Search results for "Multivariate statistics"

showing 10 items of 290 documents

A discrete mathematical model for addictive buying: Predicting the affected population evolution

2011

This paper deals with the construction of a discrete mathematical model for addictive buying. Firstly, identifications of consumers buying behavior are performed by using multivariate statistical techniques based on real data bases and sociological approaches. Then the population is divided into appropriate groups according to the level of overbuying and a discrete compartmental model is constructed. The future short term addicted population is computed assuming several future economic scenarios. © 2010 Elsevier Ltd.

Multivariate statisticsMultivariate analysismedia_common.quotation_subjectPopulationMultivariant analysisAddictive buyingPopulation evolutionModelling and SimulationShort termEconometricsBuying behavioreducationmedia_commonDiscrete mathematical modeleducation.field_of_studyMathematical modelsMathematical modelAddictionModelingPopulation evolutionMultivariate statisticsCompartmental modelComputer Science ApplicationsTerm (time)Modeling and SimulationMultivariate statistical techniquesMultivariate statisticalMATEMATICA APLICADACompulsive buying
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Association between odontoma size, age and gender: Multivariate analysis of retrospective data

2019

Background The variety of characteristics related to odontoma research, including an unexplored one such as size, merits a multivariate approach that allows the adequate drawing of inferences with pertinent conclusions. The objective of this study is to establish the possible association between some characteristics related to the odontoma, tumor size among them. Material and methods The sociodemographic characteristics of 60 patients were evaluated. Diagnosis, size, location, type of treatment performed, and prognosis were determined. These data were analyzed descriptively and through multivariate models. Results Thirty-four compound and 26 complex odontomas in 32 men and 28 women were obs…

Multivariate statisticsOral Medicine and PathologyMultivariate analysisbusiness.industryResearchConfoundingDentistryCompound OdontomaContext (language use)030206 dentistry:CIENCIAS MÉDICAS [UNESCO]medicine.diseaseLogistic regression03 medical and health sciences0302 clinical medicineOdontoma030220 oncology & carcinogenesisUNESCO::CIENCIAS MÉDICASLinear regressionmedicinebusinessGeneral DentistryJournal of Clinical and Experimental Dentistry
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Directed coherence analysis in patients with severe autonomic dysfunction

2014

Many different approaches have been applied to analyse the coupling between cardiovascular signals. This study evaluated the use of directed coherence, based on multivariate autoregressive modelling, for analysis of cardiovascular signals in patients with transthyretin amyloidosis, a rare disease where severe autonomic dysfunction is common. © 2014 IEEE.

Multivariate statisticsPathologymedicine.medical_specialtyPhysical medicine and rehabilitationAutoregressive modelbusiness.industrySettore ING-INF/06 - Bioingegneria Elettronica E InformaticaBiomedical EngineeringmedicineCoherence (signal processing)In patientbusinessCoherence analysis2014 8th Conference of the European Study Group on Cardiovascular Oscillations (ESGCO)
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Background Correction and Multivariate Curve Resolution of Online Liquid Chromatography with Infrared Spectrometric Detection

2011

J.K. acknowledges the “V Segles” grant provided by the University of Valencia to carry out this study. Authors acknowledge the financial support of Ministerio de Educación y Ciencia (Projects AGL2007-64567 and CTQ2008-05719/BQU) and Conselleria d'Educació de la Generalitat Valenciana (Project PROMETEO 2010-055).

Multivariate statisticsPrincipal Component AnalysisChromatographySpectrophotometry InfraredInfraredChemistryAnalytical chemistrySubtractionPhase (waves)CarbohydratesSignalAnalytical ChemistryNitrophenolsNitrophenolchemistry.chemical_compoundPrincipal component analysisLeast-Squares AnalysisAbsorption (electromagnetic radiation)AlgorithmsChromatography High Pressure LiquidSoftware
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Algorithms for the inference of causality in dynamic processes: Application to cardiovascular and cerebrovascular variability

2015

This study faces the problem of causal inference in multivariate dynamic processes, with specific regard to the detection of instantaneous and time-lagged directed interactions. We point out the limitations of the traditional Granger causality analysis, showing that it leads to false detection of causality when instantaneous and time-lagged effects coexist in the process structure. Then, we propose an improved algorithm for causal inference that combines the Granger framework with the approach proposed by Pearl for the study of causality among multiple random variables. This new approach is compared with the traditional one in theoretical and simulated examples of interacting processes, sho…

Multivariate statisticsProcess (engineering)Computer scienceBiomedical EngineeringInferenceHealth InformaticsMachine learningcomputer.software_genreHeart RateEconometricsHumansArterial PressureComputer Simulation1707Granger causality analysisSeries (mathematics)business.industryBrainHeartCausalityCausalityCerebrovascular CirculationCausal inferenceSignal ProcessingSettore ING-INF/06 - Bioingegneria Elettronica E InformaticaArtificial intelligencebusinesscomputerRandom variableAlgorithms2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
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T-patterns in the study of movement and behavioral disorders

