

   NNoorrmmaall ooppttiimmaall cchhooiiccee ooff ssmmooootthhiinngg ppaarraammeetteerr iinn ddeennssiittyy
   eessttiimmaattiioonn

        hnorm(x)

   AArrgguummeennttss::

          x: a vector, or matrix with two or three columns,
             containing the data.

   DDeessccrriippttiioonn::

        This functions evaluates the smoothing parameter which
        is asymptotically optimal for estimating a density
        function when the underlying distribution is Normal.
        Data in one, two or three dimensions can be handled.

   DDeettaaiillss::

        see Section 2.4.2 of the reference below.

   VVaalluuee::

        the value of the Normal optimal smoothing parameter.

   SSiiddee EEffffeeccttss::

        none

   RReeffeerreenncceess::

        Bowman, A.W. and Azzalini, A. (1997). Applied Smoothing
        Techniques for Data Analysis: the Kernel Approach with
        S-Plus Illustrations.  Oxford University Press, Oxford.

   SSeeee AAllssoo::

        `hcv', `hsj'

   EExxaammpplleess::

        x <- rnorm(50)
        hnorm(x)

