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Asked: 2026-05-16T09:15:33+00:00

I have a function, ranker , that takes a vector and assigns numerical ranks

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I have a function, ranker, that takes a vector and assigns numerical ranks to it in ascending order. For example,
ranker([5 1 3 600]) = [3 1 2 4] or
ranker([42 300 42 42 1 42] = [3.5 6 3.5 3.5 1 3.5] .

I am using a matrix, variable_data and I want to apply the ranker function to each row for all rows in variable data. This is my current solution, but I feel there is a way to vectorize it and have it as equally fast :p

variable_ranks = nan(size(variable_data));
for i=1:1:numel(nmac_ids)
    variable_ranks(i,:) = ranker(abs(variable_data(i,:)));
end
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1 Answer

  1. Editorial Team

    With collaboration from Amro and Jonas

    variable_ranks = tiedrank(variable_data')';

    Ranker has been replaced by the Matlab function in the Stat toolbox (sorry for those who don’t have it),

    [R,TIEADJ] = tiedrank(X) computes the
    ranks of the values in the vector X.
    If any X values are tied, tiedrank
    computes their average rank. The
    return value TIEADJ is an adjustment
    for ties required by the nonparametric
    tests signrank and ranksum, and for
    the computation of Spearman’s rank
    correlation.

    TIEDRANK will compute along columns in Matlab 7.9.0 (R2009b), however it is undocumented. So by transposing the input matrix, rows turn into columns and will rank them. The second transpose is then used to organize the data in the same manner as the input. There in essence is a very classy hack :p

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