Module 6 – Linear Algebra in R (Part 2)
# 1. Matrix Addition & Subtraction
A <- matrix(c(2, 0, 1, 3), ncol = 2)
B <- matrix(c(5, 2, 4, -1), ncol = 2)
# Addition
A_plus_B <- A + B
A_plus_B
# Subtraction
A_minus_B <- A - B
A_minus_B
Explanation : Matrix addition and subtraction work element-by-element on matrices of the same size, combining or contrasting values at the same positions. This is useful for quickly aggregating or comparing structured numeric data
# 2.Create a Diagonal Matrix
D <- diag(c(4, 1, 2, 3))
D
Explanation : diag() places the supplied numbers along the main diagonal and fills all other entries with zeros. Diagonal matrices are commonly used for identity/scaling operations and as building blocks in linear algebra.
# 3.Construct a Custom 5 × 5 Matrix
M <- diag(3, 5, 5)
M[1, 2:5] <- 1
M[2:5, 1] <- 2
M
Explanation : started with a diagonal of 3’s and then used indexing to set the first row (except the diagonal) to 1 and the first column (below the diagonal) to 2. This shows how to programmatically target and modify specific matrix positions to create a structured pattern.
OUTPUT
> # Matrix Addition & Subtraction > A <- matrix(c(2, 0, 1, 3), ncol = 2) > B <- matrix(c(5, 2, 4, -1), ncol = 2) > # Addition > A_plus_B <- A + B > A_plus_B [,1] [,2] [1,] 7 5 [2,] 2 2 > # Subtraction > A_minus_B <- A - B > A_minus_B [,1] [,2] [1,] -3 -3 [2,] -2 4 > # Create a Diagonal Matrix > D <- diag(c(4, 1, 2, 3)) > D [,1] [,2] [,3] [,4] [1,] 4 0 0 0 [2,] 0 1 0 0 [3,] 0 0 2 0 [4,] 0 0 0 3 > # Construct a Custom 5 × 5 Matrix > M <- diag(3, 5, 5) > M[1, 2:5] <- 1 > M[2:5, 1] <- 2 > M [,1] [,2] [,3] [,4] [,5] [1,] 3 1 1 1 1 [2,] 2 3 0 0 0 [3,] 2 0 3 0 0 [4,] 2 0 0 3 0 [5,] 2 0 0 0 3
Comments
Post a Comment