Search results for "Probability"

showing 10 items of 3417 documents

Synergetic and redundant information flow detected by unnormalized Granger causality: application to resting state fMRI

2015

Objectives: We develop a framework for the analysis of synergy and redundancy in the pattern of information flow between subsystems of a complex network. Methods: The presence of redundancy and/or synergy in multivariate time series data renders difficult to estimate the neat flow of information from each driver variable to a given target. We show that adopting an unnormalized definition of Granger causality one may put in evidence redundant multiplets of variables influencing the target by maximizing the total Granger causality to a given target, over all the possible partitions of the set of driving variables. Consequently we introduce a pairwise index of synergy which is zero when two in…

FOS: Computer and information sciencesgranger causality (GC)Multivariate statisticsComputer scienceRestComputer Science - Information TheoryBiomedical EngineeringsynergyFOS: Physical sciencescomputer.software_genre01 natural sciences03 medical and health sciences0302 clinical medicineGranger causality0103 physical sciencesConnectomeRedundancy (engineering)HumansBrain connectivityTime series010306 general physicsModels StatisticalHuman Connectome ProjectResting state fMRIredundancybusiness.industryInformation Theory (cs.IT)functional magnetic resonance imaging (fMRI)BrainPattern recognitionComplex networkMagnetic Resonance ImagingVariable (computer science)Physics - Data Analysis Statistics and ProbabilityQuantitative Biology - Neurons and CognitionFOS: Biological sciencesSettore ING-INF/06 - Bioingegneria Elettronica E InformaticaPairwise comparisonNeurons and Cognition (q-bio.NC)Artificial intelligenceData miningNerve Netbusinesscomputer030217 neurology & neurosurgeryData Analysis Statistics and Probability (physics.data-an)
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Bayesian Analysis of Population Health Data

2021

The analysis of population-wide datasets can provide insight on the health status of large populations so that public health officials can make data-driven decisions. The analysis of such datasets often requires highly parameterized models with different types of fixed and random effects to account for risk factors, spatial and temporal variations, multilevel effects and other sources on uncertainty. To illustrate the potential of Bayesian hierarchical models, a dataset of about 500,000 inhabitants released by the Polish National Health Fund containing information about ischemic stroke incidence for a 2-year period is analyzed using different types of models. Spatial logistic regression and…

FOS: Computer and information sciencesmedicine.medical_specialtyComputer scienceGeneral MathematicsBayesian probabilitydisease mappingPopulation healthbayesian inference; disease mapping; integrated nested Laplace approximation; spatial models; survival modelsBayesian inferenceLogistic regressionStatistics - Applications01 natural sciences010104 statistics & probability03 medical and health sciences0302 clinical medicineStatisticsComputer Science (miscellaneous)medicineApplications (stat.AP)spatial models0101 mathematicsEngineering (miscellaneous)Socioeconomic statusbayesian inferencesurvival modelslcsh:MathematicsPublic healthintegrated nested Laplace approximationlcsh:QA1-939Random effects modelSpatial variability030217 neurology & neurosurgeryMathematics
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Fast PET Scan Tumor Segmentation Using Superpixels, Principal Component Analysis and K-Means Clustering

2018

Positron Emission Tomography scan images are extensively used in radiotherapy planning, clinical diagnosis, assessment of growth and treatment of a tumor. These all rely on fidelity and speed of detection and delineation algorithm. Despite intensive research, segmentation remained a challenging problem due to the diverse image content, resolution, shape, and noise. This paper presents a fast positron emission tomography tumor segmentation method in which superpixels are extracted first from the input image. Principal component analysis is then applied on the superpixels and also on their average. Distance vector of each superpixel from the average is computed in principal components coordin…

