Search results for "LONG"

showing 10 items of 3969 documents

Generalized Symmetry Models for Hypercubic Concordance Tables

2000

Summary Frequency data obtained classifying a sample of 'units' by the same categorical variable repeatedly over 'components', can be arranged in a hypercubic concordance table (h.c.t.). This kind of data naturally arises in a number of different areas such as longitudinal studies, studies using matched and clustered data, item-response analysis, agreement analysis. In spite of the substantial diversity of the mechanisms that can generate them, data arranged in a h.c.t. can all be analyzed via models of symmetry and quasi-symmetry, which exploit the special structure of the h.c.t. The paper extends the definition of such models to any dimension, introducing the class of generalized symmetry…

Statistics and ProbabilityLongitudinal dataItem-response analysiStructure (category theory)InferenceClass (philosophy)Statistical modelClusteringAgreementAlgebraGeneralized symmetry modelMatchingDimension (data warehouse)Statistical theoryStatistics Probability and UncertaintySettore SECS-S/01 - StatisticaLikelihood functionCategorical variableAlgorithmMathematicsInternational Statistical Review / Revue Internationale de Statistique
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Segmented mixed models with random changepoints: a maximum likelihood approach with application to treatment for depression study

2014

We present a simple and effective iterative procedure to estimate segmented mixed models in a likelihood based framework. Random effects and covariates are allowed for each model parameter, including the changepoint. The method is practical and avoids the computational burdens related to estimation of nonlinear mixed effects models. A conventional linear mixed model with proper covariates that account for the changepoints is the key to our estimating algorithm. We illustrate the method via simulations and using data from a randomized clinical trial focused on change in depressive symptoms over time which characteristically show two separate phases of change.

Statistics and ProbabilityMixed modelMaximum likelihoodrandom changepointRandom effects modelpsychiatric longitudinal dataGeneralized linear mixed modelNonlinear systemchangepointmixed segmented regressionStatisticsCovariateMixed effectsStatistics Probability and Uncertaintynonlinear mixed modelSettore SECS-S/01 - StatisticaAlgorithmDepressive symptomsMathematics
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Degree course change and student performance: a mixed-effect approach

2015

This paper focuses on students credits earning speed over time and its determinants, dealing with the huge percentage of students who do not take the degree within the legal duration in the Italian University System. A new indicator for the performance of the student career is proposed on real data, concerning the cohort of students enrolled at a Faculty of the University of Palermo (followed for 7 years). The new indicator highlights a typical zero-inflated distribution and suggests to investigate the effect of the degree course (DC) change on the student career. A mixed-effect model for overdispersed data is considered, with the aim of taking into account the individual variability as wel…

Statistics and ProbabilityMixed modelMotion chart05 social sciences050301 education01 natural sciencesCourse (navigation)Degree (temperature)010104 statistics & probabilityOverdispersionCohortComputingMilieux_COMPUTERSANDEDUCATIONMathematics educationuniversity credits expected years to the graduation overdispersion ZIP model longitudinal data motion chartSettore SECS-S/05 - Statistica Sociale0101 mathematicsStatistics Probability and UncertaintyDuration (project management)PsychologySettore SECS-S/01 - Statistica0503 educationUniversity system
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Variable Length Memory Chains: Characterization of stationary probability measures

2021

Variable Length Memory Chains (VLMC), which are generalizations of finite order Markov chains, turn out to be an essential tool to modelize random sequences in many domains, as well as an interesting object in contemporary probability theory. The question of the existence of stationary probability measures leads us to introduce a key combinatorial structure for words produced by a VLMC: the Longest Internal Suffix. This notion allows us to state a necessary and sufficient condition for a general VLMC to admit a unique invariant probability measure. This condition turns out to get a much simpler form for a subclass of VLMC: the stable VLMC. This natural subclass, unlike the general case, enj…

