MICRO Motion capture data from groups of participants standing still to auditory stimuli (2012) 1.0
function [D,Alpha1]=DFA_main(DATA)
% DATA should be a time series of length(DATA) greater than 2000,and of column vector.
%A is the alpha in the paper
%D is the dimension of the time series
%n can be changed to your interest
n=100:100:1000;
N1=length(n);
F_n=zeros(N1,1);
for i=1:N1
F_n(i)=DFA(DATA,n(i),1);
end
n=n';
plot(log(n),log(F_n));
xlabel('n')
ylabel('F(n)')
A=polyfit(log(n(1:end)),log(F_n(1:end)),1);
Alpha1=A(1);
D=3-A(1);
return