Search results for " Uncertainty"

showing 10 items of 777 documents

Optimal Reporting of Predictions

1989

Abstract Consider a problem in which you and a group of other experts must report your individual predictive distributions for an observable random variable X to some decision maker. Suppose that the report of each expert is assigned a prior weight by the decision maker and that these weights are then updated based on the observed value of X. In this situation you will try to maximize your updated, or posterior, weight by appropriately choosing the distribution that you report, rather than necessarily simply reporting your honest predictive distribution. We study optimal reporting strategies under various conditions regarding your knowledge and beliefs about X and the reports of the other e…

Statistics and ProbabilityMathematical optimizationExpert opinionStatisticsGaining weightStatistics Probability and UncertaintyDecision makerBayesian inferenceFinite setRandom variableValue (mathematics)WeightingMathematicsJournal of the American Statistical Association
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Objective Priors for Discrete Parameter Spaces

2012

This article considers the development of objective prior distributions for discrete parameter spaces. Formal approaches to such development—such as the reference prior approach—often result in a constant prior for a discrete parameter, which is questionable for problems that exhibit certain types of structure. To take advantage of structure, this article proposes embedding the original problem in a continuous problem that preserves the structure, and then using standard reference prior theory to determine the appropriate objective prior. Four different possibilities for this embedding are explored, and applied to a population-size model, the hypergeometric distribution, the multivariate hy…

Statistics and ProbabilityMathematical optimizationNegative hypergeometric distributionGeometric distributionHypergeometric distributionDirichlet distributionBinomial distributionsymbols.namesakeBeta-binomial distributionPrior probabilitysymbolsStatistics Probability and UncertaintyCompound probability distributionMathematicsJournal of the American Statistical Association
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Calibration of optimal execution of financial transactions in the presence of transient market impact

2012

Trading large volumes of a financial asset in order driven markets requires the use of algorithmic execution dividing the volume in many transactions in order to minimize costs due to market impact. A proper design of an optimal execution strategy strongly depends on a careful modeling of market impact, i.e. how the price reacts to trades. In this paper we consider a recently introduced market impact model (Bouchaud et al., 2004), which has the property of describing both the volume and the temporal dependence of price change due to trading. We show how this model can be used to describe price impact also in aggregated trade time or in real time. We then solve analytically and calibrate wit…

Statistics and ProbabilityMathematical optimizationQuantitative Finance - Trading and Market MicrostructureStatistical Finance (q-fin.ST)Financial market Econophysics stochastic processesFinancial assetComputer scienceVolume (computing)Efficient frontierQuantitative Finance - Statistical FinanceStatistical and Nonlinear PhysicsRisk neutralTrading and Market Microstructure (q-fin.TR)FOS: Economics and businessOrder (exchange)Financial transactionfinancial instruments and regulation models of financial markets risk measure and managementTransient (computer programming)Statistics Probability and UncertaintyMarket impact
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Sequential estimation of a location parameter and powers of a scale parameter from delayed observations

2013

The problem of sequentially estimating a location parameter and powers of a scale parameter is considered in the case when the observations become available at random times. Certain classes of sequential estimation procedures are derived under an invariant balanced loss function and with the observation cost determined by a convex function of the stopping time and the number of observations up to that time.

Statistics and ProbabilityMathematical optimizationSequential estimationLocation parameterStopping timeApplied mathematicsFunction (mathematics)Statistics Probability and UncertaintyInvariant (mathematics)Convex functionScale parameterShape parameterMathematicsStatistica Neerlandica
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Deriving Reference Decisions

1998

To solve a statistical decision problem from a Bayesian viewpoint, the decision maker must specify a probability distribution on the parameter space, his prior distribution. In order to analyze the influence of this prior distribution on the solution of the problem, Bernardo (1981) proposed to compare the results with those that one would obtain by using that prior distribution which maximizes the useful experimental information, thus introducing the concept of reference decision. This definition is too involved for most of the problems usually found in practice. Here we analyze situations in which it is possible to simplify the definition of the reference decision, and we provide condition…

Statistics and ProbabilityMathematical optimizationWeak topologyOrder (exchange)Prior probabilityBayesian probabilityProbability distributionStatistics Probability and UncertaintyDecision problemParameter spaceOptimal decisionMathematicsTest
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A more efficient second order blind identification method for separation of uncorrelated stationary time series

2016

The classical second order source separation methods use approximate joint diagonalization of autocovariance matrices with several lags to estimate the unmixing matrix. Based on recent asymptotic results, we propose a novel unmixing matrix estimator which selects the best lag set from a finite set of candidate sets specified by the user. The theory is illustrated by a simulation study.

