Search results for "multivariate statistic"

showing 10 items of 327 documents

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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Multivariate geophysical survey to detect a shallow fault zone in a landfill project area

2018

An integrated analysis of 2D high-resolution shallow seismic refraction tomographies (SRT) and electrical resistivity tomographies (ERT) has been carried out along a slope where the presence of a fault zone was assumed. It was also applied a post-inversion k-means cluster analysis of the P-wave velocity, the density of the seismic rays and the electrical resistivity of the interpretation models. Distribution maps of the cluster in multi-space were built, allowing to better definethe lateral geometry of a NE-SW directed band composed of intensely tectonized carbonate breccias. Finally, the fracturing and kinematic analysis on fault planes observed along the trenches, highlighted systems of l…

Multivariate statisticsSettore GEO/02 - Geologia Stratigrafica E SedimentologicaSettore GEO/11 - Geofisica ApplicataGeophysical surveyProject areaSeimic refraction tomography Electrical resistivity tomography Cluster Analysis Fault BellolampoGeologySeismology
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Determination of vinegar acidity by attenuated total reflectance infrared measurements through the use of second-order absorbance-pH matrices and par…

2007

Univariate (zero-order), multivariate (first-order) and multiway (second-order) calibrations were assayed for the determination of vinegar acidity using a mechanized procedure based upon vibrational spectroscopy and the emerging multicommutation methodology. The second-order methodology relies on the use of a flow system based on multicommutation and binary sampling. The flow network comprises a set of three-way solenoid valves, computer-controlled to provide facilities to handle the sample and to generate a time-dependent pH gradient using two carrier solutions. The procedure is based on the volumetric fraction variation approach that maintains the same volume of sample solution and dynami…

Multivariate statisticsSpectrophotometry InfraredChemistryAnalytical chemistrySampling (statistics)Hydrogen-Ion ConcentrationAnalytical ChemistryChemometricsAbsorbanceAttenuated total reflectionPartial least squares regressionCalibrationTitrationFactor Analysis StatisticalAcetic AcidTalanta
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Non-uniform multivariate embedding to assess the information transfer in cardiovascular and cardiorespiratory variability series

2012

The complexity of the short-term cardiovascular control prompts for the introduction of multivariate (MV) nonlinear time series analysis methods to assess directional interactions reflecting the underlying regulatory mechanisms. This study introduces a new approach for the detection of nonlinear Granger causality in MV time series, based on embedding the series by a sequential, non-uniform procedure, and on estimating the information flow from one series to another by means of the corrected conditional entropy. The approach is validated on short realizations of linear stochastic and nonlinear deterministic processes, and then evaluated on heart period, systolic arterial pressure and respira…

Multivariate statisticsSupine positionMultivariate analysisQuantitative Biology::Tissues and OrgansTime delay embeddingPhysics::Medical PhysicsPostureBlood PressureHealth InformaticsCardiovascular Physiological PhenomenaGranger causalityPosition (vector)StatisticsHumansCardiovascular interactionMathematicsConditional entropySeries (mathematics)RespirationModels CardiovascularReproducibility of ResultsSignal Processing Computer-AssistedComputer Science Applications1707 Computer Vision and Pattern RecognitionComputer Science ApplicationsNonlinear systemNonlinear DynamicsMultivariate AnalysisSettore ING-INF/06 - Bioingegneria Elettronica E InformaticaGranger causalityMultivariate time serieConditional entropyAlgorithmAlgorithms
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Multivariate and Multiscale Complexity of Long-Range Correlated Cardiovascular and Respiratory Variability Series

2020

Assessing the dynamical complexity of biological time series represents an important topic with potential applications ranging from the characterization of physiological states and pathological conditions to the calculation of diagnostic parameters. In particular, cardiovascular time series exhibit a variability produced by different physiological control mechanisms coupled with each other, which take into account several variables and operate across multiple time scales that result in the coexistence of short term dynamics and long-range correlations. The most widely employed technique to evaluate the dynamical complexity of a time series at different time scales, the so-called multiscale …

Multivariate statisticsSystolic arterial pressure (SAP)Vector autoregressive fractionally integrated (VARFI) modelsComputer scienceGeneral Physics and Astronomylcsh:Astrophysics01 natural sciencesArticle010305 fluids & plasmaslcsh:QB460-4660103 physical sciencesRange (statistics)Multi-scale entropy (MSE)lcsh:Science010306 general physicsRepresentation (mathematics)Parametric statisticsvector autoregressive fractionally integrated (VARFI) modelSeries (mathematics)multi-scale entropy (MSE)Stochastic processsystolic arterial pressure (SAP)lcsh:QC1-999Term (time)Autoregressive modelSettore ING-INF/06 - Bioingegneria Elettronica E Informaticavector autoregressive fractionally integrated (VARFI) modelslcsh:QBiological systemHeart rate variability (HRV)lcsh:Physicsheart rate variability (HRV)
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Incorporating classified dispersal assumptions in predictive distribution models – A case study with grasshoppers and bush-crickets

2011

Abstract Current and future species distributions depend on environmental conditions, but the ability of species to shift their range boundaries or to expand their distribution ranges in response to global change also depends on their dispersal capacity. Dispersal capacity, however, has often been neglected in previous studies that either assumed no-dispersal or full dispersal, both of which are unrealistic for most taxa. The aims of this study are (i) to identify the predictors of the present spatial distribution on a regional scale for 13 grasshoppers and bush-crickets, and (ii) to derive predictions of their future distributions under climate change by applying different dispersal capaci…

Multivariate statisticsTaxonEcologyRange (biology)Ecological ModelingSpecies distributionBiological dispersalClimate changeGlobal changeBiologySpatial distributionEcological Modelling
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