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The solution of equality constrained least squares problem (LSE) is given through four analytics methods (Generalized QR Factorization, Lagrange Multipliers, Direct Elimination and Null Space method). We expose the orthogonal decomposition called Generalized QR Factorization (GQR) and also RQ factorization. Finally some codes for the solution of LSE applied in quaternions.
| Version: | 1.0.0 |
| Imports: | MASS, pracma |
| Published: | 2022-02-02 |
| Author: | Sergio Andrés Cabrera Miranda <https://orcid.org/0000-0002-8126-8521>, Juan Gabriel Triana Laverde <https://orcid.org/0000-0003-2991-6082> |
| Maintainer: | Sergio Andrés Cabrera Miranda <sergio05acm at gmail.com> |
| License: | GPL-3 |
| URL: | https://github.com/sergio05acm/LSE |
| NeedsCompilation: | no |
| CRAN checks: | LSE results |
| Reference manual: | LSE.pdf |
| Package source: | LSE_1.0.0.tar.gz |
| Windows binaries: | r-devel: LSE_1.0.0.zip, r-release: LSE_1.0.0.zip, r-oldrel: LSE_1.0.0.zip |
| macOS binaries: | r-release (arm64): LSE_1.0.0.tgz, r-oldrel (arm64): LSE_1.0.0.tgz, r-release (x86_64): LSE_1.0.0.tgz, r-oldrel (x86_64): LSE_1.0.0.tgz |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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