Statistics and ProbabilityMathematical optimizationaffine equivarianceminimum distance indexasymptotic normalityAsymptotic distributionlinear process01 natural sciencesSet (abstract data type)010104 statistics & probabilityMatrix (mathematics)SOBIComputingMethodologies_SYMBOLICANDALGEBRAICMANIPULATION0502 economics and businessSource separationjoint diagonalization0101 mathematicsFinite set050205 econometrics Mathematicsta112Series (mathematics)05 social sciencesEstimatorAutocovarianceStatistics Probability and UncertaintyAlgorithmStatistics & Probability Letters
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Random dynamical system generated by the 3D Navier-Stokes equation with rough transport noise

2022

We consider the Navier-Stokes system in three dimensions perturbed by a transport noise which is sufficiently smooth in space and rough in time. The existence of a weak solution was proved recently, however, as in the deterministic setting the question of uniqueness remains a major open problem. An important feature of systems with uniqueness is the semigroup property satisfied by their solutions. Without uniqueness, this property cannot hold generally. We select a system of solutions satisfying the semigroup property with appropriately shifted rough path. In addition, the selected solutions respect the well accepted admissibility criterium for physical solutions, namely, maximization of th…

Statistics and ProbabilityMathematics - Analysis of PDEsProbability (math.PR)FOS: MathematicsStatistics Probability and UncertaintyVDP::Matematikk og Naturvitenskap: 400::Matematikk: 410Mathematics - ProbabilityAnalysis of PDEs (math.AP)
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Broken ray transform on a Riemann surface with a convex obstacle

2014

We consider the broken ray transform on Riemann surfaces in the presence of an obstacle, following earlier work of Mukhometov. If the surface has nonpositive curvature and the obstacle is strictly convex, we show that a function is determined by its integrals over broken geodesic rays that reflect on the boundary of the obstacle. Our proof is based on a Pestov identity with boundary terms, and it involves Jacobi fields on broken rays. We also discuss applications of the broken ray transform.

Statistics and ProbabilityMathematics - Differential GeometryGeodesicAstrophysics::High Energy Astrophysical PhenomenaBoundary (topology)Curvature01 natural sciencessymbols.namesakeMathematics - Analysis of PDEsFOS: Mathematics0101 mathematicsMathematicsRiemann surface010102 general mathematicsMathematical analysista111Regular polygonSurface (topology)boundary010101 applied mathematicsDifferential Geometry (math.DG)Obstaclesymbolstensor tomographyGeometry and TopologyStatistics Probability and UncertaintydimensionsConvex functionAnalysisAnalysis of PDEs (math.AP)
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Central Limit Theorem for Linear Eigenvalue Statistics for a Tensor Product Version of Sample Covariance Matrices

2017

For $$k,m,n\in {\mathbb {N}}$$ , we consider $$n^k\times n^k$$ random matrices of the form $$\begin{aligned} {\mathcal {M}}_{n,m,k}({\mathbf {y}})=\sum _{\alpha =1}^m\tau _\alpha {Y_\alpha }Y_\alpha ^T,\quad {Y}_\alpha ={\mathbf {y}}_\alpha ^{(1)}\otimes \cdots \otimes {\mathbf {y}}_\alpha ^{(k)}, \end{aligned}$$ where $$\tau _{\alpha }$$ , $$\alpha \in [m]$$ , are real numbers and $${\mathbf {y}}_\alpha ^{(j)}$$ , $$\alpha \in [m]$$ , $$j\in [k]$$ , are i.i.d. copies of a normalized isotropic random vector $${\mathbf {y}}\in {\mathbb {R}}^n$$ . For every fixed $$k\ge 1$$ , if the Normalized Counting Measures of $$\{\tau _{\alpha }\}_{\alpha }$$ converge weakly as $$m,n\rightarrow \infty $$…

Statistics and ProbabilityMathematics(all)Multivariate random variableGeneral Mathematics010102 general mathematicslinear eigenvalue statisticsrandom matrices01 natural sciencesSample mean and sample covariance010104 statistics & probabilityDistribution (mathematics)Tensor productStatisticssample covariance matricescentral Limit Theorem0101 mathematicsStatistics Probability and UncertaintyRandom matrixEigenvalues and eigenvectorsMathematicsReal numberCentral limit theoremJournal of Theoretical Probability
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A generalization of the Binomial distribution based on the dependence ratio

2014

We propose a generalization of the Binomial distribution, called DR-Binomial, which accommodates dependence among units through a model based on the dependence ratio (Ekholm et al., Biometrika, 82, 1995, 847). Properties of the DR-Binomial are discussed, and the constraints on its parameter space are studied in detail. Likelihood-based inference is presented, using both the joint and profile likelihoods; the usefulness of the DR-Binomial in applications is illustrated on a real dataset displaying negative unit-dependence, and hence under-dispersion compared with the Binomial. Although the DR-Binomial turns out to be a reparameterization of Altham's Additive-Binomial and Kupper–Haseman's Cor…

Statistics and ProbabilityMathematics::Commutative AlgebraBinomial approximationNegative binomial distributionBinomial testNegative multinomial distributionBinomial distributionBeta-binomial distributionStatisticsApplied mathematicsMultinomial theoremMultinomial distributionStatistics Probability and UncertaintyMathematicsStatistica Neerlandica
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