how to calculate the linear regression of two vectors in matlab

To calculate the linear regression of two vectors in Matlab, there are different functions available, but one of the most common is "regress". Here is an example code:

main.m
% Define the two vectors
x = [1 2 3 4 5];
y = [1.5 3.5 5.5 7.5 9.5];

% Use the "regress" function to calculate the linear regression
X = [ones(length(x),1) x'];
b = regress(y',X);

% Visualize the result
plot(x,y,'o')
hold on
plot(x,X*b,'-')
xlabel('x')
ylabel('y')
title('Linear Regression')
legend('Data','Linear Fit')
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In this example, the vectors "x" and "y" represent the input data, and we want to find the linear function that fits them the best. The "regress" function computes the linear regression coefficients, which are stored in the variable "b". These coefficients define the slope and intercept of the line that best approximates the relationship between x and y. Finally, we plot the original data points and the linear regression line to visualize the result.