matrixGaussianEliminate

 

 

Overview

The matrixGaussianEliminate function triangulates the M by M+1 coefficient matrix representing a system of M simultaneous linear equations in M variables.

The input argument {NumMatrix} must be an M by M+1 number matrix representing the original independent variable observations with the dependent variable in the last column in the form of:

x x x x... y

x x x x... y

....

x x x x... y

The output will be the M by M+1 matrix after triangulation. The triangulated result matrix is now ready for Gaussian substitution.

Usage

The matrixGaussianEliminate function is a non-destructive function useful when you want to create a triangulated Gaussian matrix in preparation for primal form regression. See Sedgewick[2] chap 37.

 

Syntax


Expression:

(matrixGaussianEliminate NumMatrix)


Arguments Name Type Description
Argument:NumMatrixNumMatrix Matrix containing the original independent and dependent observations

Returns:

A new triangulated number Matrix object after Gaussian elimination.



 

Examples

Here are a number of links to Lambda coding examples which contain this instruction in various use cases.

 

Argument Types

Here are the links to the data types of the function arguments.

NumMatrix

Here are also a number of links to functions having arguments with any of these data types.

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