The fastclime Package for Linear Programming and Large-Scale Precision Matrix Estimation in R.

Pang, Haotian; Liu, Han; Vanderbei, Robert · J Mach Learn Res · 2014

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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 called <i>CLIME</i> (Constrained <i>L</i><sub>1</sub> Minimization 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.