Search results for "kernel"

showing 10 items of 357 documents

Microscopic theory for hopping transport in glass-forming liquids: mode coupling corrections

1999

Abstract By introducing an order parameter that describes the geometry of clusters of particles, Liu and Oppenheim [Physica A 247 (1997) 183] developed a microscopic theory for hopping transport in glass-forming liquids. In this work we bring this theory within the frame of mode coupling theories in the highly viscous regime. We calculate corrections to the effective longitudinal viscosity that affect its long-time dynamical behavior. Nevertheless, the relation between the longitudinal viscosity and the hopping kernel is not qualitatively altered by mode coupling.

Statistics and ProbabilityPhysicsViscosityWork (thermodynamics)Kernel (image processing)Condensed matter physicsMode couplingOrder (ring theory)Microscopic theoryCondensed Matter PhysicsGlass transitionGlass formingPhysica A: Statistical Mechanics and its Applications
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Infinite rate mutually catalytic branching in infinitely many colonies: The longtime behavior

2012

Consider the infinite rate mutually catalytic branching process (IMUB) constructed in [Infinite rate mutually catalytic branching in infinitely many colonies. Construction, characterization and convergence (2008) Preprint] and [Ann. Probab. 38 (2010) 479-497]. For finite initial conditions, we show that only one type survives in the long run if the interaction kernel is recurrent. On the other hand, under a slightly stronger condition than transience, we show that both types can coexist.

Statistics and ProbabilityPure mathematicsProbability (math.PR)coexistenceType (model theory)Characterization (mathematics)Branching (polymer chemistry)Trotter productstochastic differential equationsLévy noisesegregation of typesStochastic differential equationKernel (algebra)Mutually catalytic branching60G1760K35Convergence (routing)FOS: Mathematics60J6560J55PreprintStatistics Probability and UncertaintyMathematics - ProbabilityMathematicsBranching processThe Annals of Probability
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An Adaptive Parallel Tempering Algorithm

2013

Parallel tempering is a generic Markov chainMonteCarlo samplingmethod which allows good mixing with multimodal target distributions, where conventionalMetropolis- Hastings algorithms often fail. The mixing properties of the sampler depend strongly on the choice of tuning parameters, such as the temperature schedule and the proposal distribution used for local exploration. We propose an adaptive algorithm with fixed number of temperatures which tunes both the temperature schedule and the parameters of the random-walk Metropolis kernel automatically. We prove the convergence of the adaptation and a strong law of large numbers for the algorithm under general conditions. We also prove as a side…

Statistics and ProbabilityScheduleMathematical optimizationta112Adaptive algorithmErgodicityta111Mixing (mathematics)Law of large numbersKernel (statistics)Convergence (routing)Discrete Mathematics and CombinatoricsParallel temperingStatistics Probability and UncertaintyAlgorithmMathematicsJournal of Computational and Graphical Statistics
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SKINK: a web server for string kernel based kink prediction in α-helices

2014

Abstract Motivation: The reasons for distortions from optimal α-helical geometry are widely unknown, but their influences on structural changes of proteins are significant. Hence, their prediction is a crucial problem in structural bioinformatics. Here, we present a new web server, called SKINK, for string kernel based kink prediction. Extending our previous study, we also annotate the most probable kink position in a given α-helix sequence. Availability and implementation: The SKINK web server is freely accessible at http://biows-inf.zdv.uni-mainz.de/skink. Moreover, SKINK is a module of the BALL software, also freely available at www.ballview.org. Contact:  benny.kneissl@roche.com

Statistics and ProbabilitySkinkWeb serverTheoretical computer scienceComputer scienceReal-time computingcomputer.software_genreBiochemistryProtein Structure SecondaryStructural bioinformaticsSoftwareSequence Analysis ProteinString kernelPosition (vector)Ball (mathematics)Molecular BiologyInternetSequencebiologybusiness.industryComputational BiologyProteinsbiology.organism_classificationComputer Science ApplicationsComputational MathematicsComputational Theory and MathematicsbusinesscomputerSoftwareBioinformatics
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A comparison of nonparametric methods in the graduation of mortality: Application to data from the Valencia Region (Spain)

2006

[EN] The nonparametric graduation of mortality data aims to estimate death rates by carrying out a smoothing of the crude rates obtained directly from original data. The main difference with regard to parametric models is that the assumption of an age-dependent function is unnecessary, which is advantageous when the information behind the model is unknown, as one cause of error is often the choice of an inappropriate model. This paper reviews the various alternatives and presents their application to mortality data from the Valencia Region, Spain. The comparison leads us to the conclusion that the best model is a smoothing by means of Generalised Additive Models (GAM) with splines. The most…

Statistics and ProbabilitySplinesComputer scienceMortality rateESTADISTICA E INVESTIGACION OPERATIVANonparametric statisticsFunction (mathematics)GAMLife tablesStatisticsParametric modelEconometricsRange (statistics)Kernel smootherKernel smoothingStatistics Probability and UncertaintyLOESSAdditive modelSmoothing
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Estimation of total electricity consumption curves by sampling in a finite population when some trajectories are partially unobserved

