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20182020
most citedEstimation, Confidence Intervals, and Large-Scale Hypotheses Testing for High-Dimensional Mixed Linear Regression

7 citations · 12 across the 2 of their papers we have counts for

collaborators

6 papers

stat.ME20207 cited

Estimation, Confidence Intervals, and Large-Scale Hypotheses Testing for High-Dimensional Mixed Linear Regression

Linjun Zhang, Rong Ma, T. Tony Cai +1

This paper studies the high-dimensional mixed linear regression (MLR) where the output variable comes from one of the two linear regression models with an unknown mixing proportion…

stat.ME20205 cited

The Asymptotic Distribution of Modularity in Weighted Signed Networks

Rong Ma, Ian Barnett

Modularity is a popular metric for quantifying the degree of community structure within a network. The distribution of the largest eigenvalue of a network's edge weight or adjacenc…

math.ST2020

Optimal Structured Principal Subspace Estimation: Metric Entropy and Minimax Rates

T. Tony Cai, Hongzhe Li, Rong Ma

Driven by a wide range of applications, many principal subspace estimation problems have been studied individually under different structural constraints. This paper presents a uni…

math.ST2019

Optimal Estimation of Bacterial Growth Rates Based on Permuted Monotone Matrix

Rong Ma, T. Tony Cai, Hongzhe Li

Motivated by the problem of estimating the bacterial growth rates for genome assemblies from shotgun metagenomic data, we consider the permuted monotone matrix model , wher…

math.ST2019

Optimal Permutation Recovery in Permuted Monotone Matrix Model

Rong Ma, T. Tony Cai, Hongzhe Li

Motivated by recent research on quantifying bacterial growth dynamics based on genome assemblies, we consider a permuted monotone matrix model , where the rows represent di…

stat.ME2018

Global and Simultaneous Hypothesis Testing for High-Dimensional Logistic Regression Models

Rong Ma, T. Tony Cai, Hongzhe Li

High-dimensional logistic regression is widely used in analyzing data with binary outcomes. In this paper, global testing and large-scale multiple testing for the regression coeffi…