Search results for " Robust statistics"

showing 4 items of 4 documents

Comparison of Internal Clustering Validation Indices for Prototype-Based Clustering

2017

Clustering is an unsupervised machine learning and pattern recognition method. In general, in addition to revealing hidden groups of similar observations and clusters, their number needs to be determined. Internal clustering validation indices estimate this number without any external information. The purpose of this article is to evaluate, empirically, characteristics of a representative set of internal clustering validation indices with many datasets. The prototype-based clustering framework includes multiple, classical and robust, statistical estimates of cluster location so that the overall setting of the paper is novel. General observations on the quality of validation indices and on t…

Fuzzy clusteringlcsh:T55.4-60.8Computer scienceSingle-linkage clusteringCorrelation clustering02 engineering and technologycomputer.software_genrelcsh:QA75.5-76.95Theoretical Computer Scienceprototype-based clusteringCURE data clustering algorithm020204 information systemsprototype-based clustering; clustering validation index; robust statisticsConsensus clusteringalgoritmit0202 electrical engineering electronic engineering information engineeringlcsh:Industrial engineering. Management engineeringCluster analysisk-medians clusteringta113Numerical Analysisbusiness.industryPattern recognitionDetermining the number of clusters in a data setComputational MathematicsComputingMethodologies_PATTERNRECOGNITIONComputational Theory and Mathematicsrobust statistics020201 artificial intelligence & image processinglcsh:Electronic computers. Computer scienceArtificial intelligenceData miningtiedonlouhintabusinessclustering validation indexcomputerAlgorithms
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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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Experimental and robust modeling approach for lead(II) uptake by alginate gel beads: influence of the ionic strength and medium composition.

2014

Abstract Systematic kinetic and equilibrium studies on the lead ions removal ability by Ca-alginate gel beads have been performed by varying several internal parameters, namely, number of gel beads, nature and composition of the ionic medium and pH, which allowed us to model a wastewater in order to closely reproduce the composition of a real sample. Moreover, the effects brought about the different ionic species present in the reacting medium have been evaluated. Differential Pulse Anodic Stripping Voltammetry (DP-ASV), has been systematically used to perform kinetic and equilibrium measurements over continuous time in a wide range of concentration. Kinetic and equilibrium data have been q…

Accuracy and precisionChemistryAnalytical chemistryIonic bondingKinetic energySurfaces Coatings and FilmsElectronic Optical and Magnetic MaterialsIonBiomaterialsAnodic stripping voltammetryColloid and Surface ChemistryIonic strengthAlginate gel beads Robust statistics Metal adsorption Wastewater treatment Ionic strength Differential Pulse Anodic Stripping Voltammetry Adsorption isotherms Adsorption kinetics Lead Heavy metalmedicineComposition (visual arts)Settore CHIM/01 - Chimica AnaliticaSwellingmedicine.symptomJournal of colloid and interface science
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Improvement in fast particle track reconstruction with robust statistics

2014

The IceCube project has transformed one cubic kilometer of deep natural Antarctic ice into a Cherenkov detector. Muon neutrinos are detected and their direction inferred by mapping the light produced by the secondary muon track inside the volume instrumented with photomultipliers. Reconstructing the muon track from the observed light is challenging due to noise, light scattering in the ice medium, and the possibility of simultaneously having multiple muons inside the detector, resulting from the large flux of cosmic ray muons. This manuscript describes work on two problems: (1) the track reconstruction problem, in which, given a set of observations, the goal is to recover the track of a muo…

Nuclear and High Energy PhysicsParticle physicsCherenkov detectorPhysics::Instrumentation and DetectorsFOS: Physical sciencesddc:500.2Neutrino telescopeTrack reconstructionlaw.inventionIceCubelawCoincidentAngular resolutionddc:530InstrumentationInstrumentation and Methods for Astrophysics (astro-ph.IM)Remote sensingIce CubePhysicsMuonTrack (disk drive)DetectorIceCube; Neutrino astrophysics; Neutrino telescope; Robust statistics; Track reconstructionRobust statisticsNeutrino astrophysicsNeutrino detectorHigh Energy Physics::ExperimentNeutrinoAstrophysics - Instrumentation and Methods for AstrophysicsNuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment
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