2019

International audience; Millions of smart meters that are able to collect individual load curves, that is, electricity consumption time series, of residential and business customers at fine scale time grids are now deployed by electricity companies all around the world. It may be complex and costly to transmit and exploit such a large quantity of information, therefore it can be relevant to use survey sampling techniques to estimate mean load curves of specific groups of customers. Data collection, like every mass process, may undergo technical problems at every point of the metering and collection chain resulting in missing values. We consider imputation approaches (linear interpolation, k…

Statistics and Probabilityconstructionkernel smoothingPopulationSurvey samplingimputation01 natural sciences010104 statistics & probability[MATH.MATH-ST]Mathematics [math]/Statistics [math.ST]0502 economics and businessStatisticsImputation (statistics)0101 mathematicseducationsurvey samplingfunctional data050205 econometrics Mathematicsconfidence bandsConsumption (economics)Estimationeducation.field_of_studymissing completely at randombusiness.industry05 social sciencesprincipal analysis by conditional estimationSampling (statistics)[MATH.MATH-PR]Mathematics [math]/Probability [math.PR]nearest neighboursKernel smoothervariance-estimationElectricityStatistics Probability and Uncertaintybusinessvariance approximation
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Test of the Latent Dimension of a Spatial Blind Source Separation Model

2024

We assume a spatial blind source separation model in which the observed multivariate spatial data is a linear mixture of latent spatially uncorrelated random fields containing a number of pure white noise components. We propose a test on the number of white noise components and obtain the asymptotic distribution of its statistic for a general domain. We also demonstrate how computations can be facilitated in the case of gridded observation locations. Based on this test, we obtain a consistent estimator of the true dimension. Simulation studies and an environmental application in the Supplemental Material demonstrate that our test is at least comparable to and often outperforms bootstrap-bas…

Statistics and Probabilitymonimuuttujamenetelmätsignaalinkäsittelykernel functionFOS: Mathematicsspatial bootstrapMathematics - Statistics Theorymultivariate spatial dataStatistics Theory (math.ST)paikkatietoanalyysiStatistics Probability and Uncertaintyasymptotic distributionsignal number
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A semiparametric approach to estimate reference curves for biophysical properties of the skin

2006

Reference curves which take one covariable into account such as the age, are often required in medicine, but simple systematic and efficient statistical methods for constructing them are lacking. Classical methods are based on parametric fitting (polynomial curves). In this chapter, we describe a new methodology for the estimation of reference curves for data sets, based on nonparametric estimation of conditional quantiles. The derived method should be applicable to all clinical or more generally biological variables that are measured on a continuous quantitative scale. To avoid the curse of dimensionality when the covariate is multidimensional, a new semiparametric approach is proposed. Th…

Statistics::TheoryKernel density estimationcomputer.software_genre01 natural sciences010104 statistics & probability0502 economics and businessCovariateSliced inverse regressionApplied mathematicsStatistics::MethodologySemiparametric regression0101 mathematics[SHS.ECO] Humanities and Social Sciences/Economics and Finance050205 econometrics MathematicsParametric statisticsDimensionality reduction05 social sciencesNonparametric statistics[ SDV.SPEE ] Life Sciences [q-bio]/Santé publique et épidémiologie[SHS.ECO]Humanities and Social Sciences/Economics and Finance3. Good health[SDV.SPEE] Life Sciences [q-bio]/Santé publique et épidémiologie[SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologieC140;C630Data miningcomputerQuantile
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On rural development of NUTS 2 and 3: a non parametric approach of distribution dynamics analysis

2008

This work presents a study about dynamics of territorial gaps in agriculture between EU NUTS 2 and 3 from three perspectives: agricultural production model, rural development and productivity. Our choice of methodology is driven by two considerations. First of all, different performances in agriculture of EU areas may lead to multimodal distributions of indicators, and this implies that no significant average behaviour a parametric estimates refers to can be identified. Secondly, even if one wants to highlight multimodality within distributions, techniques like univariate density estimates can not catch intra-distribution dynamics which lead to the formation of "poles" of units showing a "s…

Stochastic Kernel Agriculture NUTS2 NUTS3 Spatial Contiguity
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Semi-supervised Hyperspectral Image Classification with Graphs

2006

This paper presents a semi-supervised graph-based method for the classification of hyperspectral images. The method is designed to exploit the spatial/contextual information in the im- ages through composite kernels. The proposed method produces smoother classifications with respect to the intrinsic structure collectively revealed by known labeled and unlabeled points. Good accuracy in high dimensional spaces and low number of labeled samples (ill-posed situations) are produced as compared to standard inductive support vector machines.

Structured support vector machineContextual image classificationbusiness.industryHyperspectral imagingPattern recognitionGraphRelevance vector machineSupport vector machineComputingMethodologies_PATTERNRECOGNITIONKernel (image processing)Artificial intelligencebusinessCluster analysisMathematics2006 IEEE International Symposium on Geoscience and Remote Sensing
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