Statistics and ProbabilityPure mathematicsLongest Internal SuffixStationary distributionMarkov chain60J05 60C05 60G10Probability (math.PR)010102 general mathematics01 natural sciencesMeasure (mathematics)Variable Length Memory Chains010104 statistics & probabilityProbability theoryConvergence of random variablesFOS: MathematicsCountable setState spaceRenewal theory[MATH]Mathematics [math]0101 mathematicsstable context treessemi-Markov chainsMathematics - Probabilitystationary probability measureMathematicsBernoulli
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Structural multilevel models for longitudinal mediation analysis: a definition variable approach

2022

Mediation analysis is used to assess the direct effect of an exposure on an outcome, and the indirect effect transmitted by a third intermediate variable. Longitudinal data are the most suited to address mediation, since they allow mediational effects to manifest over time. There exist several approaches to deal with longitudinal mediation analysis, and one of the most widely spread, especially in social and behavioural sciences, consists of using multilevel models. However, when applied to mediational settings, these models present some limitations that can be overcome moving to a structural perspective. In this paper we propose a new formalisation of multilevel models within a structural …

Statistics and ProbabilitySEMDefinition variablesLongitudinal mediation analysiStatistics Probability and UncertaintyMultilevel modelSettore SECS-S/01 - StatisticaStatistical Papers
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Understanding the determinants of volatility clustering in terms of stationary Markovian processes

2016

Abstract Volatility is a key variable in the modeling of financial markets. The most striking feature of volatility is that it is a long-range correlated stochastic variable, i.e. its autocorrelation function decays like a power-law τ − β for large time lags. In the present work we investigate the determinants of such feature, starting from the empirical observation that the exponent β of a certain stock’s volatility is a linear function of the average correlation of such stock’s volatility with all other volatilities. We propose a simple approach consisting in diagonalizing the cross-correlation matrix of volatilities and investigating whether or not the diagonalized volatilities still kee…

Statistics and ProbabilityVolatility clusteringVolatility Econophysics Long-range correlation Stochastic processes First passage timeStochastic volatilityProbability density functionCondensed Matter PhysicsSABR volatility model01 natural sciencesSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)010305 fluids & plasmasHeston modelFinancial models with long-tailed distributions and volatility clustering0103 physical sciencesForward volatilityEconometricsVolatility (finance)010306 general physicsMathematics
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Extremal polynomials in stratified groups

2018

We introduce a family of extremal polynomials associated with the prolongation of a stratified nilpotent Lie algebra. These polynomials are related to a new algebraic characterization of abnormal subriemannian geodesics in stratified nilpotent Lie groups. They satisfy a set of remarkable structure relations that are used to integrate the adjoint equations.

Statistics and Probabilityextremal polynomialsMathematics - Differential GeometryPure mathematicsGeodesicStructure (category theory)Group Theory (math.GR)Characterization (mathematics)algebra01 natural sciencesdifferentiaaligeometriaMathematics - Analysis of PDEsMathematics - Metric Geometry53C17FOS: Mathematics0101 mathematicsAlgebraic numberMathematics - Differential Geometry; Mathematics - Differential Geometry; Mathematics - Analysis of PDEs; Mathematics - Group Theory; Mathematics - Metric Geometry; Mathematics - Optimization and Control; 53C17; 49K30; 17B70Mathematics - Optimization and ControlMathematics010102 general mathematicsStatisticsta111polynomitProlongation53C17 49K30 17B70Lie groupMetric Geometry (math.MG)abnormal extremals010101 applied mathematicsNilpotent Lie algebraNilpotentsub-Riemannian geometryabnormal extremals extremal polynomials Carnot groups sub-Riemannian geometryAbnormal extremals; Carnot groups; Extremal polynomials; Sub-Riemannian geometry; Analysis; Statistics and Probability; Geometry and Topology; Statistics Probability and UncertaintyDifferential Geometry (math.DG)Optimization and Control (math.OC)Carnot groups17B70Probability and UncertaintyGeometry and TopologyStatistics Probability and UncertaintyMathematics - Group TheoryAnalysisAnalysis of PDEs (math.AP)Mathematics - Differential Geometry; Mathematics - Differential Geometry; Mathematics - Analysis of PDEs; Mathematics - Group Theory; Mathematics - Metric Geometry; Mathematics - Optimization and Control; 53C17 49K30 17B7049K30
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Networks as mediating variables: a Bayesian latent space approach

