Search results for "Modeling and Simulation"

showing 10 items of 1561 documents

Maximum likelihood estimation for the exponential power function parameters

1995

This paper addresses the problem of obtaining maximum likelihood estimates for the three parameters of the exponential power function; the information matrix is derived and the covariance matrix is here presented; the regularity conditions which ensure asymptotic normality and efficiency are examined. A numerical investigation is performed for exploring the bias and variance of the maximum likelihood estimates and their dependence on sample size and shape parameter.

Statistics and ProbabilityEstimation theoryRestricted maximum likelihoodMaximum likelihood sequence estimationLikelihood principlesymbols.namesakeEstimation of covariance matricesModeling and SimulationStatisticsExpectation–maximization algorithmsymbolsFisher informationLikelihood functionMathematicsCommunications in Statistics - Simulation and Computation
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Large deviations results for subexponential tails, with applications to insurance risk

1996

AbstractConsider a random walk or Lévy process {St} and let τ(u) = inf {t⩾0 : St > u}, P(u)(·) = P(· | τ(u) < ∞). Assuming that the upwards jumps are heavy-tailed, say subexponential (e.g. Pareto, Weibull or lognormal), the asymptotic form of the P(u)-distribution of the process {St} up to time τ(u) is described as u → ∞. Essentially, the results confirm the folklore that level crossing occurs as result of one big jump. Particular sharp conclusions are obtained for downwards skip-free processes like the classical compound Poisson insurance risk process where the formulation is in terms of total variation convergence. The ideas of the proof involve excursions and path decompositions for Mark…

Statistics and ProbabilityExponential distributionRegular variationRuin probabilityExcursionRandom walkDownwards skip-free processLévy processConditioned limit theoremTotal variation convergenceCombinatoricsInsurance riskPath decompositionIntegrated tailProbability theoryModelling and SimulationExtreme value theoryMaximum domain of attractionMathematicsStochastic processApplied MathematicsExtreme value theoryRandom walkSubexponential distributionModeling and SimulationLog-normal distributionLarge deviations theory60K1060F10Stochastic Processes and their Applications
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On 1-Laplacian Elliptic Equations Modeling Magnetic Resonance Image Rician Denoising

2015

Modeling magnitude Magnetic Resonance Images (MRI) rician denoising in a Bayesian or generalized Tikhonov framework using Total Variation (TV) leads naturally to the consideration of nonlinear elliptic equations. These involve the so called $1$-Laplacian operator and special care is needed to properly formulate the problem. The rician statistics of the data are introduced through a singular equation with a reaction term defined in terms of modified first order Bessel functions. An existence theory is provided here together with other qualitative properties of the solutions. Remarkably, each positive global minimum of the associated functional is one of such solutions. Moreover, we directly …

Statistics and ProbabilityFOS: Computer and information sciencesComputer scienceNoise reductionComputer Vision and Pattern Recognition (cs.CV)Bayesian probabilityComputer Science - Computer Vision and Pattern Recognition02 engineering and technology01 natural sciencesTikhonov regularizationsymbols.namesakeMathematics - Analysis of PDEsOperator (computer programming)Rician fading0202 electrical engineering electronic engineering information engineeringFOS: MathematicsApplied mathematicsMathematics - Numerical Analysis0101 mathematicsApplied Mathematics010102 general mathematicsNumerical Analysis (math.NA)Condensed Matter PhysicsNonlinear systemModeling and Simulationsymbols020201 artificial intelligence & image processingGeometry and TopologyComputer Vision and Pattern RecognitionLaplace operatorBessel functionAnalysis of PDEs (math.AP)
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What we look at in paintings: A comparison between experienced and inexperienced art viewers

2016

How do people look at art? Are there any differences between how experienced and inexperienced art viewers look at a painting? We approach these questions by analyzing and modeling eye movement data from a cognitive art research experiment, where the eye movements of twenty test subjects, ten experienced and ten inexperienced art viewers, were recorded while they were looking at paintings. Eye movements consist of stops of the gaze as well as jumps between the stops. Hence, the observed gaze stop locations can be thought as a spatial point pattern, which can be modeled by a spatio-temporal point process. We introduce some statistical tools to analyze the spatio-temporal eye movement data, a…

