Search results for "Numerical Analysis"

showing 10 items of 883 documents

Attractors for non-autonomous retarded lattice dynamical systems

2015

AbstractIn this paperwe study a non-autonomous lattice dynamical system with delay. Under rather general growth and dissipative conditions on the nonlinear term,we define a non-autonomous dynamical system and prove the existence of a pullback attractor for such system as well. Both multivalued and single-valued cases are considered.

Statistics and ProbabilityDifferential equations with delayDynamical systems theoryNon-autonomous systemslattice dynamical systemsPullback attractorHamiltonian systemLinear dynamical systemProjected dynamical systemAttractorQA1-939pullback attractorMathematicsNumerical AnalysisApplied MathematicsMathematical analysisdifferential equations with delaynon-autonomous systemsClassical mechanicsLattice dynamical systemsPullback attractorset-valued dynamical systemsSet-valued dynamical systemsLimit setRandom dynamical systemMathematicsAnalysis
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On the use of asymptotic expansion in computing the null distribution of page's L-statistic

1989

Suppose that each out of n randomized complete blocks is obtained by observing a jointly continuous random variable taking values in Rk. Page's L-statistic is given then as a sum of i.i.d. lattice variables with finite moments of any order. Applying a well-known theorem on asymptotic expansions for the distribution function of such a sum yields higher order approximations to the significance probability of any observed value of L. The formula obtained by discarding terms smaller than o(n –1) is still very simple to use. Yet, due to it's strong analytical basis, it can be expected to provide substantial improvement on the traditional normal approximation. The results of extensive numerical i…

Statistics and ProbabilityDistribution functionApproximation errorModeling and SimulationLattice (order)Numerical analysisStatisticsNull distributionAsymptotic expansionRandom variableStatisticMathematicsCommunications in Statistics - Simulation and Computation
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Symmetrised M-estimators of multivariate scatter

2007

AbstractIn this paper we introduce a family of symmetrised M-estimators of multivariate scatter. These are defined to be M-estimators only computed on pairwise differences of the observed multivariate data. Symmetrised Huber's M-estimator and Dümbgen's estimator serve as our examples. The influence functions of the symmetrised M-functionals are derived and the limiting distributions of the estimators are discussed in the multivariate elliptical case to consider the robustness and efficiency properties of estimators. The symmetrised M-estimators have the important independence property; they can therefore be used to find the independent components in the independent component analysis (ICA).

Statistics and ProbabilityElliptical distributionInfluence functionMultivariate statisticsNumerical AnalysisEstimatorEfficiencyM-estimatorM-estimatorIndependent component analysisEfficient estimatorScatter matrixScatter matrixMathematics::Category TheoryStatisticsApplied mathematicsStatistics Probability and UncertaintyRobustnessElliptical distributionIndependence (probability theory)MathematicsJournal of Multivariate Analysis
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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)
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DRHotNet: An R package for detecting differential risk hotspots on a linear network

2019

One of the most common applications of spatial data analysis is detecting zones, at a certain investigation level, where a point-referenced event under study is especially concentrated. The detection of this kind of zones, which are usually referred to as hotspots, is essential in certain fields such as criminology, epidemiology or traffic safety. Traditionally, hotspot detection procedures have been developed over areal units of analysis. Although working at this spatial scale can be suitable enough for many research or practical purposes, detecting hotspots at a more accurate level (for instance, at the road segment level) may be more convenient sometimes. Furthermore, it is typical that …

Statistics and ProbabilityMethodology (stat.ME)FOS: Computer and information sciencesNumerical AnalysisApplications (stat.AP)Statistics Probability and UncertaintyStatistics - ComputationStatistics - ApplicationsComputation (stat.CO)Statistics - Methodology
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An Extended Filament Based Lamellipodium Model Produces Various Moving Cell Shapes in the Presence of Chemotactic Signals

2015

The Filament Based Lamellipodium Model (FBLM) is a two-phase two-dimensional continuum model, describing the dynamcis of two interacting families of locally parallel actin filaments (C.Schmeiser and D.Oelz, How do cells move? Mathematical modeling of cytoskeleton dynamics and cell migration. Cell mechanics: from single scale-based models to multiscale modeling. Chapman and Hall, 2010). It contains accounts of the filaments' bending stiffness, of adhesion to the substrate, and of cross-links connecting the two families. An extension of the model is presented with contributions from nucleation of filaments by branching, from capping, from contraction by actin-myosin interaction, and from a pr…

