0000000000012811

AUTHOR

Jérôme Saracco

showing 8 related works from this author

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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Some extensions of multivariate sliced inverse regression

2007

Multivariate sliced inverse regression (SIR) is a method for achieving dimension reduction in regression problems when the outcome variable y and the regressor x are both assumed to be multidimensional. In this paper, we extend the existing approaches, based on the usual SIR I which only uses the inverse regression curve, to methods using properties of the inverse conditional variance. Contrary to the existing ones, these new methods are not blind for symmetric dependencies and rely on the SIR II or SIRα. We also propose their corresponding pooled slicing versions. We illustrate the usefulness of these approaches on simulation studies.

Statistics and ProbabilityMultivariate statisticsApplied MathematicsDimensionality reductionInverseOutcome variableModeling and SimulationStatisticsSliced inverse regressionStatistics::MethodologyStatistics Probability and UncertaintyConditional varianceRegression problemsMathematicsRegression curveJournal of Statistical Computation and Simulation
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Asymptotics for pooled marginal slicing estimator based on SIRα approach

2005

Pooled marginal slicing (PMS) is a semiparametric method, based on sliced inverse regression (SIR) approach, for achieving dimension reduction in regression problems when the outcome variable y and the regressor x are both assumed to be multidimensional. In this paper, we consider the SIR"@a version (combining the SIR-I and SIR-II approaches) of the PMS estimator and we establish the asymptotic distribution of the estimated matrix of interest. Then the asymptotic normality of the eigenprojector on the estimated effective dimension reduction (e.d.r.) space is derived as well as the asymptotic distributions of each estimated e.d.r. direction and its corresponding eigenvalue.

Statistics and ProbabilityNumerical AnalysisDimensionality reductionStatisticsSliced inverse regressionAsymptotic distributionEstimatorRegression analysisStatistics Probability and UncertaintyMarginal distributionEffective dimensionEigenvalues and eigenvectorsMathematicsJournal of Multivariate Analysis
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Interaspecific chemical variability and highlighting of chemotypes of leaf essential oils from Ravensara aromatica Sonnerat, a tree endemic to Madaga…

2006

Ravensara aromatica Sonnerat is a tree endemic to Madagascar. The essential oil extracted from the leaves is used in aromatherapy. Previous chemical studies have generated some confusion with regard to the chemical composition of this essential oil. In order to eliminate this uncertainty, we undertook a systematic evaluation of the chemical composition of essential oils from leaves of this species. The study focused on 28 individual samples formally identified as R. aromatica. The essential oils were obtained by hydrodistillation and analysed by GC and GC–MS. It was possible to distinguish four groups of trees through principal components analysis and agglomerative hierarchical clustering a…

K50 - Technologie des produits forestiersRavensara aromaticaF60 - Physiologie et biochimie végétaleSabinenelaw.inventionchemistry.chemical_compoundVariation génétiqueMethyl eugenolLinaloolhttp://aims.fao.org/aos/agrovoc/c_2393lawBotanyPlante médicinalehttp://aims.fao.org/aos/agrovoc/c_4510Essential oilbiologyChemotypeChemistryhttp://aims.fao.org/aos/agrovoc/c_2669FeuilleGeneral ChemistryComposition chimiquebiology.organism_classificationhttp://aims.fao.org/aos/agrovoc/c_4243ChavicolHuile essentiellehttp://aims.fao.org/aos/agrovoc/c_1794http://aims.fao.org/aos/agrovoc/c_15975Food ScienceAromatherapy
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Two-step Estimation in a Multivariate Semiparametric Sample Selection Model

2008

International audience

[ SHS.ECO ] Humanities and Social Sciences/Economies and finances[SHS.ECO] Humanities and Social Sciences/Economics and Finance[SHS.ECO]Humanities and Social Sciences/Economics and FinanceComputingMilieux_MISCELLANEOUS
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A Cluster-based Approach for Sliced Inverse Regression

2008

International audience

[ SHS.ECO ] Humanities and Social Sciences/Economies and finances[SHS.ECO] Humanities and Social Sciences/Economics and Finance[SHS.ECO]Humanities and Social Sciences/Economics and FinanceComputingMilieux_MISCELLANEOUS
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Un estimateur de la médiane spatiale conditionnelle par transformation-retransformation.

2005

[ SHS.ECO ] Humanities and Social Sciences/Economies and finances[SHS.ECO]Humanities and Social Sciences/Economics and Finance[SHS.ECO] Humanities and Social Sciences/Economics and Finance
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Quantiles de régression : applications à la construction de courbes de référence

2006

[MATH.MATH-PR]Mathematics [math]/Probability [math.PR][ SHS.ECO ] Humanities and Social Sciences/Economies and finances[SHS.ECO] Humanities and Social Sciences/Economics and Finance[SHS.ECO]Humanities and Social Sciences/Economics and Finance
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