Search results for "25"

showing 10 items of 3263 documents

Il Cyberstalking

2015

Il Cyberstalking è una forma diffusa di molestia effettuata tramite l'utilizzo delle nuove tecnologie, come e-mail, chat e social network. Si stima che tra il 2-13% e l'8-32% delle donne negli Stati Uniti è vittima di cyberstalking. Il crescente interesse per questo nuovo crimine informatico è testimoniato dal recente adeguamento del sistema legislativo italiano (art. 612-bis del Codice Penale). Le azioni dei cyberstalker potrebbero essere mosse dal desiderio di vendetta, da un'ossessione d'amore o dalla ricerca di intimità.

Stalking cyberstalkingSettore M-PSI/08 - Psicologia ClinicaSettore MED/25 - Psichiatria
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Time-dependent weak rate of convergence for functions of generalized bounded variation

2016

Let $W$ denote the Brownian motion. For any exponentially bounded Borel function $g$ the function $u$ defined by $u(t,x)= \mathbb{E}[g(x{+}\sigma W_{T-t})]$ is the stochastic solution of the backward heat equation with terminal condition $g$. Let $u^n(t,x)$ denote the corresponding approximation generated by a simple symmetric random walk with time steps $2T/n$ and space steps $\pm \sigma \sqrt{T/n}$ where $\sigma > 0$. For quite irregular terminal conditions $g$ (bounded variation on compact intervals, locally H\"older continuous) the rate of convergence of $u^n(t,x)$ to $u(t,x)$ is considered, and also the behavior of the error $u^n(t,x)-u(t,x)$ as $t$ tends to $T$

Statistics and ProbabilityApproximation using simple random walkweak rate of convergence01 natural sciencesStochastic solution41A25 65M15 (Primary) 35K05 60G50 (Secondary)010104 statistics & probabilityExponential growthFOS: Mathematics0101 mathematicsBrownian motionstokastiset prosessitMathematicsosittaisdifferentiaaliyhtälötApplied MathematicsProbability (math.PR)010102 general mathematicsMathematical analysisfinite difference approximation of the heat equationFunction (mathematics)Rate of convergenceBounded functionBounded variationnumeerinen analyysiapproksimointiStatistics Probability and UncertaintyMathematics - ProbabilityStochastic Analysis and Applications
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Robust dynamic cooperative games

2009

Classical cooperative game theory is no longer a suitable tool for those situations where the values of coalitions are not known with certainty. Recent works address situations where the values of coalitions are modelled by random variables. In this work we still consider the values of coalitions as uncertain, but model them as unknown but bounded disturbances. We do not focus on solving a specific game, but rather consider a family of games described by a polyhedron: each point in the polyhedron is a vector of coalitions’ values and corresponds to a specific game. We consider a dynamic context where while we know with certainty the average value of each coalition on the long run, at each t…

Statistics and ProbabilityBondareva–Shapley theoremEconomics and EconometricsNon-cooperative gameComputer Science::Computer Science and Game TheoryMSC-91A12Sequential gameMSC-91A25Computer scienceCooperative games Dynamic games Joint replenishmentCombinatorial game theoryTheoryofComputation_GENERALCooperative game theoryMETIS-263773Computer Science::Multiagent SystemsMathematics (miscellaneous)Example of a game without a valueEWI-15215Repeated gameIR-62781Simultaneous gameStatistics Probability and UncertaintyMathematical economicsSocial Sciences (miscellaneous)International journal of game theory
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Weighted distance-based trees for ranking data

2017

Within the framework of preference rankings, the interest can lie in finding which predictors and which interactions are able to explain the observed preference structures, because preference decisions will usually depend on the characteristics of both the judges and the objects being judged. This work proposes the use of a univariate decision tree for ranking data based on the weighted distances for complete and incomplete rankings, and considers the area under the ROC curve both for pruning and model assessment. Two real and well-known datasets, the SUSHI preference data and the University ranking data, are used to display the performance of the methodology.

