Search results for "statistical [methods]"

showing 10 items of 1664 documents

Assessment of susceptibility to earth-flow landslide using logistic regression and multivariate adaptive regression splines: A case of the Belice Riv…

2015

Abstract In this paper, terrain susceptibility to earth-flow occurrence was evaluated by using geographic information systems (GIS) and two statistical methods: Logistic regression (LR) and multivariate adaptive regression splines (MARS). LR has been already demonstrated to provide reliable predictions of earth-flow occurrence, whereas MARS, as far as we know, has never been used to generate earth-flow susceptibility models. The experiment was carried out in a basin of western Sicily (Italy), which extends for 51 km 2 and is severely affected by earth-flows. In total, we mapped 1376 earth-flows, covering an area of 4.59 km 2 . To explore the effect of pre-failure topography on earth-flow sp…

Multivariate adaptive regression splinesGeographic information systembusiness.industryGeographic Information Systems (GIS)Logistic regressionStatistical modelLandslideTerrainEarth-flowOverfittingLogistic regressionLandslide susceptibilityMultivariate adaptive regression splineDigital elevation modelbusinessCartographyReceiver operating characteristic curveGeologyEarth-Surface Processes
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Temporal variability analysis reveals biases in electronic health records due to hospital process reengineering interventions over seven years

2019

[EN] Objective To evaluate the effects of Process-Reengineering interventions on the Electronic Health Records (EHR) of a hospital over 7 years. Materials and methods Temporal Variability Assessment (TVA) based on probabilistic data quality assessment was applied to the historic monthly-batched admission data of Hospital La Fe Valencia, Spain from 2010 to 2016. Routine healthcare data with a complete EHR was expanded by processed variables such as the Charlson Comorbidity Index. Results Four Process-Reengineering interventions were detected by quantifiable effects on the EHR: (1) the hospital relocation in 2011 involved progressive reduction of admissions during the next four months, (2) th…

Multivariate analysisData managementPsychological interventionElectronic Medical Records02 engineering and technologyGeographical locationsDatabase and Informatics Methods0302 clinical medicineMathematical and Statistical TechniquesHealth care0202 electrical engineering electronic engineering information engineeringCIENCIAS DE LA COMPUTACION E INTELIGENCIA ARTIFICIALMedicine and Health Sciences03.- Garantizar una vida saludable y promover el bienestar para todos y todas en todas las edadesElectronic Health Records030212 general & internal medicineData ManagementMultidisciplinaryQStatisticsRHospitalsPatient Discharge3. Good healthEuropePhysical SciencesMedicineEngineering and TechnologyMedical emergencyRelocationMATEMATICA APLICADAManagement EngineeringResearch ArticlePatient TransferComputer and Information SciencesScienceMEDLINESurgical and Invasive Medical ProceduresHealth InformaticsResearch and Analysis Methods03 medical and health sciencesBias020204 information systemsmedicineHumansEuropean UnionStatistical MethodsQuality of Health CareProtocol (science)Business Process Reengineeringbusiness.industrymedicine.diseaseHealth CareHealth Care FacilitiesSpainData qualityFISICA APLICADAMultivariate AnalysisPeople and placesbusinessMathematicsPLoS ONE
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MuTE: a MATLAB toolbox to compare established and novel estimators of the multivariate transfer entropy.

2014

A challenge for physiologists and neuroscientists is to map information transfer between components of the systems that they study at different scales, in order to derive important knowledge on structure and function from the analysis of the recorded dynamics. The components of physiological networks often interact in a nonlinear way and through mechanisms which are in general not completely known. It is then safer that the method of choice for analyzing these interactions does not rely on any model or assumption on the nature of the data and their interactions. Transfer entropy has emerged as a powerful tool to quantify directed dynamical interactions. In this paper we compare different ap…

Multivariate statisticsInformation transferTheoretical computer scienceComputer scienceEntropyInformation TheorySocial SciencesCAUSALITYMedicine (all); Biochemistry Genetics and Molecular Biology (all); Agricultural and Biological Sciences (all)BioinformaticsMedicine and Health SciencesEntropy (energy dispersal)MultidisciplinaryEntropy (statistical thermodynamics)Medicine (all)QSoftware DevelopmentREstimatorSoftware EngineeringElectroencephalographyCausalityNeurologyCardiovascular DiseasesProbability distributionMedicineAlgorithmsResearch ArticleComputer ModelingComputer and Information SciencesScienceCardiologyProbability density functionEntropy (classical thermodynamics)Artificial IntelligenceLinear regressionEntropy (information theory)HumansComputer SimulationEntropy (arrow of time)Conditional entropyBiochemistry Genetics and Molecular Biology (all)EpilepsyBiology and Life SciencesModels TheoreticalMODELNonlinear systemAgricultural and Biological Sciences (all)ROC CurveINFORMATION-TRANSFERSettore ING-INF/06 - Bioingegneria Elettronica E InformaticaCognitive ScienceTransfer entropySoftwareEntropy (order and disorder)NeurosciencePLoS ONE
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So Many Variables: Joint Modeling in Community Ecology

