Search results for "Discriminant"

showing 10 items of 344 documents

A Comment on the Coefficient of Determination for Binary Responses

1992

Abstract Linear logistic or probit regression can be closely approximated by an unweighted least squares analysis of the regression linear in the conditional probabilities provided that these probabilities for success and failure are not too extreme. It is shown how this restriction on the probabilities translates into a restriction on the range of the coefficient of determination R 2 so that, as a consequence, R 2 is not suitable to judge the effectiveness of linear regressions with binary responses even if an important relation is present.

Statistics and ProbabilityCoefficient of determinationGeneral MathematicsProbit modelLinear regressionStatisticsConditional probabilityMultiple correlationStatistics Probability and UncertaintyLinear discriminant analysisLogistic regressionRegressionMathematicsThe American Statistician
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The affine equivariant sign covariance matrix: asymptotic behavior and efficiencies

2003

We consider the affine equivariant sign covariance matrix (SCM) introduced by Visuri et al. (J. Statist. Plann. Inference 91 (2000) 557). The population SCM is shown to be proportional to the inverse of the regular covariance matrix. The eigenvectors and standardized eigenvalues of the covariance, matrix can thus be derived from the SCM. We also construct an estimate of the covariance and correlation matrix based on the SCM. The influence functions and limiting distributions of the SCM and its eigenvectors and eigenvalues are found. Limiting efficiencies are given in multivariate normal and t-distribution cases. The estimates are highly efficient in the multivariate normal case and perform …

Statistics and ProbabilityCovariance functionaffine equivarianceinfluence functionMultivariate normal distributionrobustnessComputer Science::Human-Computer InteractionEfficiencyestimatorsEstimation of covariance matricesScatter matrixStatisticsAffine equivarianceApplied mathematicsCMA-ESMultivariate signCovariance and correlation matricesRobustnessmultivariate medianMathematicsprincipal componentsInfluence functionNumerical AnalysisMultivariate medianCovariance matrixcovariance and correlation matricesdiscriminant-analysisCovarianceComputer Science::Otherdispersion matricesefficiencyLaw of total covariancemultivariate locationtestsStatistics Probability and Uncertaintyeigenvectors and eigenvaluesEigenvectors and eigenvaluesmultivariate signJournal of Multivariate Analysis
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STATIS and DISTATIS: optimum multitable principal component analysis and three way metric multidimensional scaling

2012

STATIS is an extension of principal component analysis PCA tailored to handle multiple data tables that measure sets of variables collected on the same observations, or, alternatively, as in a variant called dual-STATIS, multiple data tables where the same variables are measured on different sets of observations. STATIS proceeds in two steps: First it analyzes the between data table similarity structure and derives from this analysis an optimal set of weights that are used to compute a linear combination of the data tables called the compromise that best represents the information common to the different data tables; Second, the PCA of this compromise gives an optimal map of the observation…

Statistics and ProbabilityMathematical optimizationSimilarity (geometry)[STAT.TH]Statistics [stat]/Statistics Theory [stat.TH]Linear discriminant analysiscomputer.software_genre01 natural sciences[ STAT.TH ] Statistics [stat]/Statistics Theory [stat.TH]Correspondence analysisSet (abstract data type)010104 statistics & probability03 medical and health sciences0302 clinical medicine[MATH.MATH-ST]Mathematics [math]/Statistics [math.ST]Multiple factor analysisPrincipal component analysisMetric (mathematics)Data miningMultidimensional scaling[ MATH.MATH-ST ] Mathematics [math]/Statistics [math.ST]0101 mathematicscomputer030217 neurology & neurosurgeryComputingMilieux_MISCELLANEOUSMathematics
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On the usage of joint diagonalization in multivariate statistics

