4 papers
Efficient Inference under Label Shift in Unsupervised Domain Adaptation
Seong-ho Lee, Yanyuan Ma, Jiwei Zhao
In many real-world applications, researchers aim to deploy models trained in a source domain to a target domain, where obtaining labeled data is often expensive, time-consuming, or…
Robust and efficient estimation in the presence of a randomly censored covariate
Seong-ho Lee, Brian D. Richardson, Yanyuan Ma +2
In Huntington's disease research, a current goal is to understand how symptoms change prior to a clinical diagnosis. Statistically, this entails modeling symptom severity as a func…
Doubly Flexible Estimation under Label Shift
Seong-ho Lee, Yanyuan Ma, Jiwei Zhao
In studies ranging from clinical medicine to policy research, complete data are usually available from a population , but the quantity of interest is often sought for…
Semiparametric Approach to Estimation of Marginal and Quantile Effects
Seong-ho Lee, Yanyuan Ma, Elvezio Ronchetti
We consider a semiparametric generalized linear model and study estimation of both marginal and quantile effects in this model. We propose an approximate maximum likelihood estimat…