Statistics and ProbabilityFOS: Computer and information sciencesCoverageComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION01 natural sciencesStatistics - Applications050105 experimental psychologyVisual arts010104 statistics & probabilitysilmänliikkeetInformationSystems_MODELSANDPRINCIPLES0501 psychology and cognitive sciencesApplications (stat.AP)0101 mathematicspoint processPaintingPoint (typography)05 social sciencesEye movementCognitioncognitive art researchtransition probabilityGazeTest (assessment)shift functionModeling and Simulationart viewersStatistics Probability and UncertaintyPsychologyintensity
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Latin hypercube sampling with inequality constraints

2010

International audience; In some studies requiring predictive and CPU-time consuming numerical models, the sampling design of the model input variables has to be chosen with caution. For this purpose, Latin hypercube sampling has a long history and has shown its robustness capabilities. In this paper we propose and discuss a new algorithm to build a Latin hypercube sample (LHS) taking into account inequality constraints between the sampled variables. This technique, called constrained Latin hypercube sampling (cLHS), consists in doing permutations on an initial LHS to honor the desired monotonic constraints. The relevance of this approach is shown on a real example concerning the numerical w…

Statistics and ProbabilityFOS: Computer and information sciencesEconomics and EconometricsMathematical optimizationDesign of Experiments020209 energyMonotonic functionSample (statistics)Mathematics - Statistics Theory02 engineering and technologyStatistics Theory (math.ST)01 natural sciencesStatistics - Computation010104 statistics & probabilityRobustness (computer science)[MATH.MATH-ST]Mathematics [math]/Statistics [math.ST]Sampling design0202 electrical engineering electronic engineering information engineeringFOS: Mathematics[ MATH.MATH-ST ] Mathematics [math]/Statistics [math.ST]0101 mathematicsDependenceUncertainty analysisLatin hypercube samplingComputation (stat.CO)MathematicsApplied MathematicsComputer experimentFunction (mathematics)[STAT.TH]Statistics [stat]/Statistics Theory [stat.TH]Computer experiment[ STAT.TH ] Statistics [stat]/Statistics Theory [stat.TH]Latin hypercube samplingModeling and SimulationUncertainty analysisSocial Sciences (miscellaneous)Analysis
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A computationally fast alternative to cross-validation in penalized Gaussian graphical models

2015

We study the problem of selection of regularization parameter in penalized Gaussian graphical models. When the goal is to obtain the model with good predicting power, cross validation is the gold standard. We present a new estimator of Kullback-Leibler loss in Gaussian Graphical model which provides a computationally fast alternative to cross-validation. The estimator is obtained by approximating leave-one-out-cross validation. Our approach is demonstrated on simulated data sets for various types of graphs. The proposed formula exhibits superior performance, especially in the typical small sample size scenario, compared to other available alternatives to cross validation, such as Akaike's i…

Statistics and ProbabilityFOS: Computer and information sciencesGaussianInformation CriteriaCross-validationMethodology (stat.ME)symbols.namesakeBayesian information criterionStatisticsPenalized estimationGeneralized approximate cross-validationGraphical modelSDG 7 - Affordable and Clean EnergyStatistics - MethodologyMathematics/dk/atira/pure/sustainabledevelopmentgoals/affordable_and_clean_energyKullback-Leibler loApplied MathematicsEstimatorCross-validationGaussian graphical modelSample size determinationModeling and SimulationsymbolsInformation criteriaStatistics Probability and UncertaintyAkaike information criterionSettore SECS-S/01 - StatisticaAlgorithm
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Importance sampling correction versus standard averages of reversible MCMCs in terms of the asymptotic variance

2017

We establish an ordering criterion for the asymptotic variances of two consistent Markov chain Monte Carlo (MCMC) estimators: an importance sampling (IS) estimator, based on an approximate reversible chain and subsequent IS weighting, and a standard MCMC estimator, based on an exact reversible chain. Essentially, we relax the criterion of the Peskun type covariance ordering by considering two different invariant probabilities, and obtain, in place of a strict ordering of asymptotic variances, a bound of the asymptotic variance of IS by that of the direct MCMC. Simple examples show that IS can have arbitrarily better or worse asymptotic variance than Metropolis-Hastings and delayed-acceptanc…

