231 citations · 359 across the 14 of their papers we have counts for
15 papers
Flexible semiparametric modeling with application to Causal Inference
Kun Ren, Wen Su, Li Liu +2
This paper proposes a flexible new framework for constructing Neyman-orthogonal scores in semiparametric models involving infinite-dimensional nuisance parameters. While locally es…
Hybrid combinations of parametric and empirical likelihoods
Nils Lid Hjort, Ian W. McKeague, Ingrid Van Keilegom
This paper develops a hybrid likelihood (HL) method based on a compromise between parametric and nonparametric likelihoods. Consider the setting of a parametric model for the distr…
Filtration-Based Learning of Multiscale Shared Structures for Multiple Functional Predictors
Shuhao Jiao, Hernando Ombao, Ian W. McKeague
It is crucial to learn the shared structures among functional predictors, as these structures characterize how predictor components exert common effects and, more generally, how pr…
Coefficient Shape Transfer Learning for Functional Linear Regression
Shuhao Jiao, Ian W. Mckeague
The shapes of functions provide highly interpretable summaries of their trajectories. This article develops a novel transfer learning methodology to tackle the challenge of data sc…
Post-selection inference for high-dimensional mediation analysis with survival outcomes
Tzu-Jung Huang, Zhonghua Liu, Ian W. McKeague
It is of substantial scientific interest to detect mediators that lie in the causal pathway from an exposure to a survival outcome. However, with high-dimensional mediators, as oft…
Efficient Estimation of the Maximal Association between Multiple Predictors and a Survival Outcome
Tzu-Jung Huang, Alex Luedtke, Ian W. McKeague
This paper develops a new approach to post-selection inference for screening high-dimensional predictors of survival outcomes. Post-selection inference for right-censored outcome d…