Search results for "Linear"

showing 10 items of 7165 documents

Analisis bayesiano de los contrastes de hipotesis parametricos

1985

Classical solutions to parametric hypothesis testing are shown to be particular instances of the Bayesian solution to a decision problem with two alternatives, in which the increase in utility for rejecting a false null is a linear function of the discrepancy between the accepted parametric model and the more likely model under the null.

Statistics and ProbabilityNull (mathematics)Parametric modelStatistics Probability and UncertaintyDecision problemAlgorithmBayesian solutionLinear functionParametric statisticsMathematicsStatistical hypothesis testingTrabajos de Estadistica Y de Investigacion Operativa
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Deflation-based separation of uncorrelated stationary time series

2014

In this paper we assume that the observed pp time series are linear combinations of pp latent uncorrelated weakly stationary time series. The problem is then to find an estimate for an unmixing matrix that transforms the observed time series back to uncorrelated time series. The so called SOBI (Second Order Blind Identification) estimate aims at a joint diagonalization of the covariance matrix and several autocovariance matrices with varying lags. In this paper, we propose a novel procedure that extracts the latent time series one by one. The limiting distribution of this deflation-based SOBI is found under general conditions, and we show how the results can be used for the comparison of es…

Statistics and ProbabilityNumerical Analysista112Series (mathematics)matematiikkaCovariance matrixaikasarjatmathematicsta111Asymptotic distributionDeflationBlind signal separationAutocovarianceMatrix (mathematics)StatisticsApplied mathematicsStatistics Probability and Uncertaintytime seriesLinear combinationMathematicsJournal of Multivariate Analysis
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Adaptive designs with correlated test statistics

2009

In clinical trials, the collected observations such as clustered data or repeated measurements are often correlated. As a consequence, test statistics in a multistage design are correlated. Adaptive designs were originally developed for independent test statistics. We present a general framework for two-stage adaptive designs with correlated test statistics. We show that the significance level for the Bauer-Köhne design is inflated for positively correlated test statistics from a bivariate normal distribution. The decision boundary for the second stage can be modified so that type one error is controlled. This general concept is expandable to other adaptive designs. In order to use these de…

Statistics and ProbabilityOptimal designClinical Trials as TopicBiometryModels StatisticalEpidemiologyCovariance matrixMultivariate normal distributionWald testGeneralized linear mixed modelExact testSample size determinationStatisticsLinear ModelsHumansMathematicsStatistical hypothesis testingStatistics in Medicine
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Efficiency Bounds for Product Designs in Linear Models

1999

We provide lower efficiency bounds for the best product design for an additive multifactor linear model. The A-optimality criterion is used to demonstrate that out bounds are better than the conventional bounds. Applications to other criteria, such as IMSE (integrated mean squared error) criterion are also indicated. In all the cases, the best product design appears to perform better when there are more levels in each factor but decreases when more factors are included. Explicit efficiency formulas for non-additive models are also constructed.

Statistics and ProbabilityOptimal designProduct designMean squared errorLinear modelMarginal modelsymbols.namesakeProduct (mathematics)StatisticssymbolsApplied mathematicsFisher informationAdditive modelMathematicsAnnals of the Institute of Statistical Mathematics
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A non-linear optimization procedure to estimate distances and instantaneous substitution rate matrices under the GTR model.

2006

Abstract Motivation: The general-time-reversible (GTR) model is one of the most popular models of nucleotide substitution because it constitutes a good trade-off between mathematical tractability and biological reality. However, when it is applied for inferring evolutionary distances and/or instantaneous rate matrices, the GTR model seems more prone to inapplicability than more restrictive time-reversible models. Although it has been previously noted that the causes for intractability are caused by the impossibility of computing the logarithm of a matrix characterised by negative eigenvalues, the issue has not been investigated further. Results: Here, we formally characterize the mathematic…

Statistics and ProbabilityOptimization problemBase Pair MismatchBiochemistryLinkage DisequilibriumNonlinear programmingInterpretation (model theory)Evolution MolecularApplied mathematicsComputer SimulationDivergence (statistics)Molecular BiologyEigenvalues and eigenvectorsPhylogenyMathematicsSequenceModels GeneticSubstitution (logic)Chromosome MappingGenetic VariationSequence Analysis DNAComputer Science ApplicationsComputational MathematicsComputational Theory and MathematicsNonlinear DynamicsLogarithm of a matrixAlgorithmAlgorithmsBioinformatics (Oxford, England)
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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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Haldane Model at finite temperature