2020

Aim of the present review is to offer an outline of the application of T-pattern analysis (TPA) in the study of neurological disorders characterized by anomalies of movement and, more in general, of behavior. TPA is a multivariate technique to detect real time patterns of behavior on the basis of statistically significant constraints among the events in sequence. TPA is particularly suitable to analyse the structure of behavior. The application of TPA to study movement and behavioral disorders is able to offer, with a high level of detail, hidden characteristics of behavior otherwise impossible to detect. For its intrinsic features, TPA is completely different not only from quantitative eva…

Multivariate statisticsQuantitative EvaluationsExperimental and Cognitive PsychologyNeuropsychological TestsSettore BIO/09 - Fisiologia03 medical and health sciencesBehavioral NeuroscienceBehavior disorderTime pattern0302 clinical medicineAnimalsHumans0501 psychology and cognitive sciences050102 behavioral science & comparative psychologyMultivariate techniqueMovement disorderMovement Disordersintegumentary systemMovement (music)Mental Disorders05 social sciencesT-pattern analysiMultivariate AnalysisBehavioral disorderTPATransition matricesPsychologyAlgorithms030217 neurology & neurosurgeryCognitive psychology
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Prediction of chromatographic properties of organophosphorus insecticides by molecular connectivity

2000

A study is reported of the relationship between theR F values for a group of organophosphorus insecticides obtained by thin layer chromatography and a series of topological descriptors. By using multivariate regression, the corresponding connectivity functions were obtained, which had been selected on the basis of their respective statistical parameters: multiple correlation coefficient (r), standard error of estimate (s), F-Snedecor values and statistical significance (Student’s t). Regression analysis of the connectivity functions can predict the elution behaviour of any structurally similar derivative of this group of compounds with different stationary and mobile phases. Stability studi…

Multivariate statisticsQuantitative structure–activity relationshipChromatographyElutionChemistryOrganic ChemistryClinical BiochemistryStatistical parameterRegression analysisDerivativeBiochemistryStability (probability)Analytical ChemistryMultiple correlation
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Multivariate approach to reveal relationships between sensory perception of cheeses and aroma profile obtained with different extraction methods

2014

A new and original statistical approach was used to compare the effectiveness of 4 different methods to analyse aroma compounds of seven different commercial semi-hard cheeses with regard to their orthonasal sensory perception. Four extraction methods were evaluated: Purge and Trap, Artificial Mouth, Solid-Phase Microextraction (SPME) and Solvent-Assisted Flavour Evaporation (SAFE). Among the headspace methods, Artificial Mouth gave the closest representation of the studied product space to the sensory perception one. The SAFE method was complementary to the dynamic headspace methods, as it was very efficient in extracting the heavy molecules but less efficient for extracting the most volat…

Multivariate statisticsRV coefficientmedia_common.quotation_subjectArtificial mouth[ SDV.AEN ] Life Sciences [q-bio]/Food and NutritionFlavourkey odorantPurge and trapCheesePerception[SDV.IDA]Life Sciences [q-bio]/Food engineeringparmigiano reggiano cheeseAromaAromamedia_commonmass spectrometryChromatographybiologyflavor compoundChemistry[ SDV.IDA ] Life Sciences [q-bio]/Food engineeringphase microextraction spmebiology.organism_classificationSensory sorting taskvolatile componentMultivariate analysisExtraction methodsgas-chromatography-olfactometryExtraction methodsdynamic headspace[SDV.AEN]Life Sciences [q-bio]/Food and NutritionFood Sciencepurge-and-trap
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Locally optimal invariant detector for testing equality of two power spectral densities

2018

This work addresses the problem of determining whether two multivariate random time series have the same power spectral density (PSD), which has applications, for instance, in physical-layer security and cognitive radio. Remarkably, existing detectors for this problem do not usually provide any kind of optimality. Thus, we study here the existence under the Gaussian assumption of optimal invariant detectors for this problem, proving that the uniformly most powerful invariant test (UMPIT) does not exist. Thus, focusing on close hypotheses, we show that the locally most powerful invariant test (LMPIT) only exists for univariate time series. In the multivariate case, we prove that the LMPIT do…

Multivariate statisticsSeries (mathematics)Computer scienceGaussianDetectorUnivariateSpectral density020206 networking & telecommunications02 engineering and technologyUniformly most powerful invariant test (UMPIT)01 natural sciencesMatrix decomposition010104 statistics & probabilitysymbols.namesakePower spectral density (PSD)0202 electrical engineering electronic engineering information engineeringsymbols0101 mathematicsInvariant (mathematics)Time seriesHypothesis testGeneralized likelihood ratio test (GLRT)AlgorithmLocally most powerful invariant test (LMPIT)Statistical hypothesis testing
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Statistical Techniques for Validation of Simulation and Analytic Stochastic Models

2014

In this paper, we consider the problem of statistical validation of multivariate stationary response simulation and analytic stochastic models of observed systems (say, transportation or service systems), which have p response variables. The problem is reduced to testing the equality of the mean vectors for two multivariate normal populations. Without assuming equality of the covariance matrices, it is referred to as the Behrens–Fisher problem. The main purpose of this paper is to bring to the attention of applied researchers the satisfactory tests that can be used for testing the equality of two normal mean vectors when the population covariance matrices are unknown and arbitrary. To illus…

Multivariate statisticsService (systems architecture)education.field_of_studyStochastic modellingStatistical validationPopulationApplied mathematicsMultivariate normal distributionCovarianceeducationStatistical hypothesis testingMathematics
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