Search results for "SIMULATION"

showing 10 items of 5095 documents

Sparse kernel methods for high-dimensional survival data

2008

Abstract Sparse kernel methods like support vector machines (SVM) have been applied with great success to classification and (standard) regression settings. Existing support vector classification and regression techniques however are not suitable for partly censored survival data, which are typically analysed using Cox's proportional hazards model. As the partial likelihood of the proportional hazards model only depends on the covariates through inner products, it can be ‘kernelized’. The kernelized proportional hazards model however yields a solution that is dense, i.e. the solution depends on all observations. One of the key features of an SVM is that it yields a sparse solution, dependin…

Statistics and ProbabilityLung NeoplasmsLymphomaComputer sciencecomputer.software_genreComputing MethodologiesBiochemistryPattern Recognition AutomatedArtificial IntelligenceMargin (machine learning)CovariateCluster AnalysisHumansComputer SimulationFraction (mathematics)Molecular BiologyProportional Hazards ModelsModels StatisticalTraining setProportional hazards modelGene Expression ProfilingComputational BiologyComputer Science ApplicationsSupport vector machineComputational MathematicsKernel methodComputational Theory and MathematicsRegression AnalysisData miningcomputerAlgorithmsSoftwareBioinformatics
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Stability of a stochastic SIR system

2005

Abstract We propose a stochastic SIR model with or without distributed time delay and we study the stability of disease-free equilibrium. The numerical simulation of the stochastic SIR model shows that the introduction of noise modifies the threshold of system for an epidemic to occur and the threshold stochastic value is found.

Statistics and ProbabilityLyapunov functionStochastic stabilityComputer simulationStochastic processComputer Science::Social and Information NetworksCondensed Matter PhysicsStability (probability)Noise (electronics)SIR model Lyapunov function Stochastic process Stochastic stabilitysymbols.namesakeControl theorysymbolsQuantitative Biology::Populations and EvolutionApplied mathematicsEpidemic modelMathematicsPhysica A: Statistical Mechanics and its Applications
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Splitting the dynamics of large biochemical interaction networks

2003

This article is inscribed in the general motivation of understanding the dynamics on biochemical networks including metabolic and genetic interactions. Our approach is continuous modeling by differential equations. We address the problem of the huge size of those systems. We present a mathematical tool for reducing the size of the model, master-slave synchronization, and fit it to the biochemical context.

Statistics and ProbabilityMaster slave synchronizationModularity (networks)Theoretical computer scienceGeneral Immunology and MicrobiologyDifferential equationSystems BiologyQuantitative Biology::Molecular NetworksApplied MathematicsSystems biologyDynamics (mechanics)Context (language use)General MedicineBiologyBioinformaticsModels BiologicalGeneral Biochemistry Genetics and Molecular BiologyCell Physiological PhenomenaGene Expression RegulationModeling and SimulationSynchronization (computer science)AnimalsGeneral Agricultural and Biological SciencesAlgorithmsJournal of Theoretical Biology
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Distribution of oxygen partial pressure in a two-dimensional tissue supplied by capillary meshes and concurrent and countercurrent systems

1969

Abstract For the calculations of oxygen partial pressure in a two-dimensional tissue model supplied by a capillary network (inhomogeneously perfused tissue), two differential equations are given that describe the process in the tissue and capillaries. The differential equations are coupled by the boundary conditions. Results obtained by using the method of successive displacements are given for the two-dimensional problem. This method exhibits a satisfactory convergence. The accuracy of the results is about ±5% based on the initial concentration. The results for the network model are compared with those for equivalent concurrent and countercurrent systems. Equivalence means in this connecti…

Statistics and ProbabilityMaterials scienceGeneral Immunology and MicrobiologyDifferential equationCapillary actionCountercurrent exchangeQuantitative Biology::Tissues and OrgansApplied MathematicsPhysics::Medical PhysicsGeneral MedicinePartial pressureMechanicsAnatomyGeneral Biochemistry Genetics and Molecular BiologyDistribution (mathematics)Modeling and SimulationConvergence (routing)Boundary value problemGeneral Agricultural and Biological SciencesNetwork modelMathematical Biosciences
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Dynamics of a map with a power-law tail

2008

We analyze a one-dimensional piecewise continuous discrete model proposed originally in studies on population ecology. The map is composed of a linear part and a power-law decreasing piece, and has three parameters. The system presents both regular and chaotic behavior. We study numerically and, in part, analytically different bifurcation structures. Particularly interesting is the description of the abrupt transition order-to-chaos mediated by an attractor made of an infinite number of limit cycles with only a finite number of different periods. It is shown that the power-law piece in the map is at the origin of this type of bifurcation. The system exhibits interior crises and crisis-induc…

Statistics and ProbabilityMathematical analysisChaoticFOS: Physical sciencesGeneral Physics and AstronomyFísicaStatistical and Nonlinear PhysicsNonlinear Sciences - Chaotic DynamicsPower lawlaw.inventionNonlinear Sciences::Chaotic DynamicslawModeling and SimulationIntermittencyAttractorPiecewiseLimit (mathematics)Chaotic Dynamics (nlin.CD)Finite setMathematical PhysicsBifurcationMathematics
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Lyapunov exponent and topological entropy plateaus in piecewise linear maps

2013

We consider a two-parameter family of piecewise linear maps in which the moduli of the two slopes take different values. We provide numerical evidence of the existence of some parameter regions in which the Lyapunov exponent and the topological entropy remain constant. Analytical proof of this phenomenon is also given for certain cases. Surprisingly however, the systems with that property are not conjugate as we prove by using kneading theory.

