2018
Improving estimation and prediction in linear regression incorporating external information from an established reduced model
Cheng W, Taylor J, Vokonas P, Park S, Mukherjee B. Improving estimation and prediction in linear regression incorporating external information from an established reduced model. Statistics In Medicine 2018, 37: 1515-1530. PMID: 29365342, PMCID: PMC5889759, DOI: 10.1002/sim.7600.Peer-Reviewed Original ResearchConceptsOutcome variable YEfficiency of estimationApproximate Bayesian inferenceBayes solutionVariable YNonlinear constraintsInferential frameworkVariable BE(Y|XImprove inferenceBayesian inferenceEffective computational methodParameter spaceReduced modelImproved estimatesLinear regression modelsTransformation approachStandard errorDunsonInferenceEstimationRegression modelsProblemCovariatesSpace
2015
Data-Adaptive Shrinkage via the Hyperpenalized EM Algorithm
Boonstra P, Taylor J, Mukherjee B. Data-Adaptive Shrinkage via the Hyperpenalized EM Algorithm. Statistics In Biosciences 2015, 7: 417-431. PMID: 26834856, PMCID: PMC4728141, DOI: 10.1007/s12561-015-9132-x.Peer-Reviewed Original Research
2013
Bayesian shrinkage methods for partially observed data with many predictors
Boonstra P, Mukherjee B, Taylor J. Bayesian shrinkage methods for partially observed data with many predictors. The Annals Of Applied Statistics 2013, 7: 2272-2292. PMID: 24436727, PMCID: PMC3891514, DOI: 10.1214/13-aoas668.Peer-Reviewed Original ResearchFraction of missing informationOptimal bias-variance tradeoffBayesian shrinkage methodsEmpirical Bayes algorithmComprehensive simulation studyBias-variance tradeoffSurrogate covariatesSimulation studyShrinkage methodCovariatesPrediction problemState-of-the-artModel parametersProblemMissing dataLung cancer datasetBayes algorithmState-of-the-art technologiesArray technologyCancer datasetsQRT-PCR
2006
A NOTE ON SAMPLING DESIGNS FOR RANDOM PROCESSES WITH NO QUADRATIC MEAN DERIVATIVE
Mukherjee B. A NOTE ON SAMPLING DESIGNS FOR RANDOM PROCESSES WITH NO QUADRATIC MEAN DERIVATIVE. Australian & New Zealand Journal Of Statistics 2006, 48: 305-319. DOI: 10.1111/j.1467-842x.2006.00442.x.Peer-Reviewed Original ResearchDesign Issues for Generalized Linear Models: A Review
Khuri A, Mukherjee B, Sinha B, Ghosh M. Design Issues for Generalized Linear Models: A Review. Statistical Science 2006, 21: 376-399. DOI: 10.1214/088342306000000105.Peer-Reviewed Original Research
2005
Nonparametric Sequential Bayes Estimation of the Distribution Function
Ghosh M, Mukherjee B. Nonparametric Sequential Bayes Estimation of the Distribution Function. Sequential Analysis 2005, 24: 389-409. DOI: 10.1080/07474940500311013.Peer-Reviewed Original ResearchSemiparametric Bayesian Analysis of Matched Case-Control Studies With Missing Exposure
Sinha S, Mukherjee B, Ghosh M, Mallick B, Carroll R. Semiparametric Bayesian Analysis of Matched Case-Control Studies With Missing Exposure. Journal Of The American Statistical Association 2005, 100: 591-601. DOI: 10.1198/016214504000001411.Peer-Reviewed Original Research
2003
Exactly optimal sampling designs for processes with a product covariance structure
Mukherjee B. Exactly optimal sampling designs for processes with a product covariance structure. Canadian Journal Of Statistics 2003, 31: 69-87. DOI: 10.2307/3315904.Peer-Reviewed Original ResearchOn Sampling Designs for Integral Estimation of a Random Process
Mukherjee B. On Sampling Designs for Integral Estimation of a Random Process. Communication In Statistics- Theory And Methods 2003, 32: 1647-1663. DOI: 10.1081/sta-120022249.Peer-Reviewed Original Research