allan.m

function [T,sigma] = allan(omega,fs,pts)
[N,M] = size(omega);             % figure out how big the output data set is
n = 2.^(0:floor(log2(N/2)))';    % determine largest bin size
maxN = n(end);
endLogInc = log10(maxN);
m = unique(ceil(logspace(0,endLogInc,pts)))';    % create log spaced vector average factor
t0 = 1/fs;                                       % t0 = sample interval
T = m*t0;                                        % T = length of time for each cluster
theta = cumsum(omega)/fs;       % integration of samples over time to obtain output angle ¦È
sigma2 = zeros(length(T),M);    % array of dimensions (cluster periods) X (#variables)
for i=1:length(m)               % loop over the various cluster sizes
    for k=1:N-2*m(i)            % implements the summation in the AV equation
        sigma2(i,:) = sigma2(i,:) + (theta(k+2*m(i),:) - 2*theta(k+m(i),:) + theta(k,:)).^2;
    end
end
sigma2 = sigma2./repmat((2*T.^2.*(N-2*m)),1,M);
sigma = sqrt(sigma2);