Statistics and ProbabilityDecision tree03 medical and health sciences0302 clinical medicine0504 sociology030225 pediatricsPreference dataStatisticsDecision treePruning (decision trees)University ranking dataDistance-based methodMathematicsWeighted distanceApplied Mathematics05 social sciencesUnivariate050401 social sciences methodsSUSHI dataComputer Science Applications1707 Computer Vision and Pattern RecognitionPreferenceComputer Science ApplicationsRankingRanking dataKemeny distanceSettore SECS-S/01 - StatisticaArea under the roc curve
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Ergodicity for a stochastic Hodgkin–Huxley model driven by Ornstein–Uhlenbeck type input

2013

We consider a model describing a neuron and the input it receives from its dendritic tree when this input is a random perturbation of a periodic deterministic signal, driven by an Ornstein-Uhlenbeck process. The neuron itself is modeled by a variant of the classical Hodgkin-Huxley model. Using the existence of an accessible point where the weak Hoermander condition holds and the fact that the coefficients of the system are analytic, we show that the system is non-degenerate. The existence of a Lyapunov function allows to deduce the existence of (at most a finite number of) extremal invariant measures for the process. As a consequence, the complexity of the system is drastically reduced in c…

Statistics and ProbabilityDegenerate diffusion processesWeak Hörmander conditionType (model theory)01 natural sciencesPeriodic ergodicity010104 statistics & probability60H0760J25FOS: Mathematics0101 mathematicsComputingMilieux_MISCELLANEOUSMathematical physicsMathematics60J60Quantitative Biology::Neurons and CognitionProbability (math.PR)010102 general mathematicsErgodicityOrnstein–Uhlenbeck processHodgkin–Huxley model[MATH.MATH-PR]Mathematics [math]/Probability [math.PR]Hodgkin–Huxley model60J60 60J25 60H07Statistics Probability and UncertaintyTime inhomogeneous diffusion processesMathematics - Probability
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New approach to numerical computation of the eigenfunctions of the continuous spectrum of three-particle Schrödinger operator: I. One-dimensional par…

2009

Basing on analogy between the three-body scattering problem and the diffraction problem of the plane wave (for the case of the short range pair potentials) by the system of six half transparent screens, we presented a new approach to the few-body scattering problem. The numerical results have been obtained for the case of the short range nonnegative pair potentials. The presented method allows a natural generalization to the case of the long range pair potentials.

Statistics and ProbabilityDiffractionGeneralizationScattering34L25 81U08ComputationOperator (physics)Continuous spectrumMathematical analysisPlane waveGeneral Physics and AstronomyStatistical and Nonlinear PhysicsGeometryEigenfunctionModeling and SimulationMathematical PhysicsMathematicsJournal of Physics A: Mathematical and Theoretical
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Stochastic order characterization of uniform integrability and tightness

2013

We show that a family of random variables is uniformly integrable if and only if it is stochastically bounded in the increasing convex order by an integrable random variable. This result is complemented by proving analogous statements for the strong stochastic order and for power-integrable dominating random variables. Especially, we show that whenever a family of random variables is stochastically bounded by a p-integrable random variable for some p>1, there is no distinction between the strong order and the increasing convex order. These results also yield new characterizations of relative compactness in Wasserstein and Prohorov metrics.

Statistics and ProbabilityDiscrete mathematicsPure mathematicsRandom fieldMultivariate random variableProbability (math.PR)ta111Random functionRandom element60E15 60B10 60F25Stochastic orderingFunctional Analysis (math.FA)Mathematics - Functional AnalysisRandom variateConvergence of random variablesStochastic simulationFOS: MathematicsStatistics Probability and UncertaintyMathematics - ProbabilityMathematicsStatistics & Probability Letters
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Dans quelle mesure les préférences individuelles contraignent-elles le développement du marché de l'assurance dépendance ?

