The fastclime package for linear programming and large-scale precision matrix estimation in R

Haotian Pang, Han Liu, Robert Joseph Vanderbei

Research output: Contribution to journalArticle

14 Scopus citations

Abstract

We develop an R package fastclime for solving a family of regularized linear programming (LP) problems. Our package effciently 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 CLIME (Constrained L1 Minimization Estimator). Compared with existing packages for this problem such as clime and flare, our package has three advantages: (1) it effciently 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.

Original languageEnglish (US)
Pages (from-to)489-493
Number of pages5
JournalJournal of Machine Learning Research
Volume15
StatePublished - Jan 1 2014

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Software
  • Statistics and Probability
  • Artificial Intelligence

Fingerprint Dive into the research topics of 'The fastclime package for linear programming and large-scale precision matrix estimation in R'. Together they form a unique fingerprint.

  • Cite this