Published by the Foundation for Open Access Statistics Editors-in-chief: Bettina Grün, Torsten Hothorn, Rebecca Killick, Edzer Pebesma, Achim Zeileis    ISSN 1548-7660; CODEN JSSOBK
Authors: Michael Braun
Title: sparseHessianFD: An R Package for Estimating Sparse Hessian Matrices
Abstract: Sparse Hessian matrices occur often in statistics, and their fast and accurate estimation can improve efficiency of numerical optimization and sampling algorithms. By exploiting the known sparsity pattern of a Hessian, methods in the sparseHessianFD package require many fewer function or gradient evaluations than would be required if the Hessian were treated as dense. The package implements established graph coloring and linear substitution algorithms that were previously unavailable to R users, and is most useful when other numerical, symbolic or algorithmic methods are impractical, inefficient or unavailable.

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Paper: sparseHessianFD: An R Package for Estimating Sparse Hessian Matrices     Download PDF (Downloads: 1221)
sparseHessianFD_0.3.3.2.tar.gz: R source package Download (Downloads: 76; 547KB) Replication materials Download (Downloads: 54; 3KB)

DOI: 10.18637/jss.v082.i10

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Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license.