From df24c3f71f4c57d31c937a005431661dd1ac4e30 Mon Sep 17 00:00:00 2001
From: Christopher Lux <59606965+LibraChris@users.noreply.github.com>
Date: Tue, 22 Oct 2024 11:08:02 +0200
Subject: [PATCH] Updated XML documentation
Updated XML documentation for qrAlternative and solveLinearQR
---
src/FSharp.Stats/Algebra/LinearAlgebra.fs | 33 ++++++++++++++++-------
1 file changed, 24 insertions(+), 9 deletions(-)
diff --git a/src/FSharp.Stats/Algebra/LinearAlgebra.fs b/src/FSharp.Stats/Algebra/LinearAlgebra.fs
index 8825450c..28e25f07 100644
--- a/src/FSharp.Stats/Algebra/LinearAlgebra.fs
+++ b/src/FSharp.Stats/Algebra/LinearAlgebra.fs
@@ -219,8 +219,20 @@ module LinearAlgebra =
// else LinearAlgebraManaged.QR a
LinearAlgebraManaged.QR a
+ ///
/// Performs QR decomposition using an alternative algorithm.
- /// Returns the orthogonal matrix Q and the upper triangular matrix R.
+ /// QR decomposition is a method to decompose a matrix A into two components:
+ /// Q (an orthogonal matrix) and R (an upper triangular matrix),
+ /// such that A = Q * R. It is commonly used in solving linear systems,
+ /// least squares fitting, and eigenvalue problems.
+ ///
+ ///
+ /// A tuple containing:
+ ///
+ /// - Q: The orthogonal matrix obtained from the decomposition.
+ /// - R: The upper triangular matrix obtained from the decomposition.
+ ///
+ ///
let qrAlternative (A: Matrix) =
let m: int = A.NumRows
let n: int = A.NumCols
@@ -266,15 +278,18 @@ module LinearAlgebra =
q, r
+ ///
/// Solves a linear system of equations using QR decomposition.
- ///
- /// Parameters:
- /// - A: The coefficient matrix of the linear system.
- /// - t: The target vector of the linear system.
- ///
- /// Returns:
- /// - mX: The solution vector of the linear system.
- /// - r: The upper triangular matrix obtained from QR decomposition.
+ ///
+ /// The coefficient matrix of the linear system.
+ /// The target vector of the linear system.
+ ///
+ /// A tuple containing:
+ ///
+ /// - mX: The solution vector of the linear system.
+ /// - r: The upper triangular matrix obtained from QR decomposition.
+ ///
+ ///
let solveLinearQR (A: Matrix) (t: Vector) =
let m = A.NumRows
let n = A.NumCols