Search results for "statistical [methods]"

showing 10 items of 1664 documents

A spatial analysis of Italian unemployment differences

2008

Using spatial econometric models, this paper focuses attention on the spatial structure of provincial unemployment disparities of Italian provinces for the year 2003. On the basis of findings from the economic literature and of the available socio-economic data, various model specifications including supply- and demand-side variables are tested. Further we use ESDA analysis as equivalent to integration analysis on time series; therefore it is applied on each variable, dependent and independent, involved in the statistical model. The suggestions of ESDA lead us to the most adequate statistical model, which estimates indicate that there is a significant degree of neighbouring effect (i.e. pos…

Statistics and ProbabilitySpatial correlationSpatial structuremedia_common.quotation_subjectESDAStatistical modelSDG 8 - Decent Work and Economic Growth/dk/atira/pure/sustainabledevelopmentgoals/decent_work_and_economic_growthMunicipal levelEconometric modelVariable (computer science)Spatial modelsUnemploymentEconometricsEconomicsCommon spatial patternRegional unemploymentStatistics Probability and Uncertaintymedia_common
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Adaptive Modifications of Hypotheses After an Interim Analysis

2001

It is investigated how one can modify hypotheses in a trial after an interim analysis such that the type I error rate is controlled. If only a global statement is desired, a solution was given by Bauer (1989). For a general multiple testing problem, Kieser, Bauer and Lehmacher (1999) and Bauer and Kieser (1999) gave solutions, by means of which the initial set of hypotheses can be reduced after the interim analysis. The same techniques can be applied to obtain more flexible strategies, as changing weights of hypotheses, changing an a priori order, or even including new hypotheses. It is emphasized that the application of these methods requires very careful planning of a trial as well as a c…

Statistics and ProbabilityStatement (computer science)Mathematical optimizationGeneral MedicineInterim analysisWeightingMultiple comparisons problemA priori and a posterioriStatistics Probability and UncertaintySet (psychology)AlgorithmStatistical hypothesis testingType I and type II errorsMathematicsBiometrical Journal
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Dynamics of a financial market index after a crash

2002

We discuss the statistical properties of index returns in a financial market just after a major market crash. The observed non-stationary behavior of index returns is characterized in terms of the exceedances over a given threshold. This characterization is analogous to the Omori law originally observed in geophysics. By performing numerical simulations and theoretical modelling, we show that the nonlinear behavior observed in real market crashes cannot be described by a GARCH(1,1) model. We also show that the time evolution of the Value at Risk observed just after a major crash is described by a power-law function lacking a typical scale.

Statistics and ProbabilityStatistical Finance (q-fin.ST)Index (economics)Actuarial scienceStatistical Mechanics (cond-mat.stat-mech)EconophysicsScale (ratio)Autoregressive conditional heteroskedasticityFinancial marketFOS: Physical sciencesQuantitative Finance - Statistical FinanceCrashFunction (mathematics)Condensed Matter PhysicsFOS: Economics and businessEconophysicsFinancial marketsCrashesValue at RiskEconometricsEconomicsCondensed Matter - Statistical MechanicsValue at riskPhysica A: Statistical Mechanics and its Applications
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Volatility in Financial Markets: Stochastic Models and Empirical Results

2002

We investigate the historical volatility of the 100 most capitalized stocks traded in US equity markets. An empirical probability density function (pdf) of volatility is obtained and compared with the theoretical predictions of a lognormal model and of the Hull and White model. The lognormal model well describes the pdf in the region of low values of volatility whereas the Hull and White model better approximates the empirical pdf for large values of volatility. Both models fails in describing the empirical pdf over a moderately large volatility range.

Statistics and ProbabilityStatistical Finance (q-fin.ST)Statistical Mechanics (cond-mat.stat-mech)Stochastic modellingEconophysicFinancial marketFOS: Physical sciencesQuantitative Finance - Statistical FinanceStatistical and Nonlinear PhysicsProbability density functionStochastic processeCondensed Matter PhysicsEmpirical probabilitySettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)FOS: Economics and businessVolatilityLognormal modelHullEconomicsEconometricsMathematical PhysicVolatility (finance)Condensed Matter - Statistical Mechanics
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Inhomogeneity and complexity measures for spatial patterns

2002

In this work, we examine two different measures for inhomogeneity and complexity that are derived from non-extensive considerations à la Tsallis. Their performance is then tested on theoretically generated patterns. All measures are found to exhibit a most sensitive behaviour for Sierpinski carpets. The procedures here introduced provide us with new, powerful Tsallis’ tools for analysing the inhomogeneity and complexity of spatial patterns.

