626 citations · 1.4k across the 31 of their papers we have counts for
31 papers
Ensemble minimaxity of James-Stein estimators
Yuzo Maruyama, Lawrence D. Brown, Edward I. George
This article discusses estimation of a multivariate normal mean based on heteroscedastic observations. Under heteroscedasticity, estimators shrinking more on the coordinates with l…
All of Linear Regression
Arun K. Kuchibhotla, Lawrence D. Brown, Andreas Buja +1
Least squares linear regression is one of the oldest and widely used data analysis tools. Although the theoretical analysis of the ordinary least squares (OLS) estimator is as old,…
Model-free Study of Ordinary Least Squares Linear Regression
Arun K. Kuchibhotla, Lawrence D. Brown, Andreas Buja
Ordinary least squares (OLS) linear regression is one of the most basic statistical techniques for data analysis. In the main stream literature and the statistical education, the s…
Assumption Lean Regression
Richard A. Berk, Andreas Buja, Lawrence Brown +4
It is well known that models used in conventional regression analysis are commonly misspecified. A standard response is little more than a shrug. Data analysts invoke Box's maxim t…
Valid Post-selection Inference in Assumption-lean Linear Regression
Arun Kumar Kuchibhotla, Lawrence D. Brown, Andreas Buja +2
Construction of valid statistical inference for estimators based on data-driven selection has received a lot of attention in the recent times. Berk et al. (2013) is possibly the fi…
Uniform-in-Submodel Bounds for Linear Regression in a Model Free Framework
Arun Kumar Kuchibhotla, Lawrence D. Brown, Andreas Buja +2
For the last two decades, high-dimensional data and methods have proliferated throughout the literature. Yet, the classical technique of linear regression has not lost its usefulne…