case of the VEC family, the number of parameters involved in the model grows as a polynomial of order four on the dimensionality of the problem. Moreover, these parameters are subjected to convoluted nonlinear constraints necessary to ensure, for instance, the existence of stationary solutions and the positive semidefinite character of the conditional covariance matrices used in the model design. So far, this problem has been addressed in the literature only in low…

Statistics and ProbabilityMathematical optimizationPolynomialComputer scienceDiagonalComputational Finance (q-fin.CP)[QFIN.CP]Quantitative Finance [q-fin]/Computational Finance [q-fin.CP]FOS: Economics and businessQuantitative Finance - Computational FinanceDimension (vector space)0502 economics and business91G70 65C60050207 economicsMathematics050205 econometrics Trust regionStatistical Finance (q-fin.ST)Series (mathematics)Applied Mathematics05 social sciencesConstrained optimizationQuantitative Finance - Statistical Finance[QFIN.ST]Quantitative Finance [q-fin]/Statistical Finance [q-fin.ST]Computational MathematicsNonlinear systemComputational Theory and MathematicsParametrizationCurse of dimensionality
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STATIS and DISTATIS: optimum multitable principal component analysis and three way metric multidimensional scaling

2012

STATIS is an extension of principal component analysis PCA tailored to handle multiple data tables that measure sets of variables collected on the same observations, or, alternatively, as in a variant called dual-STATIS, multiple data tables where the same variables are measured on different sets of observations. STATIS proceeds in two steps: First it analyzes the between data table similarity structure and derives from this analysis an optimal set of weights that are used to compute a linear combination of the data tables called the compromise that best represents the information common to the different data tables; Second, the PCA of this compromise gives an optimal map of the observation…

Statistics and ProbabilityMathematical optimizationSimilarity (geometry)[STAT.TH]Statistics [stat]/Statistics Theory [stat.TH]Linear discriminant analysiscomputer.software_genre01 natural sciences[ STAT.TH ] Statistics [stat]/Statistics Theory [stat.TH]Correspondence analysisSet (abstract data type)010104 statistics & probability03 medical and health sciences0302 clinical medicine[MATH.MATH-ST]Mathematics [math]/Statistics [math.ST]Multiple factor analysisPrincipal component analysisMetric (mathematics)Data miningMultidimensional scaling[ MATH.MATH-ST ] Mathematics [math]/Statistics [math.ST]0101 mathematicscomputer030217 neurology & neurosurgeryComputingMilieux_MISCELLANEOUSMathematics
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Broken ray transform on a Riemann surface with a convex obstacle

2014

We consider the broken ray transform on Riemann surfaces in the presence of an obstacle, following earlier work of Mukhometov. If the surface has nonpositive curvature and the obstacle is strictly convex, we show that a function is determined by its integrals over broken geodesic rays that reflect on the boundary of the obstacle. Our proof is based on a Pestov identity with boundary terms, and it involves Jacobi fields on broken rays. We also discuss applications of the broken ray transform.

Statistics and ProbabilityMathematics - Differential GeometryGeodesicAstrophysics::High Energy Astrophysical PhenomenaBoundary (topology)Curvature01 natural sciencessymbols.namesakeMathematics - Analysis of PDEsFOS: Mathematics0101 mathematicsMathematicsRiemann surface010102 general mathematicsMathematical analysista111Regular polygonSurface (topology)boundary010101 applied mathematicsDifferential Geometry (math.DG)Obstaclesymbolstensor tomographyGeometry and TopologyStatistics Probability and UncertaintydimensionsConvex functionAnalysisAnalysis of PDEs (math.AP)
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Model selection in linear mixed-effect models

2019

Linear mixed-effects models are a class of models widely used for analyzing different types of data: longitudinal, clustered and panel data. Many fields, in which a statistical methodology is required, involve the employment of linear mixed models, such as biology, chemistry, medicine, finance and so forth. One of the most important processes, in a statistical analysis, is given by model selection. Hence, since there are a large number of linear mixed model selection procedures available in the literature, a pressing issue is how to identify the best approach to adopt in a specific case. We outline mainly all approaches focusing on the part of the model subject to selection (fixed and/or ra…

Statistics and ProbabilityMixed modelEconomics and EconometricsMathematical optimizationLinear mixed modelApplied MathematicsModel selectionMDLVariance (accounting)LASSOCovarianceGeneralized linear mixed modelMixed model selectionLasso (statistics)Shrinkage methodsModeling and SimulationMCPAICBICSettore SECS-S/01 - StatisticaSocial Sciences (miscellaneous)AnalysisSelection (genetic algorithm)Curse of dimensionality
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