Search results for "Online"

showing 10 items of 4526 documents

Analyzing Temperature Effects on Mortality Within theREnvironment: The Constrained Segmented Distributed Lag Parameterization

2010

Here we present and discuss the R package modTempEff including a set of functions aimed at modelling temperature effects on mortality with time series data. The functions fit a particular log linear model which allows to capture the two main features of mortality- temperature relationships: nonlinearity and distributed lag effect. Penalized splines and segmented regression constitute the core of the modelling framework. We briefly review the model and illustrate the functions throughout a simulated dataset.

Statistics and ProbabilityDistributed lagtemperature effects segmented relationship break point P-splines RMathematical optimizationComputer scienceP-splinesRsegmented relationshipSet (abstract data type)R packageNonlinear systemBreak pointApplied mathematicsLog-linear modelbreak pointStatistics Probability and UncertaintySegmented regressionTime seriesSettore SECS-S/01 - Statisticatemperature effectslcsh:Statisticslcsh:HA1-4737SoftwareJournal of Statistical Software
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Stochastic resonance and noise delayed extinction in a model of two competing species

2003

We study the role of the noise in the dynamics of two competing species. We consider generalized Lotka-Volterra equations in the presence of a multiplicative noise, which models the interaction between the species and the environment. The interaction parameter between the species is a random process which obeys a stochastic differential equation with a generalized bistable potential in the presence of a periodic driving term, which accounts for the environment temperature variation. We find noise-induced periodic oscillations of the species concentrations and stochastic resonance phenomenon. We find also a nonmonotonic behavior of the mean extinction time of one of the two competing species…

Statistics and ProbabilityExtinctionSettore FIS/02 - Fisica Teorica Modelli E Metodi MatematiciStatistical Mechanics (cond-mat.stat-mech)BistabilityStochastic resonanceStochastic processPopulations and Evolution (q-bio.PE)FOS: Physical sciencesStatistical mechanicStatistical and Nonlinear PhysicsPopulation dynamicNoise (electronics)Multiplicative noiseStochastic partial differential equationStochastic differential equationControl theoryFOS: Biological sciencesQuantitative Biology::Populations and EvolutionStatistical physicsNoise-induced effects.Quantitative Biology - Populations and EvolutionCondensed Matter - Statistical MechanicsMathematics
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Introducing libeemd: a program package for performing the ensemble empirical mode decomposition

2016

The ensemble empirical mode decomposition (EEMD) and its complete variant (CEEMDAN) are adaptive, noise-assisted data analysis methods that improve on the ordinary empirical mode decomposition (EMD). All these methods decompose possibly nonlinear and/or nonstationary time series data into a finite amount of components separated by instantaneous frequencies. This decomposition provides a powerful method to look into the different processes behind a given time series data, and provides a way to separate short time-scale events from a general trend. We present a free software implementation of EMD, EEMD and CEEMDAN and give an overview of the EMD methodology and the algorithms used in the deco…

Statistics and ProbabilityFOS: Computer and information sciences010504 meteorology & atmospheric sciencesComputer science0211 other engineering and technologies02 engineering and technology01 natural sciencesExtensibilityStatistics - ComputationHilbert–Huang transformSoftware implementationHilbert–Huang transformSannolikhetsteori och statistikTime seriesProbability Theory and StatisticsComputation (stat.CO)021101 geological & geomatics engineering0105 earth and related environmental sciencescomputer.programming_languagenoise-assisted data analysisintrinsic mode functionPython (programming language)adaptive data analysisComputational MathematicsNonlinear systemtime series analysisData analysisStatistics Probability and UncertaintyAlgorithmcomputerdetrendingHilbert-Huang transform; Intrinsic mode function; Time series analysis; Adaptive data analysis; Noise-assisted data analysis; Detrending
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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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Multiscale Granger causality

2017

In the study of complex physical and biological systems represented by multivariate stochastic processes, an issue of great relevance is the description of the system dynamics spanning multiple temporal scales. While methods to assess the dynamic complexity of individual processes at different time scales are well-established, multiscale analysis of directed interactions has never been formalized theoretically, and empirical evaluations are complicated by practical issues such as filtering and downsampling. Here we extend the very popular measure of Granger causality (GC), a prominent tool for assessing directed lagged interactions between joint processes, to quantify information transfer a…

Statistics and ProbabilityFOS: Computer and information sciencesMathematics - Statistics TheoryStatistics Theory (math.ST)01 natural sciencesStatistics - ApplicationsMethodology (stat.ME)03 medical and health sciences0302 clinical medicinegranger causalityGranger causalityMoving average0103 physical sciencesEconometricsFOS: MathematicsState spacecarbon dioxydeApplications (stat.AP)Time series010306 general physicsTemporal scalessignal processingclimateStatistics - MethodologyMathematicsStochastic processBiology and Life SciencestemperatureCondensed Matter PhysicsScience GeneralSystem dynamicsMathematics and StatisticsAutoregressive modelEarth and Environmental SciencesSettore ING-INF/06 - Bioingegneria Elettronica E InformaticaAlgorithm030217 neurology & neurosurgeryStatistical and Nonlinear Physic
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Comparative Evaluation of Community Detection Algorithms: A Topological Approach

2012

International audience; Community detection is one of the most active fields in complex networks analysis, due to its potential value in practical applications. Many works inspired by different paradigms are devoted to the development of algorithmic solutions allowing to reveal the network structure in such cohesive subgroups. Comparative studies reported in the literature usually rely on a performance measure considering the community structure as a partition (Rand Index, Normalized Mutual information, etc.). However, this type of comparison neglects the topological properties of the communities. In this article, we present a comprehensive comparative study of a representative set of commu…

