Search results for "Correlation"

showing 10 items of 2282 documents

Statistical correlation of fractional oscillator response by complex spectral moments and state variable expansion

2016

Abstract The statistical characterization of the oscillator response with non-integer order damping under Gaussian noise represents an important challenge in the modern stochastic mechanics. In fact, this kind of problem appears in several issues of different type (wave propagation in viscoelastic media, Brownian motion, fluid dynamics, RLC circuit, etc.). The aim of this paper is to provide a stochastic characterization of the stationary response of linear fractional oscillator forced by normal white noise. In particular, this paper shows a new method to obtain the correlation function by exact complex spectral moments. These complex quantities contain all the information to describe the r…

State variableNon-Newtonian damping Fractional-order state variables Analytical stationary variance Exact complex spectral moments02 engineering and technologyFractional-order state variable01 natural sciencesAnalytical stationary variance010305 fluids & plasmassymbols.namesake0203 mechanical engineering0103 physical sciencesExact complex spectral momentNumerical AnalysiBrownian motionMathematicsNumerical AnalysisMellin transformStochastic processApplied MathematicsMathematical analysisWhite noiseNon-Newtonian dampingMoment (mathematics)Correlation function (statistical mechanics)020303 mechanical engineering & transportsGaussian noiseModeling and Simulationsymbols
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Nonlinear response functions in an exponential trap model

2014

The nonlinear response to an oscillating field is calculated for a kinetic trap model with an exponential density of states and the results are compared to those for the model with a Gaussian density of states. The calculations are limited to the high temperature phase of the model. It is found that the results are qualitatively different only in a temperature range near the glass transition temperature $T_0$ of the exponential model. While for the Gaussian model the choice of the dynamical variable that couples to the field has no impact on the shape of the linear response, this is different for the exponential model. Here, it is found that also the relaxation time strongly depends on the …

Statistical Mechanics (cond-mat.stat-mech)Field (physics)Condensed matter physicsChemistryFOS: Physical sciencesCondensed Matter - Soft Condensed MatterCondensed Matter PhysicsKinetic energyElectronic Optical and Magnetic MaterialsExponential functionNonlinear systemCorrelation function (statistical mechanics)Computational chemistryMaterials ChemistryCeramics and CompositesSoft Condensed Matter (cond-mat.soft)Limit (mathematics)ScalingCondensed Matter - Statistical MechanicsVariable (mathematics)
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Statistical Properties of Statistical Ensembles of Stock Returns

1999

We select n stocks traded in the New York Stock Exchange and we form a statistical ensemble of daily stock returns for each of the k trading days of our database from the stock price time series. We analyze each ensemble of stock returns by extracting its first four central moments. We observe that these moments are fluctuating in time and are stochastic processes themselves. We characterize the statistical properties of central moments by investigating their probability density function and temporal correlation properties.

Statistical ensemblePhysics::Physics and SocietyStatistical Finance (q-fin.ST)Statistical Mechanics (cond-mat.stat-mech)Stochastic processFinancial economicsQuantitative Finance - Statistical FinanceFOS: Physical sciencesProbability density functionTemporal correlationStock priceFOS: Economics and businessStock exchangeComputer Science::Computational Engineering Finance and ScienceEconomicsEconometricsGeneral Economics Econometrics and FinanceFinanceStock (geology)Condensed Matter - Statistical Mechanics
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Estimating person parameters via item response model and simple sum score in small samples with few polytomous items: A simulation study

2018

Background The Item Response Theory (IRT) is becoming increasingly popular for item analysis. Theoretical considerations and simulation studies suggest that parameter estimates will become precise only by utilizing many items in large samples. Method A simulation study focusing on a single scale was performed on data with (a) n = 40, 60, 80, 120, 200, 300, 500, and 900 cases utilizing (b) 4, 8, 16, or 32 items. The items were (c) symmetrically distributed vs. skew (skewness 0, 1, and 2). Item loadings were (d) homogeneous vs. heterogeneous. Item loadings were (e) low vs. high. Half of the items had (f) a correlated error or not. The number of answering categories (g) was four vs. five. A to…

Statistics and ProbabilityAnalysis of VarianceScale (ratio)EpidemiologyItem analysisSkewPolytomous Rasch modelMissing data01 natural sciences010104 statistics & probability03 medical and health sciences0302 clinical medicineSimple (abstract algebra)SkewnessSample SizeStatisticsItem response theoryHumansRegression AnalysisComputer Simulation030212 general & internal medicine0101 mathematicsCorrelation of DataMathematicsStatistics in Medicine
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Forecasting time series with missing data using Holt's model

2009

This paper deals with the prediction of time series with missing data using an alternative formulation for Holt's model with additive errors. This formulation simplifies both the calculus of maximum likelihood estimators of all the unknowns in the model and the calculus of point forecasts. In the presence of missing data, the EM algorithm is used to obtain maximum likelihood estimates and point forecasts. Based on this application we propose a leave-one-out algorithm for the data transformation selection problem which allows us to analyse Holt's model with multiplicative errors. Some numerical results show the performance of these procedures for obtaining robust forecasts.