FOS: Computer and information sciencespositron emission tomographyprincipal component analysisComputer scienceComputer Vision and Pattern Recognition (cs.CV)k-meansCoordinate systemComputer Science - Computer Vision and Pattern RecognitionFOS: Physical sciences02 engineering and technologyBenchmarkQuantitative Biology - Quantitative MethodsBiochemistry Genetics and Molecular Biology (miscellaneous)030218 nuclear medicine & medical imagingsuperpixels03 medical and health sciences0302 clinical medicineStructural Biology0202 electrical engineering electronic engineering information engineeringmedicineSegmentationComputer visionTissues and Organs (q-bio.TO)Cluster analysisQuantitative Methods (q-bio.QM)Pixelmedicine.diagnostic_testbusiness.industrysegmentationk-means clusteringQuantitative Biology - Tissues and OrgansPattern recognitionPhysics - Medical PhysicsPositron emission tomographyFOS: Biological sciencesPhysics - Data Analysis Statistics and ProbabilityPrincipal component analysis020201 artificial intelligence & image processingMedical Physics (physics.med-ph)Artificial intelligenceNoise (video)businessData Analysis Statistics and Probability (physics.data-an)BiotechnologyMethods and Protocols
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General framework for testing Poisson-Voronoi assumption for real microstructures

2020

Modeling microstructures is an interesting problem not just in Materials Science but also in Mathematics and Statistics. The most basic model for steel microstructure is the Poisson-Voronoi diagram. It has mathematically attractive properties and it has been used in the approximation of single phase steel microstructures. The aim of this paper is to develop methods that can be used to test whether a real steel microstructure can be approximated by such a model. Therefore, a general framework for testing the Poisson-Voronoi assumption based on images of 2D sections of real metals is set out. Following two different approaches, according to the use or not of periodic boundary conditions, thre…

FOS: Computer and information sciencesreal microstructuresPoisson-Voronoi diagrams0211 other engineering and technologies02 engineering and technologyManagement Science and Operations ResearchPoisson distribution01 natural sciencesStatistics - ApplicationsMethodology (stat.ME)Set (abstract data type)010104 statistics & probabilitysymbols.namesakehypothesis testingPeriodic boundary conditionsApplied mathematicsApplications (stat.AP)0101 mathematicsStatistics - MethodologyStatistical hypothesis testing021103 operations researchCumulative distribution functionDiagramscalingGeneral Business Management and Accounting62P30 62-00 62-01 62G10persistence landscapeModeling and SimulationsymbolsTopological data analysiscumulative distribution functionVoronoi diagramApplied Stochastic Models in Business and Industry
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Fast Estimation of Diffusion Tensors under Rician noise by the EM algorithm

2016

Diffusion tensor imaging (DTI) is widely used to characterize, in vivo, the white matter of the central nerve system (CNS). This biological tissue contains much anatomic, structural and orientational information of fibers in human brain. Spectral data from the displacement distribution of water molecules located in the brain tissue are collected by a magnetic resonance scanner and acquired in the Fourier domain. After the Fourier inversion, the noise distribution is Gaussian in both real and imaginary parts and, as a consequence, the recorded magnitude data are corrupted by Rician noise. Statistical estimation of diffusion leads a non-linear regression problem. In this paper, we present a f…

FOS: Computer and information sciencesreduced computationGaussianModels NeurologicalDatasets as Topicta3112Statistics - ComputationStatistics - ApplicationsTime030218 nuclear medicine & medical imagingMethodology (stat.ME)Diffusion03 medical and health sciencessymbols.namesake0302 clinical medicineScoring algorithmRician fadingPrior probabilityExpectation–maximization algorithmImage Processing Computer-AssistedMaximum a posteriori estimationHumansApplications (stat.AP)Computer SimulationComputation (stat.CO)Statistics - MethodologyMathematicsta112Likelihood FunctionsGeneral NeuroscienceBrainEstimatormaximum likelihood estimatorFisher scoringMagnetic Resonance ImagingWhite MatterRician likelihoodDiffusion Tensor ImagingFourier transformNonlinear Dynamicssymbolsmaximum a posteriori estimatorAlgorithmAlgorithms030217 neurology & neurosurgerydata augmentation
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The limit order book on different time scales

2007

Financial markets can be described on several time scales. We use data from the limit order book of the London Stock Exchange (LSE) to compare how the fluctuation dominated microstructure crosses over to a more systematic global behavior.

