Package: LSE 1.0.0
LSE: Constrained Least Squares and Generalized QR Factorization
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.
Authors:
LSE_1.0.0.tar.gz
LSE_1.0.0.zip(r-4.5)LSE_1.0.0.zip(r-4.4)LSE_1.0.0.zip(r-4.3)
LSE_1.0.0.tgz(r-4.4-any)LSE_1.0.0.tgz(r-4.3-any)
LSE_1.0.0.tar.gz(r-4.5-noble)LSE_1.0.0.tar.gz(r-4.4-noble)
LSE_1.0.0.tgz(r-4.4-emscripten)LSE_1.0.0.tgz(r-4.3-emscripten)
LSE.pdf |LSE.html✨
LSE/json (API)
| # Install 'LSE' in R: |
| install.packages('LSE', repos = c('https://sergio05acm.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/sergio05acm/lse/issues
Last updated 3 years agofrom:25b5ca1507. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 17 2024 |
| R-4.5-win | OK | Nov 17 2024 |
| R-4.5-linux | OK | Nov 17 2024 |
| R-4.4-win | OK | Nov 17 2024 |
| R-4.4-mac | OK | Nov 17 2024 |
| R-4.3-win | OK | Nov 17 2024 |
| R-4.3-mac | OK | Nov 17 2024 |
Exports:AntiquaternionDir_EliminationGQRLagrangeLSE_GQRNullspaceQuaternionRQ
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Antiquaternion | Antiquaternion |
| Direct Elimination for LSE problem. | Dir_Elimination |
| Generalized QR Factorization | GQR |
| Lagrange multipliers for LSE problem. | Lagrange |
| LSE package | LSE |
| LSE and GQR Factorization | LSE_GQR |
| Nullspace method for LSE problem. | Nullspace |
| Quaternion transformation | Quaternion |
| RQ Factorization of a matrix | RQ |
