Search results for "quantile regression"

showing 10 items of 66 documents

Design-based estimation for geometric quantiles with application to outlier detection

2010

Geometric quantiles are investigated using data collected from a complex survey. Geometric quantiles are an extension of univariate quantiles in a multivariate set-up that uses the geometry of multivariate data clouds. A very important application of geometric quantiles is the detection of outliers in multivariate data by means of quantile contours. A design-based estimator of geometric quantiles is constructed and used to compute quantile contours in order to detect outliers in both multivariate data and survey sampling set-ups. An algorithm for computing geometric quantile estimates is also developed. Under broad assumptions, the asymptotic variance of the quantile estimator is derived an…

Statistics and ProbabilityStatistics::TheoryTheoryofComputation_COMPUTATIONBYABSTRACTDEVICESStatistics::ApplicationsComputingMethodologies_SIMULATIONANDMODELINGApplied MathematicsMathematicsofComputing_NUMERICALANALYSISUnivariateInformationSystems_DATABASEMANAGEMENTEstimatorStatistics::ComputationQuantile regressionHorvitz–Thompson estimatorComputational MathematicsDelta methodComputational Theory and MathematicsTheoryofComputation_ANALYSISOFALGORITHMSANDPROBLEMCOMPLEXITYOutlierConsistent estimatorStatisticsStatistics::MethodologyMathematicsQuantileComputational Statistics & Data Analysis
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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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Modelling the timing of divorce in Italy: a survival analysis on regression quantiles

2011

The analysis of marital dissolution in Italy represents a quite interesting and challenging topic from a substantive standpoint; in fact, despite of the decreasing number of marriages and the increasing number of divorces, the traditional family based on the marriage of heterosexual partners is still considered as a fundamental institution of the society. Here we present a censored quantile regression model with additive terms to investigate the determinants of the timing of marital dissolution on a large and substantial sample from a survey carried on in Italy.

Survival data modellingquantile regressiontiming of divorceSettore SECS-S/05 - Statistica SocialeSettore SECS-S/01 - Statistica
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Increase in rear-end collision risk by acute stress-induced fatigue in on-road truck driving.

2021

Increasing road crashes related to occupational drivers’ deteriorating health has become a social problem. To prevent road crashes, warnings and predictions of increased crash risk based on drivers’ conditions are important. However, in on-road driving, the relationship between drivers’ physiological condition and crash risk remains unclear due to difficulties in the simultaneous measurement of both. This study aimed to elucidate the relationship between drivers’ physiological condition assessed by autonomic nerve function (ANF) and an indicator of rear-end collision risk in on-road driving. Data from 20 male truck drivers (mean ± SD, 49.0±8.2 years; range, 35–63 years) were analyzed. Over …

TruckAdultMaleRiskmedicine.medical_specialtyAutomobile DrivingGradient boosting decision treeScienceRear-end collisionPhysical medicine and rehabilitationReaction TimeMedicineHumansAttentionAcute stressFatigueMultidisciplinarybusiness.industryQRAccidents TrafficMiddle AgedCollision riskQuantile regressionMotor VehiclesMedicinebusinessRisk assessmenthuman activitiesQuantileResearch ArticlePloS one
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Peer effects in the light of students interactions and the subjective dimensions of school experience

2011

This Thesis addresses the issue of peer-effects in the context of school. From analysis of a large database produced by a Chilean national study (SIMCE 2004), this work investigates the mechanisms through which pupils with different levels of scholastic, human and cultural capital influence each other. These influences seem present for a diverse range of school outcomes, including academic achievement. Drawing on the literature produced by different disciplinary approaches —sociology, economics, social psychology and education— the study focuses on ways of identifying and measuring peer-effects. The presence of subjective dimensions capable of reflecting, in part, the school experience of p…

[SHS.EDU]Humanities and Social Sciences/Education[SHS.EDU] Humanities and Social Sciences/EducationPeer-effectsModèles multiniveauxPratiques d'étude[ SHS.EDU ] Humanities and Social Sciences/EducationSégrégation socio-scolaireStudy practicesEntraideSchool well-beingFactorial analysisConcept de soi académiqueHierarchical modelsEffets de pairsPeer assistanceQuantile regressionChiliAcademic self-conceptChileRégression par quantilesBien-être à l'écoleSocial and academic segregationAnalyse factorielle
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Carbon and safe-haven flows

