Doctoral Students' Published Research

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Liu H and Rao JS (2017. Prediction Weighted Maximum Frequency Selection. Electronic Journal of Statistics, 11: 640-681.


Rao JS and Liu H (2017). Discordancy Partitioning for Validating Potentially Inconsistent Pharmacogenomic Studies www.nature.com, 7: 15169.


Papamichail D, Liu H, Machado V, Gould N, Coleman JR, and Papamichail G (2018). Codon Context Optimization in Synthetic Gene Design. IEEE/ACM Trans Comput Biol Bioinform, 15(2): 452-459.


Jiang J, Rao JS, Fan J and Nguyen T (2016. Classified Mixed Model Prediction. Journal of the American Statistical Association, DOI: 10.1080/01621459.2016.1246367.


Ishwaran H and Lu M (2018). Standard Errors and Confidence Intervals for Variable Importance in Random Forest Regression, Classification and Survival. Statistics in Medicine, DOI: 10.1002/sim.7803.


Tang F and Ishwaran H (2017). Random Forest Missing Data Algorithms. Stat Anal Data Min: The ASA Data Sci Journal, 10: 363-377.


Lu M, Sadiq S, Feaster D and Ishwaran H (2018). Estimating Individual Treatment Effect in Observational Data Using Random Forest Methods. J Comput Graph Stat, 27(1): 209-219.


Lu M and Ishwaran H (2018). A Prediction-Based Alternative to P Values in Regression Models. J Thorac Cardiovasc Surg, 155(3): 1130-1136.


Pande A, Li L, Rajeswaran J, Ehrlinger J, Kogalur UB, Blackstone E, and Ishwaran H (2017). Boosted Multivariate Trees for Longitudinal Data. Mach Learn, 106(2): 277-305.