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LSE  

Constrained Least Squares and Generalized QR Factorization
View on CRAN: Click here


Download and install LSE package within the R console
Install from CRAN:
install.packages("LSE")

Install from Github:
library("remotes")
install_github("cran/LSE")

Install by package version:
library("remotes")
install_version("LSE", "1.0.0")



Attach the package and use:
library("LSE")
Maintained by
Sergio Andrés Cabrera Miranda
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-02-02
Latest Update: 2022-02-02
Description:
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.
How to cite:
Sergio Andrés Cabrera Miranda (2022). LSE: Constrained Least Squares and Generalized QR Factorization. R package version 1.0.0, https://cran.r-project.org/web/packages/LSE. Accessed 06 Nov. 2024.
Previous versions and publish date:
No previous versions
Other packages that cited LSE R package
View LSE citation profile
Other R packages that LSE depends, imports, suggests or enhances
Complete documentation for LSE
Functions, R codes and Examples using the LSE R package
Some associated functions: Antiquaternion . Dir_Elimination . GQR . LSE . LSE_GQR . Lagrange . Nullspace . Quaternion . RQ . 
Some associated R codes: Antiquaternion.R . Dir_Elimination.R . GQR.R . LSE.R . LSE_GQR.R . Lagrange.R . Nullspace.R . Quaternion.R . RQ.R .  Full LSE package functions and examples
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