Search results for "Covar"

showing 10 items of 509 documents

Flexible modelling of serial correlation in GLMM

2008

Covariance structures longitudinal data fractional polynomialsSettore SECS-S/01 - Statistica
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New constraints on Lorentz invariance violation from the neutron electric dipole moment

2010

We propose an original test of Lorentz invariance in the interaction between a particle spin and an electromagnetic field and report on a first measurement using ultracold neutrons. We used a high sensitivity neutron electric dipole moment (nEDM) spectrometer and searched for a direction dependence of a nEDM signal leading to a modulation of its magnitude at periods of 12 and 24 hours. We constrain such a modulation to $d_{12} < 15 \times 10^{-25} \ e\,{\rm cm}$ and $d_{24} < 10 \times 10^{-25} \ e\,{\rm cm}$ at 95~\% C.L. The result translates into a limit on the energy scale for this type of Lorentz violation effect at the level of ${\cal E}_{LV} > 10^{10}$~GeV.

Electromagnetic fieldPhysicsSpectrometerNeutron electric dipole moment010308 nuclear & particles physicsFOS: Physical sciencesGeneral Physics and AstronomyLorentz covariance[PHYS.NEXP]Physics [physics]/Nuclear Experiment [nucl-ex]01 natural sciencesSignalModulationQuantum electrodynamics0103 physical sciencesUltracold neutronsSensitivity (control systems)Nuclear Experiment (nucl-ex)Nuclear Experiment010306 general physicsNuclear Experiment
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Standard forms and entanglement engineering of multimode Gaussian states under local operations

2007

We investigate the action of local unitary operations on multimode (pure or mixed) Gaussian states and single out the minimal number of locally invariant parametres which completely characterise the covariance matrix of such states. For pure Gaussian states, central resources for continuous-variable quantum information, we investigate separately the parametre reduction due to the additional constraint of global purity, and the one following by the local-unitary freedom. Counting arguments and insights from the phase-space Schmidt decomposition and in general from the framework of symplectic analysis, accompany our description of the standard form of pure n-mode Gaussian states. In particula…

Statistics and ProbabilitySchmidt decompositionGaussianGeneral Physics and AstronomyFOS: Physical sciencesQuantum entanglementUnitary statesymbols.namesakeSYSTEMSFOS: MathematicsCONTINUOUS-VARIABLESStatistical physicsQuantum informationMathematical PhysicsMathematicsQuantum PhysicsCovariance matrixStatistical and Nonlinear PhysicsInvariant (physics)QUANTUM TELEPORTATION NETWORKMathematics - Symplectic GeometryModeling and SimulationPhase spacesymbolsSymplectic Geometry (math.SG)Quantum Physics (quant-ph)Optics (physics.optics)Physics - Optics
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Detección de cambios anómalos mediante teledetección

2016

Este trabajo de fin de máster aborda el problema de la detección automática de cambios anómalos ocurridos en la superficie terrestre mediante imágenes satelitales de la Tierra. Dichos cambios implican cualquier variación fuera de lo típicamente esperado que se produzca en un área determinada del planeta. Su detección es muy importante dentro de las ciencias de la Tierra, ya que en el contexto actual de calentamiento global y cambio climático, presentan una importancia muy elevada en la escala global y local, permitiendo descubrir nuevos efectos generados por las actividades humanas que alteren el medio natural, y también posibles desestabilizaciones a gran escala entre los sistemas terrestr…

distancia mahalanobisteledeteccióncontorneado elípticomatriz covarianzasUNESCO::CIENCIAS DE LA TIERRA Y DEL ESPACIOreed-xiaolidetección cambios anómalosgaussianidad
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Explicit signal to noise ratio in reproducing kernel Hilbert spaces

2011

This paper introduces a nonlinear feature extraction method based on kernels for remote sensing data analysis. The proposed approach is based on the minimum noise fraction (MNF) transform, which maximizes the signal variance while also minimizing the estimated noise variance. We here propose an alternative kernel MNF (KMNF) in which the noise is explicitly estimated in the reproducing kernel Hilbert space. This enables KMNF dealing with non-linear relations between the noise and the signal features jointly. Results show that the proposed KMNF provides the most noise-free features when confronted with PCA, MNF, KPCA, and the previous version of KMNF. Extracted features with the explicit KMNF…

Kernel methodSignal-to-noise ratiobusiness.industryNoise (signal processing)Covariance matrixKernel (statistics)Feature extractionPattern recognitionArtificial intelligencebusinessKernel principal component analysisMathematicsReproducing kernel Hilbert space2011 IEEE International Geoscience and Remote Sensing Symposium
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Birkhoff-Frink representations as functors

2010

In an earlier article we characterized, from the viewpoint of set theory, those closure operators for which the classical result of Birkhoff and Frink, stating the equivalence between algebraic closure spaces, subalgebra lattices and algebraic lattices, holds in a many-sorted setting. In the present article we investigate, from the standpoint of category theory, the form these equivalences take when the adequate morphisms of the several different species of structures implicated in them are also taken into account. Specifically, our main aim is to provide a functorial rendering of the Birkhoff-Frink representation theorems for both single-sorted algebras and many-sorted algebras, by definin…

AlgebraMorphismFunctorMathematics::Category TheoryGeneral MathematicsSubalgebraClosure (topology)Covariant transformationAlgebraic numberCategory theoryAlgebraic closureMathematicsMathematische Nachrichten
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Thinking outside the box: effects of modes larger than the survey on matter power spectrum covariance

