Search results for "Statistical inference"

showing 10 items of 40 documents

Model‐based approaches to unconstrained ordination

2014

Summary Unconstrained ordination is commonly used in ecology to visualize multivariate data, in particular, to visualize the main trends between different sites in terms of their species composition or relative abundance. Methods of unconstrained ordination currently used, such as non-metric multidimensional scaling, are algorithm-based techniques developed and implemented without directly accommodating the statistical properties of the data at hand. Failure to account for these key data properties can lead to misleading results. A model-based approach to unconstrained ordination can address this issue, and in this study, two types of models for ordination are proposed based on finite mixtu…

0106 biological sciencesComputer science010604 marine biology & hydrobiologyEcological ModelingModel selectionLatent variableMixture modelcomputer.software_genre010603 evolutionary biology01 natural sciencesData typeStatistical inferenceOrdinationMultidimensional scalingData miningLatent variable modelcomputerEcology Evolution Behavior and SystematicsMethods in Ecology and Evolution
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Investigation of the consequences of the modifiable areal unit problem in macroscopic traffic safety analysis: A case study accounting for scale and …

2019

Abstract Traffic safety analysis at the macroscopic level usually relies on previously defined areal traffic analysis zones (TAZs) that are used as the units of investigation. Hence, statistical inference is made on the basis of such units, implying that the consideration of a certain TAZ configuration may influence the results and conclusions achieved. Regarding this, the modifiable areal unit problem (MAUP) is a well-known issue in the field of spatial statistics, which refers to the effects that arise in statistical properties and estimations when there is a change in areal units of analysis. In this paper, the consequences of MAUP have been investigated through a dataset of traffic cras…

050210 logistics & transportationSpatial AnalysisModels StatisticalComputer science05 social sciencesPublic Health Environmental and Occupational HealthAccidents TrafficPoison controlHuman Factors and ErgonomicsStatistical modelModifiable areal unit problemMulticollinearitySpain0502 economics and businessStatisticsCovariateStatistical inferenceHumans0501 psychology and cognitive sciencesCity PlanningSafetySafety Risk Reliability and QualityScale (map)Spatial analysis050107 human factorsAccident; analysis and prevention
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Importance of proper conduct of clinical trials

2021

AFRICAclinical trialsModels StatisticalActuarial sciencebusiness.industryMEDICINEinferential statisticsEvidence-based medicinerandomised controlled trialsBayesian statisticsBayesian statisticBayesian statisticsClinical trialAnesthesiology and Pain MedicineResearch DesignData Interpretation StatisticalCausal inferenceStatistical inferenceHumansMedicinecausal inferencebusinessevidence-based medicineRandomized Controlled Trials as Topic
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The anisotropy of personal space.

2019

Violations of personal space are associated with discomfort. However, the exact function linking the magnitude of discomfort to interpersonal distance has not yet been specified. In this study, we explore whether interpersonal distance and discomfort are isotropic with respect to uncomfortably far or close distances. We also extend previous findings with regard to intrusions into personal space as well as maintenance of distances outside of personal space. We presented subjects with 15 interpersonal distances ranging from 40 to 250 cm and obtained verbal and joystick-based ratings of discomfort. Whereas discomfort rose immediately when personal space was entered, the gradient was less steep…

AdultMaleResearch ValidityTopographyScienceMaterials ScienceMaterial PropertiesEmotionsSocial SciencesResearch and Analysis MethodsStatistical InferencePersonal SpaceYoung AdultMathematical and Statistical TechniquesTask Performance and AnalysisPsychologyHumansStatistical MethodsStatistical DataAnalysis of VarianceLandformsBehaviorPhysicsStatisticsQRBiology and Life SciencesReproducibility of ResultsGeomorphologyFearResearch AssessmentMiddle AgedCondensed Matter Physics150 PsychologiePhysical SciencesEarth SciencesAnisotropyMedicineFemale150 PsychologyMathematicsResearch ArticleValleysPLoS ONE
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Unreliable predictions about COVID‐19 infections and hospitalizations make people worry: The case of Italy

