Search results for " uncertainty"

showing 10 items of 777 documents

On the empirical spectral distribution for certain models related to sample covariance matrices with different correlations

2021

Given [Formula: see text], we study two classes of large random matrices of the form [Formula: see text] where for every [Formula: see text], [Formula: see text] are iid copies of a random variable [Formula: see text], [Formula: see text], [Formula: see text] are two (not necessarily independent) sets of independent random vectors having different covariance matrices and generating well concentrated bilinear forms. We consider two main asymptotic regimes as [Formula: see text]: a standard one, where [Formula: see text], and a slightly modified one, where [Formula: see text] and [Formula: see text] while [Formula: see text] for some [Formula: see text]. Assuming that vectors [Formula: see t…

Statistics and ProbabilityPhysicsAlgebra and Number TheorySpectral power distributionComputer Science::Information RetrievalProbability (math.PR)Astrophysics::Instrumentation and Methods for AstrophysicsBlock (permutation group theory)Marchenko–Pastur lawComputer Science::Computation and Language (Computational Linguistics and Natural Language and Speech Processing)Bilinear form60F05 60B20 47N30Sample mean and sample covarianceCombinatoricsConvergence of random variablesFOS: Mathematicssample covariance matricesComputer Science::General LiteratureDiscrete Mathematics and CombinatoricsRandom matriceshigh dimensional statisticsStatistics Probability and UncertaintyRandom matrixRandom variableMathematics - ProbabilityRandom Matrices: Theory and Applications
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Disentangling Derivatives, Uncertainty and Error in Gaussian Process Models

2020

Gaussian Processes (GPs) are a class of kernel methods that have shown to be very useful in geoscience applications. They are widely used because they are simple, flexible and provide very accurate estimates for nonlinear problems, especially in parameter retrieval. An addition to a predictive mean function, GPs come equipped with a useful property: the predictive variance function which provides confidence intervals for the predictions. The GP formulation usually assumes that there is no input noise in the training and testing points, only in the observations. However, this is often not the case in Earth observation problems where an accurate assessment of the instrument error is usually a…

FOS: Computer and information sciencesComputer Science - Machine Learning010504 meteorology & atmospheric sciencesComputer science0211 other engineering and technologiesMachine Learning (stat.ML)02 engineering and technology01 natural sciencesMachine Learning (cs.LG)symbols.namesakeStatistics - Machine LearningGaussian process021101 geological & geomatics engineering0105 earth and related environmental sciencesVariance functionPropagation of uncertaintyVariance (accounting)Function (mathematics)Confidence intervalNonlinear systemNoiseKernel method13. Climate actionKernel (statistics)symbolsAlgorithmIGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium
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Uncertainty management in the measurements of low frequency magnetic fields

2014

The paper deals with low-frequency magnetic field measurements carried out by using a broadband and isotropic instrument. These measurements are characterized by very high uncertainty values, which imply a high risk of wrong decisions when there is the need to establish if a site complies or does not comply with specified emission limits. To reduce this risk, we decided to perform the so called “uncertainty management” that is the discipline of optimizing the cost of a measurement versus the uncertainty target. The task is achieved by using the PUMA method that is an iterative technique originally conceived for geometrical and mechanical measurements. The approach is completely based on the…

magnetic field measurement measurement uncertainty uncertainty managementSettore ING-IND/31 - ElettrotecnicaSettore ING-INF/07 - Misure Elettriche E Elettroniche
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Integrated modelling of the influence of urbanization and climate change on river water quality

2010

Climate change is one of the most important drivers modifying the hydrologic and environmental characteristics of natural catchments. When dealing with the quality of natural waters, these factors should be weighed up against anthropogenic factors that may increase or decrease the effect of climatic modifications. However, a detailed and more generalised analysis of such environmental impacts at a relatively small scale is currently lack. This paper aims to fill this gap. The use of a holistic approach is also required by the EU Water Framework Directive, which prescribes integrated analysis for river basin management in order to meet environmental and ecological objectives. In order to qua…

Integrated system modelling[SDE.IE]Environmental Sciences/Environmental EngineeringSettore ICAR/02 - Costruzioni Idrauliche E Marittime E IdrologiaNetworksRéseauxreceiving water body uncertainty analysiwater quality
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Multi-omics HeCaToS dataset of repeated dose toxicity for cardiotoxic & hepatotoxic compounds.

