Function check_change_points

Generates different data and checks reproducibility of change points.

Contents

Input

Output

Copyrights

(C) All rights reserved

The code may be used free of charge for non-commercial and educational purposes, the only requirement is that this text is preserved within the derivative work. For any other purpose you must contact the authors for permission. This code may not be redistributed without written permission from the authors.

ABOUT: This software implements our approach to detect changes in multi-variate time series

IMPORTANT: If you use this software you should cite the following in any resulting publication:
[1] Michal Staniszewski, Agnieszka Skorupa, Lukasz Boguszewicz, Maria Sokol and Andrzej Polanski. Quality Control Procedure Based on Partitioning of NMR Time Series.

function [members,means]=check_change_points(data_points,nb_repeat,nb_ch_p,snr)

    %generate set of random data
    [data,ch_p] = gen_rand(data_points,nb_ch_p,nb_repeat,snr);
    members = zeros(nb_repeat,nb_ch_p);
    %iterate over number of repeats
    for i = 1:nb_repeat
%         disp(i)
        %generate confidence intervals of found change points
        [conf_int,~,~] = gen_ar(data(:,i),100,nb_ch_p,0,0,0);
        check = [];
        %built check data from change points and its confidence intervals
        for j=1:size(conf_int,1)
            check = [check conf_int(j,3):conf_int(j,4)];
        end
        members(i,:) = ismember(ch_p(2:end-1),check);
    end
    members(i+1,:) = sum(members,1)/nb_repeat*100;
    means = mean(members(i+1,:));
end

ans =

     1     1     0     0     1
     0     0     0     1     0
     1     1     0     0     0
     0     1     0     0     0
     0     1     0     1     1
    40    80     0    40    40

Published with MATLAB® R2013b