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