@article{b24b4935496142bcadf4825f8bffa4fb,
title = "Partial factor modeling: Predictor-dependent shrinkage for linear regression",
abstract = "We develop a modified Gaussian factor model for the purpose of inducing predictor-dependent shrinkage for linear regression. The new model predicts well across a wide range of covariance structures, on real and simulated data. Furthermore, the new model facilitates variable selection in the case of correlated predictor variables, which often stymies other methods.",
keywords = "Prediction, Shrinkage estimators, Variable selection, g Prior",
author = "{Richard Hahn}, P. and Carvalho, {Carlos M.} and Sayan Mukherjee",
note = "Funding Information: P. Richard Hahn is Assistant Professor of Econometrics and Statistics, Booth School of Business, University of Chicago, Chicago, IL 60637 (E-mail: richard.hahn@chicagobooth.edu). Carlos M. Carvalho is Associate Professor of Statistics, McCombs School of Business, The University of Texas, Austin, TX 78712 (E-mail: carlos.carvalho@mccombs.utexas.edu). Sayan Mukherjee is Associate Professor of Statistics, Departments of Statistical Science, Computer Science, Mathematics, and Institute for Genome Sciences Policy, Duke University, Durham, NC 27708 (E-mail: sayan@stat.duke.edu). P. Richard Hahn thanks Dan Merl for helpful discussions. Carlos M. Carvalho thanks the McCombs School of Business Research Excellence Grant. Sayan Mukher-jee acknowledges AFOSR FA9550-10-1-0436, NSF DMS-1045153, and NSF CCF-1049290 for partial support. Sayan Mukherjee acknowledges Mike West, Anirban Bhattacharya, and David Dunson for useful comments. The authors thank the referees for helpful suggestions.",
year = "2013",
doi = "10.1080/01621459.2013.779843",
language = "English (US)",
volume = "108",
pages = "999--1008",
journal = "Journal of the American Statistical Association",
issn = "0162-1459",
publisher = "Taylor and Francis Ltd.",
number = "503",
}