MATLAB: Fast and simple trend

fitlmspeedtrend

Hi,
I need a fast and simple way to calculate the trend of a variable at each point in time for data over the preceding 1 hour. All I need is whether the trend is increasing or decreasing and to what degree. At the moment I am using fitlm to return the slope for each row but have found this to be too slow. Below is a simple example but my application has a much bigger dataset and I need at least an order of magnitude speedup. Appreciate some help please, especially if there are ways to vectorize the calculation. Thank you.
    time=[0.2,0.8,0.9,1.1,1.2,1.7,1.8,2.1,2.2];
    x=[0.2,0.4,0.5,0.7,1.1,0.7,0.6,1.7,2.1];
    slopes=repmat(NaN,length(x),1);
    for row=1:length(x)
        startrow=find(time >= time(row)-1,1);
        %calculate slope if there are more 2 or more data points
        if row > startrow
            temptime=time(startrow:row);
            tempx=x(startrow:row);
            mdl = fitlm(temptime,tempx);
            slopes(row)=mdl.Coefficients.Estimate(2);
        end
    end

Best Answer

You can do the fit directly with matrix operations. It should be roughly a gazillion times faster.
coeffs = [ones(size(temptime')) temptime']\tempx';
slopes(row) = coeffs(2);
There are presumably other efficiencies if you restructure your data ahead such that you do not need to do the transposes, or create the "ones" matrix inside the loop.
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