626 citations · 759 across the 13 of their papers we have counts for
14 papers
Network regression and supervised centrality estimation
Junhui Cai, Dan Yang, Ran Chen +3
The centrality in a network is often used to measure nodes' importance and model network effects on a certain outcome. Empirical studies widely adopt a two-stage procedure, which f…
Nonparametric Empirical Bayes Estimation and Testing for Sparse and Heteroscedastic Signals
Junhui Cai, Xu Han, Ya'acov Ritov +1
Large-scale modern data often involves estimation and testing for high-dimensional unknown parameters. It is desirable to identify the sparse signals, ``the needles in the haystack…
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…
Models as Approximations II: A Model-Free Theory of Parametric Regression
Andreas Buja, Lawrence Brown, Arun Kumar Kuchibhotla +3
We develop a model-free theory of general types of parametric regression for iid observations. The theory replaces the parameters of parametric models with statistical functionals,…
Semi-Supervised linear regression
David Azriel, Lawrence D. Brown, Michael Sklar +3
We study a regression problem where for some part of the data we observe both the label variable () and the predictors (), while for other part of the data only the pre…
Uniform Correlation Mixture of Bivariate Normal Distributions and Hypercubically-contoured Densities That Are Marginally Normal
Kai Zhang, Lawrence D. Brown, Edward George +1
The bivariate normal density with unit variance and correlation is well-known. We show that by integrating out , the result is a function of the maximum norm. The Bayesian i…
Calibrated Percentile Double Bootstrap For Robust Linear Regression Inference
Daniel McCarthy, Kai Zhang, Lawrence Brown +4
We consider inference for the parameters of a linear model when the covariates are random and the relationship between response and covariates is possibly non-linear. Conventional…
Models as Approximations I: Consequences Illustrated with Linear Regression
Andreas Buja, Richard Berk, Lawrence Brown +5
In the early 1980s Halbert White inaugurated a "model-robust'' form of statistical inference based on the "sandwich estimator'' of standard error. This estimator is known to be "he…
Improved Precision in Estimating Average Treatment Effects
Emil Pitkin, Richard Berk, Lawrence Brown +4
The Average Treatment Effect (ATE) is a global measure of the effectiveness of an experimental treatment intervention. Classical methods of its estimation either ignore relevant co…
Valid post-selection inference
Richard Berk, Lawrence Brown, Andreas Buja +2
It is common practice in statistical data analysis to perform data-driven variable selection and derive statistical inference from the resulting model. Such inference enjoys none o…
A Geometrical Explanation of Stein Shrinkage
Lawrence D. Brown, Linda H. Zhao
Shrinkage estimation has become a basic tool in the analysis of high-dimensional data. Historically and conceptually a key development toward this was the discovery of the inadmiss…
An autoregressive approach to house price modeling
Chaitra H. Nagaraja, Lawrence D. Brown, Linda H. Zhao
A statistical model for predicting individual house prices and constructing a house price index is proposed utilizing information regarding sale price, time of sale and location (Z…