Statistics and ProbabilityApplied MathematicsAutocorrelationExponential smoothingLinear modelData transformation (statistics)EstimatorMissing dataExpectation–maximization algorithmStatisticsStatistics Probability and UncertaintyAdditive modelAlgorithmMathematicsJournal of Statistical Planning and Inference
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Derived variables calculated from similar joint responses: some characteristics and examples

1995

Abstract A technique (Cox and Wermuth, 1992) is reviewed for finding linear combinations of a set of response variables having special relations of linear conditional independence with a set of explanatory variables. A theorem in linear algebra is used both to examine conditions in which the derived variables take a specially simple form and lead to reduced computations. Examples are discussed of medical and psychological investigations in which the method has aided interpretation.

Statistics and ProbabilityApplied MathematicsDesign matrixComputational MathematicsComputational Theory and MathematicsConditional independenceLinear predictor functionLinear algebraCalculusApplied mathematicsMarginal distributionCanonical correlationLinear combinationIndependence (probability theory)MathematicsComputational Statistics & Data Analysis
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A Monte Carlo study comparing PIV, ULS and DWLS in the estimation of dichotomous confirmatory factor analysis

2012

We conducted a Monte Carlo study to investigate the performance of the polychoric instrumental variable estimator (PIV) in comparison to unweighted least squares (ULS) and diagonally weighted least squares (DWLS) in the estimation of a confirmatory factor analysis model with dichotomous indicators. The simulation involved 144 conditions (1,000 replications per condition) that were defined by a combination of (a) two types of latent factor models, (b) four sample sizes (100, 250, 500, 1,000), (c) three factor loadings (low, moderate, strong), (d) three levels of non-normality (normal, moderately, and extremely non-normal), and (e) whether the factor model was correctly specified or misspecif…

Statistics and ProbabilityArts and Humanities (miscellaneous)Sample size determinationMonte Carlo methodStatisticsInstrumental variable estimatorGeneral MedicinePolychoric correlationLeast squaresGeneral PsychologyConfirmatory factor analysisFactor analysisMathematicsBritish Journal of Mathematical and Statistical Psychology
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On Independent Component Analysis with Stochastic Volatility Models

2017

Consider a multivariate time series where each component series is assumed to be a linear mixture of latent mutually independent stationary time series. Classical independent component analysis (ICA) tools, such as fastICA, are often used to extract latent series, but they don't utilize any information on temporal dependence. Also financial time series often have periods of low and high volatility. In such settings second order source separation methods, such as SOBI, fail. We review here some classical methods used for time series with stochastic volatility, and suggest modifications of them by proposing a family of vSOBI estimators. These estimators use different nonlinearity functions to…

Statistics and ProbabilityAutoregressive conditional heteroskedasticity01 natural sciencesQA273-280GARCH model010104 statistics & probabilityblind source separation0502 economics and businessSource separationEconometricsApplied mathematics0101 mathematics050205 econometrics MathematicsStochastic volatilitymultivariate time seriesApplied MathematicsStatistics05 social sciencesAutocorrelationEstimatorIndependent component analysisHA1-4737nonlinear autocorrelationFastICAStatistics Probability and UncertaintyVolatility (finance)Probabilities. Mathematical statistics
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Automatic variable selection for exposure-driven propensity score matching with unmeasured confounders.

2020

Multivariable model building for propensity score modeling approaches is challenging. A common propensity score approach is exposure-driven propensity score matching, where the best model selection strategy is still unclear. In particular, the situation may require variable selection, while it is still unclear if variables included in the propensity score should be associated with the exposure and the outcome, with either the exposure or the outcome, with at least the exposure or with at least the outcome. Unmeasured confounders, complex correlation structures, and non-normal covariate distributions further complicate matters. We consider the performance of different modeling strategies in …

Statistics and ProbabilityBiometryModels StatisticalComputer scienceModel selectionFeature selectionGeneral MedicineVariance (accounting)01 natural sciencesOutcome (game theory)Correlation010104 statistics & probability03 medical and health sciencesAutomation0302 clinical medicineCovariatePropensity score matchingStatisticsMultivariate Analysis030212 general & internal medicine0101 mathematicsStatistics Probability and UncertaintyPropensity ScoreCounterexampleBiometrical journal. Biometrische ZeitschriftREFERENCES
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Response functions in multicomponent Luttinger liquids

2012

We derive an analytic expression for the zero temperature Fourier transform of the density-density correlation function of a multicomponent Luttinger liquid with different velocities. By employing Schwinger identity and a generalized Feynman identity exact integral expressions are derived, and approximate analytical forms are given for frequencies close to each component singularity. We find power-like singularities and compute the corresponding exponents. Numerical results are shown for the case of three components.

Statistics and ProbabilityBosonizationFOS: Physical sciences01 natural sciences010305 fluids & plasmassymbols.namesakeIdentity (mathematics)Condensed Matter - Strongly Correlated ElectronsSingularityCorrelation functionLuttinger liquid0103 physical sciencesFeynman diagramLuttinger liquids (theory)010306 general physics71.10.Pm 02.30.Nw 02.30.UuMathematical physicsPhysicsStrongly Correlated Electrons (cond-mat.str-el)Statistical and Nonlinear PhysicsFourier transformsymbolsGravitational singularityStatistics Probability and Uncertaintybosonization[PHYS.COND.CM-SCE]Physics [physics]/Condensed Matter [cond-mat]/Strongly Correlated Electrons [cond-mat.str-el]
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