Search results for " Probability"

showing 10 items of 2176 documents

Wing morphometrics as a possible tool for the diagnosis of the Ceratitis fasciventris, C. anonae, C. rosa complex (Diptera, Tephritidae)

2015

Abstract Previous attempts to resolve the Ceratitis FAR complex (Ceratitis fasciventris, Ceratitis anonae, Ceratitis rosa, Diptera, Tephritidae) showed contrasting results and revealed the occurrence of five microsatellite genotypic clusters (A, F1, F2, R1, R2). In this paper we explore the potential of wing morphometrics for the diagnosis of FAR morphospecies and genotypic clusters. We considered a set of 227 specimens previously morphologically identified and genotyped at 16 microsatellite loci. Seventeen wing landmarks and 6 wing band areas were used for morphometric analyses. Permutational multivariate analysis of variance detected significant differences both across morphospecies and g…

Species complexInsectaArthropodaDipteraAnimaliarosaTephritidaeCeratitis fasciventrisAnimaliaCeratitisCeratitisBiologyfasciventrisEcology Evolution Behavior and Systematicsintegrative taxonomyMorphometricscryptic speciesWingbiologyEcologyDipteraTephritidaeanonaeCeratitis rosaposterior group membership probabilitywing morphometricsCeratitis rosabiology.organism_classificationCeratitis fasciventrisAnimaliaEvolutionary biologyfruit fliesPrincipal component analysista1181MicrosatellitePosterior Group Membership ProbabilityCeratitis anonaeAnimal Science and ZoologyResearch Article
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Transitivity in coherence-based probability logic

2016

We study probabilistically informative (weak) versions of transitivity by using suitable definitions of defaults and negated defaults in the setting of coherence and imprecise probabilities. We represent p-consistent sequences of defaults and/or negated defaults by g-coherent imprecise probability assessments on the respective sequences of conditional events. Moreover, we prove the coherent probability propagation rules for Weak Transitivity and the validity of selected inference patterns by proving p-entailment of the associated knowledge bases. Finally, we apply our results to study selected probabilistic versions of classical categorical syllogisms and construct a new version of the squa…

Square of oppositionSettore MAT/06 - Probabilita' E Statistica MatematicaTheoretical computer scienceLogicInferenceSquare of oppositionProbability logicSettore M-FIL/02 - Logica E Filosofia Della Scienza02 engineering and technologyComputer Science::Artificial Intelligence0603 philosophy ethics and religion0202 electrical engineering electronic engineering information engineeringGeneralized coherenceCategorical variableMathematicsTransitivityTransitive relationApplied MathematicsDefaultProbabilistic logicSyllogism06 humanities and the artsCoherence (statistics)Settore MAT/01 - Logica MatematicaImprecise probabilityp-EntailmentSyllogism060302 philosophyImprecise probabilityp-Consistency020201 artificial intelligence & image processingCoherenceAlgorithmJournal of Applied Logic
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Square of Opposition Under Coherence

2016

Various semantics for studying the square of opposition have been proposed recently. So far, only (Gilio et al., 2016) studied a probabilistic version of the square where the sentences were interpreted by (negated) defaults. We extend this work by interpreting sentences by imprecise (set-valued) probability assessments on a sequence of conditional events. We introduce the acceptability of a sentence within coherence-based probability theory. We analyze the relations of the square in terms of acceptability and show how to construct probabilistic versions of the square of opposition by forming suitable tripartitions. Finally, as an application, we present a new square involving generalized qu…

Square of oppositionSettore MAT/06 - Probabilita' E Statistica Matematicat-coherenceGeneralized quantifierSquare of oppositionSettore M-FIL/02 - Logica E Filosofia Della Scienza02 engineering and technology01 natural sciencesSquare (algebra)OpticsProbability theory0202 electrical engineering electronic engineering information engineering0101 mathematicsMathematicsbusiness.industry010102 general mathematicsProbabilistic logicCoherence (statistics)Imprecise probabilityconditional eventimprecise probabilityAlgebrag-coherencegeneralized quantifier020201 artificial intelligence & image processingbusinessSentenceacceptance
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A Bayesian analysis of the thermal challenge problem

2008

Abstract A major question for the application of computer models is Does the computer model adequately represent reality? Viewing the computer models as a potentially biased representation of reality, Bayarri et al. [M. Bayarri, J. Berger, R. Paulo, J. Sacks, J. Cafeo, J. Cavendish, C. Lin, J. Tu, A framework for validation of computer models, Technometrics 49 (2) (2007) 138–154] develop the simulator assessment and validation engine ( SAVE ) method as a general framework for answering this question. In this paper, we apply the SAVE method to the challenge problem which involves a thermal computer model designed for certain devices. We develop a statement of confidence that the devices mode…

