Search results for "covariate"

showing 10 items of 110 documents

Clusters of effects curves in quantile regression models

2018

In this paper, we propose a new method for finding similarity of effects based on quantile regression models. Clustering of effects curves (CEC) techniques are applied to quantile regression coefficients, which are one-to-one functions of the order of the quantile. We adopt the quantile regression coefficients modeling (QRCM) framework to describe the functional form of the coefficient functions by means of parametric models. The proposed method can be utilized to cluster the effect of covariates with a univariate response variable, or to cluster a multivariate outcome. We report simulation results, comparing our approach with the existing techniques. The idea of combining CEC with QRCM per…

Statistics and ProbabilityStatistics::TheoryMultivariate statistics05 social sciencesUnivariateFunctional data analysis01 natural sciencesQuantile regressionQuantile regression coefficients modeling Multivariate analysis Functional data analysis Curves clustering Variable selection010104 statistics & probabilityComputational Mathematics0502 economics and businessParametric modelCovariateStatistics::MethodologyApplied mathematics0101 mathematicsStatistics Probability and UncertaintyCluster analysisSettore SECS-S/01 - Statistica050205 econometrics MathematicsQuantile
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Nonlinear parametric quantile models

2020

Quantile regression is widely used to estimate conditional quantiles of an outcome variable of interest given covariates. This method can estimate one quantile at a time without imposing any constraints on the quantile process other than the linear combination of covariates and parameters specified by the regression model. While this is a flexible modeling tool, it generally yields erratic estimates of conditional quantiles and regression coefficients. Recently, parametric models for the regression coefficients have been proposed that can help balance bias and sampling variability. So far, however, only models that are linear in the parameters and covariates have been explored. This paper …

Statistics and ProbabilityStatistics::Theoryquantile regressionEpidemiologyparametric010501 environmental sciences01 natural sciencesquantile regression coefficients models010104 statistics & probabilityOutcome variableHealth Information ManagementCovariateEconometricsHumansStatistics::MethodologyComputer Simulation0101 mathematicsChild0105 earth and related environmental sciencesParametric statisticsMathematicsModels StatisticalForced oscillation technique integrated loss function parametric quantile regression quantile regression coefficients models Child Computer Simulation Humans Regression Analysis Models Statistical Nonlinear DynamicsStatistics::ComputationQuantile regressionNonlinear systemNonlinear Dynamicsintegrated loss functionRegression AnalysisQuantileStatistical Methods in Medical Research
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Comment on ‘Generating survival times to simulate Cox proportional hazards models with time-varying covariates’

2013

Statistics and ProbabilityTime-varying covariateta112EpidemiologyProportional hazards modelStatisticsSurvival analysisMathematicsStatistics in Medicine
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Segmented relationships to model erosion of regression effect in Cox regression

2010

In this article we propose a parsimonious parameterisation to model the so-called erosion of the covariate effect in the Cox model, namely a covariate effect approaching to zero as the follow-up time increases. The proposed parameterisation is based on the segmented relationship where proper constraints are set to accomodate for the erosion. Relevant hypothesis testing is discussed. The approach is illustrated on two historical datasets in the survival analysis literature, and some simulation studies are presented to show how the proposed framework leads to a test for a global effect with good power as compared with alternative procedures. Finally, possible generalisations are also present…

Statistics and ProbabilitybreakpointEpidemiologyProportional hazards modelLiver Cirrhosis BiliaryErosion (morphology)Lupus NephritisSet (abstract data type)Segmented regressionHealth Information ManagementNonlinear DynamicsRegression toward the meanCox modelCovariateStatisticsEconometricsHumansComputer SimulationSettore SECS-S/05 - Statistica SocialeSettore SECS-S/01 - Statisticaerosion of effectStatistical hypothesis testingMathematicsFollow-Up StudiesProportional Hazards Models
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A semiparametric approach to estimate reference curves for biophysical properties of the skin

2006

Reference curves which take one covariable into account such as the age, are often required in medicine, but simple systematic and efficient statistical methods for constructing them are lacking. Classical methods are based on parametric fitting (polynomial curves). In this chapter, we describe a new methodology for the estimation of reference curves for data sets, based on nonparametric estimation of conditional quantiles. The derived method should be applicable to all clinical or more generally biological variables that are measured on a continuous quantitative scale. To avoid the curse of dimensionality when the covariate is multidimensional, a new semiparametric approach is proposed. Th…

Statistics::TheoryKernel density estimationcomputer.software_genre01 natural sciences010104 statistics & probability0502 economics and businessCovariateSliced inverse regressionApplied mathematicsStatistics::MethodologySemiparametric regression0101 mathematics[SHS.ECO] Humanities and Social Sciences/Economics and Finance050205 econometrics MathematicsParametric statisticsDimensionality reduction05 social sciencesNonparametric statistics[ SDV.SPEE ] Life Sciences [q-bio]/Santé publique et épidémiologie[SHS.ECO]Humanities and Social Sciences/Economics and Finance3. Good health[SDV.SPEE] Life Sciences [q-bio]/Santé publique et épidémiologie[SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologieC140;C630Data miningcomputerQuantile
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ETAS Space–Time Modeling of Chile Triggered Seismicity Using Covariates: Some Preliminary Results

2021

Chilean seismic activity is one of the strongest in the world. As already shown in previous papers, seismic activity can be usefully described by a space–time branching process, such as the ETAS (Epidemic Type Aftershock Sequences) model, which is a semiparametric model with a large time-scale component for the background seismicity and a small time-scale component for the triggered seismicity. The use of covariates can improve the description of triggered seismicity in the ETAS model, so in this paper, we study the Chilean seismicity separately for the North and South area, using some GPS-related data observed together with ordinary catalog data. Our results show evidence that the use of s…