Statistics and ProbabilityFOS: Computer and information sciencesdelayed-acceptanceMarkovin ketjut01 natural sciencesStatistics - Computationasymptotic variance010104 statistics & probabilitysymbols.namesake60J22 65C05unbiased estimatorFOS: MathematicsApplied mathematics0101 mathematicsComputation (stat.CO)stokastiset prosessitestimointiMathematicsnumeeriset menetelmätpseudo-marginal algorithmApplied Mathematics010102 general mathematicsProbability (math.PR)EstimatorMarkov chain Monte CarloCovarianceInfimum and supremumWeightingMarkov chain Monte CarloMonte Carlo -menetelmätDelta methodimportance samplingModeling and SimulationBounded functionsymbolsImportance samplingMathematics - Probability
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Weak pseudo-bosons

2020

We show how the notion of {\em pseudo-bosons}, originally introduced as operators acting on some Hilbert space, can be extended to a distributional settings. In doing so, we are able to construct a rather general framework to deal with generalized eigenvectors of the multiplication and of the derivation operators. Connections with the quantum damped harmonic oscillator are also briefly considered.

Statistics and ProbabilityFOS: Physical sciencesGeneral Physics and Astronomy01 natural sciences010305 fluids & plasmassymbols.namesakeGeneralized eigenvector0103 physical sciences010306 general physicsQuantumSettore MAT/07 - Fisica MatematicaHarmonic oscillatorMathematical PhysicsMathematical physicsBosonPhysicsHilbert spaceStatistical and Nonlinear PhysicsMathematical Physics (math-ph)Construct (python library)non self-adjoint HamiltonianModeling and SimulationsymbolsBiorthogonal setMultiplicationpseudo-bosons
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Tridiagonality, supersymmetry and non self-adjoint Hamiltonians

2019

In this paper we consider some aspects of tridiagonal, non self-adjoint, Hamiltonians and of their supersymmetric counterparts. In particular, the problem of factorization is discussed, and it is shown how the analysis of the eigenstates of these Hamiltonians produce interesting recursion formulas giving rise to biorthogonal families of vectors. Some examples are proposed, and a connection with bi-squeezed states is analyzed.

Statistics and ProbabilityFOS: Physical sciencesGeneral Physics and Astronomy01 natural sciencesFactorization0103 physical sciences010306 general physicsSettore MAT/07 - Fisica MatematicaMathematical PhysicsEigenvalues and eigenvectorsMathematicsQuantum PhysicsTridiagonal matrix010308 nuclear & particles physicsRecursion (computer science)Statistical and Nonlinear Physicstridiagonal matriceMathematical Physics (math-ph)SupersymmetryConnection (mathematics)non self-adjoint HamiltonianAlgebrabiorthogonal basesModeling and SimulationBiorthogonal systemQuantum Physics (quant-ph)Self-adjoint operatorJournal of Physics A: Mathematical and Theoretical
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On the function of modified nucleosides in the RNA world.

1998

Presumably ribosome and transfer RNA (tRNA) evolved from a pre-existing function in the RNA stage of life and were secondarily adapted for protein synthesis. Various possible initial functions of the primitive ribosome (protoribosome) have been suggested. The initial function of the primitive ribosome and primitive genetic translation would have been quite similar. It is possible that, initially, both functions coexisted in the protoribosome. Given that the three-dimensional structure of ribosomal RNAs shows only minor variations throughout time, it is, then, most likely that present ribosomes can still recall (remember) the most important parts of the mechanism of their initial function. A…

Statistics and ProbabilityGeneral Immunology and MicrobiologyApplied MathematicsRibozymeRNATranslation (biology)NucleosidesGeneral MedicineBiologyRibosomeGeneral Biochemistry Genetics and Molecular BiologyGenetic translationEvolution MolecularBiochemistryRNA TransferRNA RibosomalModeling and SimulationProtein BiosynthesisTransfer RNAbiology.proteinProtein biosynthesisAnimalsRNAGeneral Agricultural and Biological SciencesEukaryotic RibosomeJournal of theoretical biology
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