Search results for "Probability."

showing 10 items of 3396 documents

Supplementary material 1 from: Van Cann J, Virgilio M, Jordaens K, De Meyer M (2015) Wing morphometrics as a possible tool for the diagnosis of the C…

2015

Morphometric data: Explanation note: Specimen list and details and raw morphometric data (for both wing landmarks and wing band areas).

cryptic speciesfruit fliesCeratitis fasciventriswing morphometricsCeratitis anonaePosterior Group Membership ProbabilityCeratitis rosaintegrative taxonomy
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Supplementary material 6 from: Van Cann J, Virgilio M, Jordaens K, De Meyer M (2015) Wing morphometrics as a possible tool for the diagnosis of the C…

2015

Preliminary methodological experiment: unconstrained ordination of wing band areas: Explanation note: Principal component analysis (PCA) showing morphometric differences in wing band areas of 14 Ceratitis rosa specimens across sexes, wings (LW: left wing, RW: right wing), repeated images of the same wing (1, 2), repeated measures of the same image (A, B).

cryptic speciesfruit fliesCeratitis fasciventriswing morphometricsCeratitis anonaePosterior Group Membership ProbabilityCeratitis rosaintegrative taxonomy
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Supplementary material 10 from: Van Cann J, Virgilio M, Jordaens K, De Meyer M (2015) Wing morphometrics as a possible tool for the diagnosis of the …

2015

Constrained ordination of wing landmarks: Explanation note: Discriminant analysis of principal coordinates (DAPC) maximising morphometric differences in wing landmarks between males and females (a) Ceratitis anonae, Ceratitis fasciventris and Ceratitis rosa and (b) genotypic clusters A, F1, F2, R1, R2.

cryptic speciesfruit fliesCeratitis fasciventriswing morphometricsCeratitis anonaePosterior Group Membership ProbabilityCeratitis rosaintegrative taxonomy
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Supplementary material 7 from: Van Cann J, Virgilio M, Jordaens K, De Meyer M (2015) Wing morphometrics as a possible tool for the diagnosis of the C…

2015

Unconstrained ordination of wing landmarks across sexes of each morphospecies: Explanation note: Principal component analysis (PCA) showing morphometric differences in wing landmarks between sexes of each morphospecies (Ceratitis anonae, Ceratitis fasciventris, Ceratitis rosa). (all 227 specimens included).

cryptic speciesfruit fliesCeratitis fasciventriswing morphometricsCeratitis anonaePosterior Group Membership ProbabilityCeratitis rosaintegrative taxonomy
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Computational Techniques for the Analysis of Small Signals in High-Statistics Neutrino Oscillation Experiments

2020

The current and upcoming generation of Very Large Volume Neutrino Telescopes – collecting unprecedented quantities of neutrino events – can be used to explore subtle effects in oscillation physics, such as (but not restricted to) the neutrino mass ordering. The sensitivity of an experiment to these effects can be estimated from Monte Carlo simulations. With the high number of events that will be collected, there is a trade-off between the computational expense of running such simulations and the inherent statistical uncertainty in the determined values. In such a scenario, it becomes impractical to produce and use adequately-sized sets of simulated events with traditional methods, such as M…

data analysis methodNuclear and High Energy PhysicsMonte Carlo methodFVLV nu TData analysis; Detector; KDE; MC; Monte Carlo; Neutrino; Neutrino mass ordering; Smoothing; Statistics; VLVνTData analysisKDEFOS: Physical sciences01 natural sciencesIceCubeHigh Energy Physics - ExperimentHigh Energy Physics - Experiment (hep-ex)statistical analysisnumerical methods0103 physical sciencesStatisticsNeutrinoddc:530Sensitivity (control systems)MC010306 general physicsNeutrino oscillationInstrumentation and Methods for Astrophysics (astro-ph.IM)InstrumentationMonte CarloPhysicsVLVνT010308 nuclear & particles physicsOscillationStatisticsoscillation [neutrino]ObservableDetectorMonte Carlo [numerical calculations]WeightingNeutrino mass orderingPhysics and AstronomyPhysics - Data Analysis Statistics and ProbabilityPhysique des particules élémentairesNeutrinoAstrophysics - Instrumentation and Methods for AstrophysicsMATTERData Analysis Statistics and Probability (physics.data-an)SmoothingSmoothing
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Centile estimation for a proportion response variable.