2022

The data currently described was generated within the EU/FP7 HeCaToS project (Hepatic and Cardiac Toxicity Systems modeling). The project aimed to develop an in silico prediction system to contribute to drug safety assessment for humans. For this purpose, multi-omics data of repeated dose toxicity were obtained for 10 hepatotoxic and 10 cardiotoxic compounds. Most data were gained from in vitro experiments in which 3D microtissues (either hepatic or cardiac) were exposed to a therapeutic (physiologically relevant concentrations calculated through PBPK-modeling) or a toxic dosing profile (IC20 after 7 days). Exposures lasted for 14 days and samples were obtained at 7 time points (therapeutic…

Statistics and ProbabilityEpigenomicsProteomicsBioquímicaBiologiaDrug-Related Side Effects and Adverse ReactionsLibrary and Information SciencesCardiotoxicityComputer Science ApplicationsEducationHumansMetabolomicsStatistics Probability and UncertaintyTranscriptomeInformation Systems
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Probabilistic Flood Hazard Mapping Using Bivariate Analysis Based on Copulas

2017

This study presents a methodology to extract probabilistic flood hazard maps in an area subject to flood risk, taking into account uncertainties in the definition of design hydrographs. Particularly, the authors present a new method to produce probabilistic inundation and flood hazard maps in which the hydrological input (i.e., synthetic flood design event) to a 2D hydraulic model has been obtained by using a bivariate statistical analysis (copulas) to generate flood peak discharges and volumes. This study also aims to quantify the contribution of boundary conditions’ uncertainty in order to evaluate the effect of this uncertainty source on probabilistic flood hazard mapping. Different comb…

Multivariate statisticsFlood myth0208 environmental biotechnologyCopula (linguistics)Settore ICAR/02 - Costruzioni Idrauliche E Marittime E IdrologiaProbabilistic logicHydrograph02 engineering and technologyBuilding and ConstructionBivariate analysisFlood Risk Mapping020801 environmental engineeringRisk managementFlood hazard mapping100-year floodStatisticsEconometricsEnvironmental scienceFlood risk and hazard mapping; Uncertainty analysis; Copula; Sicily.Uncertainty analysisSafety Risk Reliability and QualityUncertainty analysisCivil and Structural Engineering
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Prevalence of unwillingness and uncertainty to vaccinate against COVID-19 in older people: A systematic review and meta-analysis.

2021

The coronavirus disease 2019 (COVID-19) has been shown to have more severe health outcomes in older people specifically in relation to mortality and disability. Vaccination seems to be efficacious and safe for preventing the negative consequences of COVID-19, but vaccine hesitancy seems to be high in older adults. We therefore aimed to investigate the prevalence of unwillingness and the uncertainty to vaccinate against COVID-19 in older people and the factors that can be associated with the unwillingness to vaccinate. For this work, we searched several databases until 18th June 2021 for studies reporting the prevalence of unwillingness and the uncertainty to vaccinate against COVID-19 in pe…

Low incomeAgingCOVID-19 VaccinesCoronavirus disease 2019 (COVID-19)ReviewHealth outcomesBiochemistryolder adultvaccinePrevalenceMedicineHumansMolecular Biologyolder adultsAgedbusiness.industrySARS-CoV-2VaccinationUncertaintyCOVID-19Odds ratioConfidence intervalVaccinationCross-Sectional StudiesNeurologyMeta-analysisCOVID-19; hesitancy; older adults; vaccine; Aged; Cross-Sectional Studies; Humans; Prevalence; SARS-CoV-2; Uncertainty; Vaccination; COVID-19; COVID-19 VaccineshesitancyOlder peoplebusinessBiotechnologyDemographyAgeing research reviews
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Robust Discrete-Time Lateral Control of Racecars by Unknown Input Observers

