Search results for "Parametric statistics"

showing 10 items of 354 documents

Accurate representation of the distributions of the 3D Poisson-Voronoi typical cell geometrical features

2019

Understanding the intricate and complex materials microstructure and how it is related to materials properties is an important problem in the Materials Science field. For a full comprehension of this relation, it is fundamental to be able to describe the main characteristics of the 3-dimensional microstructure. The most basic model used for approximating steel microstructure is the Poisson-Voronoi diagram. Poisson-Voronoi diagrams have interesting mathematical properties, and they are used as a good model for single-phase materials. In this paper we exploit the scaling property of the underlying Poisson process to derive the distribution of the main geometrical features of the grains for ev…

General Computer SciencePoisson-Voronoi diagramsMonte Carlo methodVoronoiGeneral Physics and Astronomy02 engineering and technology010402 general chemistryPoisson distribution01 natural sciencesParametric representationsymbols.namesakeGeneral Materials ScienceStatistical physicsRepresentation (mathematics)ScalingParametric statisticsDiagramGeneral Chemistry021001 nanoscience & nanotechnology0104 chemical sciencesComputational MathematicsDistribution (mathematics)Mechanics of Materialssymbols0210 nano-technologyVoronoi diagram3D grain sizeComputational Materials Science
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Solutions for parametric double phase Robin problems

2021

We consider a parametric double phase problem with Robin boundary condition. We prove two existence theorems. In the first the reaction is ( p − 1 )-superlinear and the solutions produced are asymptotically big as λ → 0 + . In the second the conditions on the reaction are essentially local at zero and the solutions produced are asymptotically small as λ → 0 + .

General Mathematics010102 general mathematicsasymptotically small solutionssuperlinear reactionC-conditionasymptotically big solutions01 natural sciences010101 applied mathematicsDouble phaseSettore MAT/05 - Analisi MatematicaUnbalanced growthApplied mathematics0101 mathematicsMathematicsParametric statisticsAsymptotic Analysis
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Order statistics-based parametric classification for multi-dimensional distributions

2013

Traditionally, in the field of Pattern Recognition (PR), the moments of the class-conditional densities of the respective classes have been used to perform classification. However, the use of phenomena that utilized the properties of the Order Statistics (OS) were not reported. Recently, in [10,8], we proposed a new paradigm named CMOS, Classification by the Moments of Order Statistics, which specifically used these quantifiers. It is fascinating that CMOS is essentially ''anti''-Bayesian in its nature because the classification is performed in a counter-intuitive manner, i.e., by comparing the testing sample to a few samples distant from the mean, as opposed to the Bayesian approach in whi…

GeneralizationGaussianBayesian probabilityOrder statisticExponential functionsymbols.namesakeExponential familyArtificial IntelligenceSignal ProcessingPattern recognition (psychology)symbolsComputer Vision and Pattern RecognitionAlgorithmSoftwareMathematicsParametric statisticsPattern Recognition
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Role of topological phase-defects in the parametric generation process

2008

Abstract We show that topological phase-defects are spontaneously generated from noise fluctuations in the degenerate configuration of the parametric interaction. These localized coherent structures are shown to affect the coherence properties of the parametrically generated field. It is shown that the emergence of coherence in the fundamental field relies on a previously unrecognized process of mutual annihilation of pairs of neighboring phase-defects. More precisely, the density of phase-defects N , and the time correlation τ c of the generated field, are shown to exhibit a power-law behavior with the propagation length, i.e., τ c ∝ z 1 / 4 , N ∝ z - 1 / 4 .

Generation processPhysicsAnnihilationbusiness.industryDegenerate energy levelsNonlinear opticsTopology01 natural sciencesAtomic and Molecular Physics and OpticsElectronic Optical and Magnetic MaterialsTime correlation010309 opticsOpticsParametric process0103 physical sciencesElectrical and Electronic EngineeringPhysical and Theoretical Chemistry010306 general physicsbusinessComputingMilieux_MISCELLANEOUSCoherence (physics)Parametric statisticsOptics Communications
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Nonparametric clustering of seismic events

2006

In this paper we propose a clustering technique, based on the maximization of the likelihood function defined from the generalization of a model for seismic activity (ETAS model, (Ogata (1988))), iteratively changing the partitioning of the events. In this context it is useful to apply models requiring the distinction between independent events (i.e. the background seismicity) and strongly correlated ones. This technique develops nonparametric estimation methods of the point process intensity function. To evaluate the goodness of fit of the model, from which the clustering method is implemented, residuals process analysis is used.

Goodness of fitGeneralizationComputer scienceNonparametric statisticsContext (language use)Maximization.Cluster analysisLikelihood functionAlgorithmPoint process
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On the classification of observations structured into groups

1988

The paper is concerned with the problem of classifying a specific group into two populations (insect eggs of the same clutch belonging therefore to the same species). Two approaches, one parametric and the other non-parametric, are described. The classical likelihood ratio procedure is derived. An interpretation and a decomposition of the test criteria is given. A misclassification estimate using the Chernoff–Kullback–Kailath region is provided.

