2025
Probabilistic exponential family inverse regression and its applications
Pang D, Zhu R, Zhao H, Wang T. Probabilistic exponential family inverse regression and its applications. Biometrics 2025, 81: ujaf065. PMID: 40407023, DOI: 10.1093/biomtc/ujaf065.Peer-Reviewed Original ResearchConceptsExponential familyDouble exponential familyHigh-dimensional regressionLow-dimensional reductionHierarchical likelihoodData exampleInverse regressionDiscrete predictorsSimulation studyDiscrete dataHigh-dimensional dataParallelizable algorithmContinuous predictorsPresence–absence recordsDimension reductionResponse variablesAccumulation of high dimensional dataHigh-throughput sequencing technologyFactor model frameworkLatent factorsRecords of speciesSequence readsSingle-cell studiesSequencing technologiesCommunity ecology
2023
Factor Augmented Inverse Regression and its Application to Microbiome Data Analysis
Pang D, Zhao H, Wang T. Factor Augmented Inverse Regression and its Application to Microbiome Data Analysis. Journal Of The American Statistical Association 2023, 119: 1957-1967. DOI: 10.1080/01621459.2023.2231577.Peer-Reviewed Original ResearchInverse regressionCount vectorsLow-dimensional summariesAsymptotic propertiesVariational expectation-maximization algorithmExpectation-maximization algorithmGroup lassoVariational approximationApproximate inferenceSupplementary materialsCount dataModel selectionInformation criterionAbundance of featuresVectorPrediction of host phenotypeOverdispersionLatent factorsApproximation
2019
Prediction Analysis for Microbiome Sequencing Data
Wang T, Yang C, Zhao H. Prediction Analysis for Microbiome Sequencing Data. Biometrics 2019, 75: 875-884. PMID: 30994187, DOI: 10.1111/biom.13061.Peer-Reviewed Original ResearchConceptsMonte Carlo expectation-maximization algorithmInverse regression modelReal data exampleTypes of covariatesNew statistical frameworkMaximum likelihood estimationExpectation-maximization algorithmDimension reduction structureInverse regressionStatistical frameworkData examplesStatistical challengesLikelihood estimationMicrobiome sequencing dataHuman microbiome studiesHuman microbiome compositionDifferent library sizesZerosPredictive analysisModelEstimationAlgorithmSimulationsRegression modelsFramework
2016
Estimating a sparse reduction for general regression in high dimensions
Wang T, Chen M, Zhao H, Zhu L. Estimating a sparse reduction for general regression in high dimensions. Statistics And Computing 2016, 28: 33-46. DOI: 10.1007/s11222-016-9714-6.Peer-Reviewed Original Research
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