2023

This brief addresses the robust lateral control problem for self-driving racecars. It proposes a discrete-time estimation and control solution consisting of a delayed unknown input-state observer (UIO) and a robust tracking controller. Based on a nominal vehicle model, describing its motion with respect to a generic desired trajectory and requiring no information about the surrounding environment, the observer reconstructs the total force disturbance signal, resulting from imperfect knowledge of the time-varying tire-road interface characteristics, presence of other vehicles nearby, wind gusts, and other model uncertainty. Then, the controller actively compensates the estimated force and as…

Settore ING-INF/04 - AutomaticaControl and Systems EngineeringAutonomous vehicles Estimation extended state observer (ESO) Force input-state estimation Mathematical models Observers racecars robust vehicle control self-driving Trajectory Uncertainty Vehicle dynamicsElectrical and Electronic EngineeringIEEE Transactions on Control Systems Technology
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Global data on earthworm abundance, biomass, diversity and corresponding environmental properties

2021

Earthworms are an important soil taxon as ecosystem engineers, providing a variety of crucial ecosystem functions and services. Little is known about their diversity and distribution at large spatial scales, despite the availability of considerable amounts of local-scale data. Earthworm diversity data, obtained from the primary literature or provided directly by authors, were collated with information on site locations, including coordinates, habitat cover, and soil properties. Datasets were required, at a minimum, to include abundance or biomass of earthworms at a site. Where possible, site-level species lists were included, as well as the abundance and biomass of individual species and ec…

Data DescriptorDistribuição GeográficaPlan_S-Compliant-OASoilBiomassbiodiversityDiversityEcologyBiodiversidadeQBiodiversityeliöyhteisötmaaperäeliöstöPE&RCComputer Science ApplicationsMultidisciplinary SciencesBiogeographyinternational1181 Ecology evolutionary biologyEcosystem engineersScience & Technology - Other TopicsStatistics Probability and UncertaintyInformation SystemsStatistics and ProbabilitylierotScienceInvertebradosLibrary and Information Sciences[SDV.SA.SDS]Life Sciences [q-bio]/Agricultural sciences/Soil studyEcology and EnvironmentEducationeliömaantiede[SDV.EE.ECO]Life Sciences [q-bio]/Ecology environment/EcosystemsMinhocaServiço ambientalBIODIVERSITY CHANGELife ScienceEcosystem servicesEarthwormsDatasetsAnimalsSpatial distributionCommunity ecologyOligochaetaLaboratorium voor NematologieEcosystem1172 Environmental sciencesbiogeographyScience & TechnologyLAND-USEBiology and Life SciencesPLATFORMBodemfysica en LandbeheerEcologíaEcossistemabiodiversiteettiSoil Physics and Land ManagementSoloBiologia do Solomaaperäeläimistö570 Life sciences; biologyeartworm ; abundance ; biomass ; diversityLaboratory of Nematology[SDE.BE]Environmental Sciences/Biodiversity and EcologyCOMMUNITIEScommunity ecology
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Discussion of "modern statistics of spatial point processes"

2007

The paper ‘Modern statistics for spatial point processes' by Jesper Møller and Rasmus P. Waagepetersen is based on a special invited lecture given by the authors at the 21st Nordic Conference on Mathematical Statistics, held at Rebild, Denmark, in June 2006. At the conference, Antti Penttinen and Eva B. Vedel Jensen were invited to discuss the paper. We here present the comments from the two invited discussants and from a number of other scholars, as well as the authors' responses to these comments. Below Figure 1, Figure 2, etc., refer to figures in the paper under discussion, while Figure A, Figure B, etc., refer to figures in the current discussion. All numbered sections and formulas ref…

Statistics and Probability010104 statistics & probabilityPoint (typography)[MATH.MATH-ST]Mathematics [math]/Statistics [math.ST]010102 general mathematicsStatisticsMathematical statistics[STAT.TH]Statistics [stat]/Statistics Theory [stat.TH]0101 mathematicsStatistics Probability and Uncertainty01 natural sciencesPoint processMathematics
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