144 citations · 418 across the 15 of their papers we have counts for
16 papers
Fundamentals of path analysis in the social sciences
R. Dennis Cook, Liliana Forzani
Motivated by a recent series of diametrically opposed articles on the relative value of statistical methods for the analysis of path diagrams in the social sciences, we discuss fro…
Enveloped Huber Regression
Le Zhou, R. Dennis Cook, Hui Zou
Huber regression (HR) is a popular robust alternative to the least squares regression when the error follows a heavy-tailed distribution. We propose a new method called the envelop…
A convex formulation for high-dimensional sparse sliced inverse regression
Kean Ming Tan, Zhaoran Wang, Tong Zhang +2
Sliced inverse regression is a popular tool for sufficient dimension reduction, which replaces covariates with a minimal set of their linear combinations without loss of informatio…
Inverse regression for ridge recovery II: Numerics
Andrew Glaws, Paul G. Constantine, R. Dennis Cook
We investigate the application of sufficient dimension reduction (SDR) to a noiseless data set derived from a deterministic function of several variables. In this context, SDR prov…
Multivariate Design of Experiments for Engineering Dimensional Analysis
Daniel J. Eck, Christopher J. Nachtsheim, R. Dennis Cook +1
We consider the design of dimensional analysis experiments when there is more than a single response. We first give a brief overview of dimensional analysis experiments and the dim…
Inverse regression for ridge recovery: A data-driven approach for parameter reduction in computer experiments
Andrew T. Glaws, Paul G. Constantine, R. Dennis Cook
Parameter reduction can enable otherwise infeasible design and uncertainty studies with modern computational science models that contain several input parameters. In statistical re…