Statistics and ProbabilityNucleationNanotechnologymacromolecular substancesMyosinsBranching (polymer chemistry)Models BiologicalGeneral Biochemistry Genetics and Molecular BiologyPolymerizationQuantitative Biology::Cell BehaviorProtein filamentQuantitative Biology::Subcellular ProcessesCell Behavior (q-bio.CB)CoulombAnimalsComputer SimulationPseudopodiaCytoskeletonCell ShapeActinPhysicsGeneral Immunology and MicrobiologyApplied MathematicsChemotaxisChemotaxisNumerical Analysis Computer-AssistedGeneral Medicine92C17Actin CytoskeletonClassical mechanicsModeling and SimulationFOS: Biological sciencesQuantitative Biology - Cell BehaviorLamellipodiumGeneral Agricultural and Biological SciencesSignal Transduction
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Parallel Construction and Query of Index Data Structures for Pattern Matching on Square Matrices

1999

AbstractWe describe fast parallel algorithms for building index data structures that can be used to gather various statistics on square matrices. The main data structure is the Lsuffix tree, which is a generalization of the classical suffix tree for strings. Given ann×ntext matrixA, we build our data structures inO(logn) time withn2processors on a CRCW PRAM, so that we can quickly processAin parallel as follows: (i) report some statistical information aboutA, e.g., find the largest repeated square submatrices that appear at least twice inAor determine, for each position inA, the smallest submatrix that occurs only there; (ii) given, on-line, anm×mpattern matrixPAT, check whether it occurs i…

Statistics and ProbabilityNumerical AnalysisControl and OptimizationAlgebra and Number TheoryApplied MathematicsGeneral MathematicsSuffix treeParallel algorithmData structureSquare matrixSquare (algebra)law.inventionTree (data structure)lawPattern matchingAlgorithmMathematicsData compressionJournal of Complexity
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A matrix-valued Bernoulli distribution

2006

AbstractMatrix-valued distributions are used in continuous multivariate analysis to model sample data matrices of continuous measurements; their use seems to be neglected for binary, or more generally categorical, data. In this paper we propose a matrix-valued Bernoulli distribution, based on the log-linear representation introduced by Cox [The analysis of multivariate binary data, Appl. Statist. 21 (1972) 113–120] for the Multivariate Bernoulli distribution with correlated components.

Statistics and ProbabilityNumerical AnalysisDISCRETEMODELSMatrix t-distributionMultivariate normal distributionMatrix-valued distributionsBINARYNormal-Wishart distributionBinomial distributionBernoulli distributionCategorical distributionStatisticsApplied mathematicsBernoulli processStatistics Probability and UncertaintyCorrelated multivariate binary responsesMathematicsMultivariate stable distributionMultivariate Bernoulli distributionJournal of Multivariate Analysis
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Asymptotics for pooled marginal slicing estimator based on SIRα approach

2005

Pooled marginal slicing (PMS) is a semiparametric method, based on sliced inverse regression (SIR) approach, for achieving dimension reduction in regression problems when the outcome variable y and the regressor x are both assumed to be multidimensional. In this paper, we consider the SIR"@a version (combining the SIR-I and SIR-II approaches) of the PMS estimator and we establish the asymptotic distribution of the estimated matrix of interest. Then the asymptotic normality of the eigenprojector on the estimated effective dimension reduction (e.d.r.) space is derived as well as the asymptotic distributions of each estimated e.d.r. direction and its corresponding eigenvalue.

Statistics and ProbabilityNumerical AnalysisDimensionality reductionStatisticsSliced inverse regressionAsymptotic distributionEstimatorRegression analysisStatistics Probability and UncertaintyMarginal distributionEffective dimensionEigenvalues and eigenvectorsMathematicsJournal of Multivariate Analysis
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Measure differential inclusions: existence results and minimum problems

2020

AbstractWe focus on a very general problem in the theory of dynamic systems, namely that of studying measure differential inclusions with varying measures. The multifunction on the right hand side has compact non-necessarily convex values in a real Euclidean space and satisfies bounded variation hypotheses with respect to the Pompeiu excess (and not to the Hausdorff-Pompeiu distance, as usually in literature). This is possible due to the use of interesting selection principles for excess bounded variation set-valued mappings. Conditions for the minimization of a generic functional with respect to a family of measures generated by equiregulated left-continuous, nondecreasing functions and to…

Statistics and ProbabilityNumerical AnalysisEuclidean spaceApplied MathematicsRegular polygonMeasure (mathematics)Differential inclusionSettore MAT/05 - Analisi MatematicaBounded variationTrajectoryApplied mathematicsGeometry and TopologyMinificationFocus (optics)Measure differential inclusion Bounded variation Pompeiu excess Selection Minimality conditionAnalysisMathematics
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