Statistics and ProbabilityStatistical Mechanics (cond-mat.stat-mech)Computer scienceFOS: Physical sciencesFísicaComplexityCondensed Matter PhysicsNon-extensive statisticsSierpinski triangleSpatial patternsSpatial ecologyStatistical physicsCondensed Matter - Statistical MechanicsCiencias ExactasPhysica A: Statistical Mechanics and its Applications
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Escape Times in Fluctuating Metastable Potential and Acceleration of Diffusion in Periodic Fluctuating Potentials

2004

The problems of escape from metastable state in randomly flipping potential and of diffusion in fast fluctuating periodic potentials are considered. For the overdamped Brownian particle moving in a piecewise linear dichotomously fluctuating metastable potential we obtain the mean first-passage time (MFPT) as a function of the potential parameters, the noise intensity and the mean rate of switchings of the dichotomous noise. We find noise enhanced stability (NES) phenomenon in the system investigated and the parameter region of the fluctuating potential where the effect can be observed. For the diffusion of the overdamped Brownian particle in a fast fluctuating symmetric periodic potential w…

Statistics and ProbabilityStatistical Mechanics (cond-mat.stat-mech)FOS: Physical sciencesSawtooth waveCondensed Matter PhysicsNoise (electronics)Fluctuating Metastable PotentialPiecewise linear functionClassical mechanicsMetastabilityPiecewiseEffective diffusion coefficientStatistical physicsDiffusion (business)Brownian motionCondensed Matter - Statistical MechanicsMathematics
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Geometric Entropies of Mixing (EOM)

2005

Trigonometric and trigonometric-algebraic entropies are introduced. Regularity increases the entropy and the maximal entropy is shown to result when a regular $n$-gon is inscribed in a circle. A regular $n$-gon circumscribing a circle gives the largest entropy reduction, or the smallest change in entropy from the state of maximum entropy which occurs in the asymptotic infinite $n$ limit. EOM are shown to correspond to minimum perimeter and maximum area in the theory of convex bodies, and can be used in the prediction of new inequalities for convex sets. These expressions are shown to be related to the phase functions obtained from the WKB approximation for Bessel and Hermite functions.

Statistics and ProbabilityStatistical Mechanics (cond-mat.stat-mech)Principle of maximum entropyConfiguration entropyMathematical analysisMaximum entropy thermodynamicsMin entropyFOS: Physical sciencesStatistical and Nonlinear PhysicsComputer Science::Computational GeometryQuantum relative entropyMaximum entropy probability distributionMathematics::Metric GeometryMathematical PhysicsEntropy rateJoint quantum entropyCondensed Matter - Statistical MechanicsMathematics
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Identification of clusters of companies in stock indices via Potts super-paramagnetic transitions

2000

The clustering of companies within a specific stock market index is studied by means of super-paramagnetic transitions of an appropriate q-state Potts model where the spins correspond to companies and the interactions are functions of the correlation coefficients determined from the time dependence of the companies' individual stock prices. The method is a generalization of the clustering algorithm by Domany et. al. to the case of anti-ferromagnetic interactions corresponding to anti-correlations. For the Dow Jones Industrial Average where no anti-correlations were observed in the investigated time period, the previous results obtained by different tools were well reproduced. For the Standa…

Statistics and ProbabilityStatistical Mechanics (cond-mat.stat-mech)SpinsFOS: Physical sciencesCondensed Matter PhysicsStock market indexParamagnetismCluster (physics)Statistical physicsCluster analysisStock (geology)Condensed Matter - Statistical MechanicsPotts modelMathematics
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Heavy-tailed targets and (ab)normal asymptotics in diffusive motion

2010

We investigate temporal behavior of probability density functions (pdfs) of paradigmatic jump-type and continuous processes that, under confining regimes, share common heavy-tailed asymptotic (target) pdfs. Namely, we have shown that under suitable confinement conditions, the ordinary Fokker-Planck equation may generate non-Gaussian heavy-tailed pdfs (like e.g. Cauchy or more general L\'evy stable distribution) in its long time asymptotics. For diffusion-type processes, our main focus is on their transient regimes and specifically the crossover features, when initially infinite number of the pdf moments drops down to a few or none at all. The time-dependence of the variance (if in existence…

Statistics and ProbabilityStatistical Mechanics (cond-mat.stat-mech)Stochastic processMathematical analysisCrossoverProbability (math.PR)Cauchy distributionFOS: Physical sciencesProbability and statisticsProbability density functionMathematical Physics (math-ph)Condensed Matter Physicslaw.inventionlawUniversal TimePhysics - Data Analysis Statistics and ProbabilityExponentFOS: MathematicsFokker–Planck equationCondensed Matter - Statistical MechanicsMathematical PhysicsMathematics - ProbabilityData Analysis Statistics and Probability (physics.data-an)Mathematics
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The Induced Smoothed lasso: A practical framework for hypothesis testing in high dimensional regression.

2020

This paper focuses on hypothesis testing in lasso regression, when one is interested in judging statistical significance for the regression coefficients in the regression equation involving a lot of covariates. To get reliable p-values, we propose a new lasso-type estimator relying on the idea of induced smoothing which allows to obtain appropriate covariance matrix and Wald statistic relatively easily. Some simulation experiments reveal that our approach exhibits good performance when contrasted with the recent inferential tools in the lasso framework. Two real data analyses are presented to illustrate the proposed framework in practice.

Statistics and ProbabilityStatistics::TheoryInduced smoothingEpidemiologyComputer scienceFeature selectionWald test01 natural sciencesasthma researchStatistics::Machine Learning010104 statistics & probability03 medical and health sciencesHealth Information ManagementLasso (statistics)Linear regressionsparse modelsStatistics::MethodologyComputer Simulation0101 mathematicssandwich formula030304 developmental biologyStatistical hypothesis testing0303 health sciencesCovariance matrixlung functionRegression analysisStatistics::Computationsparse modelResearch DesignAlgorithmSmoothingvariable selectionStatistical methods in medical research
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