2017
A group adaptive elastic-net approach for variable selection in high-dimensional linear regression
Hu J, Huang J, Qiu F. A group adaptive elastic-net approach for variable selection in high-dimensional linear regression. Science China Mathematics 2017, 61: 173-188. DOI: 10.1007/s11425-016-0071-x.Peer-Reviewed Original ResearchAdaptive elastic-netHigh-dimensional linear regressionProblem of group selectionElastic-netOracle propertyOracle inequalitiesHigh-dimensional problemsVariable selectionGroup structureSample sizeModel selectionCollinearity problemElastic netOracleElastic-net approachHigh-dimensionalCompetitive methodsData studiesLinear regression modelsProblemInequalityModel consistencyGroup numberStatistical modelInference
2015
Asymptotic properties of Lasso in high-dimensional partially linear models
Ma C, Huang J. Asymptotic properties of Lasso in high-dimensional partially linear models. Science China Mathematics 2015, 59: 769-788. DOI: 10.1007/s11425-015-5093-2.Peer-Reviewed Original ResearchHigh-dimensional partially linear modelsPartially linear modelsLinear partPerformance of variable selectionFinite sample performanceNonparametric function estimationRate of convergenceTruncated series expansionNonparametric componentAsymptotic propertiesNonparametric functionOracle inequalitiesRegularity conditionsSufficient conditionsLasso estimatorPolynomial splinesFunction estimationSparsity assumptionLinear modelVariable selectionSimulation studySeries expansionEstimation errorRegression coefficientsLinear component