Search results for "Probability Theory"

showing 10 items of 269 documents

Reassessing Accuracy Rates of Median Decisions

2007

We show how Bruno de Finetti''s fundamental theorem of prevision has computable applications in statistical problems that involve only partial information. Specifically, we assess accuracy rates for median decision procedures used in the radiological diagnosis of asbestosis. Conditional exchangeability of individual radiologists'' diagnoses is recognized as more appropriate than independence which is commonly presumed. The FTP yields coherent bounds on probabilities of interest when available information is insufficient to determine a complete distribution. Further assertions that are natural to the problem motivate a partial ordering of conditional probabilities, extending the computation …

Statistics and ProbabilityFOS: Computer and information sciencesFundamental theorem of previsionComputer scienceGeneral MathematicsComputationSpecificity.Quadratic programmingStatistics - ApplicationsMedical diagnosiSensitivityLinear programmingProbability boundApplications (stat.AP)Second opinionQuadratic programmingMedical diagnosisIndependence (probability theory)Fundamental theoremAsbestosiConditional probabilityDistribution (mathematics)ExchangeabilityPredictivevalueStatistics Probability and UncertaintyPartially ordered setCoherenceMathematical economics
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Multivariate nonparametric estimation of the Pickands dependence function using Bernstein polynomials

2017

Abstract Many applications in risk analysis require the estimation of the dependence among multivariate maxima, especially in environmental sciences. Such dependence can be described by the Pickands dependence function of the underlying extreme-value copula. Here, a nonparametric estimator is constructed as the sample equivalent of a multivariate extension of the madogram. Shape constraints on the family of Pickands dependence functions are taken into account by means of a representation in terms of Bernstein polynomials. The large-sample theory of the estimator is developed and its finite-sample performance is evaluated with a simulation study. The approach is illustrated with a dataset of…

Statistics and ProbabilityFOS: Computer and information sciencesMultivariate statisticsNONPARAMETRIC ESTIMATIONMULTIVARIATE MAX-STABLE DISTRIBUTION01 natural sciencesCopula (probability theory)Methodology (stat.ME)010104 statistics & probabilityStatisticsStatistics::Methodology0101 mathematicsExtreme-value copulaEXTREMAL DEPENDENCEEXTREMEVALUE COPULA[SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces environmentStatistics - MethodologyComputingMilieux_MISCELLANEOUSMathematics[SDU.OCEAN]Sciences of the Universe [physics]/Ocean AtmosphereApplied Mathematics010102 general mathematicsNonparametric statisticsEstimatorExtremal dependenceHEAVY RAINFALLBernstein polynomialBERNSTEIN POLYNOMIALS EXTREMAL DEPENDENCE EXTREMEVALUE COPULA HEAVY RAINFALL NONPARAMETRIC ESTIMATION MULTIVARIATE MAX-STABLE DISTRIBUTION PICKANDS DEPENDENCE FUNCTION13. Climate actionDependence functionStatistics Probability and UncertaintyMaximaSettore SECS-S/01 - StatisticaBERNSTEIN POLYNOMIALSPICKANDS DEPENDENCE FUNCTION
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Fractional Brownian motion and Martingale-differences

2004

Abstract We generalize a result of Sottinen (Finance Stochastics 5 (2001) 343) by proving an approximation theorem for the fractional Brownian motion, with H> 1 2 , using martingale-differences.