FOS: Economics and businessPhysics - Physics and SocietyQuantitative Finance - Trading and Market MicrostructureStock exchangePhysics - Data Analysis Statistics and ProbabilityFinancial marketEconomicsEconometricsFOS: Physical sciencesPhysics and Society (physics.soc-ph)Data Analysis Statistics and Probability (physics.data-an)Trading and Market Microstructure (q-fin.TR)
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Ensemble properties of securities traded in the NASDAQ market

2001

We study the price dynamics of stocks traded in the NASDAQ market by considering the statistical properties of an ensemble of stocks traded simultaneously. For each trading day of our database, we study the ensemble return distribution by extracting its first two central moments. According to previous results obtained for the NYSE market, we find that the second moment is a long-range correlated variable. We compare time-averaged and ensemble-averaged price returns and we show that the two averaging procedures lead to different statistical results.

FOS: Economics and businessStatistics and ProbabilityReturn distributionVariable (computer science)Statistical Finance (q-fin.ST)Statistical Mechanics (cond-mat.stat-mech)EconometricsQuantitative Finance - Statistical FinanceFOS: Physical sciencesSecond moment of areaCondensed Matter PhysicsCondensed Matter - Statistical MechanicsMathematicsPhysica A: Statistical Mechanics and its Applications
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Levels of complexity in financial markets

2001

We consider different levels of complexity which are observed in the empirical investigation of financial time series. We discuss recent empirical and theoretical work showing that statistical properties of financial time series are rather complex under several ways. Specifically, they are complex with respect to their (i) temporal and (ii) ensemble properties. Moreover, the ensemble return properties show a behavior which is specific to the nature of the trading day reflecting if it is a normal or an extreme trading day.

FOS: Economics and businessStatistics and ProbabilityStatistical Finance (q-fin.ST)Statistical Mechanics (cond-mat.stat-mech)Series (mathematics)Work (electrical)Financial marketEconometricsEconomicsFOS: Physical sciencesQuantitative Finance - Statistical FinanceCondensed Matter PhysicsCondensed Matter - Statistical MechanicsPhysica A: Statistical Mechanics and its Applications
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Outage statistics for Beckmann fading channels in non-isotropic scattering environments

2015

In this paper, the outage statistics are studied for non-isotropic Beckmann fading channel model. Non-isotropic scattering generally results in an asymmetrical Doppler power spectral density (PSD). In this context, an expression for the outage probability (OP) (or equivalently the cumulative distribution function (CDF)) of the fading envelope is first derived. Then, the probability density function (PDF) of the rate of change of the fading envelope is investigated. Thereafter, an expression for the average rate of outages (ARO) (or equivalently the level-crossing rate (LCR)) is provided. Finally, by making use of the analytical results of the ARO and OP, an expression for the average durati…

Fading distributionCumulative distribution functionStatisticsSpectral densityContext (language use)Probability density functionFadingEnvelope (mathematics)Expression (mathematics)Computer Science::Information TheoryMathematics2015 21st Asia-Pacific Conference on Communications (APCC)
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Multimodal and multicriteria analysis for VLSI expertises and defects localization

2017

The purpose of this manuscript is to exhibit the research work solving the issue of data processing stem from defect localization techniques. This step being decisive in the failure analysis process, scientists have to harness data coming from light emission and laser techniques. Nevertheless, this analysis process is sequential and only depends on the expert’s decision. This factor leads to a not quantified probability of localization. Consequently to solve these issues, a multimodal and multicriteria analysis has been developped, taking advantage of the heterogeneous andcomplementary nature of light emission and laser probing techniques. This kind of process is based on advanced level too…

Failure analysisdata fusionAnalyse de défaillancescircuits intégrés[SPI.NANO] Engineering Sciences [physics]/Micro and nanotechnologies/Microelectronicsanalyse multimodale et multicritèrestraitement du signal/imagesignal/image processingVLSI[STAT] Statistics [stat]multimodal and criteria analysisdefect localizationlocalisation de défauts[PHYS.PHYS.PHYS-DATA-AN] Physics [physics]/Physics [physics]/Data Analysis Statistics and Probability [physics.data-an]fusion de données[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing
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