Search results for "Statistical"

showing 10 items of 4960 documents

Spatial analysis of traffic accidents near and between road intersections in a directed linear network.

2019

Although most of the literature on traffic safety analysis has been developed over areal zones, there is a growing interest in using the specific road structure of the region under investigation, which is known as a linear network in the field of spatial statistics. The use of linear networks entails several technical complications, ranging from the accurate location of traffic accidents to the definition of covariates at a spatial micro-level. Therefore, the primary goal of this study was to display a detailed analysis of a dataset of traffic accidents recorded in Valencia (Spain), which were located into a linear network representing more than 30 km of urban road structure corresponding t…

050210 logistics & transportationModels StatisticalComputer science05 social sciencesKernel density estimationPublic Health Environmental and Occupational HealthNegative binomial distributionAccidents TrafficHuman Factors and ErgonomicsRangingSpatial heterogeneityLinear networkSpatio-Temporal AnalysisOverdispersionSpain0502 economics and businessStatisticsCovariateHumans0501 psychology and cognitive sciencesBuilt EnvironmentSafety Risk Reliability and QualitySpatial analysis050107 human factorsAccident; analysis and prevention
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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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Measurement of the W boson mass

1996

The W boson mass is measured using proton-proton collision data at root s = 13 TeV corresponding to an integrated luminosity of 1.7fb(-1) recorded during 2016 by the LHCb experiment. With a simultaneous fit of the muon q/p(T) distribution of a sample of W ->mu y decays and the phi* distribution of a sample of Z -> mu mu decays the W boson mass is determined to be

13000 GeV-cmsTevatronparton: distribution functionQC770-798W: leptonic decay7. Clean energy01 natural sciencesLuminosityPhysics Particles & FieldsSubatomär fysikHadron-Hadron scattering (experiments)scattering [p p]Electroweak interactionNuclear Experimentparticle identification [muon]Settore FIS/01PhilosophyPhysicsCoupling (probability)CERN LHC CollHadron colliderPhysical SciencesTransverse masscolliding beams [p p]distribution function [parton]Collider Detector at FermilabParticles and fieldCOLLISIONSp p: scatteringCERN PBARP COLLIDERAstrophysics::High Energy Astrophysical PhenomenaW: mass: measuredStandard ModelNuclear physicsddc:530010306 general physics0206 Quantum PhysicsMuonScience & Technology010308 nuclear & particles physicsWeinberg angleHEPFERMILAB TEVATRONElectroweak interaction Hadron-Hadron scattering (experiments) QCD For- ward physicsCDFp p: colliding beamsPhysics::Instrumentation and DetectorsElectron–positron annihilation= 1.8 TEVGeneral Physics and Astronomy= 1.8 TEV; PBARP COLLISIONS; DECAYVector bosonHigh Energy Physics - ExperimentHigh Energy Physics - Experiment (hep-ex)Computer Science::Systems and ControlSubatomic Physics[PHYS.HEXP]Physics [physics]/High Energy Physics - Experiment [hep-ex]PhysicFermilabBosonPhysics0105 Mathematical PhysicsStatistics::ApplicationsSettore FIS/01 - Fisica Sperimentalestatistical [error]Nuclear & Particles PhysicsCENTRAL TRACKING CHAMBERerror: statisticalCENTRAL ELECTROMAGNETIC CALORIMETERTransverse momentum0202 Atomic Molecular Nuclear Particle and Plasma PhysicsLHCmass: measured [W]Particle Physics - ExperimentStatistics::TheoryParticle physicsNuclear and High Energy Physicselectroweak interaction: precision measurementRegular Article - Experimental PhysicsTRANSVERSE ENERGYFOS: Physical sciencesmuon: particle identification530Particle decayPBARP COLLISIONSNuclear and particle physics. Atomic energy. Radioactivityprecision measurement [electroweak interaction]0103 physical sciencesForward physicVECTOR BOSONElectroweak interaction Hadron-Hadron scattering (experiments) QCD Forward physicsCERN PBARP COLLIDER; CENTRAL ELECTROMAGNETIC CALORIMETER; CENTRAL TRACKING CHAMBER; = 1.8 TEV; PARTON DISTRIBUTIONS; FERMILAB TEVATRON; VECTOR BOSON; TRANSVERSE ENERGY; CDF; COLLISIONShep-exHigh Energy Physics::PhenomenologyLHC-BQCDleptonic decay [W]LHCbPARTON DISTRIBUTIONSMass spectrumForward physicsPhysics::Accelerator PhysicsHigh Energy Physics::ExperimentDECAYHumanitiesexperimental results
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Statistical analysis of sensory profiling data. Graphs for presenting results (PCA and ANOVA)

