how to calculate the moving variance of a vector in matlab

To calculate the moving variance of a vector in MATLAB, you can use the built-in function "filter" and "var".

Here's an example code:

main.m
% create a sample vector
x = randn(1,100);

% set the window size
win_size = 10;

% calculate the moving variance using filter and var
mvar = filter(ones(1,win_size)/win_size,1,x.^2) - (filter(ones(1,win_size)/win_size,1,x).^2);
mvar = mvar(win_size:end);

% plot the original vector and its moving variance
subplot(2,1,1)
plot(x)
title('Original Vector')
subplot(2,1,2)
plot(mvar)
title('Moving Variance')
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In this code, we first create a sample vector "x" with 100 random numbers. Then, we set the window size "win_size" to be 10. This means we want to calculate the moving variance with a window size of 10.

We then use the "filter" function to calculate the moving variance. The first "filter" calculates the sum of squares of the elements in each window of size "win_size". The second "filter" calculates the mean of the elements in each window of size "win_size". Finally, we subtract the square of the mean from the sum of squares to obtain the variance.

Note that we need to remove the first "win_size-1" elements from the output of "mvar" because the variance cannot be calculated for the first "win_size-1" elements.

We then plot the original vector and its moving variance using the "subplot" function to compare the two.