Search results for "Probability Theory"

showing 10 items of 269 documents

Testing the “physical model concept” by soil loss data measured in Sicily

2012

The best possible model to predict the erosion from an area of land has been suggested to be a physical model of the area that has similar soil type, land use, size, shape, slope and erosive inputs. Therefore, a replicated plot has to be considered the best possible, unbiased, real world model. In this paper the physical model concept was tested by using soil loss data collected on plots of different length at the experimental station of Sparacia, in Sicily (South Italy). This investigation supported the conclusions that i) a coefficient of determination between measured and predicted soil loss values of 0.77 has to be considered as the best-case prediction scenario and ii) an uncalibrated …

Soil lossCoefficient of determinationScale (ratio)Land useSoil erosion plot measurements soil loss data physical modelErosionSettore AGR/08 - Idraulica Agraria E Sistemazioni Idraulico-ForestaliSoil scienceSoil typePlot (graphics)Earth-Surface ProcessesEvent (probability theory)MathematicsCATENA
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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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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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$L_2$-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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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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Independent component analysis based on symmetrised scatter matrices

2007

A new method for separating the mixtures of independent sources has been proposed recently in [Oja et al. (2006). Scatter matrices and independent component analysis. Austrian J. Statist., to appear]. This method is based on two scatter matrices with the so-called independence property. The corresponding method is now further examined. Simple simulation studies are used to compare the performance of so-called symmetrised scatter matrices in solving the independence component analysis problem. The results are also compared with the classical FastICA method. Finally, the theory is illustrated by some examples. peerReviewed

Statistics and ProbabilityApplied MathematicsIndependence propertyStatistical computationhajontamatriisitIndependent component analysisComputational MathematicsComputational Theory and MathematicsComponent analysisSimple (abstract algebra)CalculusSource separationFastICAApplied mathematicsICAIndependence (probability theory)MathematicsComputational Statistics & Data Analysis
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Sparse Sampling and Maximum Likelihood Estimation for Boolean Models

1991

A condition for practical independence of contact distribution functions in Boolean models is obtained. This result allows the authors to use maximum likelihcod methods, via sparse sampling, for estimating unknown parameters of an isotropic Boolean model. The second part of this paper is devoted to a simulation study of the proposed method. AMS classification: 60D05

Statistics and ProbabilityBiometricsBoolean modelIsotropySampling (statistics)General MedicineLikelihood-ratio testStatisticsMaximum satisfiability problemStatistics Probability and UncertaintyAlgorithmIndependence (probability theory)Standard Boolean modelMathematicsBiometrical Journal
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Response models for mixed binary and quantitative variables

1992

SUMMARY A number of special representations are considered for the joint distribution of qualitative, mostly binary, and quantitative variables. In addition to the conditional Gaussian models and to conditional Gaussian regression chain models some emphasis is placed on models derived from an underlying multivariate normal distribution and on models in which discrete probabilities are specified linearly in terms of unknown parameters. The possibilities for choosing between the models empirically are examined, as well as the testing of independence and conditional independence and the estimation of parameters. Often the testing of independence is exactly or nearly the same for a number of di…

Statistics and ProbabilityChain rule (probability)Applied MathematicsGeneral MathematicsMultivariate normal distributionConditional probability distributionAgricultural and Biological Sciences (miscellaneous)Discriminative modelConditional independenceJoint probability distributionStatisticsStatistics Probability and UncertaintyGeneral Agricultural and Biological SciencesConditional varianceIndependence (probability theory)MathematicsBiometrika
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Opportunities and challenges of combined effect measures based on prioritized outcomes

2013

Many authors have proposed different approaches to combine multiple endpoints in a univariate outcome measure in the literature. In case of binary or time-to-event variables, composite endpoints, which combine several event types within a single event or time-to-first-event analysis are often used to assess the overall treatment effect. A main drawback of this approach is that the interpretation of the composite effect can be difficult as a negative effect in one component can be masked by a positive effect in another. Recently, some authors proposed more general approaches based on a priority ranking of outcomes, which moreover allow to combine outcome variables of different scale levels. …

Statistics and ProbabilityClinical Trials as TopicEpidemiologyUnivariatecomputer.software_genreOutcome (game theory)Treatment OutcomeRankingScale (social sciences)Component (UML)Outcome Assessment Health CareMultiple comparisons problemHumansComputer SimulationData miningcomputerProportional Hazards ModelsMathematicsStatistical hypothesis testingEvent (probability theory)Statistics in Medicine
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