Search results for " dependence"

showing 10 items of 2018 documents

Modeling accident risk at the road level through zero-inflated negative binomial models: A case study of multiple road networks

2021

Abstract This paper presents a case study carried out in multiple cities of the Valencian Community (Spain) to determine the effect of sociodemographic and road characteristics on traffic accident risk. The analyzes are performed at the road segment level, considering the linear network representing the road structure of each city as a spatial lattice. The number of accidents observed in each road segment from 2010 to 2019 is taken as the response variable, and a zero-inflated modeling approach is considered. Count overdispersion and spatial dependence are also accounted for. Despite the complexity and sparsity of the data, the fitted models performed considerably well, with few exceptions.…

Statistics and ProbabilityComputer sciencespatial dependence0208 environmental biotechnologyAccident riskMagnitude (mathematics)Distribution (economics)02 engineering and technologyManagement Monitoring Policy and Law01 natural sciencestraffic accidents010104 statistics & probabilityOverdispersionCovariateStatisticsZero-inflated model0101 mathematicsComputers in Earth SciencesSpatial dependencelattice structurebusiness.industryIntegrated Nested Laplace Approximationzero-inflated model020801 environmental engineeringVariable (computer science)linear networksbusiness
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Booms, Busts and normal times in the housing market

2015

We assess the existence of duration dependence in the likelihood of an end in housing booms, busts, and normal times. Using data for 20 industrial countries and a continuous-time Weibull duration model, we find evidence of positive duration dependence suggesting that housing market cycles have become longer over the last decades. Then, we extend the baseline Weibull model and allow for the presence of a change-point in the duration dependence parameter.We show that positive duration dependence is present in booms and busts that last less than 26 quarters, but that does not seem to be the case for longer phases of the housing market cycle. For normal times, no evidence of change-points is fo…

Statistics and ProbabilityEconomics and EconometricsHousing booms and bustsSocial SciencesDuration dependenceBoomWeibull modelEconomicsDuration (project management)Baseline (configuration management)Weibull distributionScience & TechnologyActuarial scienceCiências Sociais::Economia e Gestãohousing booms and busts duration analysis Weibull model duration dependence change-pointsSettore SECS-P/02 Politica EconomicaDuration analysis8. Economic growthChange pointsChange-pointsDemographic economics:Economia e Gestão [Ciências Sociais]Statistics Probability and UncertaintyDuration dependenceSocial Sciences (miscellaneous)
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A spatially filtered mixture of β-convergence regressions for EU regions, 1980–2002

2007

Assessing regional growth and convergence across Europe is a matter of primary relevance. Empirical models that do not account for structural heterogeneities and spatial effects may face serious misspecification problems. In this work, a mixture regression approach is applied to the beta-convergence model, in order to produce an endogenous selection of regional growth patterns. A priori choices, such as North-South or centre-periphery divisions, are avoided. In addition to this, we deal with the spatial dependence existing in the data, applying a local filter to the data. The results indicate that spatial effects matter, and either absolute, conditional, or club convergence, if extended to …

Statistics and ProbabilityEconomics and EconometricsSmall numberEmpirical modellingSample (statistics)Filter (signal processing)Mathematics (miscellaneous)Rate of convergenceConvergence (routing)StatisticsOutlierEconometricsSpatial dependenceSettore SECS-P/01 - Economia PoliticaRegional growth - Convergence patterns - Mixture regression - Spatial effectsSocial Sciences (miscellaneous)MathematicsEmpirical Economics
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A spatial analysis of new business formation: Replicative vs innovative behaviour

2017

Abstract Using spatial econometric tools, the paper examines the spatial structure of new business formation of Italian regions during the period 2004–2007. In particular, the study empirically investigates whether new business formation in a given geographical area may be explained in terms of replicative and/or innovative entrepreneurial behaviour in each area as well as in the neighbouring areas. Additionally, the analysis focuses on the influence of urbanization on the birth of new firms. From the estimation of a Spatial Durbin Model, we find a significant degree of spatial dependence among Italian regions not only in new business formation but also in some of its determinants. We also …

Statistics and ProbabilityEstimationSpatial structureUrbanization05 social sciencesSpatial analysis0211 other engineering and technologies021107 urban & regional planning02 engineering and technologyManagement Monitoring Policy and LawDegree (music)Replicative and innovative behaviourUrbanizationSettore SECS-S/03 - Statistica Economica0502 economics and businessEconomicsEconomic geography050207 economicsComputers in Earth SciencesSpatial dependenceNew business formationSpatial Statistics
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Multivariate nonparametric estimation of the Pickands dependence function using Bernstein polynomials

2017

Abstract Many applications in risk analysis require the estimation of the dependence among multivariate maxima, especially in environmental sciences. Such dependence can be described by the Pickands dependence function of the underlying extreme-value copula. Here, a nonparametric estimator is constructed as the sample equivalent of a multivariate extension of the madogram. Shape constraints on the family of Pickands dependence functions are taken into account by means of a representation in terms of Bernstein polynomials. The large-sample theory of the estimator is developed and its finite-sample performance is evaluated with a simulation study. The approach is illustrated with a dataset of…