2015

This paper introduces two general models for computing centiles when the response variable Y can take values between 0 and 1, inclusive of 0 or 1. The models developed are more flexible alternatives to the beta inflated distribution. The first proposed model employs a flexible four parameter logit skew Student t (logitSST) distribution to model the response variable Y on the unit interval (0, 1), excluding 0 and 1. This model is then extended to the inflated logitSST distribution for Y on the unit interval, including 1. The second model developed in this paper is a generalised Tobit model for Y on the unit interval, including 1. Applying these two models to (1-Y) rather than Y enables model…

dewey510Least-Squares AnalysiStatistics and ProbabilityMaleModels StatisticalLogistic ModelGeneralised Tobit modelEpidemiologyFractional dataLogit skew Student t distributionStatistical DistributionLogistic ModelsGAMLSSBeta inflated distributionHumansComputer SimulationSettore SECS-S/05 - Statistica SocialeLeast-Squares AnalysisSettore SECS-S/01 - StatisticaLungHumanStatistical DistributionsStatistics in medicine
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Information and communication technologies and teacher education in the new paradigms of higher education

2018

Abstract Media use in the teaching process occurs in several forms. Information and communication technologies can be used as work equipment and teaching aids, as well as tools or curriculum units, particularly in higher education. Technological changes and new information technologies, in addition to substantive knowledge of the material, require from teachers creativity, knowledge, and the skills of the didactic design of teaching using modern multimedia tools. In Croatia, there is a lack of research aimed at assessing the initial state of computer literacy within the higher education institutions. The aim of this study was to determine the level of knowledge and digital competence of (no…

didactic challenges; digital competences; representative sample; survey sampling research; the purpose of the application of new technologiesComplementary and alternative medicineHigher educationInformation and Communications Technologybusiness.industrydidactic challenges ; digital competences ; representative sample ; survey sampling research ; the purpose of the application of new technologiesMathematics educationComputingMilieux_COMPUTERSANDEDUCATIONPharmaceutical SciencePharmacology (medical)Probability and statisticsbusinessTeacher education
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Generalized heat equation and transitions between different heat-transport regimes in narrow stripes

2019

Abstract In the framework of weakly nonlocal thermodynamic theory, in this paper we derive a nonlocal and nonlinear heat-transport equation beyond the Fourier law by means of thermodynamic considerations in agreement with the second law. The obtained equation describes the transitions among different heat-transport regimes. The stability of the solution of that equation is also analyzed in a special case.

diffusive regimegeneralized heat equation05.70.Ln46.05.+b02 engineering and technologyballistic regime01 natural sciencesStability (probability)010305 fluids & plasmasphonon-hydrodynamic regime0203 mechanical engineering0103 physical sciencesGeneral Materials ScienceSpecial caseCivil and Structural EngineeringPhysicsMechanical EngineeringBallistic regimeCondensed Matter PhysicsNonlinear system020303 mechanical engineering & transportsClassical mechanics66.70.-fMechanics of MaterialsFourier lawHeat equationgeneralized heat equation; diffusive regime; phonon-hydrodynamic regime; ballistic regimeMechanics Research Communications
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Beyond Tandem Analysis: Joint Dimension Reduction and Clustering in R

2019

We present the R package clustrd which implements a class of methods that combine dimension reduction and clustering of continuous or categorical data. In particular, for continuous data, the package contains implementations of factorial K-means and reduced K-means; both methods combine principal component analysis with K-means clustering. For categorical data, the package provides MCA K-means, i-FCB and cluster correspondence analysis, which combine multiple correspondence analysis with K-means. Two examples on real data sets are provided to illustrate the usage of the main functions.

dimension reduction; clustering; principal component analysis; multiple correspondence analysis; K-meansStatistics and Probabilitydimension reduction clustering principal component analysis multiple correspon-dence analysis K-meansFactorialmultiple correspon-dence analysisMultiple correspondence analysiComputer sciencedimension reductionprincipal component analysisk-meansmultiple correspondence analysisPrincipal component analysicomputer.software_genre01 natural sciencesCorrespondence analysis010104 statistics & probabilityMultiple correspondence analysis0101 mathematicsCluster analysisCategorical variablelcsh:Statisticslcsh:HA1-4737Dimensionality reductionk-means clusteringK-meanPrincipal component analysisData miningHA29-32Statistics Probability and UncertaintycomputerSoftwareclusteringJournal of Statistical Software
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Natural induction: An objective bayesian approach

2009

The statistical analysis of a sample taken from a finite population is a classic problem for which no generally accepted objective Bayesian results seem to exist. Bayesian solutions to this problem may be very sensitive to the choice of the prior, and there is no consensus as to the appropriate prior to use.

education.field_of_studyAlgebra and Number Theorybusiness.industryApplied MathematicsBayesian probabilityPopulationBayes factorSample (statistics)Machine learningcomputer.software_genreBinomial distributionBayesian statisticsComputational MathematicsEconometricsBayesian hierarchical modelingGeometry and TopologyArtificial intelligencebusinesseducationcomputerAnalysisJeffreys priorMathematicsRevista de la Real Academia de Ciencias Exactas, Fisicas y Naturales. Serie A. Matematicas
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