Statement (computer science)Stochastic processComputer sciencebusiness.industryMechanical EngineeringBayesian probabilityComputational MechanicsGeneral Physics and AstronomyUnbiased EstimationComputer Science Applicationssymbols.namesakeMechanics of MaterialssymbolsArtificial intelligenceRepresentation (mathematics)businessGaussian processSimulationComputer Methods in Applied Mechanics and Engineering
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Stationary Probability Characteristics of Superdiffusion

2006

Stationary Probability
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Stationary and non-stationary probability density function for non-linear oscillators

1997

A method for the evaluation of the stationary and non-stationary probability density function of non-linear oscillators subjected to random input is presented. The method requires the approximation of the probability density function of the response in terms of C-type Gram-Charlier series expansion. By applying the weighted residual method, the Fokker-Planck equation is reduced to a system of non-linear first order ordinary differential equations, where the unknowns are the coefficients of the series expansion. Furthermore, the relationships between the A-type and C-type Gram-Charlier series coefficient are derived.

Stationary distributionCharacteristic function (probability theory)Applied MathematicsMechanical EngineeringMathematical analysisProbability density functionStationary sequencestochastic non-linear dynamics; Gram-Charlier expansions; approximate probability density functionGram-Charlier expansionsMechanics of Materialsstochastic non-linear dynamicsProbability distributionProbability-generating functionapproximate probability density functionSeries expansionRandom variableMathematics
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Non-Gaussian probability density function of SDOF linear structures under wind actions

1998

Abstract Wind velocity is usually analytically described adding a static mean term to a zero mean fluctuation stationary process. The corresponding aerodynamic alongwind force acting on a single degree of freedom (SDOF) structure can be considered as a sum of three terms proportional to the mean wind velocity, to the product between mean and fluctuating part of the wind velocity and to the square power of the fluctuating wind velocity, respectively. The latter term, often neglected in the literature, is responsible for the non-Gaussian behaviour of the response. In this paper a method for the evaluation of the stationary probability density function of SDOF structures subjected to non-Gauss…

Stationary processStationary distributionSeries (mathematics)Renewable Energy Sustainability and the EnvironmentMechanical EngineeringGaussianMathematical analysisProbability density functionWind speedAerodynamic forcesymbols.namesakesymbolsSeries expansionCivil and Structural EngineeringMathematicsAlongwind response; Probability density function; Non-Gaussian stochastic analysis
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$L_2$-variation of L\'{e}vy driven BSDEs with non-smooth terminal conditions

2016

We consider the $L_2$-regularity of solutions to backward stochastic differential equations (BSDEs) with Lipschitz generators driven by a Brownian motion and a Poisson random measure associated with a L\'{e}vy process $(X_t)_{t\in[0,T]}$. The terminal condition may be a Borel function of finitely many increments of the L\'{e}vy process which is not necessarily Lipschitz but only satisfies a fractional smoothness condition. The results are obtained by investigating how the special structure appearing in the chaos expansion of the terminal condition is inherited by the solution to the BSDE.

Statistics and Probability$L_{2}$-regularityPure mathematicsSmoothness (probability theory)Malliavin calculus010102 general mathematicsChaos expansionPoisson random measureFunction (mathematics)Lipschitz continuityMalliavin calculus01 natural sciencesLévy process010104 statistics & probabilityStochastic differential equationMathematics::ProbabilityLévy processesbackward stochastic differential equations0101 mathematicsL 2 -regularityBrownian motionMathematics - ProbabilityMathematics
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Conditional convex orders and measurable martingale couplings

2014

Strassen's classical martingale coupling theorem states that two real-valued random variables are ordered in the convex (resp.\ increasing convex) stochastic order if and only if they admit a martingale (resp.\ submartingale) coupling. By analyzing topological properties of spaces of probability measures equipped with a Wasserstein metric and applying a measurable selection theorem, we prove a conditional version of this result for real-valued random variables conditioned on a random element taking values in a general measurable space. We also provide an analogue of the conditional martingale coupling theorem in the language of probability kernels and illustrate how this result can be appli…

Statistics and Probability01 natural sciencesStochastic ordering010104 statistics & probabilitysymbols.namesakeMathematics::ProbabilityStrassen algorithmWasserstein metricmartingale couplingvektorit (matematiikka)FOS: MathematicsApplied mathematics0101 mathematicsstokastiset prosessitMathematicsProbability measurekytkentäconvex stochastic ordermatematiikka010102 general mathematicsProbability (math.PR)Random elementMarkov chain Monte Carloconditional couplingincreasing convex stochastic orderpointwise couplingsymbols60E15probability kernelMartingale (probability theory)Random variableMathematics - Probability
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Author response to the contributors to the discussion on “A critical evaluation of the current ‘p -value controversy’”

2017

Statistics and Probability010104 statistics & probability03 medical and health sciences0302 clinical medicineMEDLINE030212 general & internal medicineGeneral Medicine0101 mathematicsStatistics Probability and UncertaintyCurrent (fluid)Positive economicsPsychology01 natural sciencesBiometrical Journal
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