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-4.7-any)LSE_1.0.0.zip(r-4.6-any)LSE_1.0.0.zip(r-4.5-any)
LSE_1.0.0.tgz(r-4.6-any)LSE_1.0.0.tgz(r-4.5-any)
LSE_1.0.0.tar.gz(r-4.7-any)LSE_1.0.0.tar.gz(r-4.6-any)
LSE_1.0.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
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 1 stars 237 downloads 8 exports 2 dependencies

Last updated from:25b5ca1507. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK90
source / vignettesOK125
linux-releaseOK108
macos-releaseOK111
macos-oldrelOK162
windows-develOK69
windows-releaseOK87
windows-oldrelOK64
wasm-releaseOK69

Exports:AntiquaternionDir_EliminationGQRLagrangeLSE_GQRNullspaceQuaternionRQ

Dependencies:MASSpracma