2017
Graphical model selection with latent variables
Wu C, Zhao H, Fang H, Deng M. Graphical model selection with latent variables. Electronic Journal Of Statistics 2017, 11: 3485-3521. DOI: 10.1214/17-ejs1331.Peer-Reviewed Original ResearchGraphical model selectionModel selection consistencyEfficient ADMM algorithmSparse precision matrixGraphical modelsGaussian graphical modelsGenetical genomics dataSelection consistencyPenalized estimationStatistical inferencePrecision matrixLatent variablesParameter estimationTheoretical propertiesIdentifiability conditionsADMM algorithmModel selectionSimulation studyConditional dependenceEstimationTrace lossSuperior performanceEstimatorGraphVariables
2013
Application of Bayesian Sparse Factor Analysis Models in Bioinformatics
Ma H, Zhao H. Application of Bayesian Sparse Factor Analysis Models in Bioinformatics. 2013, 350-365. DOI: 10.1017/cbo9781139226448.018.Peer-Reviewed Original ResearchFactor analysis modelClassical factor analysis modelLatent variable modelStatistical methodsInferential methodsVariable modelComputational biologyLarge data setsGeometrical procedureObserved variablesCorrelated variablesAnalysis modelGeneral approachLatent variablesFactor modelingLatent factorsStrong prior beliefsUnderlying structureData setsPrincipal component analysisModelVariablesRegulatory networksLarge numberPrior beliefs