2022

AbstractThe use of network analysis to investigate social structures has recently seen a rise due to the high availability of data and the numerous insights it can provide into different fields. Most analyses focus on the topological characteristics of networks and the estimation of relationships between the nodes. We adopt a different perspective by considering the whole network as a random variable conveying the effect of an exposure on a response. This point of view represents a classical mediation setting, where the interest lies in estimating the indirect effect, that is, the effect propagated through the mediating variable. We introduce a latent space model mapping the network into a …

Statistics and Probabilitylongitudinal datalatent space modelmediation analysiStatistics Probability and UncertaintyNetwork analysiSettore SECS-S/01 - StatisticaBayesian method
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The kinematics of water masers in the stellar molecular outflow source, IRAS 19134+2131

2004

Using the Very Large Array (VLA) and the Very Long Baseline Array (VLBA), we have observed water maser emission in the proto-planetary nebula candidate IRAS 19134+2131, in which the water maser spectrum has two groups of emission features separated in radial velocity by ∼100 km s^−1. The blue-shifted and red-shifted clusters of maser features are clearly separated spatially by ∼150 mas, indicative of a fast collimated flow. However, not all of the maser features are aligned along the axis of the flow, as is seen in the similar high-velocity water maser source, W43A. Comparing the VLA and VLBA maps of the water maser source, we find 4 maser features that were active for 2 years. Using only V…

Stellar kinematicsAstrophysics::High Energy Astrophysical PhenomenaOutflowsAstrophysics::Cosmology and Extragalactic AstrophysicsAstrophysicsUNESCO::ASTRONOMÍA Y ASTROFÍSICAAGB and post-AGBlaw.inventionlawIndividual starsAstrophysics::Solar and Stellar AstrophysicsAsymptotic giant branchOH/IR starMaserMasers stars ; AGB and post-AGB ; Distances ; Kinematics Winds ; Outflows ; Individual stars ; IRAS 19134+2131Astrophysics::Galaxy AstrophysicsVery Long Baseline ArrayPhysicsNebulaKinematics WindsAstronomyIRAS 19134+2131Astronomy and AstrophysicsGalactic plane:ASTRONOMÍA Y ASTROFÍSICA::Cosmología y cosmogonia [UNESCO]Masers starsDistancesRadial velocitySpace and Planetary ScienceUNESCO::ASTRONOMÍA Y ASTROFÍSICA::Cosmología y cosmogonia:ASTRONOMÍA Y ASTROFÍSICA [UNESCO]Astronomy & Astrophysics
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THE ROLE OF UNBOUNDED TIME-SCALES IN GENERATING LONG-RANGE MEMORY IN ADDITIVE MARKOVIAN PROCESSES

2013

Any additive stationary and continuous Markovian process described by a Fokker–Planck equation can also be described in terms of a Schrödinger equation with an appropriate quantum potential. By using such analogy, it has been proved that a power-law correlated stationary Markovian process can stem from a quantum potential that (i) shows an x-2 decay for large x values and (ii) whose eigenvalue spectrum admits a null eigenvalue and a continuum part of positive eigenvalues attached to it. In this paper we show that such two features are both necessary. Specifically, we show that a potential with tails decaying like x-μ with μ < 2 gives rise to a stationary Markovian process which is not p…

Stochastic processGeneral MathematicsAutocorrelationNull (mathematics)Mathematical analysisSpectrum (functional analysis)Quantum potentialstochastic processes survival probabilityGeneral Physics and AstronomyMarkov processStochastic processeSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)Schrödinger equationsymbols.namesakelong range correlationsymbolsEigenvalues and eigenvectorsMathematicsFluctuation and Noise Letters
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