2024
Optimal and Safe Estimation for High-Dimensional Semi-Supervised Learning
Deng S, Ning Y, Zhao J, Zhang H. Optimal and Safe Estimation for High-Dimensional Semi-Supervised Learning. Journal Of The American Statistical Association 2024, ahead-of-print: 1-12. DOI: 10.1080/01621459.2023.2277409.Peer-Reviewed Original ResearchSemi-supervised estimatorConditional mean functionMean functionSupervised estimationParameters of linear modelsSemi-supervised learningRegression parametersEstimation problemLinear modelSupplementary materialsTheoretical resultsParameter estimationSemi-supervised settingUnlabeled dataLabeled dataEstimationMinimaxMisspecificationNumerical simulationsDataFunctionLearningProblemData analysis
2020
Relative Efficiency of Using Summary Versus Individual Data in Random-Effects Meta-Analysis
Chen D, Liu D, Min X, Zhang H. Relative Efficiency of Using Summary Versus Individual Data in Random-Effects Meta-Analysis. Biometrics 2020, 76: 1319-1329. PMID: 32056197, PMCID: PMC7955582, DOI: 10.1111/biom.13238.Peer-Reviewed Original ResearchConceptsMaximum likelihood estimationSummary statisticsAsymptotic senseStatistical methodologyLikelihood estimationGaussian distributionInference settingHeterogeneity parametersRelative efficiencyRandom effectsSample sizeStatisticsInferenceData setsModelEfficient conclusionsEstimationIndividual participant dataAssumptionParametersEfficiency
2015
Association Tests of Multiple Phenotypes: ATeMP
Guo X, Li Y, Ding X, He M, Wang X, Zhang H. Association Tests of Multiple Phenotypes: ATeMP. PLOS ONE 2015, 10: e0140348. PMID: 26479245, PMCID: PMC4610695, DOI: 10.1371/journal.pone.0140348.Peer-Reviewed Original ResearchConceptsExtensive simulation studyStatistical literatureJoint association analysisMultiPhenSimulation studyEquivalence relationshipProportional odds modelReal case studyMeasurement errorMultivariate methodsOdds modelMultiple intermediate phenotypesJoint analysisMultiple phenotypesExplanatory variablesEquivalenceEstimationDistributionPhenotypic distributionATempSolutionError
2006
Asymptotics for estimation and testing procedures under loss of identifiability
Zhu H, Zhang H. Asymptotics for estimation and testing procedures under loss of identifiability. Journal Of Multivariate Analysis 2006, 97: 19-45. DOI: 10.1016/j.jmva.2004.11.005.Peer-Reviewed Original ResearchLoss of identifiabilityTrue parameter valuesParameter pointsParameter valuesDifficult statistical problemStationary ARMA processesStatistical problemsQuadratic approximationParameter estimationTrue modelARMA processesParameter spaceLarge classObjective functionTesting statisticsIdentifiabilityHellinger distanceHypothesis testingUse of modelsSpecific examplesEstimationAsymptoticsApproximationStatistical analysisEstimator
1997
Multivariate Adaptive Splines for Analysis of Longitudinal Data
Zhang H. Multivariate Adaptive Splines for Analysis of Longitudinal Data. Journal Of Computational And Graphical Statistics 1997, 6: 74-91. DOI: 10.1080/10618600.1997.10474728.Peer-Reviewed Original ResearchSemi-parametric modelNonparametric modelLongitudinal dataMultivariate adaptive splinesGeneral time trendExistence of autocorrelationMultivariate adaptive regression splinesRandom-effects linear modelsAdaptive regression splinesAdaptive splinesCovariance estimationDesign matrixRegression splinesFast algorithmTime trendsIterative procedureGeneral algorithmLinear modelSplinesModel buildingMean curveEstimationAlgorithmData structureEssential features