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sparseHessianFD: An R Package for Estimating Sparse Hessian Matrices
Author(s) -
Michael Braun
Publication year - 2017
Publication title -
journal of statistical software
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 7.636
H-Index - 145
ISSN - 1548-7660
DOI - 10.18637/jss.v082.i10
Subject(s) - hessian matrix , computer science , graph , r package , hessian equation , algorithm , mathematical optimization , mathematics , function (biology) , quasi newton method , substitution (logic) , theoretical computer science , computational science , newton's method , mathematical analysis , evolutionary biology , first order partial differential equation , partial differential equation , biology , physics , nonlinear system , quantum mechanics , programming language
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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