Search results for "Uncertainty"

showing 10 items of 1010 documents

Tests and estimates of shape based on spatial signs and ranks

2009

Nonparametric procedures for testing and estimation of the shape matrix in the case of multivariate elliptic distribution are considered. Testing for sphericity is an important special case. The tests and estimates are based on the spatial sign and rank covariance matrices. The estimates based on the spatial sign covariance matrix and symmetrized spatial sign covariance matrix are Tyler's [A distribution-free M-estimator of multivariate scatter, Ann. Statist. 15 (1987), pp. 234–251] shape matrix and and Dümbgen's [On Tyler's M-functional of scatter in high dimension, Ann. Inst. Statist. Math. 50 (1998), pp. 471–491] shape matrix, respectively. The test based on the spatial sign covariance m…

Statistics and ProbabilityStatistics::TheoryRank (linear algebra)Covariance matrixNonparametric statisticsCovarianceEstimation of covariance matricesScatter matrixStatisticsStatistics::MethodologySign testStatistics Probability and Uncertaintymoniulotteiset merkki- ja jarjestysluvutMathematicsSign (mathematics)Journal of Nonparametric Statistics
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On the relationship between the reversed hazard rate and elasticity

2012

Despite hazard and reversed hazard rates sharing a number of similar aspects, reversed hazard functions are far less frequently used. Understanding their meaning is not a simple task. The aim of this paper is to expand the usefulness of the reversed hazard function by relating it to other well-known concepts broadly used in economics: (linear or cumulative) rates of increase and elasticity. This will make it possible (i) to improve our understanding of the consequences of using a particular distribution and, in certain cases, (ii) to introduce our hypotheses and knowledge about the random process in a more meaningful and intuitive way, thus providing a means to achieving distributions that …

Statistics and ProbabilityStochastic processHazard ratioEconometricsProbability distributionStatistics Probability and UncertaintyElasticity (economics)EconomiaMathematicsElasticity of a functionRate of increase
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Building up adjusted indicators of students' evaluation of university courses using generalized item response models

2012

This article advances a proposal for building up adjusted composite indicators of the quality of university courses from students’ assessments. The flexible framework of Generalized Item Response Models is adopted here for controlling the sources of heterogeneity in the data structure that make evaluations across courses not directly comparable. Specifically, it allows us to: jointly model students’ ratings to the set of items which define the quality of university courses; explicitly consider the dimensionality of the items composing the evaluation form; evaluate and remove the effect of potential confounding factors which may affect students’ evaluation; model the intra-cluster variabilit…

Statistics and ProbabilityStructure (mathematical logic)Computer sciencemedia_common.quotation_subjectadjusted indicators explanatory item response models multidimensional latent traits multilevel models evaluation of university courses potential confounding factorsRegression analysisData structureAffect (psychology)Multilevel dataComputingMilieux_COMPUTERSANDEDUCATIONEconometricsMathematics educationQuality (business)Settore SECS-S/05 - Statistica SocialeStatistics Probability and UncertaintySet (psychology)Settore SECS-S/01 - Statisticamedia_commonCurse of dimensionality
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Quantitative ergodicity for some switched dynamical systems

2012

International audience; We provide quantitative bounds for the long time behavior of a class of Piecewise Deterministic Markov Processes with state space Rd × E where E is a finite set. The continuous component evolves according to a smooth vector field that switches at the jump times of the discrete coordinate. The jump rates may depend on the whole position of the process. Under regularity assumptions on the jump rates and stability conditions for the vector fields we provide explicit exponential upper bounds for the convergence to equilibrium in terms of Wasserstein distances. As an example, we obtain convergence results for a stochastic version of the Morris-Lecar model of neurobiology.

Statistics and ProbabilitySwitched dynamical systemsDynamical systems theoryMarkov process01 natural sciences34D2393E15010104 statistics & probabilitysymbols.namesakeCouplingPiecewise Deterministic Markov ProcessPosition (vector)60J25FOS: MathematicsState spaceApplied mathematicsWasserstein distance0101 mathematicsMathematicsProbability (math.PR)010102 general mathematicsErgodicityErgodicity[MATH.MATH-PR]Mathematics [math]/Probability [math.PR]Linear Differential EquationsPiecewisesymbolsJumpAMS-MSC. 60J75; 60J25; 93E15; 34D23Vector fieldStatistics Probability and Uncertainty60J75[ MATH.MATH-PR ] Mathematics [math]/Probability [math.PR]Mathematics - Probability
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Gossip: The Architecture of SpreadPlots

2003

A spreadplot is a visualization that simultaneously shows several different views of a dataset or model. The individual views can be dynamic, can support high-interaction direct manipulation, and can be algebraically linked with each other, possibly via an underlying statistical model. Thus, when a data analyst changes the information shown in one view of a statistical model, the changes can be processed by the model and instantly represented in the other views. Spreadplots simplify the analyst's task when many different plots are relevant to the analysis at hand, as is the case in regression analysis, where there are many plots that can be used for model building and diagnosis. On the othe…