Statistics and ProbabilityFOS: Computer and information sciencesPhysics - Physics and SocietyComputer science[INFO.INFO-OH]Computer Science [cs]/Other [cs.OH]Rand indexFOS: Physical sciences02 engineering and technologyPhysics and Society (physics.soc-ph)Topology01 natural sciencesMeasure (mathematics)010305 fluids & plasmasSet (abstract data type)Development (topology)0103 physical sciences0202 electrical engineering electronic engineering information engineeringEquivalence (measure theory)Random graphSocial and Information Networks (cs.SI)Computer Science - Social and Information NetworksStatistical and Nonlinear PhysicsNetwork dynamicsPartition (database)[ INFO.INFO-OH ] Computer Science [cs]/Other [cs.OH]020201 artificial intelligence & image processingStatistics Probability and Uncertainty
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Weak pseudo-bosons

2020

We show how the notion of {\em pseudo-bosons}, originally introduced as operators acting on some Hilbert space, can be extended to a distributional settings. In doing so, we are able to construct a rather general framework to deal with generalized eigenvectors of the multiplication and of the derivation operators. Connections with the quantum damped harmonic oscillator are also briefly considered.

Statistics and ProbabilityFOS: Physical sciencesGeneral Physics and Astronomy01 natural sciences010305 fluids & plasmassymbols.namesakeGeneralized eigenvector0103 physical sciences010306 general physicsQuantumSettore MAT/07 - Fisica MatematicaHarmonic oscillatorMathematical PhysicsMathematical physicsBosonPhysicsHilbert spaceStatistical and Nonlinear PhysicsMathematical Physics (math-ph)Construct (python library)non self-adjoint HamiltonianModeling and SimulationsymbolsBiorthogonal setMultiplicationpseudo-bosons
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Tridiagonality, supersymmetry and non self-adjoint Hamiltonians

2019

In this paper we consider some aspects of tridiagonal, non self-adjoint, Hamiltonians and of their supersymmetric counterparts. In particular, the problem of factorization is discussed, and it is shown how the analysis of the eigenstates of these Hamiltonians produce interesting recursion formulas giving rise to biorthogonal families of vectors. Some examples are proposed, and a connection with bi-squeezed states is analyzed.

Statistics and ProbabilityFOS: Physical sciencesGeneral Physics and Astronomy01 natural sciencesFactorization0103 physical sciences010306 general physicsSettore MAT/07 - Fisica MatematicaMathematical PhysicsEigenvalues and eigenvectorsMathematicsQuantum PhysicsTridiagonal matrix010308 nuclear & particles physicsRecursion (computer science)Statistical and Nonlinear Physicstridiagonal matriceMathematical Physics (math-ph)SupersymmetryConnection (mathematics)non self-adjoint HamiltonianAlgebrabiorthogonal basesModeling and SimulationBiorthogonal systemQuantum Physics (quant-ph)Self-adjoint operatorJournal of Physics A: Mathematical and Theoretical
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Rare events and scaling properties in field-induced anomalous dynamics

2012

We show that, in a broad class of continuous time random walks (CTRW), a small external field can turn diffusion from standard into anomalous. We illustrate our findings in a CTRW with trapping, a prototype of subdiffusion in disordered and glassy materials, and in the L\'evy walk process, which describes superdiffusion within inhomogeneous media. For both models, in the presence of an external field, rare events induce a singular behavior in the originally Gaussian displacements distribution, giving rise to power-law tails. Remarkably, in the subdiffusive CTRW, the combined effect of highly fluctuating waiting times and of a drift yields a non-Gaussian distribution characterized by long sp…

Statistics and ProbabilityField (physics)GaussianFOS: Physical sciencesQuantitative Biology::Cell Behaviorsymbols.namesaketransport processes/heat transfer (theory). diffusionRare eventsstochastic particle dynamics (theory)Statistical physicsDiffusion (business)ScalingPhysicsdiffusiondriven diffusive systems (theory)Statistical and Nonlinear PhysicsDisordered Systems and Neural Networks (cond-mat.dis-nn)Condensed Matter - Disordered Systems and Neural NetworksRandom walkDistribution (mathematics)Lévy flighttransport processes/heat transfer (theory)symbolsdiffusion; stochastic particle dynamics (theory); driven diffusive systems (theory); transport processes/heat transfer (theory)Statistics Probability and UncertaintyStatistical and Nonlinear PhysicJournal of Statistical Mechanics: Theory and Experiment
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Cross-diffusion-induced subharmonic spatial resonances in a predator-prey system.

2018

In this paper we investigate the complex dynamics originated by a cross-diffusion-induced subharmonic destabilization of the fundamental subcritical Turing mode in a predator-prey reaction-diffusion system. The model we consider consists of a two-species Lotka-Volterra system with linear diffusion and a nonlinear cross-diffusion term in the predator equation. The taxis term in the search strategy of the predator is responsible for the onset of complex dynamics. In fact, our model does not exhibit any Hopf or wave instability, and on the basis of the linear analysis one should only expect stationary patterns; nevertheless, the presence of the nonlinear cross-diffusion term is able to induce …

Statistics and ProbabilityFood ChainTime FactorsChaoticSpatial Behavior01 natural sciencesInstabilityModels BiologicalSquare (algebra)010305 fluids & plasmasDiffusion0103 physical sciencesAnimalsDiffusion (business)010306 general physicsSettore MAT/07 - Fisica MatematicaPhysicsFourier AnalysisMathematical analysisResonanceCondensed Matter PhysicsNonlinear systemComplex dynamicsNonlinear DynamicsPredatory BehaviorHarmonicLinear ModelsStatistical and Nonlinear PhysicPhysical review. E
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