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.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.0.0 |
rolling linux/jammy R-4.5 | LSE_1.0.0.tar.gz |
37.0 KiB |
1.0.0 |
rolling linux/noble R-4.5 | LSE_1.0.0.tar.gz |
37.0 KiB |
1.0.0 |
rolling source/ R- | LSE_1.0.0.tar.gz |
5.7 KiB |
1.0.0 |
latest linux/jammy R-4.5 | LSE_1.0.0.tar.gz |
37.0 KiB |
1.0.0 |
latest linux/noble R-4.5 | LSE_1.0.0.tar.gz |
37.0 KiB |
1.0.0 |
latest source/ R- | LSE_1.0.0.tar.gz |
5.7 KiB |
1.0.0 |
2026-04-26 source/ R- | LSE_1.0.0.tar.gz |
5.7 KiB |
1.0.0 |
2026-04-23 source/ R- | LSE_1.0.0.tar.gz |
5.7 KiB |
1.0.0 |
2026-04-09 windows/windows R-4.5 | LSE_1.0.0.zip |
39.6 KiB |
1.0.0 |
2025-04-20 source/ R- | LSE_1.0.0.tar.gz |
5.7 KiB |