Given a set of real numbers drawn from a unknown continuous univariate distribution (let\'s say is is one of beta, Cauchy, chi-square, exponential, F, gamma, Laplace, log-no
I find it hard to imagine a realistic situation where this would be useful. Why not use a non-parametric tool like a kernel density estimate?