2015

Dans un contexte de vieillissement de la population, différents scenarii sont envisagés pour réformer l’organisation et le financement de la prise en charge des personnes âgées dépendantes. La place de la prévoyance individuelle dans le financement de la dépendance est à ce titre largement débattue. À l’heure actuelle, malgré des restes à charge potentiellement conséquents, peu d’individus disposent d’une couverture assurantielle. Cet article vise à enrichir la littérature existante en évaluant dans quelle mesure les préférences observées dans la population limitent cette couverture. Nous mobilisons pour cela l’enquête Patrimoine et préférences vis-à-vis du temps et du risque (Pater) de 201…

Statistics and ProbabilityEconomics and Econometricsdemande d’assurance[SHS.STAT]Humanities and Social Sciences/Methods and statistics050208 financeSociology and Political Science05 social sciencespréférence pour le présentPréférences individuelles[SHS.ECO]Humanities and Social Sciences/Economics and Financeperte d’autonomieassurance dépendanceassurance0502 economics and business[SHS.STAT] Humanities and Social Sciences/Methods and statistics[ SHS.ECO ] Humanities and Social Sciences/Economies and financesaversion du risque.dépendance050207 economics[SHS.ECO] Humanities and Social Sciences/Economics and Finance[ SHS.STAT ] Humanities and Social Sciences/Methods and statisticsdépendance ; perte d’autonomie ; assurance dépendance ; demande d’assurance ; préférence pour le présent ; aversion du risque ; Codes JEL C25- D91- G22- I12- I18- J14ComputingMilieux_MISCELLANEOUSprise en charge
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Centile estimation for a proportion response variable

2015

This paper introduces two general models for computing centiles when the response variable Y can take values between 0 and 1, inclusive of 0 or 1. The models developed are more flexible alternatives to the beta inflated distribution. The first proposed model employs a flexible four parameter logit skew Student t (logitSST) distribution to model the response variable Y on the unit interval (0, 1), excluding 0 and 1. This model is then extended to the inflated logitSST distribution for Y on the unit interval, including 1. The second model developed in this paper is a generalised Tobit model for Y on the unit interval, including 1. Applying these two models to (1-Y) rather than Y enables model…

Statistics and ProbabilityEstimationDistribution (number theory)EpidemiologyLogitSkew01 natural sciences010104 statistics & probability03 medical and health sciencesVariable (computer science)0302 clinical medicineUnit interval (data transmission)030225 pediatricsStatisticsProbability distributionTobit model0101 mathematicsMathematicsStatistics in Medicine
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Wardowski conditions to the coincidence problem

2015

In this article we first discuss the existence and uniqueness of a solution for the coincidence problem: Find p ∈ X such that Tp = Sp, where X is a nonempty set, Y is a complete metric space, and T, S:X → Y are two mappings satisfying a Wardowski type condition of contractivity. Later on, we will state the convergence of the Picard-Juncgk iteration process to the above coincidence problem as well as a rate of convergence for this iteration scheme. Finally, we shall apply our results to study the existence and uniqueness of a solution as well as the convergence of the Picard-Juncgk iteration process toward the solution of a second order differential equation. Ministerio de Economía y Competi…

Statistics and ProbabilityIterative methodsIterative methodCoincidence pointsComplete metric space54H25common fixed pointsConvergence (routing)Applied mathematicsUniquenessMathematicsApplied Mathematics and Statistics47J25lcsh:T57-57.97Applied MathematicsMathematical analysisOrder (ring theory)State (functional analysis)Rate of convergencecoincidence pointsRate of convergenceordinary differential equationsOrdinary differential equationlcsh:Applied mathematics. Quantitative methodsCommon fixed pointsiterative methodslcsh:Probabilities. Mathematical statisticslcsh:QA273-280rate of convergenceFrontiers in Applied Mathematics and Statistics
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