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:Sergio Andrés Cabrera Miranda <https://orcid.org/0000-0002-8126-8521>, Juan Gabriel Triana Laverde <https://orcid.org/0000-0003-2991-6082>

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-4.5-any)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

On CRAN:

Conda:

2.70 score 153 downloads 8 exports 2 dependencies

Last updated 3 years agofrom:25b5ca1507. Checks:9 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 17 2025
R-4.5-winOKMar 17 2025
R-4.5-macOKMar 17 2025
R-4.5-linuxOKMar 17 2025
R-4.4-winOKMar 17 2025
R-4.4-macOKMar 17 2025
R-4.4-linuxOKMar 17 2025
R-4.3-winOKMar 17 2025
R-4.3-macOKMar 17 2025

Exports:AntiquaternionDir_EliminationGQRLagrangeLSE_GQRNullspaceQuaternionRQ

Dependencies:MASSpracma