2019

We consider the Haldane model, a 2D topological insulator whose phase is defined by the Chern number. We study its phases as temperature varies by means of the Uhlmann number, a finite temperature generalization of the Chern number. Because of the relation between the Uhlmann number and the dynamical transverse conductivity of the system, we evaluate also the conductivity of the model. This analysis does not show any sign of a phase transition induced by the temperature, nonetheless it gives a better understanding of the fate of the topological phase with the increase of the temperature, and it provides another example of the usefulness of the Uhlmann number as a novel tool to study topolog…

Statistics and ProbabilityPhase transitionGeneralizationFOS: Physical sciencesConductivity01 natural sciences010305 fluids & plasmasCondensed Matter - Strongly Correlated ElectronsPhase (matter)0103 physical sciencesStatistical physics010306 general physicsCondensed Matter - Statistical MechanicsPhysicstopological insulatorQuantum PhysicsChern classStatistical Mechanics (cond-mat.stat-mech)Strongly Correlated Electrons (cond-mat.str-el)Topological phase of matter phase transition geometric phase quantum transportStatistical and Nonlinear PhysicsTransverse planeTopological insulatorStatistics Probability and UncertaintyQuantum Physics (quant-ph)Sign (mathematics)
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Fisher Renormalization for Logarithmic Corrections

2008

For continuous phase transitions characterized by power-law divergences, Fisher renormalization prescribes how to obtain the critical exponents for a system under constraint from their ideal counterparts. In statistical mechanics, such ideal behaviour at phase transitions is frequently modified by multiplicative logarithmic corrections. Here, Fisher renormalization for the exponents of these logarithms is developed in a general manner. As for the leading exponents, Fisher renormalization at the logarithmic level is seen to be involutory and the renormalized exponents obey the same scaling relations as their ideal analogs. The scheme is tested in lattice animals and the Yang-Lee problem at t…

Statistics and ProbabilityPhase transitionLogarithmStatistical Mechanics (cond-mat.stat-mech)Multiplicative functionFOS: Physical sciencesStatistical and Nonlinear PhysicsStatistical mechanicsRenormalizationIdeal (order theory)Statistics Probability and UncertaintyCritical exponentScalingCondensed Matter - Statistical MechanicsMathematical physicsMathematics
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Generalized Heisenberg algebra and (non linear) pseudo-bosons

2018

We propose a deformed version of the generalized Heisenberg algebra by using techniques borrowed from the theory of pseudo-bosons. In particular, this analysis is relevant when non self-adjoint Hamiltonians are needed to describe a given physical system. We also discuss relations with nonlinear pseudo-bosons. Several examples are discussed.

Statistics and ProbabilityPhysical systemGeneral Physics and AstronomyFOS: Physical sciences01 natural sciencesbiorthogonal bases in quantum mechanicPhysics and Astronomy (all)0103 physical sciencesMathematical PhysicAlgebra over a field010306 general physicsSettore MAT/07 - Fisica MatematicaMathematical PhysicsComputingMilieux_MISCELLANEOUSMathematicsBoson[PHYS]Physics [physics]Quantum Physics010308 nuclear & particles physicsStatistical and Nonlinear PhysicsMathematical Physics (math-ph)pseudo-bosonAlgebraNonlinear systemModeling and Simulationgeneralized Heisenberg algebraQuantum Physics (quant-ph)[PHYS.ASTR]Physics [physics]/Astrophysics [astro-ph]Statistical and Nonlinear Physic
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Degree stability of a minimum spanning tree of price return and volatility

2002

We investigate the time series of the degree of minimum spanning trees obtained by using a correlation based clustering procedure which is starting from (i) asset return and (ii) volatility time series. The minimum spanning tree is obtained at different times by computing correlation among time series over a time window of fixed length $T$. We find that the minimum spanning tree of asset return is characterized by stock degree values, which are more stable in time than the ones obtained by analyzing a minimum spanning tree computed starting from volatility time series. Our analysis also shows that the degree of stocks has a very slow dynamics with a time-scale of several years in both cases.

Statistics and ProbabilityPhysics - Physics and SocietyFOS: Physical sciencesPhysics and Society (physics.soc-ph)Minimum spanning treeFOS: Economics and businessTime windowsStatisticsMathematical PhysicCluster analysisStock (geology)Condensed Matter - Statistical MechanicsMathematicsSpanning treeStatistical Finance (q-fin.ST)Statistical Mechanics (cond-mat.stat-mech)EconophysicQuantitative Finance - Statistical FinanceStatistical and Nonlinear PhysicsAsset returnCondensed Matter PhysicsSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)VolatilityCorrelation-based clusteringPrice returnVolatility (finance)
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