2015

Technological advances have enabled a new class of multivariate models for ecology, with the potential now to specify a statistical model for abundances jointly across many taxa, to simultaneously explore interactions across taxa and the response of abundance to environmental variables. Joint models can be used for several purposes of interest to ecologists, including estimating patterns of residual correlation across taxa, ordination, multivariate inference about environmental effects and environment-by-trait interactions, accounting for missing predictors, and improving predictions in situations where one can leverage knowledge of some species to predict others. We demonstrate this by exa…

Multivariate statisticsModels StatisticalCommunityEcologyLinear modelInferenceStatistical model15. Life on landBiologyBiotaLinear ModelsResidual correlationEconometricsLeverage (statistics)OrdinationEcosystemEcology Evolution Behavior and SystematicsTrends in Ecology & Evolution
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Different Representation Procedures Originated from Multivariate Temporal Pattern Analysis of the Behavioral Response to Pain in Wistar Rats Tested i…

2019

Temporal pattern analysis is an advanced multivariate technique able to investigate the structure of behavior by unveiling the existence of statistically significant constraints among the interval length separating events in sequence. If on the one hand, such an approach allows investigating the behavioral response to pain in its most intimate and inner features, on the other hand, due to the meaning of the studies on pain, it is of relevant importance that the results utilize intuitive and easily comprehensible ways of representation. The aim of this paper is to show various procedures useful to represent the results originating from the multivariate T-pattern analysis of the behavioral re…

Multivariate statisticsMultivariate analysisPain -- Animal modelsPattern analysisNeurophysiologyT-pattern analysisSettore BIO/09 - FisiologiaArticlemultivariate analyseslcsh:RC321-571medicinepainHot platelcsh:Neurosciences. Biological psychiatry. NeuropsychiatryAnimal behavior -- Statistical methodsmultivariate analyseMorphineGeneral NeuroscienceRepresentation (systemics)T-pattern analysimorphinehot-plateBehavioral responseMultivariate analysisMorphineT-patternPsychologyNeurosciencemedicine.drug
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On Mardia’s Tests of Multinormality

2004

Classical multivariate analysis is based on the assumption that the data come from a multivariate normal distribution. The tests of multinormality have therefore received very much attention. Several tests for assessing multinormality, among them Mardia’s popular multivariate skewness and kurtosis statistics, are based on standardized third and fourth moments. In Mardia’s construction of the affine invariant test statistics, the data vectors are first standardized using the sample mean vector and the sample covariance matrix. In this paper we investigate whether, in the test construction, it is advantageous to replace the regular sample mean vector and sample covariance matrix by their affi…

Multivariate statisticsMultivariate analysisScatter matrixStatisticsKurtosisMultivariate normal distributionAffine transformationBivariate analysisMathematicsStatistical hypothesis testing
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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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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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Comparison of differences in resolution and sources of controlling factors for gully erosion susceptibility mapping

2018

Abstract Gully erosion has been identified as an important soil degradation process and sediment source, especially in arid and semiarid areas. Thus, it is useful to identify the spatial occurrence of this form of water erosion in the landscape and the most vulnerable areas. In this study, we explored the effects of different pixel sizes on some controlling factors extracted from a digital elevation model and remote sensing data when producing a gully erosion susceptibility map (GESM) of Ekbatan Dam Basin, Hamadan, Iran. An inventory map of the gully landforms was prepared based on global positioning system routes of the gullies, extensive field surveys, and visual interpretations of satell…

Multivariate statisticsTopographic Wetness IndexRemote sensing data010504 meteorology & atmospheric sciencesPixelTopographic attributeSettore GEO/04 - Geografia Fisica E Geomorfologia0208 environmental biotechnologySoil Science02 engineering and technology01 natural sciencesNormalized Difference Vegetation Index020801 environmental engineeringData setGully erosionMachine learning modelSoil retrogression and degradationRobustneEnvironmental scienceDigital elevation model0105 earth and related environmental sciencesRemote sensingStatistical hypothesis testingGeoderma
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