Prashant Kumar answered . 2024-04-19 19:42:39

    function y = fitchangepts(x, icp, statistic)

    y = nan(size(x));
    K = length(icp);
    nseg = K+1;
    istart = [1; icp(:)];
    istop = [icp(:)-1; length(x)];

    if strcmp(statistic,'mean') || strcmp(statistic,'std')
      for s=1:nseg
        ix = (istart(s):istop(s))';
        y(ix) = mean(x(ix));
      end
    elseif strcmp(statistic,'rms')
      for s=1:nseg
        ix = (istart(s):istop(s))';
        y(ix) = rms(x(ix));
      end
    else % linear
      for s=1:nseg
        ix = (istart(s):istop(s))';
        y(ix) = polyval(polyfit(ix,x(ix),1),ix);
      end
    end

Test it:

load engineRPM.mat
plot(fitchangepts(x,findchangepts(x,'Statistic','linear','MinThreshold',var(x)/2),'linear'))

ipt = findchangepts(x) returns the index at which the mean of x changes most significantly.