2022

<abstract> <p>This paper explores the role of European Union Allowances (EUAs) as a safe haven for a range of assets and analyses the effect of safe-haven flows on the European carbon futures market. In particular, we demonstrate that EUAs can be considered a refuge against fluctuations in corporate bonds, gold and volatility-related assets in periods of market turmoil. Furthermore, we have shown that extremely bearish and bullish movements in those assets for which the EUA acts as a safe haven induce excess volatility in carbon markets, higher carbon trading volume and larger than normal EUA bid-ask spreads. These findings support the idea that some traders, by considering carb…

carbon futuressafe-haven assetquantile regressionsafe-haven flowsOrganic ChemistryvolatilityEUAsUNESCO::CIENCIAS ECONÓMICASBiochemistry
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A new approach for clustering of effects in quantile regression

2017

In this paper we aim at nding similarities among the coefficients from a multivariate regression. Using a quantile regression coefficients modeling, the effect of each covariate, given a response (also multivariate) is a curve in the multidimensional space of the percentiles. Collecting all the curves, describing the effects of each covariate on each response variable, we could be able to assess if only one or more covariates have same effects on different responses.

curves clustering; quantile regression coefficients modeling; multivariate analysis; functional datacurves clusteringmultivariate analysiSettore SECS-S/01 - Statisticaquantile regression coefficients modelingfunctional data
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Functional principal component analysis of quantile curves

2017

Literature on functional data analysis is mainly focused on estimation of individuals curves and characterization of average dynamics. The idea underlying this proposal is to focus attention on other particular features of the distribution of the observed data, moving from mean functions towards functional quantiles. The motivating examples are functional data sets that are collections of high frequency data recorded along time. As quantiles provide information on various aspects of a time series, we propose a modelling framework for the joint estimation of functional quantiles, varying along time, and functional principal components, summarizing some common dynamics shared by the functiona…

functional data nonparametric quantile regression penalized splines functional principal componentsSettore SECS-S/01 - Statistica
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Growth curves of sorghum roots via quantile regression with P-splines

2014

Plant roots are a major pool of total carbon in the planet and their dynamics are directly relevant to greenhouse gas balance. Composted wastes are increasingly used in agriculture for environmental and economic reasons and their role as a substitute for traditional fertilizers needs to be tested on all plant components. Here we propose a regression quantile approach based on P-splines to assess, quantify and compare the root growth patterns in two treatment groups respectively undergoing compost and traditional fertilization.

growth curves quantile regression penalized splines noncrossing curves
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Interactions, spillovers de connaissance et croissance des économies modernes. Faut-il préférer la globalisation ou la proximité géographique ?

2009

Globalisation and metropolisation in modern economies induce some locational strategies of knowledge based activities towards cities and deeply increase trade and move of ideas across cities. In that context, we study the way knowledge spillovers have influenced the economic growth of 82 European Metropolises over the 1990-2005 period. We model knowledge spillovers across cities according to three specific interaction patterns depending either on geography or on global advanced services or thought a combination of these patterns. We show that the mixed pattern matters the best for economic growth of cities in Europe.

modern economiesJEL: C - Mathematical and Quantitative Methods/C.C2 - Single Equation Models • Single Variables/C.C2.C21 - Cross-Sectional Models • Spatial Models • Treatment Effect Models • Quantile RegressionsO4JEL : C - Mathematical and Quantitative Methods/C.C2 - Single Equation Models • Single Variables/C.C2.C21 - Cross-Sectional Models • Spatial Models • Treatment Effect Models • Quantile Regressionsurban climate C31JEL : R - Urban Rural Regional Real Estate and Transportation Economics/R.R1 - General Regional Economics/R.R1.R12 - Size and Spatial Distributions of Regional Economic Activityclimat des affaires[ SHS.ECO ] Humanities and Social Sciences/Economies and financesJEL: O - Economic Development Innovation Technological Change and Growth/O.O4 - Economic Growth and Aggregate Productivity[SHS.ECO] Humanities and Social Sciences/Economics and Financecroissance urbainejel:C31JEL: R - Urban Rural Regional Real Estate and Transportation Economics/R.R1 - General Regional Economics/R.R1.R11 - Regional Economic Activity: Growth Development Environmental Issues and Changes[SHS.ECO]Humanities and Social Sciences/Economics and FinanceJEL : R - Urban Rural Regional Real Estate and Transportation Economics/R.R1 - General Regional Economics/R.R1.R11 - Regional Economic Activity: Growth Development Environmental Issues and ChangesR11R12jel:O4metropolisesmétropolesJEL: R - Urban Rural Regional Real Estate and Transportation Economics/R.R1 - General Regional Economics/R.R1.R12 - Size and Spatial Distributions of Regional Economic Activityurban growthspatial interactionsinteractions spatialesjel:R12jel:R11économies modernesmodern economiesurban growthmetropolisesspatial interactionsurban climate C31O4R11R12croissance urbainemétropolesinteractions spatialesclimat des affaireséconomies modernesJEL : O - Economic Development Innovation Technological Change and Growth/O.O4 - Economic Growth and Aggregate Productivity
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