Group (mathematics)business.industryManagement of Technology and InnovationModeling and SimulationStatisticsPattern recognitionArtificial intelligencebusinessMathematicsParametric statisticsInterpretation (model theory)Applied Stochastic Models and Data Analysis
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Empirical Likelihood-Based ANOVA for Trimmed Means

2016

In this paper, we introduce an alternative to Yuen’s test for the comparison of several population trimmed means. This nonparametric ANOVA type test is based on the empirical likelihood (EL) approach and extends the results for one population trimmed mean from Qin and Tsao (2002). The results of our simulation study indicate that for skewed distributions, with and without variance heterogeneity, Yuen’s test performs better than the new EL ANOVA test for trimmed means with respect to control over the probability of a type I error. This finding is in contrast with our simulation results for the comparison of means, where the EL ANOVA test for means performs better than Welch’s heteroscedastic…

HeteroscedasticityHealth Toxicology and MutagenesisPopulationRobust statisticslcsh:Medicineempirical likelihood01 natural sciencesArticletrimmed means010104 statistics & probabilityF-testStatisticshypothesis testing0101 mathematicseducationMathematicseducation.field_of_studyANOVA010102 general mathematicslcsh:RANOVA; empirical likelihood; trimmed means; robust statistics; hypothesis testingPublic Health Environmental and Occupational HealthNonparametric statisticsTruncated meanBrown–Forsythe testEmpirical likelihoodrobust statisticsInternational Journal of Environmental Research and Public Health; Volume 13; Issue 10; Pages: 953
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Biophysical parameter retrieval with warped Gaussian processes

2015

This paper focuses on biophysical parameter retrieval based on Gaussian Processes (GPs). Very often an arbitrary transformation is applied to the observed variable (e.g. chlorophyll content) to better pose the problem. This standard practice essentially tries to linearize/uniformize the distribution by applying non-linear link functions like the logarithmic, the exponential or the logistic functions. In this paper, we propose to use a GP model that automatically learns the optimal transformation directly from the data. The so-called warped GP regression (WGPR) presented in [1] models output observations as a parametric nonlinear transformation of a GP. The parameters of such prior model are…

HeteroscedasticityLogarithmbusiness.industryComputer scienceMaximum likelihoodExponential functionsymbols.namesakeTransformation (function)symbolsComputer visionArtificial intelligencebusinessGaussian processAlgorithmParametric statisticsVariable (mathematics)2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)
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Experimental Sentinel-2 LAI estimation using parametric, non-parametric and physical retrieval methods – A comparison

2015

Abstract Given the forthcoming availability of Sentinel-2 (S2) images, this paper provides a systematic comparison of retrieval accuracy and processing speed of a multitude of parametric, non-parametric and physically-based retrieval methods using simulated S2 data. An experimental field dataset (SPARC), collected at the agricultural site of Barrax (Spain), was used to evaluate different retrieval methods on their ability to estimate leaf area index (LAI). With regard to parametric methods, all possible band combinations for several two-band and three-band index formulations and a linear regression fitting function have been evaluated. From a set of over ten thousand indices evaluated, the …

HeteroscedasticityMean squared errorEconomicsComputer scienceImage processingBiophysical variablessymbols.namesakeLaboratory of Geo-information Science and Remote SensingMachine learningStatisticsLinear regressionLaboratorium voor Geo-informatiekunde en Remote SensingComputers in Earth SciencesParametricEngineering (miscellaneous)Gaussian processPhysically-based RTM inversionParametric statisticsPhysicsNonparametric statisticsPE&RCNon-parametricAtomic and Molecular Physics and OpticsComputer Science ApplicationsLookup tablesymbolsSentinel-2Engineering sciences. TechnologyAlgorithmISPRS Journal of Photogrammetry and Remote Sensing
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Gravitational Test beyond the First Post-Newtonian Order with the Shadow of the M87 Black Hole

2020

All authors: Psaltis, Dimitrios; Medeiros, Lia; Christian, Pierre; Özel, Feryal; Akiyama, Kazunori; Alberdi, Antxon; Alef, Walter; Asada, Keiichi; Azulay, Rebecca; Ball, David; Baloković, Mislav; Barrett, John; Bintley, Dan; Blackburn, Lindy; Boland, Wilfred; Bower, Geoffrey C.; Bremer, Michael; Brinkerink, Christiaan D.; Brissenden, Roger; Britzen, Silke Broguiere, Dominique; Bronzwaer, Thomas; Byun, Do-Young; Carlstrom, John E.; Chael, Andrew; Chan, Chi-kwan; Chatterjee, Shami; Chatterjee, Koushik; Chen, Ming-Tang; Chen, Yongjun; Cho, Ilje; Conway, John E.; Cordes, James M.; Crew, Geoffrey B.; Cui, Yuzhu; Davelaar, Jordy; De Laurentis, Mariafelicia; Deane, Roger; Dempsey, Jessica; Desvign…

High Energy Astrophysical Phenomena (astro-ph.HE)Event Horizon TelescopePhysicsGravitational waveAstronomyKerr metricFOS: Physical sciencesGeneral Physics and AstronomyGeneral Relativity and Quantum Cosmology (gr-qc)Gravitation and Astrophysics01 natural sciencesGeneral Relativity and Quantum CosmologyBlack holeGravitationGeneral Relativity and Quantum Cosmology0103 physical sciencesMetric (mathematics)Shadow[PHYS.GRQC]Physics [physics]/General Relativity and Quantum Cosmology [gr-qc]Statistical physics[PHYS.ASTR]Physics [physics]/Astrophysics [astro-ph]010306 general physicsAstrophysics - High Energy Astrophysical PhenomenaParametric statisticsPhysical Review Letters
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