activity
20082022
most citedEfficient estimation in sufficient dimension reduction

93 citations · 124 across the 14 of their papers we have counts for

collaborators

17 papers

stat.ME20221 cited

Testing for high-dimensional white noise

Long Feng, Binghui Liu, Yanyuan Ma

Testing for multi-dimensional white noise is an important subject in statistical inference. Such test in the high-dimensional case becomes an open problem waiting to be solved, esp…

stat.ME2022

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…

stat.ME2021

Semi-supervised Approach to Event Time Annotation Using Longitudinal Electronic Health Records

Liang Liang, Jue Hou, Hajime Uno +3

Large clinical datasets derived from insurance claims and electronic health record (EHR) systems are valuable sources for precision medicine research. These datasets can be used to…

stat.ME20211 cited

Avoid Estimating the Unknown Function in a Semiparametric Nonignorable Propensity Model

Samidha Shetty, Yanyuan Ma, Jiwei Zhao

We study the problem of estimating a functional or a parameter in the context where outcome is subject to nonignorable missingness. We completely avoid modeling the regression rela…

math.ST2021

Efficient computational algorithms for approximate optimal designs

Jiangtao Duan, Wei Gao, Yanyuan Ma +1

In this paper, we propose two simple yet efficient computational algorithms to obtain approximate optimal designs for multi-dimensional linear regression on a large variety of desi…

math.ST2020

Semiparametric regression of mean residual life with censoring and covariate dimension reduction

Ge Zhao, Yanyuan Ma, Huazhen Lin +1

We propose a new class of semiparametric regression models of mean residual life for censored outcome data. The models, which enable us to estimate the expected remaining survival…