Technologymodel selectionQH301-705.5QC1-999Induced seismicityPhysics::Geophysicssemiparametric modelComponent (UML)CovariateGeneral Materials Sciencetriggered seismicityBiology (General)InstrumentationQD1-999AftershockBranching processFluid Flow and Transfer ProcessesProcess Chemistry and TechnologySpace timeModel selectionTPhysicsGeneral EngineeringcovariatesEngineering (General). Civil engineering (General)Computer Science ApplicationsSemiparametric modelETAS modelChemistrycovariatesemiparametric modelsTA1-2040GeologySeismologyApplied Sciences
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Estimating the occurrence of traffic accidents near school locations: A case study from Valencia (Spain) including several approaches

2019

Traffic safety around school locations is a topic of particular interest given the large number of vulnerable users, such as pedestrians or cyclists, that commute to them at certain times of the day. A dataset of traffic accidents recorded in Valencia (Spain) during 2014 and 2015 is analyzed in order to estimate the effects that school locations produce on traffic risk within their surroundings. The four typologies of school in this city according to the academic levels they offer (All-level, Preschool, Primary, Secondary) are distinguished and taken into consideration for the analysis. Two time windows comprising the starting time in the morning and the evening time once day school has end…

Time FactorsEveningPoison controlHuman Factors and ErgonomicsLogistic regressionOccupational safety and health0502 economics and businessStatisticsInjury preventionCovariateHumans0501 psychology and cognitive sciencesBuilt EnvironmentChildSafety Risk Reliability and QualitySocioeconomic status050107 human factorsSpatial Analysis050210 logistics & transportationSchools05 social sciencesAccidents TrafficPublic Health Environmental and Occupational HealthHuman factors and ergonomicsLogistic ModelsGeographySpainCase-Control StudiesAccident Analysis & Prevention
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Application of the group method of data handling (GMDH) approach for landslide susceptibility zonation using readily available spatial covariates

2022

Abstract Landslide susceptibility (LS) mapping is an essential tool for landslide risk assessment. This study aimed to provide a new approach with better performance for landslide mapping and adopting readily available variables. In addition, it investigates the capability of a state-of-the-art model developed using the group method of data handling (GMDH) to spatially model LS. Furthermore, hybridized models of GMDH were developed using different metaheuristic algorithms. The study area was the Bonghwa region of South Korea, for which an accurate landslide inventory dataset is available. We considered a total of 13 spatial covariates (altitude, slope, aspect, topographic wetness index, val…

Topographic Wetness IndexVariablesReceiver operating characteristicMean squared errorGroup method of data handlingmedia_common.quotation_subjectLandslideArtificial intelligence Data-scarcity Factor selection GIS Natural disasterscomputer.software_genreRegressionCovariateData miningcomputerEarth-Surface Processesmedia_commonMathematicsCATENA
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Spatial Bayesian Modeling Applied to the Surveys of Xylella fastidiosa in Alicante (Spain) and Apulia (Italy)

2020

The plant-pathogenic bacterium Xylella fastidiosa was first reported in Europe in 2013, in the province of Lecce, Italy, where extensive areas were affected by the olive quick decline syndrome, caused by the subsp. pauca. In Alicante, Spain, almond leaf scorch, caused by X. fastidiosa subsp. multiplex, was detected in 2017. The effects of climatic and spatial factors on the geographic distribution of X. fastidiosa in these two infested regions in Europe were studied. The presence/absence data of X. fastidiosa in the official surveys were analyzed using Bayesian hierarchical models through the integrated nested Laplace approximation (INLA) methodology. Climatic covariates were obtained from …

Xylella fastidiosa0106 biological scienceshierarchical Bayesian modelsDiurnal rangeLeaf scorchPlant Sciencelcsh:Plant cultureBayesian inference01 natural sciences010104 statistics & probabilityCovariatemedicinelcsh:SB1-11100101 mathematicsspecies distribution modelsXylella fastidiosabiologySpatial structurealmond leaf scorchintegrated nested Laplace approximation15. Life on landbiology.organism_classificationmedicine.diseaseConfounding effectstochastic partial differential equationGeographyolive quick declineSampling distributionXylella fastidiosaCartography010606 plant biology & botanyFrontiers in Plant Science
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Analyse et Estimations Spectrales des Processus alpha-Stables non-Stationnaires

2006

In this work a new spectral representation of a symmetric alpha-stable processes is introduced. It is based on a covariation pseudo-additivity and Morse-Transue's integral with respect to a bimesure built by using pseudo-additivity property. This representation, specific to S$\alpha$S processes, is analogous to the covariance of second order processes. On the other hand, it generalizes the representation established for stochastic integrals with respect to symmetric alpha-stable process of independent increments. We provide a classification of non-stationary harmonizable processes; this classification is based on the bimesure structure. In particular, we defined and investigated periodicall…

[ MATH ] Mathematics [math]Densité spectraleSpectral estimation[MATH] Mathematics [math]Estimation spectraleLepage Seriesnon-parametrique StatistiquesPeriodically covariated processesSéries de LepageSpectral AnalysisSpectral densityStrong mixing.Statistiques non paramétriquesMélange fortCovariationProcessus \alpha-stables[MATH]Mathematics [math]Mélange fort.Processus périodiquement covariés\alpha-stable ProcessesAnalyse spectrale
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