When @math{\alpha = 1} the term @math{\tan(\pi \alpha/2)} is replaced by
@math{-(2/\pi)\log|t|}. There is no explicit solution for the form of
@math{p(x)} and the library does not define a corresponding pdf
function. For @math{\alpha = 2} the distribution reduces to a Gaussian
distribution with @c{$\sigma = \sqrt{2} c$}
@math{\sigma = \sqrt{2} c} and the skewness parameter has no effect.
For @math{\alpha < 1} the tails of the distribution become extremely
wide. The symmetric distribution corresponds to @math{\beta =
0}.
The algorithm only works for @c{$0 < \alpha \le 2$} @math{0 < alpha <= 2}.
The Levy alpha-stable distributions have the property that if @math{N} alpha-stable variates are drawn from the distribution @math{p(c, \alpha, \beta)} then the sum @math{Y = X_1 + X_2 + \dots + X_N} will also be distributed as an alpha-stable variate, @math{p(N^(1/\alpha) c, \alpha, \beta)}.