2012

Considering the matter power spectrum covariance matrix, it has recently been found that there is a potentially dominant effect on mildly non-linear scales due to power in modes of size equal to and larger than the survey volume. This {\it beat coupling} effect has been derived analytically in perturbation theory and while it has been tested with simulations, some questions remain unanswered. Moreover, there is an additional effect of these large modes, which has so far not been included in analytic studies, namely the effect on the estimated {\it average} density which enters the power spectrum estimate. In this article, we work out analytic, perturbation theory based expressions including…

Astrofísicadark matter simulationsCosmology and GravitationCosmology and Nongalactic Astrophysics (astro-ph.CO)FOS: Physical sciencesBeat (acoustics)Astrophysicspower spectrumAstrophysics01 natural sciences0103 physical sciencesStatistical physics010303 astronomy & astrophysics/dk/atira/pure/core/subjects/cosmologyPhysicsCosmologia010308 nuclear & particles physicsCovariance matrixMatter power spectrumcosmological simulationsSpectral densityFísicaAstronomy and AstrophysicsCovarianceRedshiftGalaxyCosmologyStepping stonegalaxy clusteringAstrophysics - Cosmology and Nongalactic Astrophysics
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Joint second-order parameter estimation for spatio-temporal log-Gaussian Cox processes

2018

We propose a new fitting method to estimate the set of second-order parameters for the class of homogeneous spatio-temporal log-Gaussian Cox point processes. With simulations, we show that the proposed minimum contrast procedure, based on the spatio-temporal pair correlation function, provides reliable estimates and we compare the results with the current available methods. Moreover, the proposed method can be used in the case of both separable and non-separable parametric specifications of the correlation function of the underlying Gaussian Random Field. We describe earthquake sequences comparing several Cox model specifications.

spatio-temporal pair correlation functionEnvironmental EngineeringGaussianminimum contrast methodnon-separable covariance function010502 geochemistry & geophysics01 natural sciencesPoint processGaussian random fieldSet (abstract data type)010104 statistics & probabilitysymbols.namesakeCorrelation functionEnvironmental Chemistry0101 mathematicsSafety Risk Reliability and Qualityearthquakes0105 earth and related environmental sciencesGeneral Environmental ScienceWater Science and TechnologyParametric statisticsMathematicslog-Gaussian Cox processesEstimation theoryContrast (statistics)symbolsEarthquakes Log-Gaussian Cox processes Minimum contrast method Non-separable covariance function Spatio-temporal pair correlation functionSettore SECS-S/01 - StatisticaAlgorithm
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A Bayesian unified framework for risk estimation and cluster identification in small area health data analysis.

2020

Many statistical models have been proposed to analyse small area disease data with the aim of describing spatial variation in disease risk. In this paper, we propose a Bayesian hierarchical model that simultaneously allows for risk estimation and cluster identification. Our model formulation assumes that there is an unknown number of risk classes and small areas are assigned to a risk class by means of independent allocation variables. Therefore, areas within each cluster are assumed to share a common risk but they may be geographically separated. The posterior distribution of the parameter representing the number of risk classes is estimated using a novel procedure that combines its prior …

Computer scienceEpidemiologyPathology and Laboratory Medicine01 natural sciencesGeographical locations010104 statistics & probabilityChickenpoxMathematical and Statistical TechniquesStatisticsMedicine and Health SciencesPublic and Occupational Health0303 health sciencesMultidisciplinarySimulation and ModelingQREuropeIdentification (information)Medical MicrobiologySmall-Area AnalysisViral PathogensVirusesPhysical SciencesMedicinePathogensAlgorithmsResearch ArticleHerpesvirusesScienceBayesian probabilityPosterior probabilityBayesian MethodDisease SurveillanceDisease clusterResearch and Analysis MethodsRisk AssessmentMicrobiologyVaricella Zoster Virus03 medical and health sciencesRisk classPrior probabilityCovariateBayesian hierarchical modelingHumansEuropean Union0101 mathematicsMicrobial Pathogens030304 developmental biologyBiology and life sciencesOrganismsStatistical modelBayes TheoremProbability TheoryProbability DistributionMarginal likelihoodConvolutionSpainPeople and placesDNA virusesMathematical FunctionsMathematicsPloS one
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The Happy-Productive Worker Model and Beyond: Patterns of Wellbeing and Performance at Work

2019

According to the happy-productive worker thesis (HPWT), &ldquo

AdultEmploymentMaleIMPACTHealth Toxicology and MutagenesisHappinesslcsh:Medicine050109 social psychologyEnvironmental Sciences & EcologyEfficiencyDisease clusterLogistic regressionGOALSEudaimoniaORGANIZATIONAL CITIZENSHIPArticleJob SatisfactionRATINGShappy-productive worker0502 economics and businessCovariateHumans0501 psychology and cognitive sciencesoccupational wellbeingWork PerformancePublic Environmental & Occupational HealthHAPPINESSScience & Technology05 social scienceslcsh:RPublic Health Environmental and Occupational HealthMiddle AgedJOB-SATISFACTIONWork (electrical)SpainYOUNGFemaleEMPLOYEESHEALTHPsychologySocial psychologyLife Sciences & Biomedicine050203 business & managementEnvironmental SciencesperformanceInternational Journal of Environmental Research and Public Health
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