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All of these examples run rather quickly (in a few seconds). If you are studying the behavior of the algorithms, you should probably increase the number of iterations in the code.

sample_distributions.cpp produces histograms of the supported distributions.
tabulate_normals.cpp generating normals in base 10 from the RAND table of random numbers (the data in Table 1 of the paper).
compare_times.cpp (with num multiplied by 10) produces the timing data in Table 2, columns A and B, of the paper.
hist_data.cpp generates the data used to create Figure 1 of the paper.
chisq_test.cpp performs the χ² test on unit_normal_distribution, unit_exponential_distribution, unit_uniform_distribution, and discrete_normal_distribution.
count_bits.cpp compute the cost and toll of the various continuous distributions (with base = 2) and produces histograms of the bit counts.
discrete_count_bits.cpp compute the cost and toll of Algorithm D (with base = 2).
exrandom_test.cpp run some simple unit tests.

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