Statistics and ProbabilityGeometric Brownian motionFractional Brownian motionMathematics::ProbabilityDiffusion processReflected Brownian motionMathematical analysisBrownian excursionStatistics Probability and UncertaintyHeavy traffic approximationMartingale (probability theory)Martingale representation theoremMathematicsStatistics & Probability Letters
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p-harmonic coordinates for Hölder metrics and applications

2017

We show that on any Riemannian manifold with H¨older continuous metric tensor, there exists a p-harmonic coordinate system near any point. When p = n this leads to a useful gauge condition for regularity results in conformal geometry. As applications, we show that any conformal mapping between manifolds having C α metric tensors is C 1+α regular, and that a manifold with W1,n ∩ C α metric tensor and with vanishing Weyl tensor is locally conformally flat if n ≥ 4. The results extend the works [LS14, LS15] from the case of C 1+α metrics to the H¨older continuous case. In an appendix, we also develop some regularity results for overdetermined elliptic systems in divergence form. peerReviewed

Statistics and ProbabilityHarmonic coordinatesSmoothness (probability theory)010102 general mathematicsMathematical analysista111p-harmonic coordinatesHölder metrics01 natural sciencesGeometry and Topology0101 mathematicsStatistics Probability and UncertaintyAnalysisMathematicsCommunications in Analysis and Geometry
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A weighted combined effect measure for the analysis of a composite time-to-first-event endpoint with components of different clinical relevance

2018

Composite endpoints combine several events within a single variable, which increases the number of expected events and is thereby meant to increase the power. However, the interpretation of results can be difficult as the observed effect for the composite does not necessarily reflect the effects for the components, which may be of different magnitude or even point in adverse directions. Moreover, in clinical applications, the event types are often of different clinical relevance, which also complicates the interpretation of the composite effect. The common effect measure for composite endpoints is the all-cause hazard ratio, which gives equal weight to all events irrespective of their type …

Statistics and ProbabilityHazard (logic)EpidemiologyEndpoint Determination01 natural sciencesMeasure (mathematics)WIN RATIO010104 statistics & probability03 medical and health sciences0302 clinical medicineResamplingStatisticstime-to-eventHumansComputer Simulation030212 general & internal medicinerelevance weighting0101 mathematicsParametric statisticsEvent (probability theory)MathematicsProportional Hazards Modelsclinical trialsHazard ratiocomposite endpointWeightingPRIORITIZED OUTCOMESTRIALSData Interpretation StatisticalMULTISTATE MODELSINFERENCENull hypothesisMonte Carlo MethodStatistics in Medicine
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PROBABILISTIC QUANTIFICATION OF HAZARDS: A METHODOLOGY USING SMALL ENSEMBLES OF PHYSICS-BASED SIMULATIONS AND STATISTICAL SURROGATES

2015

This paper presents a novel approach to assessing the hazard threat to a locale due to a large volcanic avalanche. The methodology combines: (i) mathematical modeling of volcanic mass flows; (ii) field data of avalanche frequency, volume, and runout; (iii) large-scale numerical simulations of flow events; (iv) use of statistical methods to minimize computational costs, and to capture unlikely events; (v) calculation of the probability of a catastrophic flow event over the next T years at a location of interest; and (vi) innovative computational methodology to implement these methods. This unified presentation collects elements that have been separately developed, and incorporates new contri…

Statistics and ProbabilityHazard (logic)Volcanic hazardsgeographyControl and Optimizationgeography.geographical_feature_categoryProcess (engineering)Probabilistic logicHazard analysiscomputer.software_genreFlow (mathematics)VolcanoModeling and SimulationEconometricsDiscrete Mathematics and CombinatoricsEnvironmental scienceData miningcomputerEvent (probability theory)International Journal for Uncertainty Quantification
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Sample-size calculation and reestimation for a semiparametric analysis of recurrent event data taking robust standard errors into account

2014

In some clinical trials, the repeated occurrence of the same type of event is of primary interest and the Andersen-Gill model has been proposed to analyze recurrent event data. Existing methods to determine the required sample size for an Andersen-Gill analysis rely on the strong assumption that all heterogeneity in the individuals' risk to experience events can be explained by known covariates. In practice, however, this assumption might be violated due to unknown or unmeasured covariates affecting the time to events. In these situations, the use of a robust variance estimate in calculating the test statistic is highly recommended to assure the type I error rate, but this will in turn decr…

