Search results for "JOINT"

showing 10 items of 1472 documents

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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Global and multiple test procedures using ordered p-values—a review

2004

This paper reviews global and multiple tests for the combination ofn hypotheses using the orderedp-values of then individual tests. In 1987, Rohmel and Streitberg presented a general method to construct global level α tests based on orderedp-values when there exists no prior knowledge regarding the joint distribution of the corresponding test statistics. In the case of independent test statistics, construction of global tests is available by means of recursive formulae presented by Bicher (1989), Kornatz (1994) and Finner and Roters (1994). Multiple test procedures can be developed by applying the closed test principle using these global tests as building blocks. Liu (1996) proposed represe…

Statistics and ProbabilityGeneral methodTest proceduresJoint probability distributionExistential quantificationStatisticsApplied mathematicsStatistics Probability and UncertaintyConstruct (philosophy)Statistical hypothesis testingMathematicsDynamic testingTest (assessment)Statistical Papers
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On the convenience of heteroscedasticity in highly multivariate disease mapping

2019

Highly multivariate disease mapping has recently been proposed as an enhancement of traditional multivariate studies, making it possible to perform the joint analysis of a large number of diseases. This line of research has an important potential since it integrates the information of many diseases into a single model yielding richer and more accurate risk maps. In this paper we show how some of the proposals already put forward in this area display some particular problems when applied to small regions of study. Specifically, the homoscedasticity of these proposals may produce evident misfits and distorted risk maps. In this paper we propose two new models to deal with the variance-adaptiv…

Statistics and ProbabilityHeteroscedasticityMultivariate statisticsComputer scienceDiseaseJoint analysisMachine learningcomputer.software_genreBayesian statistics01 natural sciencesGaussian Markov random fields010104 statistics & probability03 medical and health sciences0302 clinical medicineHomoscedasticity0101 mathematicsMultivariate disease mappingSpatial analysisMortality studiesInterpretation (logic)Spatial statisticsbusiness.industryBayesian statisticsEstadística bayesianaMalalties030211 gastroenterology & hepatologyArtificial intelligenceStatistics Probability and Uncertaintybusinesscomputer
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Pairwise Markov properties for regression graphs

2016

With a sequence of regressions, one may generate joint probability distributions. One starts with a joint, marginal distribution of context variables having possibly a concentration graph structure and continues with an ordered sequence of conditional distributions, named regressions in joint responses. The involved random variables may be discrete, continuous or of both types. Such a generating process specifies for each response a conditioning set that contains just its regressor variables, and it leads to at least one valid ordering of all nodes in the corresponding regression graph that has three types of edge: one for undirected dependences among context variables, another for undirect…

Statistics and ProbabilityMarkov chain010102 general mathematicsMixed graphConditional probability distribution01 natural sciencesCombinatorics010104 statistics & probabilityConditional independenceJoint probability distributionMarkov property0101 mathematicsStatistics Probability and UncertaintyMarginal distributionRandom variableMathematicsStat
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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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Frequentist and Bayesian approaches for a joint model for prostate cancer risk and longitudinal prostate-specific antigen data

2015

The paper describes the use of frequentist and Bayesian shared-parameter joint models of longitudinal measurements of prostate-specific antigen (PSA) and the risk of prostate cancer (PCa). The motivating dataset corresponds to the screening arm of the Spanish branch of the European Randomized Screening for Prostate Cancer study. The results show that PSA is highly associated with the risk of being diagnosed with PCa and that there is an age-varying effect of PSA on PCa risk. Both the frequentist and Bayesian paradigms produced very close parameter estimates and subsequent 95% confidence and credibility intervals. Dynamic estimations of disease-free probabilities obtained using Bayesian infe…

Statistics and ProbabilityPREDICTIONBayesian probabilityurologic and male genital diseasesBayesian inferenceGeneralized linear mixed modelPSAProstate cancerLATENT CLASS MODELSAnàlisi de supervivència (Biometria)Frequentist inference62N01Statisticsprostate cancer screeningSurvival analysis (Biometry)FAILUREMedicineProstate cancer riskTO-EVENT DATAbusiness.industryjoint modelsMORTALITYDISEASE PROGRESSIONmedicine.diseaselinear mixed modelsTIMEProstate-specific antigenProstate cancer screeningshared-parameter models:Matemàtiques i estadística::Estadística matemàtica [Àrees temàtiques de la UPC]62P10SURVIVALStatistics Probability and Uncertaintyrelative risk modelsFOLLOW-UPbusinessJournal of Applied Statistics
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(H,ρ)-induced dynamics and large time behaviors

