C = cov(A)
- It returns the covariance of array A.
- If A is a scalar, then it returns 0.
- If A is a vector, then it returns the variance of vector A.
- If A is a matrix, then it considers each column as a random variable and returns the covariance matrix of matrix A.
Note: disp (x) displays the value of variable X without printing the variable name. Another way to display a variable is to type its name, which displays a leading “X =” before the value. If a variable contains an empty array, disp returns without displaying anything.
Example 1:
Matlab
% Input vectorA = [1 3 4];disp("Vector :");disp(A);% Variance of vector AC = cov(A);disp("Variance :");disp(C); |
Output :
Example 2:
Matlab
% Input vectorA = [2 7 1; 3 5 1 4 1 2];disp("Matrix :");disp(A);% Covariance of matrix AC = cov(A);disp("Covariance matrix :");disp(C); |
Output :
How to Calculate Covariance in MATLAB
Covariance is the measure of the strength of correlation between two or more random variables. Covariance of two random variables X and Y can be defined as:
Where E(X) and E(Y) are expectation or mean of random variables X and Y respectively.
The covariance matrix of two random variables A and B is defined as
MATLAB language allows users to calculate the covariance of random variables using cov() method. Different syntax of cov() method are:
- C = cov(A)
- C = cov(A,B)
- C = cov(___,w)
- C = cov(___,nanflag)