Statistics and ProbabilityMathematical analysisGeneral Physics and AstronomyStatistical and Nonlinear PhysicsTopological entropyLyapunov exponentTopological entropy in physicsModuliPiecewise linear functionsymbols.namesakeModeling and SimulationsymbolsConstant (mathematics)Mathematical PhysicsMathematicsJournal of Physics A: Mathematical and Theoretical
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Pseudo-Cut Strategies for Global Optimization

2011

Motivated by the successful use of a pseudo-cut strategy within the setting of constrained nonlinear and nonconvex optimization in Lasdon et al. (2010), we propose a framework for general pseudo-cut strategies in global optimization that provides a broader and more comprehensive range of methods. The fundamental idea is to introduce linear cutting planes that provide temporary, possibly invalid, restrictions on the space of feasible solutions, as proposed in the setting of the tabu search metaheuristic in Glover (1989), in order to guide a solution process toward a global optimum, where the cutting planes can be discarded and replaced by others as the process continues. These strategies can…

Statistics and ProbabilityMathematical optimizationControl and OptimizationProcess (engineering)Space (commercial competition)Tabu searchComputer Science ApplicationsComputational MathematicsNonlinear systemRange (mathematics)Computational Theory and MathematicsOrder (exchange)Modeling and SimulationDecision Sciences (miscellaneous)Global optimizationMetaheuristicMathematicsInternational Journal of Applied Metaheuristic Computing
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Quantile regression via iterative least squares computations

2012

We present an estimating framework for quantile regression where the usual L 1-norm objective function is replaced by its smooth parametric approximation. An exact path-following algorithm is derived, leading to the well-known ‘basic’ solutions interpolating exactly a number of observations equal to the number of parameters being estimated. We discuss briefly possible practical implications of the proposed approach, such as early stopping for large data sets, confidence intervals, and additional topics for future research.

Statistics and ProbabilityMathematical optimizationEarly stoppingquantile regressionsmooth approximationApplied MathematicsRegression analysisLeast squaresQuantile regressionleast squareModeling and SimulationNon-linear least squaresApplied mathematicsStatistics Probability and UncertaintyTotal least squaresSettore SECS-S/01 - StatisticaQuantileParametric statisticsMathematicsJournal of Statistical Computation and Simulation
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Bayesian analysis of a Gibbs hard-core point pattern model with varying repulsion range

2014

A Bayesian solution is suggested for the modelling of spatial point patterns with inhomogeneous hard-core radius using Gaussian processes in the regularization. The key observation is that a straightforward use of the finite Gibbs hard-core process likelihood together with a log-Gaussian random field prior does not work without penalisation towards high local packing density. Instead, a nearest neighbour Gibbs process likelihood is used. This approach to hard-core inhomogeneity is an alternative to the transformation inhomogeneous hard-core modelling. The computations are based on recent Markovian approximation results for Gaussian fields. As an application, data on the nest locations of Sa…

Statistics and ProbabilityMathematical optimizationGaussianBayesian probabilityBayesian analysisMarkov processRegularization (mathematics)symbols.namesakeGaussian process regularisationPERFECT SIMULATIONRange (statistics)Statistical physicsGaussian processMathematicsta113ta112Random fieldApplied MathematicsInhomogeneousSand Martin's nestsTRANSFORMATIONHard-core point processComputational MathematicsTransformation (function)Computational Theory and MathematicssymbolsINFERENCECOMPUTATIONAL STATISTICS AND DATA ANALYSIS
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Sample Size Requirements of a Mixture Analysis Method with Applications in Systematic Biology

1999

The available information on sample size requirements of mixture analysis methods is insufficient to permit a precise evaluation of the potential problems facing practical applications of mixture analysis. We use results from Monte Carlo simulation to assess the sample size requirements of a simple mixture analysis method under conditions relevant to biological applications of mixture analysis. The mixture model used includes two univariate normal components with equal variances but assumes that the researcher is ignorant as to the equality of the variances. The method used relies on the EM algorithm to compute the maximum likelihood estimates of the mixture parameters, and the likelihood r…

Statistics and ProbabilityMathematical optimizationGeneral Immunology and MicrobiologyApplied MathematicsMonte Carlo methodUnivariateGeneral MedicineMixture modelGeneral Biochemistry Genetics and Molecular BiologySample size determinationSimple (abstract algebra)Modeling and SimulationLikelihood-ratio testExpectation–maximization algorithmGeneral Agricultural and Biological SciencesAnalysis methodMathematicsJournal of Theoretical Biology
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