  A parametric method similar to autoregressive spectral estimators is proposed
to determine the probability density function (pdf) of a random set. The method
proceeds by maximizing the likelihood of the pdf, yielding estimates that
perform equally well in the tails as in the bulk of the distribution. It is
therefore well suited for the analysis short sets drawn from smooth pdfs and
stands out by the simplicity of its computational scheme. Its advantages and
limitations are discussed.