Statistics and ProbabilityFOS: Computer and information sciencesMultivariate statisticsNONPARAMETRIC ESTIMATIONMULTIVARIATE MAX-STABLE DISTRIBUTION01 natural sciencesCopula (probability theory)Methodology (stat.ME)010104 statistics & probabilityStatisticsStatistics::Methodology0101 mathematicsExtreme-value copulaEXTREMAL DEPENDENCEEXTREMEVALUE COPULA[SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces environmentStatistics - MethodologyComputingMilieux_MISCELLANEOUSMathematics[SDU.OCEAN]Sciences of the Universe [physics]/Ocean AtmosphereApplied Mathematics010102 general mathematicsNonparametric statisticsEstimatorExtremal dependenceHEAVY RAINFALLBernstein polynomialBERNSTEIN POLYNOMIALS EXTREMAL DEPENDENCE EXTREMEVALUE COPULA HEAVY RAINFALL NONPARAMETRIC ESTIMATION MULTIVARIATE MAX-STABLE DISTRIBUTION PICKANDS DEPENDENCE FUNCTION13. Climate actionDependence functionStatistics Probability and UncertaintyMaximaSettore SECS-S/01 - StatisticaBERNSTEIN POLYNOMIALSPICKANDS DEPENDENCE FUNCTION
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Bayesian Mapping of Lichens Growing on Trees

2001

Suitability of trees as hosts for epiphytic lichens are studied in a forest stand of size 25 ha. Suitability is measured as occupation probabilites which are modelled using hierarchical Bayesian approach. These probabilities are useful for an ecologist. They give smoothed spatial distribution map of suitability for each of the species and can be used in detecting high- and low-probability areas. In addition, suitability is explained by tree-level covariates. Spatial dependence, which is due to unobserved spatially structured covariates, is modelled through an unobserved Markov random field. Markov chain Monte Carlo method has been applied in Bayesian computation. The extensive spatial data …

Statistics and ProbabilityMarkov chainbiologyBayesian probabilityDiameter at breast heightMarkov chain Monte CarloGeneral Medicinebiology.organism_classificationsymbols.namesakeStatisticsCovariatesymbolsStatistics Probability and UncertaintySpatial dependenceSpatial analysisMathematicsLobaria pulmonariaBiometrical Journal
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Gaussian component mixtures and CAR models in Bayesian disease mapping

2012

Hierarchical Bayesian models involving conditional autoregression (CAR) components are commonly used in disease mapping. An alternative model to the proper or improper CAR is the Gaussian component mixture (GCM) model. A review of CAR and GCM models is provided in univariate settings where only one disease is considered, and also in multivariate situations where in addition to the spatial dependence between regions, the dependence among multiple diseases is analyzed. A performance comparison between models using a set of simulated data to help illustrate their respective properties is reported. The results show that both in univariate and multivariate settings, both models perform in a comp…

Statistics and ProbabilityMultivariate statisticsApplied MathematicsGaussianBayesian probabilityUnivariateVariable-order Bayesian networkComputational Mathematicssymbols.namesakeComputational Theory and MathematicsAutoregressive modelStatisticsRange (statistics)symbolsEconometricsSpatial dependenceMathematicsComputational Statistics & Data Analysis
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Quantum correlations in generalized spin star system

2006

The problem of detecting quantum signatures in the correlations formed in dynamical evolution of quantum bipartite systems receives a lot of attention in current literature. Generally speaking, the occurrence of correlations between two observables of a system does not necessarily reflect nonclassical behaviour. In this paper, the exact dynamics of a pair of uncoupled spins 1/2 interacting with a common spin 1/2 bath is investigated. Starting from a separable initial condition, the ability of the system to develop purely quantum correlations is brought to light. Physical interpretation of the concurrence function as well as a suggestion on how to measure it are given.

Statistics and ProbabilityPhysicsDISSOCIATION-CONSTANTSQuantum discordQuantum dynamicsTETRAETHYLAMMONIUM IODIDEStatistical and Nonlinear PhysicsObservable25 DEGREES CSODIUM-CHLORIDEHEAT-CAPACITIESIONIC-STRENGTH DEPENDENCEMOLECULAR-WEIGHTQuantum mechanicsQuantum processQuantum operationQuantum algorithmACTIVITY-COEFFICIENTSIONIZATION-CONSTANTQuantumCOMPLEX-FORMATIONMathematical PhysicsSpin-½
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Spatial Mark-Recapture Method in the Estimation of Crayfish Population Size

1995

The mark-recapture method is considered for estimation of population size of slowly moving animals like crayfish. The Petersen type estimator for closed population is generalized for situations where recaptures are spatially dependent between the capture sites, and its variance approximation is derived using point processes as models for the population. The method of quadratic forms is suggested to be used as variance estimator. Finally, a trapping design is proposed where onc trap at recapture is replaced by four adjacent traps. A simulation experiment is performed to explain the robusticity of the new trapping design against movements of animals.

Statistics and Probabilityeducation.field_of_studyPopulation sizePopulationEstimatorGeneral MedicineTrappingCrayfishPoint processMark and recaptureStatisticsStatistics Probability and UncertaintySpatial dependenceeducationMathematicsBiometrical Journal
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"Table 2" of "Exclusive production of pion and kaon meson pairs in two photon collisions at LEP."

2003

Measured angular distribution for kaon production.

Strange productionElectron productionNuclear Theory0.0GAMMA GAMMA --> K+ K-Single Differential Cross SectionPhotoproductionE+ E- ScatteringDSIG/DCOSTHETATwo-PhotonExclusiveHigh Energy Physics::ExperimentNuclear ExperimentAngular DependenceE+ E- --> E+ E- K+ K-
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