Statistics and ProbabilityTheoretical computer scienceComputer scienceGossipDiscrete Mathematics and CombinatoricsStatistical modelStatistics Probability and UncertaintyGraphicsUser interfaceSoftware architectureModel buildingVisualizationTask (project management)Journal of Computational and Graphical Statistics
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Bayesian Design of “Successful” Replications

2002

Replication of experiments is commonin applied research. However, systematic studies of the goals and motivations of a “replication” are rare. As a consequence, there does not seem to be a precise notion of what a “success” when replicating means. This article discusses some of the possible goals for replication; this leads to different (but precise) notions of “success” when replicating. Bayesian hierarchical models allow for a flexible and explicit incorporation of the assumed relationship among the experiments. Bayesian predictive distributions are a natural tool to compute the probability of the replication being successful, and hence to design the replication so that the probability of…

Statistics and ProbabilityTheoretical computer scienceGeneral MathematicsBayesian probabilityHierarchical database modelBayesian designProbability of successNoncentral t-distributionReplication (statistics)Applied researchStatistics Probability and UncertaintyAlgorithmMathematicsStatistical hypothesis testingThe American Statistician
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Portfolio optimisation with strictly positive transaction costs and impulse control

1998

One crucial assumption in modern portfolio theory of continuous-time models is the no transaction cost assumption. This assumption normally leads to trading strategies with infinite variation. However, following such a strategy in the presence of transaction costs will lead to immediate ruin. We present an impulse control approach where the investor can change his portfolio only finitely often in finite time intervals. Further, we consider transaction costs including a fixed and a proportional cost component. For the solution of the resulting control problems we present a formal optimal stopping approach and an approach using quasi-variational inequalities. As an application we derive a non…

Statistics and ProbabilityTransaction costMathematical optimizationExponential utilityMerton's portfolio problemReplicating portfolioEconomicsPortfolio optimisation transaction costs impulse control asymptotic analysis.PortfolioOptimal stoppingStatistics Probability and UncertaintyPortfolio optimizationFinanceModern portfolio theory
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A Bayesian SIRS model for the analysis of respiratory syncytial virus in the region of Valencia, Spain

2014

We present a Bayesian stochastic susceptible-infected-recovered-susceptible (SIRS) model in discrete time to understand respiratory syncytial virus dynamics in the region of Valencia, Spain. A SIRS model based on ordinary differential equations has also been proposed to describe RSV dynamics in the region of Valencia. However, this continuous-time deterministic model is not suitable when the initial number of infected individuals is small. Stochastic epidemic models based on a probability of disease transmission provide a more natural description of the spread of infectious diseases. In addition, by allowing the transmission rate to vary stochastically over time, the proposed model provides…

Statistics and ProbabilityTransmission rateBayesian probabilityPosterior probabilityPrediction intervalGeneral MedicineDiscrete time and continuous timePosterior predictive distributionOrdinary differential equationQuantitative Biology::Populations and EvolutionApplied mathematicsStatistics Probability and UncertaintyDisease transmissionMathematicsBiometrical Journal
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Eleccion de variables en regresion lineal un problema de decision

1986

A general structure for the problem of selection of variables in regression is proposed using the decision theory framework. In particular, some results for the choice of the best linear normal homocedastic model are obtained when the main purpose is either to specify the predictive distribution over the response variable or to obtain a point estimate of it. A comparison of our results with the most widespread classical ones is presented

Statistics and ProbabilityVariable (computer science)Distribution (number theory)Decision theoryStatisticsStructure (category theory)Point estimationStatistics Probability and UncertaintyRegressionSelection (genetic algorithm)MathematicsTrabajos de Estadistica
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Asymptotic efficiency of the calibration estimator in a high-dimensional data setting

2022

Abstract In a finite population sampling survey, auxiliary information is commonly used to improve the Horvitz-Thompson estimators and calibration has been extensively used by national statistical agencies over the last decades for that purpose. This method enables to make estimators consistent with known totals of auxiliary variables and to reduce variance if the calibration variables are explanatory for the variable of interest. Nowadays, it is not unusual anymore to have high-dimensional auxiliary data sets and adding too much additional calibration variables may increase the variance of calibration estimators. We study in this paper the asymptotic efficiency of the calibration estimator…

Statistics and ProbabilityVariance inflation factorAuxiliary variablesVariable (computer science)Calibration (statistics)Applied MathematicsStatisticsEstimatorVariance (accounting)Statistics Probability and UncertaintyPopulation samplingMathematicsJournal of Statistical Planning and Inference
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