Abstract
SparseM provides some basic R functionality for linear algebra with sparse matrices. Use of the package is illustrated by a family of linear model fitting functions that implement least squares methods for problems with sparse design matrices. Significant performance improvements in memory utilization and computational speed are possible for applications involving large sparse matrices.
Original language | English (US) |
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Pages (from-to) | 1-9 |
Number of pages | 9 |
Journal | Journal of Statistical Software |
Volume | 8 |
DOIs | |
State | Published - 2003 |
ASJC Scopus subject areas
- Software
- Statistics and Probability
- Statistics, Probability and Uncertainty