2000

Abstract A principal component analysis is performed to analyse the matrix of median values, with 16 varieties in rows, and all descriptors in columns. Only texture descriptors contribute to the definition of the main axes. Six varieties are identified that score high on mealiness and low on moisture, the 10 other varieties are ordered according to a mashable axis which involves texture descriptors. Next we exclude texture descriptors since the main characteristics are already found, and mealy varieties since they are not suitable for steamed potatoes. A mixed linear model (ANOVA) with random subject effects is then used for each descriptor. Flavour and taste differences are found among the…

2. Zero hunger0303 health sciencesNutrition and Dietetics030309 nutrition & dieteticsFlavour04 agricultural and veterinary sciences[SDV.IDA] Life Sciences [q-bio]/Food engineering040401 food scienceSensory analysis03 medical and health sciences0404 agricultural biotechnology[SDV.IDA]Life Sciences [q-bio]/Food engineeringPrincipal component analysisMixed linear modelStatisticsStatistical analysisAnalysis of varianceComputingMilieux_MISCELLANEOUSFood ScienceMathematicsFood Quality and Preference
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Application of replicated difference testing

2000

International audience; In a recent paper, Brockho€ and Schlich (1998, Handling replications in discrimination tests. Food Quality and Preference, 9(5), 303±312) proposed a statistically sound way of handling replications in di€erence testing. In the present paper, this new test is applied to the data obtained in six experiments on non alcoholic beverages, where triangle tests were intensively replicated (between eight and 60 times) with groups of subjects composed of 12±61 students. The paper aims to estimate in these practical situations the extent to which a group of panelists is heterogeneous towards the ability of detecting a sensory di€erence among two products. As the results indicat…

2. Zero hunger0303 health sciencesNutrition and Dietetics030309 nutrition & dieteticsdifference testNon alcoholic04 agricultural and veterinary sciences[SDV.IDA] Life Sciences [q-bio]/Food engineering040401 food scienceSensory analysis03 medical and health sciences0404 agricultural biotechnology[SDV.IDA]Life Sciences [q-bio]/Food engineeringStatisticsreplicationsEconometricsStatistical analysisPsychologyFood ScienceFood Quality and Preference
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The significance of climate variability on early modern European grain prices

2021

AbstractGrain was the most important food source in early modern Europe (c. 1500–1800), and its price influenced the entire economy. The extent to which climate variability determined grain price variations remains contested, and claims of solar cycle influences on prices are disputed. We thoroughly reassess these questions, within a framework of comprehensive statistical analysis, by employing an unprecedentedly large grain price data set together with state-of-the-art palaeoclimate reconstructions and long meteorological series. A highly significant negative grain price–temperature relationship (i.e. colder = high prices and vice versa) is found across Europe. This association increases a…

2. Zero hungerEconomic HistoryEconomics and EconometricsHistory010504 meteorology & atmospheric sciences060106 history of social sciences06 humanities and the arts01 natural sciencesSolar cycleGeography13. Climate actionEkonomisk historiaClimatology0601 history and archaeologyStatistical analysisPrecipitationTemporal scalesHistory general0105 earth and related environmental sciencesCliometrica
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Building a statistical surveillance dashboard for COVID-19 infection worldwide

2020

When a pandemic like the current novel coronavirus (COVID-19) breaks out, it is important that authorities, healthcare organizations and official decision makers, have in place an effective monitoring system to promptly analyze data, create new insights into problematic areas and generate actionable knowledge for fact-based decision making. The aim of this article is to describe an initial work focused on building a comprehensive statistical surveillance dashboard for the epidemic of COVID-19, which can be exploited also for future needs. We propose novel ways of exploring, analyzing and presenting data, using metrics that have not been used previously. We also show the steps necessary to b…

