Search results for "NETWORK"

showing 10 items of 7718 documents

A network analysis of student mobility patterns from high school to master’s

2021

Human migration involves the movement of people from one place to another. An example of undirected migration is Italian student mobility where students move from the South to the Center-North. This kind of mobility has become of general interest, and this work explores student mobility from Sicily towards universities outside the island. The data used in this paper regards six cohorts of students, from 2008/09 to 2013/14. In particular, our goal is to study the 3-step migration path: the area of origin (Sicilian provinces), the regional university for the bachelor’s degree, and the regional university for the master’s. Our analysis is conducted by building a multipartite network with four …

Statistics and ProbabilityGeneral interestHuman migrationbusiness.industrymedia_common.quotation_subjectLink weightBachelorlanguage.human_languageGeographyMathematics educationlanguageMaster sHigher educationStatistics Probability and UncertaintyNetworksSet (psychology)businessStudents’ mobilitySicilianNetwork analysismedia_common
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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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Comments on "Identifying inconsistency in network meta-analysis: Is the net heat plot a reliable method?"

2021

One of the biggest challenges for network meta‐analysis is inconsistency, which occurs when the direct and indirect evidence conflict. Inconsistency causes problems for the estimation and interpretation of treatment effects and treatment contrasts. Krahn and colleagues proposed the net heat approach as a graphical tool for identifying and locating inconsistency within a network of randomized controlled trials. For networks with a treatment loop, the net heat plot displays statistics calculated by temporarily removing each design one at a time, in turn, and assessing the contribution of each remaining design to the inconsistency. The net heat plot takes the form of a matrix which is displaye…

Statistics and ProbabilityHot TemperatureEpidemiologyComputer scienceNetwork Meta-AnalysisHealth ServicesinconsistencyPlot (graphics)Research DesignMeta-analysisStatisticsHumansnetwork meta‐analysisResearch ArticlesResearch Articlenet heat plotStatistics in medicineREFERENCES
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Immune networks: multitasking capabilities near saturation

2013

Pattern-diluted associative networks were introduced recently as models for the immune system, with nodes representing T-lymphocytes and stored patterns representing signalling protocols between T- and B-lymphocytes. It was shown earlier that in the regime of extreme pattern dilution, a system with $N_T$ T-lymphocytes can manage a number $N_B!=!\order(N_T^\delta)$ of B-lymphocytes simultaneously, with $\delta!<!1$. Here we study this model in the extensive load regime $N_B!=!\alpha N_T$, with also a high degree of pattern dilution, in agreement with immunological findings. We use graph theory and statistical mechanical analysis based on replica methods to show that in the finite-connectivit…

Statistics and ProbabilityImmune Network Statistical Mechanics Hopfield Model Parallel RetrievalQuantitative Biology::Tissues and OrgansPhase (waves)FOS: Physical sciencesGeneral Physics and AstronomyInterference (wave propagation)TopologyQuantitative Biology::Cell BehaviorCell Behavior (q-bio.CB)Physics - Biological PhysicsFinite setMathematical PhysicsConnectivityAssociative propertyPhysicsDegree (graph theory)ReplicaStatistical and Nonlinear PhysicsGraph theoryDisordered Systems and Neural Networks (cond-mat.dis-nn)Condensed Matter - Disordered Systems and Neural NetworksBiological Physics (physics.bio-ph)FOS: Biological sciencesModeling and SimulationQuantitative Biology - Cell BehaviorJournal of Physics A: Mathematical and Theoretical
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A Knowledge Management and Decision Support Model for Enterprises

2011

We propose a novel knowledge management system (KMS) for enterprises. Our system exploits two different approaches for knowledge representation and reasoning: a document-based approach based on data-driven creation of a semantic space and an ontology-based model. Furthermore, we provide an expert system capable of supporting the enterprise decisional processes and a semantic engine which performs intelligent search on the enterprise knowledge bases. The decision support process exploits the Bayesian networks model to improve business planning process when performed under uncertainty. Copyright © 2011 Patrizia Ribino et al.

Statistics and ProbabilityKnowledge Management SystemsSettore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniDecision support systemKnowledge managementArticle SubjectKnowledge representation and reasoningExploitProcess (engineering)business.industryComputer sciencelcsh:MathematicsApplied MathematicsGeneral Decision SciencesBayesian networkOntology (information science)lcsh:QA1-939computer.software_genreExpert systemComputational MathematicsKnowledge-based systemsbusinesscomputer
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Local inhomogeneous second-order characteristics for spatio-temporal point processes occurring on linear networks

2022

AbstractPoint processes on linear networks are increasingly being considered to analyse events occurring on particular network-based structures. In this paper, we extend Local Indicators of Spatio-Temporal Association (LISTA) functions to the non-Euclidean space of linear networks, allowing to obtain information on how events relate to nearby events. In particular, we propose the local version of two inhomogeneous second-order statistics for spatio-temporal point processes on linear networks, the K- and the pair correlation functions. We put particular emphasis on the local K-functions, deriving come theoretical results which enable us to show that these LISTA functions are useful for diagn…

Statistics and ProbabilityLocal Indicators of Spatio-Temporal Associationlocal propertiessecond-order characteristicsresidual analysislinear networksspatio-temporal point patternsStatistics Probability and UncertaintySettore SECS-S/01 - StatisticaLinear networks Local Indicators of Spatio-temporal Association Local properties Residual analysis Second-order characteristics Spatio-temporal point patterns
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Local Asymptotic Normality for Shape and Periodicity in the Drift of a Time Inhomogeneous Diffusion

2017

We consider a one-dimensional diffusion whose drift contains a deterministic periodic signal with unknown periodicity $T$ and carrying some unknown $d$-dimensional shape parameter $\theta$. We prove Local Asymptotic Normality (LAN) jointly in $\theta$ and $T$ for the statistical experiment arising from continuous observation of this diffusion. The local scale turns out to be $n^{-1/2}$ for the shape parameter and $n^{-3/2}$ for the periodicity which generalizes known results about LAN when either $\theta$ or $T$ is assumed to be known.

Statistics and ProbabilityLocal asymptotic normalityMathematical analysisLocal scale62F12 60J60020206 networking & telecommunicationsMathematics - Statistics Theory02 engineering and technologyStatistics Theory (math.ST)01 natural sciencesShape parameterPeriodic function010104 statistics & probability0202 electrical engineering electronic engineering information engineeringFOS: Mathematics0101 mathematicsDiffusion (business)Mathematics
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Inhomogeneous spatio-temporal point processes on linear networks for visitors’ stops data

2022

We analyse the spatio-temporal distribution of visitors' stops by touristic attractions in Palermo (Italy) using theory of stochastic point processes living on linear networks. We first propose an inhomogeneous Poisson point process model, with a separable parametric spatio-temporal first-order intensity. We account for the spatial interaction among points on the given network, fitting a Gibbs point process model with mixed effects for the purely spatial component. This allows us to study first-order and second-order properties of the point pattern, accounting both for the spatio-temporal clustering and interaction and for the spatio-temporal scale at which they operate. Due to the strong d…

Statistics and ProbabilityLog-Gaussian Cox processeSpatio-temporal point processesIntensity estimationGlobal Positioning SystemModeling and SimulationGibbs point processeLinear networkStatistics Probability and UncertaintySettore SECS-S/01 - StatisticaThe Annals of Applied Statistics
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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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