walker_sample, a MATLAB code which efficiently samples a discrete probability vector.
For outcomes labeled 1, 2, 3, ..., N, a discrete probability vector X is an array of N non-negative values which sum to 1, such that X[i] is the probability of outcome i.
To sample the probability vector is to produce a sequence of outcomes i1, i2, i3, ..., which are each drawn with probability corresponding to X. For a general discrete probability vector X, a single sample operation might be expected to take a time that is proportional to O(N), the number of outcomes. Walker showed that, by constructing a new data structure, it was possible to carry out a sample in time of order O(1), that is, independent of the number of possible outcomes.
The information on this web page is distributed under the MIT license.
walker_sample is available in a C version and a C++ version and a Fortrran90 version and a Matlab version and an Octave version and a Python version.
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