Statistics and ProbabilityInflationComputer sciencemedia_common.quotation_subjectRobust statisticsGeneral MedicineVariance (accounting)Sample size determinationStatisticsCovariateTest statisticEconometricsStatistics Probability and UncertaintyType I and type II errorsEvent (probability theory)media_commonBiometrical Journal
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k-Step shape estimators based on spatial signs and ranks

2010

In this paper, the shape matrix estimators based on spatial sign and rank vectors are considered. The estimators considered here are slight modifications of the estimators introduced in Dümbgen (1998) and Oja and Randles (2004) and further studied for example in Sirkiä et al. (2009). The shape estimators are computed using pairwise differences of the observed data, therefore there is no need to estimate the location center of the data. When the estimator is based on signs, the use of differences also implies that the estimators have the so called independence property if the estimator, that is used as an initial estimator, has it. The influence functions and limiting distributions of the es…

Statistics and ProbabilityInfluence functionCovariance matrixApplied MathematicsAffiinisti ekvivarianttitehokkuusspatiaalinen järjestyslukuEstimatorSpatial signEfficiencyM-estimatorEfficient estimatorinfluenssifunktioExtremum estimatorHeavy-tailed distributionStatisticsAffine equivarianceStatistics Probability and UncertaintySpatial rankInvariant estimatorIndependence (probability theory)Mathematicsspatiaalinen merkki
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Fractional calculus approach to the statistical characterization of random variables and vectors

2009

Fractional moments have been investigated by many authors to represent the density of univariate and bivariate random variables in different contexts. Fractional moments are indeed important when the density of the random variable has inverse power-law tails and, consequently, it lacks integer order moments. In this paper, starting from the Mellin transform of the characteristic function and by fractional calculus method we present a new perspective on the statistics of random variables. Introducing the class of complex moments, that include both integer and fractional moments, we show that every random variable can be represented within this approach, even if its integer moments diverge. A…

Statistics and ProbabilityMellin transformStatistical Mechanics (cond-mat.stat-mech)Characteristic function (probability theory)Multivariate distributionMultivariate random variableMathematical analysisFOS: Physical sciencesMoment-generating functionCondensed Matter PhysicsFractional calculusFractional and complex moments; Multivariate distributions; Power-law tails; Inverse Mellin transformFractional and complex momentIngenieurwissenschaftenApplied mathematicsddc:620Inverse Mellin transformSettore ICAR/08 - Scienza Delle CostruzioniRandom variableCondensed Matter - Statistical MechanicsMathematicsInteger (computer science)Taylor expansions for the moments of functions of random variablesPower-law tail
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Affine-invariant rank tests for multivariate independence in independent component models

2016

We consider the problem of testing for multivariate independence in independent component (IC) models. Under a symmetry assumption, we develop parametric and nonparametric (signed-rank) tests. Unlike in independent component analysis (ICA), we allow for the singular cases involving more than one Gaussian independent component. The proposed rank tests are based on componentwise signed ranks, à la Puri and Sen. Unlike the Puri and Sen tests, however, our tests (i) are affine-invariant and (ii) are, for adequately chosen scores, locally and asymptotically optimal (in the Le Cam sense) at prespecified densities. Asymptotic local powers and asymptotic relative efficiencies with respect to Wilks’…

Statistics and ProbabilityMultivariate statisticssingular information matricesRank (linear algebra)Gaussianuniform local asymptotic02 engineering and technology01 natural sciencesdistribution-free testsCombinatoricstests for multivariate independence010104 statistics & probabilitysymbols.namesakenormaalius0202 electrical engineering electronic engineering information engineeringApplied mathematics0101 mathematicsStatistique mathématiqueIndependence (probability theory)Parametric statisticsMathematicsDistribution-free testsuniform local asymptotic normalityNonparametric statistics020206 networking & telecommunicationsIndependent component analysisrank testsAsymptotically optimal algorithmsymbolsindependent component models62H1562G35Statistics Probability and UncertaintyUniform local asymptotic normality62G10
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