Search results for "probability"

showing 10 items of 3417 documents

Phase transformation kinetics in d-dimensional grains-containing systems: diffusion-type model

1998

Abstract An analytical approach to the phase transformation in d-dimensional grains-containing complex systems is offered. It is based on considering the mechanism of surface material exchange among neighbouring grains as the so-called state-dependent diffusion process, where the diffusion function is related to the magnitude of the grain boundary. The approach proposed deals with the kinetics of that ensemble under circumstances of a volume increase of the new phase or microstructure. Probabilistic characteristics of the process are derived and analyzed. A comparison with 2D modelling of similar kind is presented for the 3D case, and some possible practical realizations of the situation un…

Statistics and ProbabilityGrain growthMaterials scienceTransformation (function)Diffusion processPhase (matter)Complex systemThermodynamicsGrain boundary diffusion coefficientGrain boundaryDiffusion (business)Condensed Matter PhysicsPhysica A: Statistical Mechanics and its Applications
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On the derivation of a linear Boltzmann equation from a periodic lattice gas

2004

We consider the problem of deriving the linear Boltzmann equation from the Lorentz process with hard spheres obstacles. In a suitable limit (the Boltzmann-Grad limit), it has been proved that the linear Boltzmann equation can be obtained when the position of obstacles are Poisson distributed, while the validation fails, also for the "correct" ratio between obstacle size and lattice parameter, when they are distributed on a purely periodic lattice, because of the existence of very long free trajectories. Here we validate the linear Boltzmann equation, in the limit when the scatterer's radius epsilon vanishes, for a family of Lorentz processes such that the obstacles have a random distributio…

Statistics and ProbabilityHPP modelApplied MathematicsMathematical analysisLattice Boltzmann methodsHard spheresLattice gaBoltzmann equationLattice gasLattice constantModelling and SimulationModeling and SimulationLattice (order)Linear Boltzmann equationMarkov proceMarkov processJump processScalingLinear equationMathematicsStochastic Processes and their Applications
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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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Efficient spatial designs using Hausdorff distances and Bayesian optimization

2021

An iterative Bayesian optimisation technique is presented to find spatial designs of data that carry much information. We use the decision theoretic notion of value of information as the design criterion. Gaussian process surrogate models enable fast calculations of expected improvement for a large number of designs, while the full-scale value of information evaluations are only done for the most promising designs. The Hausdorff distance is used to model the similarity between designs in the surrogate Gaussian process covariance representation, and this allows the suggested algorithm to learn across different designs. We study properties of the Bayesian optimisation design algorithm in a sy…

Statistics and ProbabilityHausdorff distancebayesilainen menetelmäBayesian optimizationHausdorff spacepäätöksentukijärjestelmätBayesian optimisationpaikkatietoanalyysivalue of informationValue of informationHausdorff distanceoptimointiStatistics Probability and UncertaintyAlgorithmMathematics
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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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Generating survival times to simulate Cox proportional hazards models

2005

Simulation studies present an important statistical tool to investigate the performance, properties and adequacy of statistical models in pre-specified situations. One of the most important statistical models in medical research is the proportional hazards model of Cox. In this paper, techniques to generate survival times for simulation studies regarding Cox proportional hazards models are presented. A general formula describing the relation between the hazard and the corresponding survival time of the Cox model is derived, which is useful in simulation studies. It is shown how the exponential, the Weibull and the Gompertz distribution can be applied to generate appropriate survival times f…

Statistics and ProbabilityHazard (logic)Exponential distributionEpidemiologyComputer scienceProportional hazards modelStatisticsEconometricsStatistical modelSurvival analysisGompertz distributionExponential functionWeibull distributionStatistics in Medicine
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Using Statistical and Computer Models to Quantify Volcanic Hazards

2009

Risk assessment of rare natural hazards, such as large volcanic block and ash or pyroclastic flows, is addressed. Assessment is approached through a combination of computer modeling, statistical modeling, and extreme-event probability computation. A computer model of the natural hazard is used to provide the needed extrapolation to unseen parts of the hazard space. Statistical modeling of the available data is needed to determine the initializing distribution for exercising the computer model. In dealing with rare events, direct simulations involving the computer model are prohibitively expensive. The solution instead requires a combination of adaptive design of computer model approximation…

Statistics and ProbabilityHazard (logic)Risk analysisVolcanic hazardsComputer scienceApplied MathematicsComputationInitializationStatistical modelcomputer.software_genreModeling and SimulationNatural hazardRare eventsData miningcomputerTechnometrics
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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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Latent class models for multiple ordered categorical health data: testing violation of the local independence assumption

2019

Latent class models are now widely applied in health economics to analyse heterogeneity in multiple outcomes generated by subgroups of individuals who vary in unobservable characteristics, such as genetic information or latent traits. These models rely on the underlying assumption that associations between observed outcomes are due to their relationship to underlying subgroups, captured in these models by conditioning on a set of latent classes. This implies that outcomes are locally independent within a class. Local independence assumption, however, is sometimes violated in practical applications when there is uncaptured unobserved heterogeneity resulting in residual associations between c…

Statistics and ProbabilityHealthcare utilizationEconomics and EconometricsClass (set theory)Categorical health dataEconomicsComputer science05 social sciencesContext (language use)UnobservableOutcome (probability)Health insuranceLocal independence assumptionMathematics (miscellaneous)0502 economics and businessEconometricsLatent class model050207 economicsLocal independenceSet (psychology)Association (psychology)Categorical variable14 EconomicsSocial Sciences (miscellaneous)050205 econometrics Empirical Economics
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Premature conclusions about the signal‐to‐noise ratio in structural equation modeling research : A commentary on Yuan and Fang (2023)

2023

In a recent article published in this journal, Yuan and Fang (British Journal of Mathematical and Statistical Psychology, 2023) suggest comparing structural equation modeling (SEM), also known as covariance-based SEM (CB-SEM), estimated by normal-distribution-based maximum likelihood (NML), to regression analysis with (weighted) composites estimated by least squares (LS) in terms of their signal-to-noise ratio (SNR). They summarize their findings in the statement that “[c]ontrary to the common belief that CB-SEM is the preferred method for the analysis of observational data, this article shows that regression analysis via weighted composites yields parameter estimates with much smaller stan…

Statistics and ProbabilityHenseler-Ogasawara specificationeffect sizetilastomenetelmätpartial least squares structural equation modelingGeneral MedicinerakenneyhtälömallitregressioanalyysiArts and Humanities (miscellaneous)sum scorescovariance-based structural equation modelingcomposite modelregression analysis with weighted compositesfactor score regressionGeneral Psychology
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