2018

Abstract In some recent papers, the so called ( H , ρ ) -induced dynamics of a system S whose time evolution is deduced adopting an operatorial approach, borrowed in part from quantum mechanics, has been introduced. Here, H is the Hamiltonian for S , while ρ is a certain rule applied periodically (or not) on S . The analysis carried on throughout this paper shows that, replacing the Heisenberg dynamics with the ( H , ρ ) -induced one, we obtain a simple, and somehow natural, way to prove that some relevant dynamical variables of S may converge, for large t , to certain asymptotic values. This cannot be so, for finite dimensional systems, if no rule is considered. In this case, in fact, any …

Statistics and ProbabilityPhysicsTime evolutionCondensed Matter Physics01 natural sciences010305 fluids & plasmasTwo degrees of freedomsymbols.namesakeLattice (order)0103 physical sciencessymbols010306 general physicsHamiltonian (quantum mechanics)Self-adjoint operatorMathematical physicsPhysica A: Statistical Mechanics and its Applications
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Non-self-adjoint Hamiltonians with complex eigenvalues

2016

Motivated by what one observes dealing with PT-symmetric quantum mechanics, we discuss what happens if a physical system is driven by a diagonalizable Hamiltonian with not all real eigenvalues. In particular, we consider the functional structure related to systems living in finite-dimensional Hilbert spaces, and we show that certain intertwining relations can be deduced also in this case if we introduce suitable antilinear operators. We also analyze a simple model, computing the transition probabilities in the broken and in the unbroken regime.

Statistics and ProbabilityPure mathematicsDiagonalizable matrixPhysical systemFOS: Physical sciencesGeneral Physics and Astronomyintertwining relation01 natural sciencesModeling and simulationPhysics and Astronomy (all)symbols.namesakePT-quantum mechanic0103 physical sciencesMathematical Physic010306 general physicsSettore MAT/07 - Fisica Matematicaantilinear operatorMathematical PhysicsEigenvalues and eigenvectorsMathematicsQuantum Physics010308 nuclear & particles physicsHilbert spaceStatistical and Nonlinear PhysicsProbability and statisticsMathematical Physics (math-ph)Modeling and SimulationsymbolsQuantum Physics (quant-ph)Hamiltonian (quantum mechanics)Self-adjoint operatorStatistical and Nonlinear PhysicJournal of Physics A: Mathematical and Theoretical
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Quadratic ${\mathcal P}{\mathcal T}$-symmetric operators with real spectrum and similarity to self-adjoint operators

2012

It is established that a -symmetric elliptic quadratic differential operator with real spectrum is similar to a self-adjoint operator precisely when the associated fundamental matrix has no Jordan blocks.This article is part of a special issue of Journal of Physics A: Mathematical and Theoretical devoted to ‘Quantum physics with non-Hermitian operators’.

Statistics and ProbabilityPure mathematicsSimilarity (geometry)Spectrum (functional analysis)General Physics and AstronomyStatistical and Nonlinear PhysicsOperator (computer programming)Quadratic equationFundamental matrix (linear differential equation)Modeling and SimulationQuadratic differentialMathematical PhysicsSelf-adjoint operatorMathematicsJournal of Physics A: Mathematical and Theoretical
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Mathematical aspects of intertwining operators: the role of Riesz bases

2010

In this paper we continue our analysis of intertwining relations for both self-adjoint and not self-adjoint operators. In particular, in this last situation, we discuss the connection with pseudo-hermitian quantum mechanics and the role of Riesz bases.

Statistics and ProbabilityQuantum PhysicsComputer scienceGeneral Physics and AstronomyFOS: Physical sciencesStatistical and Nonlinear PhysicsRiesz basesMathematical Physics (math-ph)Intertwining operatorMathematics::Spectral TheoryConnection (mathematics)AlgebraModeling and SimulationQuantum Physics (quant-ph)Settore MAT/07 - Fisica MatematicaMathematical PhysicsSelf-adjoint operator
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