2021

Computer modeling &ltmedicine.medical_specialty2019-20 coronavirus outbreakCoronavirus disease 2019 (COVID-19)BioinformaticsSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)media_common.quotation_subjectcomputer modeling < biostatistics & bioinformatics; epidemiology; statistical inference < biostatistics & bioinformaticsMEDLINEVirologycomputer modeling < biostatistics & bioinformaticsEpidemiologyHumansMedicineLetters to the EditorIntensive care medicineLetter to the Editormedia_commonSARS-CoV-2business.industryCommunicationBiostatistics &ampCOVID-19Computer modeling &lt; Biostatistics &amp; Bioinformaticsstatistical inference < biostatistics & bioinformaticsVirologyInfectious DiseasesItalyStatistical inference &lt; Biostatistics &amp; BioinformaticsepidemiologyWorrySettore SECS-S/01businessForecastingJournal of Medical Virology
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Efficient linear fusion of partial estimators

2018

Abstract Many signal processing applications require performing statistical inference on large datasets, where computational and/or memory restrictions become an issue. In this big data setting, computing an exact global centralized estimator is often either unfeasible or impractical. Hence, several authors have considered distributed inference approaches, where the data are divided among multiple workers (cores, machines or a combination of both). The computations are then performed in parallel and the resulting partial estimators are finally combined to approximate the intractable global estimator. In this paper, we focus on the scenario where no communication exists among the workers, de…

Computer scienceBayesian probabilityInferenceAsymptotic distribution02 engineering and technology01 natural sciences010104 statistics & probability[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingArtificial Intelligence0202 electrical engineering electronic engineering information engineeringStatistical inferenceFusion rules0101 mathematicsElectrical and Electronic EngineeringComputingMilieux_MISCELLANEOUSMinimum mean square errorApplied MathematicsConstrained optimizationEstimator020206 networking & telecommunicationsComputational Theory and MathematicsSignal ProcessingComputer Vision and Pattern RecognitionStatistics Probability and Uncertainty[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingAlgorithmDigital Signal Processing
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Testing for goodness rather than lack of fit of continuous probability distributions.

2021

The vast majority of testing procedures presented in the literature as goodness-of-fit tests fail to accomplish what the term is promising. Actually, a significant result of such a test indicates that the true distribution underlying the data differs substantially from the assumed model, whereas the true objective is usually to establish that the model fits the data sufficiently well. Meeting that objective requires to carry out a testing procedure for a problem in which the statement that the deviations between model and true distribution are small, plays the role of the alternative hypothesis. Testing procedures of this kind, for which the term tests for equivalence has been coined in sta…

Computer scienceStatement (logic)Alternative hypothesisScienceTest StatisticsResearch and Analysis MethodsStatistical InferenceMathematical and Statistical TechniquesStatistical inferenceEconometricsHumansLack-of-fit sum of squaresStatistical MethodsEquivalence (measure theory)Statistical hypothesis testingStatistical DataProbabilityMultidisciplinaryModels StatisticalApplied MathematicsSimulation and ModelingStatisticsQRProbability TheoryProbability DistributionTerm (time)Monte Carlo methodStatistical TheoriesPhysical SciencesProbability distributionMedicineMathematicsAlgorithmsResearch ArticleStatistical DistributionsPLoS ONE
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Finite Sample Sizes of the GRS Test in the Presence of Dynamic Correlation and Conditional Heteroskedasticity

2017

This paper investigates the finite sample properties of the widely-used Gibbons, Ross, Shanken (1989) (GRS) test in the presence of both conditional correlation and conditional heteroskedasticity. It finds that the GRS test exhibits serious size distortions resulting in potentially misleading statistical inferences. The correct critical values, as reported in the study, are considerably larger than suggested by the GRS test.

CorrelationHeteroscedasticitySample size determinationStatisticsStatistical inferenceEconometricsSample (statistics)Wald testMathematicsTest (assessment)SSRN Electronic Journal
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Inference for Lorenz curve orderings

1999

In this paper we consider the issue of performing statistical inference for Lorenz curve orderings. This involves testing for an ordered relationship in a multivariate context and making comparisons among more than two population distributions. Our approach is to frame the hypotheses of interest as sets of linear inequality constraints on the vector of Lorenz curve ordinates, and apply order-restricted statistical inference to derive test statistics and their sampling distributions. We go on to relate our results to others which have appeared in recent literature, and use Monte Carlo analysis to highlight their respective properties and comparative performances. Finally, we discuss in gener…

Economics and EconometricsLinear inequalitySampling distributionFrequentist inferenceEconometricsFiducial inferenceStatistical inferenceInferenceLorenz curveMathematical economicsStatistical hypothesis testingMathematicsThe Econometrics Journal
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Basic Statistical Techniques

2012

Exploratory data analysisData collectionComputer scienceInterval estimationStatisticsData analysisStatistical inferenceSampling (statistics)Statistical and Managerial Techniques for Six Sigma Methodology
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