2022

Scatter matrices generalize the covariance matrix and are useful in many multivariate data analysis methods, including well-known principal component analysis (PCA), which is based on the diagonalization of the covariance matrix. The simultaneous diagonalization of two or more scatter matrices goes beyond PCA and is used more and more often. In this paper, we offer an overview of many methods that are based on a joint diagonalization. These methods range from the unsupervised context with invariant coordinate selection and blind source separation, which includes independent component analysis, to the supervised context with discriminant analysis and sliced inverse regression. They also enco…

Statistics and ProbabilityScatter matricesMultivariate statisticsContext (language use)010103 numerical & computational mathematics01 natural sciencesBlind signal separation010104 statistics & probabilitySliced inverse regression0101 mathematicsB- ECONOMIE ET FINANCESupervised dimension reductionMathematicsNumerical Analysisbusiness.industryCovariance matrixPattern recognitionriippumattomien komponenttien analyysimatemaattinen tilastotiedeLinear discriminant analysisInvariant component selectionIndependent component analysismonimuuttujamenetelmätPrincipal component analysisDimension reductionBlind source separationArtificial intelligenceStatistics Probability and Uncertaintybusiness
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Large-sample properties of unsupervised estimation of the linear discriminant using projection pursuit

2021

We study the estimation of the linear discriminant with projection pursuit, a method that is unsupervised in the sense that it does not use the class labels in the estimation. Our viewpoint is asymptotic and, as our main contribution, we derive central limit theorems for estimators based on three different projection indices, skewness, kurtosis, and their convex combination. The results show that in each case the limiting covariance matrix is proportional to that of linear discriminant analysis (LDA), a supervised estimator of the discriminant. An extensive comparative study between the asymptotic variances reveals that projection pursuit gets arbitrarily close in efficiency to LDA when the…

Statistics and Probabilitylinear discriminant analysismatematiikkakurtosisprojection pursuitskewnessStatistics Probability and Uncertaintyclusteringestimointi
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The Development of the Dealing with Challenging Interaction (DCI) Method to Evaluate Teachers’ Social Interaction Skills

2012

The Dealing with Challenging Interaction (DCI) method was developed to measure social interaction skills of teacher study groups. The participants were 70 teachers from three schools. The inter-rater agreement, Cohen’s kappa, varied between 0.57- 1.00. The discriminant validity was supported by a cluster analysis differentiating between the skilful and less skilful teachers. The results of the supplementary instrument were equivalent to the cluster analysis maintaining criterion oriented validity of the method developed. The DCI appeared to be a reliable and valid tool for measuring teachers’ social interaction skills. Peer reviewed

Study groupsevaluation methodologies515 Psychologymedia_common.quotation_subjectsupporting autonomychallenging interactionteacher trainingevaluation method03 medical and health sciences0302 clinical medicineSocial interaction skillsEvaluation methodsSocial emotional learningMathematics educationTeacher Effectiveness TrainingDealing with Challenging InteractionGeneral Materials Sciencevuorovaikutuksen tutkimus030212 general & internal medicineautonomyopettajankoulutusta515media_common4. Education05 social sciencesteacher study groupDiscriminant validity050301 educationsocial interactionglobal ratingsocial and emotional learningSocial relationGlobal Rating516 Educational sciencesPsychology0503 educationSocial psychologyAutonomyProcedia - Social and Behavioral Sciences
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Arithmetic and geometry of a K3 surface emerging from virtual corrections to Drell–Yan scattering

2020

We study a K3 surface, which appears in the two-loop mixed electroweak-quantum chromodynamic virtual corrections to Drell--Yan scattering. A detailed analysis of the geometric Picard lattice is presented, computing its rank and discriminant in two independent ways: first using explicit divisors on the surface and then using an explicit elliptic fibration. We also study in detail the elliptic fibrations of the surface and use them to provide an explicit Shioda--Inose structure. Moreover, we point out the physical relevance of our results.

Surface (mathematics)Algebra and Number TheoryRank (linear algebra)ScatteringHigh Energy Physics::PhenomenologyFibrationStructure (category theory)General Physics and AstronomyLattice (discrete subgroup)K3 surfaceTheoretical physicsMathematics::Algebraic GeometryDiscriminantMathematical PhysicsMathematicsCommunications in Number Theory and Physics
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Use of linear discriminant analysis applied to vibrational spectroscopy data to characterize commercial varnishes employed for art purposes.

