Interface to the 'sparseLM' Levenberg-Marquardt Library

Provides an R interface to the 'sparseLM' C library for large-scale nonlinear least squares problems with arbitrarily sparse Jacobians. The underlying solver implements a sparse variant of the Levenberg-Marquardt algorithm for minimizing sum-of-squares objective functions, supports user-supplied analytic Jacobians or finite-difference approximation, and is designed to exploit sparsity for improved memory use and performance. This package exposes the solver in R and uses sparse matrix classes and the 'CHOLMOD' sparse Cholesky factorization routines through the 'Matrix' package interface. Methods from the C library are described in Lourakis (2010) .

sparseLM R Package

sparseLM provides an R interface to the sparseLM library for solving nonlinear least squares problems with sparse Jacobians. The package wraps the underlying C solver and uses CHOLMOD through the Matrix package interface, exposing the results through an R-friendly fitting interface.

The underlying sparseLM algorithms and C library were created by Manolis Lourakis. The R package interface was created by Colin Smith.

Documentation

Package documentation is available at:

https://smith-group.github.io/sparseLM/

Upstream project

The original sparseLM project page is:

https://users.ics.forth.gr/~lourakis/sparseLM/

Package scope

This package is focused on bringing sparseLM into R with:

• a wrapper for sparse Levenberg-Marquardt fitting
• support for user-supplied sparse Jacobians via Matrix classes

Citation

If you use sparseLM, please cite the original sparseLM publication:

Lourakis, M. I. A. (2010). Sparse Non-linear Least Squares Optimization for Geometric Vision. In Computer Vision - ECCV 2010, Lecture Notes in Computer Science 6312, 43-56. Springer. https://doi.org/10.1007/978-3-642-15552-9_4