2019-20 coronavirus outbreakCoronavirus disease 2019 (COVID-19)Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Dashboard (business)0211 other engineering and technologies02 engineering and technology01 natural sciencesIndustrial and Manufacturing Engineering010104 statistics & probabilitymultiple attribute decision-makingprocess monitoringPandemicHealth carestatistical process control0101 mathematicsSafety Risk Reliability and Quality021103 operations researchbusiness.industrySettore SECS-S/02 - Statistica Per La Ricerca Sperimentale E Tecnologicastatistical decision makingPublic relationsStatistical thinkingstatistical thinkingBusinessDecision analysisDecision analysiQuality Engineering
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Quantization of Poisson Lie Groups and Applications

1996

LetG be a connected Poisson-Lie group. We discuss aspects of the question of Drinfel'd:can G be quantized? and give some answers. WhenG is semisimple (a case where the answer isyes), we introduce quantizable Poisson subalgebras ofC ∞(G), related to harmonic analysis onG; they are a generalization of F.R.T. models of quantum groups, and provide new examples of quantized Poisson algebras.

58B30Pure mathematicsGeneralizationPoisson distribution01 natural sciencesHarmonic analysissymbols.namesakeQuantization (physics)58F060103 physical sciences0101 mathematicsQuantumMathematical PhysicsComputingMilieux_MISCELLANEOUSMathematicsPoisson algebraDiscrete mathematics[MATH.MATH-RT]Mathematics [math]/Representation Theory [math.RT]Group (mathematics)010102 general mathematicsLie groupStatistical and Nonlinear Physics81S1017B37[ MATH.MATH-RT ] Mathematics [math]/Representation Theory [math.RT]symbols010307 mathematical physics16W30
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Uncertainty quantification on a spatial Markov-chain model for the progression of skin cancer

2019

AbstractA spatial Markov-chain model is formulated for the progression of skin cancer. The model is based on the division of the computational domain into nodal points, that can be in a binary state: either in ‘cancer state’ or in ‘non-cancer state’. The model assigns probabilities for the non-reversible transition from ‘non-cancer’ state to the ‘cancer state’ that depend on the states of the neighbouring nodes. The likelihood of transition further depends on the life burden intensity of the UV-rays that the skin is exposed to. The probabilistic nature of the process and the uncertainty in the input data is assessed by the use of Monte Carlo simulations. A good fit between experiments on mi…

65C05Skin NeoplasmsComputer scienceQuantitative Biology::Tissues and OrgansMarkovin ketjut0206 medical engineeringMonte Carlo methodPhysics::Medical PhysicsBinary number02 engineering and technologyArticleihosyöpä03 medical and health sciencesMicemedicineAnimalsHumansComputer SimulationStatistical physicsUncertainty quantification60J20stokastiset prosessit030304 developmental biologyProbability0303 health sciencesMarkov chainApplied MathematicsProbabilistic logicUncertaintyState (functional analysis)medicine.disease020601 biomedical engineeringAgricultural and Biological Sciences (miscellaneous)Markov ChainsCardinal pointModeling and Simulation65C40Disease Progressionmatemaattiset mallitSkin cancerMonte Carlo MethodJournal of Mathematical Biology
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Combined Innovation Policy: Linking Scientific and Practical Knowledge in Innovation Systems

2012

New research indicates that firms combining the science-based STI (Science, Technology, Innovation) and the experience-based DUI (Doing, Using, Interacting) modes of innovation are more efficient when it comes to improving innovation capacity and competitiveness. With regard to innovation policy, the STI mode calls for a supply driven policy, typically aimed to commercialise research results. The DUI mode suggests a demand driven policy approach, such as supporting the development of new products or services to specific markets. This paper analyses how the two types of innovation policy and the two innovation modes can be combined in regional innovation systems. The analysis builds on studi…

9. Industry and infrastructure05 social sciencesGeography Planning and Development0211 other engineering and technologiesInnovation management021107 urban & regional planning02 engineering and technologyPolicy initiativesInnovation policy Regional system of innovation Modes of innovation Food industry Agribusiness Farm Management Food Consumption/Nutrition/Food Safety Industrial Organization Research Methods/ Statistical Methods0502 economics and businessEconomicsMarketing050203 business & managementIndustrial organizationAgribusiness
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