2007

An improvement of methodologies for characterising synthetic resins used in varnishes employed for art purposes has been suggested. Several kinds of standard of the most common polymeric resins (acrylic, vinyl, poly(vinyl alcohol), alkyd, cellulose nitrate, latex, polyester, polyurethane, epoxy, organosilicic, and ketonic) were analyzed by Fourier transform infrared (FTIR) spectroscopy. Synthetic resins characterization is based on the mathematical treatment of their whole spectrum, dividing it in 13 sections, avoiding the one-by-one interpretation of the absorption bands. The mathematical model takes as variables the maximal absorbance of each section, and each synthetic standard resin as …

Synthetic resinChemistryAlkydVarnishAnalytical chemistryEpoxyLinear discriminant analysisBiochemistryFourier transform spectroscopyAnalytical ChemistryChemometricsvisual_artPrincipal component analysisvisual_art.visual_art_mediumEnvironmental ChemistryBiological systemSpectroscopyAnalytica chimica acta
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Time, frequency and information domain analysis of short-term heart rate variability before and after focal and generalized seizures in epileptic chi…

2019

OBJECTIVE In this work we explore the potential of combining standard time and frequency domain indexes with novel information measures, to characterize pre- and post-ictal heart rate variability (HRV) in epileptic children, with the aim of differentiating focal and generalized epilepsy regarding the autonomic control mechanisms. APPROACH We analyze short-term HRV in 37 children suffering from generalized or focal epilepsy, monitored 10 s, 300 s, 600 s and 1800 s both before and after seizure episodes. Nine indexes are computed in time (mean, standard deviation of normal-to-normal intervals, root mean square of the successive differences (RMSSD)), frequency (low-to-high frequency power rati…

TachycardiaMalefocal epilepsymedicine.medical_specialtyPhysiology0206 medical engineeringBiomedical EngineeringBiophysicsHeart Rate Variability02 engineering and technologyAutonomic Nervous SystemSettore ING-INF/01 - ElettronicaStandard deviation03 medical and health sciencesEpilepsy0302 clinical medicineHeart RateSeizuresPhysiology (medical)Internal medicinemedicineHeart rate variabilityHumansClinical significanceGeneralized epilepsyChildgeneralized epilepsybusiness.industryLinear discriminant analysismedicine.disease020601 biomedical engineeringTime–frequency analysisSettore ING-INF/06 - Bioingegneria Elettronica E InformaticaCardiologyFemalemedicine.symptombusinesscomplexity030217 neurology & neurosurgery
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Assessing the territorial influence of an Iberian worship site. The chemical characterisation of the terracotta from the Iron Age sanctuary of La Ser…

2017

This paper presents the study of the prestigious terracotta votive figurines from the Iberian Iron Age sanctuary of La Serreta (Alicante province, Spain) composed of 174 items. Portable X-ray fluorescence (PXRF) was used to identify elemental markers that permit us to observe the differences between local and non-local terracotta figurines and furthermore to evaluate the geographical influence of the La Serreta sanctuary using Principal Component Analysis (PCA). The Partial Least Squares Discriminant Analysis (PLSDA) statistical method was also used to classify the figurines of uncertain geographical origin. The resulting groups were related to typological and stylistic groups of figurines …

TerracottaAlicanteArcheology060102 archaeologyTerritorial influence010308 nuclear & particles physicsmedia_common.quotation_subjectLa Serreta06 humanities and the artsLinear discriminant analysisWorship01 natural sciencesArchaeologyArqueologíaGeographyIron Agevisual_art0103 physical sciencesPartial least squares regressionPrincipal component analysisvisual_art.visual_art_medium0601 history and archaeologyIberian Iron Age sanctuaryTerracottamedia_common
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