Alex Herbert created RNG-195:
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Summary: DirichletSampler has unbounded recursion and stack
overflow for small alpha parameters
Key: RNG-195
URL: https://issues.apache.org/jira/browse/RNG-195
Project: Commons RNG
Issue Type: Bug
Components: sampling
Affects Versions: 1.3
Reporter: Alex Herbert
The DirichletSampler uses a rejection method to sample. A gamma sample is
obtained for each concentration parameter alpha. The vector of k samples is
normalised to unit length. When the sum of the samples is zero or infinite the
sample cannot be normalised and recursion occurs to generate another sample.
If the alpha parameters are very small the gamma samples are always zero and a
stack overflow error occurs.
Note that recursion is expected to be used to indicate a non-functional RNG
underlying the sampler. It was not the original intention to use a stack
overflow error to indicate a badly parameterised sampler where samples are
impossible.
Issue identified using a security scan.
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