2024
Integrative factor-adjusted sparse generalized linear models
Xu F, Ma S, Zhang Q. Integrative factor-adjusted sparse generalized linear models. Journal Of Statistical Computation And Simulation 2024, 95: 764-780. DOI: 10.1080/00949655.2024.2439450.Peer-Reviewed Original ResearchVariable selection consistencyHigh-dimensional dataIncreased accessibility of dataSelection consistencyConsistency propertiesCorrelated covariatesGeneralized linear modelVariable selectionAnalysis of genetic dataAccessibility of dataIdiosyncratic componentsCompetitive performanceCovariatesGenetic dataLinear modelSample sizeImprove model performanceEstimationIntegrated analysisModel estimatesLatent factorsModel performancePractical useConsistencyEstimation of multiple networks with common structures in heterogeneous subgroups
Qin X, Hu J, Ma S, Wu M. Estimation of multiple networks with common structures in heterogeneous subgroups. Journal Of Multivariate Analysis 2024, 202: 105298. PMID: 38433779, DOI: 10.1016/j.jmva.2024.105298.Peer-Reviewed Original ResearchGaussian graphical modelsMultiple networksGraphical modelsSparse regression problemHigh-dimensional data analysisNetwork estimationMinimax concave penaltyLarge-scale dataRegularized likelihoodJoint estimation approachRegression problemSelection consistency propertyConcave penaltyComplex dependence structureNetworkBreast cancer dataConsistency propertiesConvexity propertiesTCGA breast cancer dataNetwork identificationReparameterization techniqueEstimation approachDistributional assumptionsDependence structureBiological networks
2022
Network-adaptive robust penalized estimation of time-varying coefficient models with longitudinal data
Fang K, Fan X, Ma S, Zhang Q. Network-adaptive robust penalized estimation of time-varying coefficient models with longitudinal data. Journal Of Statistical Computation And Simulation 2022, 92: 3045-3065. DOI: 10.1080/00949655.2022.2055758.Peer-Reviewed Original ResearchTime-varying coefficient modelsLikelihood-based estimationPenalization approachCoefficient modelStatistical modelPractical problemsNovel penaltyConsistency propertiesPractical performanceLoss functionNumerical studyLongitudinal dataEstimationNetwork structureNetwork connectivityConnection measuresModelData analysisRobustnessSimulationsInterconnectionProblemCovariatesField
2021
Promote sign consistency in the joint estimation of precision matrices
Zhang Q, Ma S, Huang Y. Promote sign consistency in the joint estimation of precision matrices. Computational Statistics & Data Analysis 2021, 159: 107210. DOI: 10.1016/j.csda.2021.107210.Peer-Reviewed Original ResearchMultiple precision matricesPrecision matrixRegularization methodJoint estimationGroup parametersSign consistencyConsistency propertiesGaussian graphical modelsNovel regularization methodHigh-dimensional dataRandom variablesSparsity structureData examplesMore interpretable resultsNatural interpretationConditional independenceInterpretable resultsGraphical modelsPractical examplesEstimationConflicting signsPopular toolMatrixParametersFull flexibility
2019
Penalized Relative Error Estimation of a Partially Functional Linear Multiplicative Model
Zhang T, Huang Y, Zhang Q, Ma S, Ahmed S. Penalized Relative Error Estimation of a Partially Functional Linear Multiplicative Model. Contributions To Statistics 2019, 127-144. DOI: 10.1007/978-3-030-17519-1_10.Peer-Reviewed Original ResearchFinite sample performanceRelative error estimationTecator dataScalar responseLinear multiplicative modelsScalar variablesSample performanceFunctional predictorsError estimationBasis functionsMultiplicative modelConsistency propertiesLeast squaresLoss functionTrue structureRelative errorClassic methodsEstimationPenalizationModelFunctional dataSquaresSimulations
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