title: The fastclime Package for Linear Programming and Large-Scale Precision Matrix Estimation in R.
abstract: We develop an R package fastclime for solving a family of regularized linear programming (LP) problems. Our package efficiently implements the parametric simplex algorithm, which provides a scalable and sophisticated tool for solving large-scale linear programs. As an illustrative example, one use of our LP solver is to implement an important sparse precision matrix estimation method calledCLIME(ConstrainedL1Minimization Estimator). Compared with existing packages for this problem such as clime and flare, our package has three advantages: (1) it efficiently calculates the full piecewise-linear regularization path; (2) it provides an accurate dual certificate as stopping criterion; (3) it is completely coded in C and is highly portable. This package is designed to be useful to statisticians and machine learning researchers for solving a wide range of problems.
authors.affiliation: Department of Electrical Engineering, Princeton University, Olden St Princeton, NJ 08540, USA.
authors.forename: Haotian
authors.initials: H
authors.lastname: Pang
authors.forename: Han
authors.initials: H
authors.lastname: Liu
authors.affiliation: Department of Operations Research and Financial Engineering Princeton University, 98 Charlton St Princeton, NJ 08540, USA.
authors.forename: Robert
authors.initials: R
authors.lastname: Vanderbei
keywords: high dimensional data; linear programming; parametric simplex method; sparse precision matrix; undirected graphical model