Learn how to code matrix algebra operations in R with the main C++ matrix algebra libraries: RcppArmadillo and RcppEigen.

Become an R Developer

This module aims to teach us how to code matrix algebra operations in R and with the main C++ matrix algebra libraries: RcppArmadillo and RcppEigen. Moreover, to clarify the matrix algebra operations, we’ll go through a simple algorithm to understand the computing implications. By the end of this module, we’ll have hands-on experience in performing matrix algebra computation in the R and Rcpp ecosystem, and the ability to develop algorithms for areas such as machine learning, image processing, and signal processing.

Computing Matrix Algebra with R and Rcpp

## Exercise

A **symmetrical matrix** in linear algebra is defined as a square matrix equal to its transposed matrix. For example:

$$ A = A^T $$

> **Note:** A square matrix $A$ of size $(n \times n)$ is considered to be symmetric if and only if $A^T = A$.

Your challenge is to complete the function so that it can determine whether the matrices are symmetrical or not. Use the code editor below to implement your solution.

# Exercise

A **symmetrical matrix** in linear algebra is defined as a square matrix equal to its transposed matrix. For example:

$$ A = A^T $$

> **Note:** A square matrix $A$ of size $(n \times n)$ is considered to be symmetric if and only if $A^T = A$.

Your challenge is to complete the function so that it can determine whether the matrices are symmetrical or not. Use the code editor below to implement your solution.

Solve this challenge on matrix transposition in R.

Introduction

Assignment Operator

Addition of Matrices

Scalar Multiplication of Matrices

Multiplication of Matrices

Transposition of Matrices

Determinant of a Matrix

Inverse of a Matrix

System of Linear Equations

Conclusion

Challenge: Matrix Transposition

Exercise